RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
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// Copyright (c) 2011-present, Facebook, Inc. All rights reserved.
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// This source code is licensed under both the GPLv2 (found in the
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// COPYING file in the root directory) and Apache 2.0 License
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// (found in the LICENSE.Apache file in the root directory).
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//
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// Copyright (c) 2012 The LevelDB Authors. All rights reserved.
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// Use of this source code is governed by a BSD-style license that can be
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// found in the LICENSE file. See the AUTHORS file for names of contributors.
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#ifndef ROCKSDB_LITE
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#ifndef GFLAGS
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#include <cstdio>
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int main() {
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fprintf(stderr, "Please install gflags to run trace_analyzer test\n");
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return 0;
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RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
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}
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#else
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#include <chrono>
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#include <cstdio>
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#include <cstdlib>
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#include <sstream>
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#include <thread>
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#include "db/db_test_util.h"
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#include "file/line_file_reader.h"
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RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
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#include "rocksdb/db.h"
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#include "rocksdb/env.h"
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#include "rocksdb/status.h"
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#include "rocksdb/trace_reader_writer.h"
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#include "test_util/testharness.h"
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#include "test_util/testutil.h"
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#include "tools/trace_analyzer_tool.h"
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#include "trace_replay/trace_replay.h"
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RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
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namespace ROCKSDB_NAMESPACE {
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RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
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namespace {
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static const int kMaxArgCount = 100;
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static const size_t kArgBufferSize = 100000;
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} // namespace
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RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
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// Note that, the QPS part verification of the analyzing result is not robost
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// enough and causes the failure in some rare cases. Disable them temporally and
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// wait for future refactor.
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RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
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// The helper functions for the test
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class TraceAnalyzerTest : public testing::Test {
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public:
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TraceAnalyzerTest() : rnd_(0xFB) {
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// test_path_ = test::TmpDir() + "trace_analyzer_test";
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test_path_ = test::PerThreadDBPath("trace_analyzer_test");
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env_ = ROCKSDB_NAMESPACE::Env::Default();
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env_->CreateDir(test_path_).PermitUncheckedError();
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RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
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dbname_ = test_path_ + "/db";
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}
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~TraceAnalyzerTest() override {}
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RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
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void GenerateTrace(std::string trace_path) {
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Options options;
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options.create_if_missing = true;
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options.merge_operator = MergeOperators::CreatePutOperator();
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Slice upper_bound("a");
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Slice lower_bound("abce");
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RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
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ReadOptions ro;
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ro.iterate_upper_bound = &upper_bound;
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ro.iterate_lower_bound = &lower_bound;
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RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
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WriteOptions wo;
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TraceOptions trace_opt;
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DB* db_ = nullptr;
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std::string value;
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std::unique_ptr<TraceWriter> trace_writer;
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Iterator* single_iter = nullptr;
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RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
|
|
|
|
ASSERT_OK(
|
|
|
|
NewFileTraceWriter(env_, env_options_, trace_path, &trace_writer));
|
|
|
|
ASSERT_OK(DB::Open(options, dbname_, &db_));
|
|
|
|
ASSERT_OK(db_->StartTrace(trace_opt, std::move(trace_writer)));
|
|
|
|
|
|
|
|
WriteBatch batch;
|
|
|
|
ASSERT_OK(batch.Put("a", "aaaaaaaaa"));
|
|
|
|
ASSERT_OK(batch.Merge("b", "aaaaaaaaaaaaaaaaaaaa"));
|
|
|
|
ASSERT_OK(batch.Delete("c"));
|
|
|
|
ASSERT_OK(batch.SingleDelete("d"));
|
|
|
|
ASSERT_OK(batch.DeleteRange("e", "f"));
|
|
|
|
ASSERT_OK(db_->Write(wo, &batch));
|
|
|
|
std::vector<Slice> keys;
|
|
|
|
keys.push_back("a");
|
|
|
|
keys.push_back("b");
|
|
|
|
keys.push_back("df");
|
|
|
|
keys.push_back("gege");
|
|
|
|
keys.push_back("hjhjhj");
|
|
|
|
std::vector<std::string> values;
|
|
|
|
std::vector<Status> ss = db_->MultiGet(ro, keys, &values);
|
|
|
|
ASSERT_GE(ss.size(), 0);
|
|
|
|
ASSERT_OK(ss[0]);
|
|
|
|
ASSERT_NOK(ss[2]);
|
|
|
|
std::vector<ColumnFamilyHandle*> cfs(2, db_->DefaultColumnFamily());
|
|
|
|
std::vector<PinnableSlice> values2(keys.size());
|
|
|
|
db_->MultiGet(ro, 2, cfs.data(), keys.data(), values2.data(), ss.data(),
|
|
|
|
false);
|
|
|
|
ASSERT_OK(ss[0]);
|
|
|
|
db_->MultiGet(ro, db_->DefaultColumnFamily(), 2, keys.data() + 3,
|
|
|
|
values2.data(), ss.data(), false);
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
ASSERT_OK(db_->Get(ro, "a", &value));
|
|
|
|
|
|
|
|
single_iter = db_->NewIterator(ro);
|
|
|
|
single_iter->Seek("a");
|
|
|
|
ASSERT_OK(single_iter->status());
|
|
|
|
single_iter->SeekForPrev("b");
|
|
|
|
ASSERT_OK(single_iter->status());
|
|
|
|
delete single_iter;
|
|
|
|
std::this_thread::sleep_for (std::chrono::seconds(1));
|
|
|
|
|
|
|
|
db_->Get(ro, "g", &value).PermitUncheckedError();
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
|
|
|
|
ASSERT_OK(db_->EndTrace());
|
|
|
|
|
|
|
|
ASSERT_OK(env_->FileExists(trace_path));
|
|
|
|
|
|
|
|
std::unique_ptr<WritableFile> whole_f;
|
|
|
|
std::string whole_path = test_path_ + "/0.txt";
|
|
|
|
ASSERT_OK(env_->NewWritableFile(whole_path, &whole_f, env_options_));
|
|
|
|
std::string whole_str = "0x61\n0x62\n0x63\n0x64\n0x65\n0x66\n";
|
|
|
|
ASSERT_OK(whole_f->Append(whole_str));
|
|
|
|
delete db_;
|
|
|
|
ASSERT_OK(DestroyDB(dbname_, options));
|
|
|
|
}
|
|
|
|
|
|
|
|
void RunTraceAnalyzer(const std::vector<std::string>& args) {
|
|
|
|
char arg_buffer[kArgBufferSize];
|
|
|
|
char* argv[kMaxArgCount];
|
|
|
|
int argc = 0;
|
|
|
|
int cursor = 0;
|
|
|
|
|
|
|
|
for (const auto& arg : args) {
|
|
|
|
ASSERT_LE(cursor + arg.size() + 1, kArgBufferSize);
|
|
|
|
ASSERT_LE(argc + 1, kMaxArgCount);
|
|
|
|
snprintf(arg_buffer + cursor, arg.size() + 1, "%s", arg.c_str());
|
|
|
|
|
|
|
|
argv[argc++] = arg_buffer + cursor;
|
|
|
|
cursor += static_cast<int>(arg.size()) + 1;
|
|
|
|
}
|
|
|
|
|
|
|
|
ASSERT_EQ(0, ROCKSDB_NAMESPACE::trace_analyzer_tool(argc, argv));
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
}
|
|
|
|
|
|
|
|
void CheckFileContent(const std::vector<std::string>& cnt,
|
|
|
|
std::string file_path, bool full_content) {
|
|
|
|
const auto& fs = env_->GetFileSystem();
|
|
|
|
FileOptions fopts(env_options_);
|
|
|
|
|
|
|
|
ASSERT_OK(fs->FileExists(file_path, fopts.io_options, nullptr));
|
|
|
|
std::unique_ptr<FSSequentialFile> file;
|
|
|
|
ASSERT_OK(fs->NewSequentialFile(file_path, fopts, &file, nullptr));
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
|
|
|
|
LineFileReader lf_reader(std::move(file), file_path,
|
|
|
|
4096 /* filereadahead_size */);
|
|
|
|
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
std::vector<std::string> result;
|
|
|
|
std::string line;
|
|
|
|
while (
|
|
|
|
lf_reader.ReadLine(&line, Env::IO_TOTAL /* rate_limiter_priority */)) {
|
|
|
|
result.push_back(line);
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
}
|
|
|
|
|
|
|
|
ASSERT_OK(lf_reader.GetStatus());
|
|
|
|
|
|
|
|
size_t min_size = std::min(cnt.size(), result.size());
|
|
|
|
for (size_t i = 0; i < min_size; i++) {
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
if (full_content) {
|
|
|
|
ASSERT_EQ(result[i], cnt[i]);
|
|
|
|
} else {
|
|
|
|
ASSERT_EQ(result[i][0], cnt[i][0]);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
return;
|
|
|
|
}
|
|
|
|
|
|
|
|
void AnalyzeTrace(std::vector<std::string>& paras_diff,
|
|
|
|
std::string output_path, std::string trace_path) {
|
|
|
|
std::vector<std::string> paras = {"./trace_analyzer",
|
|
|
|
"-convert_to_human_readable_trace",
|
|
|
|
"-output_key_stats",
|
|
|
|
"-output_access_count_stats",
|
|
|
|
"-output_prefix=test",
|
|
|
|
"-output_prefix_cut=1",
|
|
|
|
"-output_time_series",
|
|
|
|
"-output_value_distribution",
|
|
|
|
"-output_qps_stats",
|
|
|
|
"-no_key",
|
|
|
|
"-no_print"};
|
|
|
|
for (auto& para : paras_diff) {
|
|
|
|
paras.push_back(para);
|
|
|
|
}
|
|
|
|
Status s = env_->FileExists(trace_path);
|
|
|
|
if (!s.ok()) {
|
|
|
|
GenerateTrace(trace_path);
|
|
|
|
}
|
|
|
|
ASSERT_OK(env_->CreateDir(output_path));
|
|
|
|
RunTraceAnalyzer(paras);
|
|
|
|
}
|
|
|
|
|
|
|
|
ROCKSDB_NAMESPACE::Env* env_;
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
EnvOptions env_options_;
|
|
|
|
std::string test_path_;
|
|
|
|
std::string dbname_;
|
|
|
|
Random rnd_;
|
|
|
|
};
|
|
|
|
|
|
|
|
TEST_F(TraceAnalyzerTest, Get) {
|
|
|
|
std::string trace_path = test_path_ + "/trace";
|
|
|
|
std::string output_path = test_path_ + "/get";
|
|
|
|
std::string file_path;
|
|
|
|
std::vector<std::string> paras = {
|
|
|
|
"-analyze_get=true", "-analyze_put=false",
|
|
|
|
"-analyze_delete=false", "-analyze_single_delete=false",
|
|
|
|
"-analyze_range_delete=false", "-analyze_iterator=false",
|
|
|
|
"-analyze_multiget=false"};
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
paras.push_back("-output_dir=" + output_path);
|
|
|
|
paras.push_back("-trace_path=" + trace_path);
|
|
|
|
paras.push_back("-key_space_dir=" + test_path_);
|
|
|
|
AnalyzeTrace(paras, output_path, trace_path);
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
|
|
|
|
// check the key_stats file
|
|
|
|
std::vector<std::string> k_stats = {"0 10 0 1 1.000000", "0 10 1 1 1.000000"};
|
|
|
|
file_path = output_path + "/test-get-0-accessed_key_stats.txt";
|
|
|
|
CheckFileContent(k_stats, file_path, true);
|
|
|
|
|
|
|
|
// Check the access count distribution
|
|
|
|
std::vector<std::string> k_dist = {"access_count: 1 num: 2"};
|
|
|
|
file_path = output_path + "/test-get-0-accessed_key_count_distribution.txt";
|
|
|
|
CheckFileContent(k_dist, file_path, true);
|
|
|
|
|
|
|
|
// Check the trace sequence
|
|
|
|
std::vector<std::string> k_sequence = {"1", "5", "2", "3", "4", "8",
|
|
|
|
"8", "8", "8", "8", "8", "8",
|
|
|
|
"8", "8", "0", "6", "7", "0"};
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
file_path = output_path + "/test-human_readable_trace.txt";
|
|
|
|
CheckFileContent(k_sequence, file_path, false);
|
|
|
|
|
|
|
|
// Check the prefix
|
|
|
|
std::vector<std::string> k_prefix = {"0 0 0 0.000000 0.000000 0x30",
|
|
|
|
"1 1 1 1.000000 1.000000 0x61"};
|
|
|
|
file_path = output_path + "/test-get-0-accessed_key_prefix_cut.txt";
|
|
|
|
CheckFileContent(k_prefix, file_path, true);
|
|
|
|
|
|
|
|
// Check the time series
|
|
|
|
std::vector<std::string> k_series = {"0 1533000630 0", "0 1533000630 1"};
|
|
|
|
file_path = output_path + "/test-get-0-time_series.txt";
|
|
|
|
CheckFileContent(k_series, file_path, false);
|
|
|
|
|
|
|
|
// Check the accessed key in whole key space
|
|
|
|
std::vector<std::string> k_whole_access = {"0 1"};
|
|
|
|
file_path = output_path + "/test-get-0-whole_key_stats.txt";
|
|
|
|
CheckFileContent(k_whole_access, file_path, true);
|
|
|
|
|
|
|
|
// Check the whole key prefix cut
|
|
|
|
std::vector<std::string> k_whole_prefix = {"0 0x61", "1 0x62", "2 0x63",
|
|
|
|
"3 0x64", "4 0x65", "5 0x66"};
|
|
|
|
file_path = output_path + "/test-get-0-whole_key_prefix_cut.txt";
|
|
|
|
CheckFileContent(k_whole_prefix, file_path, true);
|
|
|
|
|
|
|
|
/*
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
// Check the overall qps
|
|
|
|
std::vector<std::string> all_qps = {"1 0 0 0 0 0 0 0 0 1"};
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
file_path = output_path + "/test-qps_stats.txt";
|
|
|
|
CheckFileContent(all_qps, file_path, true);
|
|
|
|
|
|
|
|
// Check the qps of get
|
|
|
|
std::vector<std::string> get_qps = {"1"};
|
|
|
|
file_path = output_path + "/test-get-0-qps_stats.txt";
|
|
|
|
CheckFileContent(get_qps, file_path, true);
|
|
|
|
|
|
|
|
// Check the top k qps prefix cut
|
|
|
|
std::vector<std::string> top_qps = {"At time: 0 with QPS: 1",
|
|
|
|
"The prefix: 0x61 Access count: 1"};
|
|
|
|
file_path = output_path + "/test-get-0-accessed_top_k_qps_prefix_cut.txt";
|
|
|
|
CheckFileContent(top_qps, file_path, true);
|
|
|
|
*/
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
}
|
|
|
|
|
|
|
|
// Test analyzing of Put
|
|
|
|
TEST_F(TraceAnalyzerTest, Put) {
|
|
|
|
std::string trace_path = test_path_ + "/trace";
|
|
|
|
std::string output_path = test_path_ + "/put";
|
|
|
|
std::string file_path;
|
|
|
|
std::vector<std::string> paras = {
|
|
|
|
"-analyze_get=false", "-analyze_put=true",
|
|
|
|
"-analyze_delete=false", "-analyze_single_delete=false",
|
|
|
|
"-analyze_range_delete=false", "-analyze_iterator=false",
|
|
|
|
"-analyze_multiget=false"};
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
paras.push_back("-output_dir=" + output_path);
|
|
|
|
paras.push_back("-trace_path=" + trace_path);
|
|
|
|
paras.push_back("-key_space_dir=" + test_path_);
|
|
|
|
AnalyzeTrace(paras, output_path, trace_path);
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
|
|
|
|
// check the key_stats file
|
|
|
|
std::vector<std::string> k_stats = {"0 9 0 1 1.000000"};
|
|
|
|
file_path = output_path + "/test-put-0-accessed_key_stats.txt";
|
|
|
|
CheckFileContent(k_stats, file_path, true);
|
|
|
|
|
|
|
|
// Check the access count distribution
|
|
|
|
std::vector<std::string> k_dist = {"access_count: 1 num: 1"};
|
|
|
|
file_path = output_path + "/test-put-0-accessed_key_count_distribution.txt";
|
|
|
|
CheckFileContent(k_dist, file_path, true);
|
|
|
|
|
|
|
|
// Check the trace sequence
|
|
|
|
std::vector<std::string> k_sequence = {"1", "5", "2", "3", "4", "8",
|
|
|
|
"8", "8", "8", "8", "8", "8",
|
|
|
|
"8", "8", "0", "6", "7", "0"};
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
file_path = output_path + "/test-human_readable_trace.txt";
|
|
|
|
CheckFileContent(k_sequence, file_path, false);
|
|
|
|
|
|
|
|
// Check the prefix
|
|
|
|
std::vector<std::string> k_prefix = {"0 0 0 0.000000 0.000000 0x30"};
|
|
|
|
file_path = output_path + "/test-put-0-accessed_key_prefix_cut.txt";
|
|
|
|
CheckFileContent(k_prefix, file_path, true);
|
|
|
|
|
|
|
|
// Check the time series
|
|
|
|
std::vector<std::string> k_series = {"1 1533056278 0"};
|
|
|
|
file_path = output_path + "/test-put-0-time_series.txt";
|
|
|
|
CheckFileContent(k_series, file_path, false);
|
|
|
|
|
|
|
|
// Check the accessed key in whole key space
|
|
|
|
std::vector<std::string> k_whole_access = {"0 1"};
|
|
|
|
file_path = output_path + "/test-put-0-whole_key_stats.txt";
|
|
|
|
CheckFileContent(k_whole_access, file_path, true);
|
|
|
|
|
|
|
|
// Check the whole key prefix cut
|
|
|
|
std::vector<std::string> k_whole_prefix = {"0 0x61", "1 0x62", "2 0x63",
|
|
|
|
"3 0x64", "4 0x65", "5 0x66"};
|
|
|
|
file_path = output_path + "/test-put-0-whole_key_prefix_cut.txt";
|
|
|
|
CheckFileContent(k_whole_prefix, file_path, true);
|
|
|
|
|
|
|
|
// Check the overall qps
|
|
|
|
std::vector<std::string> all_qps = {"0 1 0 0 0 0 0 0 0 1"};
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
file_path = output_path + "/test-qps_stats.txt";
|
|
|
|
CheckFileContent(all_qps, file_path, true);
|
|
|
|
|
|
|
|
/*
|
|
|
|
// Check the qps of Put
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
std::vector<std::string> get_qps = {"1"};
|
|
|
|
file_path = output_path + "/test-put-0-qps_stats.txt";
|
|
|
|
CheckFileContent(get_qps, file_path, true);
|
|
|
|
|
|
|
|
// Check the top k qps prefix cut
|
|
|
|
std::vector<std::string> top_qps = {"At time: 0 with QPS: 1",
|
|
|
|
"The prefix: 0x61 Access count: 1"};
|
|
|
|
file_path = output_path + "/test-put-0-accessed_top_k_qps_prefix_cut.txt";
|
|
|
|
CheckFileContent(top_qps, file_path, true);
|
|
|
|
|
|
|
|
// Check the value size distribution
|
|
|
|
std::vector<std::string> value_dist = {
|
|
|
|
"Number_of_value_size_between 0 and 16 is: 1"};
|
|
|
|
file_path = output_path + "/test-put-0-accessed_value_size_distribution.txt";
|
|
|
|
CheckFileContent(value_dist, file_path, true);
|
|
|
|
*/
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
}
|
|
|
|
|
|
|
|
// Test analyzing of delete
|
|
|
|
TEST_F(TraceAnalyzerTest, Delete) {
|
|
|
|
std::string trace_path = test_path_ + "/trace";
|
|
|
|
std::string output_path = test_path_ + "/delete";
|
|
|
|
std::string file_path;
|
|
|
|
std::vector<std::string> paras = {
|
|
|
|
"-analyze_get=false", "-analyze_put=false",
|
|
|
|
"-analyze_delete=true", "-analyze_single_delete=false",
|
|
|
|
"-analyze_range_delete=false", "-analyze_iterator=false",
|
|
|
|
"-analyze_multiget=false"};
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
paras.push_back("-output_dir=" + output_path);
|
|
|
|
paras.push_back("-trace_path=" + trace_path);
|
|
|
|
paras.push_back("-key_space_dir=" + test_path_);
|
|
|
|
AnalyzeTrace(paras, output_path, trace_path);
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
|
|
|
|
// check the key_stats file
|
|
|
|
std::vector<std::string> k_stats = {"0 10 0 1 1.000000"};
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
file_path = output_path + "/test-delete-0-accessed_key_stats.txt";
|
|
|
|
CheckFileContent(k_stats, file_path, true);
|
|
|
|
|
|
|
|
// Check the access count distribution
|
|
|
|
std::vector<std::string> k_dist = {"access_count: 1 num: 1"};
|
|
|
|
file_path =
|
|
|
|
output_path + "/test-delete-0-accessed_key_count_distribution.txt";
|
|
|
|
CheckFileContent(k_dist, file_path, true);
|
|
|
|
|
|
|
|
// Check the trace sequence
|
|
|
|
std::vector<std::string> k_sequence = {"1", "5", "2", "3", "4", "8",
|
|
|
|
"8", "8", "8", "8", "8", "8",
|
|
|
|
"8", "8", "0", "6", "7", "0"};
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
file_path = output_path + "/test-human_readable_trace.txt";
|
|
|
|
CheckFileContent(k_sequence, file_path, false);
|
|
|
|
|
|
|
|
// Check the prefix
|
|
|
|
std::vector<std::string> k_prefix = {"0 0 0 0.000000 0.000000 0x30"};
|
|
|
|
file_path = output_path + "/test-delete-0-accessed_key_prefix_cut.txt";
|
|
|
|
CheckFileContent(k_prefix, file_path, true);
|
|
|
|
|
|
|
|
// Check the time series
|
|
|
|
std::vector<std::string> k_series = {"2 1533000630 0"};
|
|
|
|
file_path = output_path + "/test-delete-0-time_series.txt";
|
|
|
|
CheckFileContent(k_series, file_path, false);
|
|
|
|
|
|
|
|
// Check the accessed key in whole key space
|
|
|
|
std::vector<std::string> k_whole_access = {"2 1"};
|
|
|
|
file_path = output_path + "/test-delete-0-whole_key_stats.txt";
|
|
|
|
CheckFileContent(k_whole_access, file_path, true);
|
|
|
|
|
|
|
|
// Check the whole key prefix cut
|
|
|
|
std::vector<std::string> k_whole_prefix = {"0 0x61", "1 0x62", "2 0x63",
|
|
|
|
"3 0x64", "4 0x65", "5 0x66"};
|
|
|
|
file_path = output_path + "/test-delete-0-whole_key_prefix_cut.txt";
|
|
|
|
CheckFileContent(k_whole_prefix, file_path, true);
|
|
|
|
|
|
|
|
/*
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
// Check the overall qps
|
|
|
|
std::vector<std::string> all_qps = {"0 0 1 0 0 0 0 0 0 1"};
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
file_path = output_path + "/test-qps_stats.txt";
|
|
|
|
CheckFileContent(all_qps, file_path, true);
|
|
|
|
|
|
|
|
// Check the qps of Delete
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
std::vector<std::string> get_qps = {"1"};
|
|
|
|
file_path = output_path + "/test-delete-0-qps_stats.txt";
|
|
|
|
CheckFileContent(get_qps, file_path, true);
|
|
|
|
|
|
|
|
// Check the top k qps prefix cut
|
|
|
|
std::vector<std::string> top_qps = {"At time: 0 with QPS: 1",
|
|
|
|
"The prefix: 0x63 Access count: 1"};
|
|
|
|
file_path = output_path + "/test-delete-0-accessed_top_k_qps_prefix_cut.txt";
|
|
|
|
CheckFileContent(top_qps, file_path, true);
|
|
|
|
*/
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
}
|
|
|
|
|
|
|
|
// Test analyzing of Merge
|
|
|
|
TEST_F(TraceAnalyzerTest, Merge) {
|
|
|
|
std::string trace_path = test_path_ + "/trace";
|
|
|
|
std::string output_path = test_path_ + "/merge";
|
|
|
|
std::string file_path;
|
|
|
|
std::vector<std::string> paras = {
|
|
|
|
"-analyze_get=false", "-analyze_put=false",
|
|
|
|
"-analyze_delete=false", "-analyze_merge=true",
|
|
|
|
"-analyze_single_delete=false", "-analyze_range_delete=false",
|
|
|
|
"-analyze_iterator=false", "-analyze_multiget=false"};
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
paras.push_back("-output_dir=" + output_path);
|
|
|
|
paras.push_back("-trace_path=" + trace_path);
|
|
|
|
paras.push_back("-key_space_dir=" + test_path_);
|
|
|
|
AnalyzeTrace(paras, output_path, trace_path);
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
|
|
|
|
// check the key_stats file
|
|
|
|
std::vector<std::string> k_stats = {"0 20 0 1 1.000000"};
|
|
|
|
file_path = output_path + "/test-merge-0-accessed_key_stats.txt";
|
|
|
|
CheckFileContent(k_stats, file_path, true);
|
|
|
|
|
|
|
|
// Check the access count distribution
|
|
|
|
std::vector<std::string> k_dist = {"access_count: 1 num: 1"};
|
|
|
|
file_path = output_path + "/test-merge-0-accessed_key_count_distribution.txt";
|
|
|
|
CheckFileContent(k_dist, file_path, true);
|
|
|
|
|
|
|
|
// Check the trace sequence
|
|
|
|
std::vector<std::string> k_sequence = {"1", "5", "2", "3", "4", "8",
|
|
|
|
"8", "8", "8", "8", "8", "8",
|
|
|
|
"8", "8", "0", "6", "7", "0"};
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
file_path = output_path + "/test-human_readable_trace.txt";
|
|
|
|
CheckFileContent(k_sequence, file_path, false);
|
|
|
|
|
|
|
|
// Check the prefix
|
|
|
|
std::vector<std::string> k_prefix = {"0 0 0 0.000000 0.000000 0x30"};
|
|
|
|
file_path = output_path + "/test-merge-0-accessed_key_prefix_cut.txt";
|
|
|
|
CheckFileContent(k_prefix, file_path, true);
|
|
|
|
|
|
|
|
// Check the time series
|
|
|
|
std::vector<std::string> k_series = {"5 1533000630 0"};
|
|
|
|
file_path = output_path + "/test-merge-0-time_series.txt";
|
|
|
|
CheckFileContent(k_series, file_path, false);
|
|
|
|
|
|
|
|
// Check the accessed key in whole key space
|
|
|
|
std::vector<std::string> k_whole_access = {"1 1"};
|
|
|
|
file_path = output_path + "/test-merge-0-whole_key_stats.txt";
|
|
|
|
CheckFileContent(k_whole_access, file_path, true);
|
|
|
|
|
|
|
|
// Check the whole key prefix cut
|
|
|
|
std::vector<std::string> k_whole_prefix = {"0 0x61", "1 0x62", "2 0x63",
|
|
|
|
"3 0x64", "4 0x65", "5 0x66"};
|
|
|
|
file_path = output_path + "/test-merge-0-whole_key_prefix_cut.txt";
|
|
|
|
CheckFileContent(k_whole_prefix, file_path, true);
|
|
|
|
|
|
|
|
/*
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
// Check the overall qps
|
|
|
|
std::vector<std::string> all_qps = {"0 0 0 0 0 1 0 0 0 1"};
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
file_path = output_path + "/test-qps_stats.txt";
|
|
|
|
CheckFileContent(all_qps, file_path, true);
|
|
|
|
|
|
|
|
// Check the qps of Merge
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
std::vector<std::string> get_qps = {"1"};
|
|
|
|
file_path = output_path + "/test-merge-0-qps_stats.txt";
|
|
|
|
CheckFileContent(get_qps, file_path, true);
|
|
|
|
|
|
|
|
// Check the top k qps prefix cut
|
|
|
|
std::vector<std::string> top_qps = {"At time: 0 with QPS: 1",
|
|
|
|
"The prefix: 0x62 Access count: 1"};
|
|
|
|
file_path = output_path + "/test-merge-0-accessed_top_k_qps_prefix_cut.txt";
|
|
|
|
CheckFileContent(top_qps, file_path, true);
|
|
|
|
*/
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
|
|
|
|
// Check the value size distribution
|
|
|
|
std::vector<std::string> value_dist = {
|
|
|
|
"Number_of_value_size_between 0 and 24 is: 1"};
|
|
|
|
file_path =
|
|
|
|
output_path + "/test-merge-0-accessed_value_size_distribution.txt";
|
|
|
|
CheckFileContent(value_dist, file_path, true);
|
|
|
|
}
|
|
|
|
|
|
|
|
// Test analyzing of SingleDelete
|
|
|
|
TEST_F(TraceAnalyzerTest, SingleDelete) {
|
|
|
|
std::string trace_path = test_path_ + "/trace";
|
|
|
|
std::string output_path = test_path_ + "/single_delete";
|
|
|
|
std::string file_path;
|
|
|
|
std::vector<std::string> paras = {
|
|
|
|
"-analyze_get=false", "-analyze_put=false",
|
|
|
|
"-analyze_delete=false", "-analyze_merge=false",
|
|
|
|
"-analyze_single_delete=true", "-analyze_range_delete=false",
|
|
|
|
"-analyze_iterator=false", "-analyze_multiget=false"};
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
paras.push_back("-output_dir=" + output_path);
|
|
|
|
paras.push_back("-trace_path=" + trace_path);
|
|
|
|
paras.push_back("-key_space_dir=" + test_path_);
|
|
|
|
AnalyzeTrace(paras, output_path, trace_path);
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
|
|
|
|
// check the key_stats file
|
|
|
|
std::vector<std::string> k_stats = {"0 10 0 1 1.000000"};
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
file_path = output_path + "/test-single_delete-0-accessed_key_stats.txt";
|
|
|
|
CheckFileContent(k_stats, file_path, true);
|
|
|
|
|
|
|
|
// Check the access count distribution
|
|
|
|
std::vector<std::string> k_dist = {"access_count: 1 num: 1"};
|
|
|
|
file_path =
|
|
|
|
output_path + "/test-single_delete-0-accessed_key_count_distribution.txt";
|
|
|
|
CheckFileContent(k_dist, file_path, true);
|
|
|
|
|
|
|
|
// Check the trace sequence
|
|
|
|
std::vector<std::string> k_sequence = {"1", "5", "2", "3", "4", "8",
|
|
|
|
"8", "8", "8", "8", "8", "8",
|
|
|
|
"8", "8", "0", "6", "7", "0"};
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
file_path = output_path + "/test-human_readable_trace.txt";
|
|
|
|
CheckFileContent(k_sequence, file_path, false);
|
|
|
|
|
|
|
|
// Check the prefix
|
|
|
|
std::vector<std::string> k_prefix = {"0 0 0 0.000000 0.000000 0x30"};
|
|
|
|
file_path = output_path + "/test-single_delete-0-accessed_key_prefix_cut.txt";
|
|
|
|
CheckFileContent(k_prefix, file_path, true);
|
|
|
|
|
|
|
|
// Check the time series
|
|
|
|
std::vector<std::string> k_series = {"3 1533000630 0"};
|
|
|
|
file_path = output_path + "/test-single_delete-0-time_series.txt";
|
|
|
|
CheckFileContent(k_series, file_path, false);
|
|
|
|
|
|
|
|
// Check the accessed key in whole key space
|
|
|
|
std::vector<std::string> k_whole_access = {"3 1"};
|
|
|
|
file_path = output_path + "/test-single_delete-0-whole_key_stats.txt";
|
|
|
|
CheckFileContent(k_whole_access, file_path, true);
|
|
|
|
|
|
|
|
// Check the whole key prefix cut
|
|
|
|
std::vector<std::string> k_whole_prefix = {"0 0x61", "1 0x62", "2 0x63",
|
|
|
|
"3 0x64", "4 0x65", "5 0x66"};
|
|
|
|
file_path = output_path + "/test-single_delete-0-whole_key_prefix_cut.txt";
|
|
|
|
CheckFileContent(k_whole_prefix, file_path, true);
|
|
|
|
|
|
|
|
/*
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
// Check the overall qps
|
|
|
|
std::vector<std::string> all_qps = {"0 0 0 1 0 0 0 0 0 1"};
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
file_path = output_path + "/test-qps_stats.txt";
|
|
|
|
CheckFileContent(all_qps, file_path, true);
|
|
|
|
|
|
|
|
// Check the qps of SingleDelete
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
std::vector<std::string> get_qps = {"1"};
|
|
|
|
file_path = output_path + "/test-single_delete-0-qps_stats.txt";
|
|
|
|
CheckFileContent(get_qps, file_path, true);
|
|
|
|
|
|
|
|
// Check the top k qps prefix cut
|
|
|
|
std::vector<std::string> top_qps = {"At time: 0 with QPS: 1",
|
|
|
|
"The prefix: 0x64 Access count: 1"};
|
|
|
|
file_path =
|
|
|
|
output_path + "/test-single_delete-0-accessed_top_k_qps_prefix_cut.txt";
|
|
|
|
CheckFileContent(top_qps, file_path, true);
|
|
|
|
*/
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
}
|
|
|
|
|
|
|
|
// Test analyzing of delete
|
|
|
|
TEST_F(TraceAnalyzerTest, DeleteRange) {
|
|
|
|
std::string trace_path = test_path_ + "/trace";
|
|
|
|
std::string output_path = test_path_ + "/range_delete";
|
|
|
|
std::string file_path;
|
|
|
|
std::vector<std::string> paras = {
|
|
|
|
"-analyze_get=false", "-analyze_put=false",
|
|
|
|
"-analyze_delete=false", "-analyze_merge=false",
|
|
|
|
"-analyze_single_delete=false", "-analyze_range_delete=true",
|
|
|
|
"-analyze_iterator=false", "-analyze_multiget=false"};
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
paras.push_back("-output_dir=" + output_path);
|
|
|
|
paras.push_back("-trace_path=" + trace_path);
|
|
|
|
paras.push_back("-key_space_dir=" + test_path_);
|
|
|
|
AnalyzeTrace(paras, output_path, trace_path);
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
|
|
|
|
// check the key_stats file
|
|
|
|
std::vector<std::string> k_stats = {"0 10 0 1 1.000000", "0 10 1 1 1.000000"};
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
file_path = output_path + "/test-range_delete-0-accessed_key_stats.txt";
|
|
|
|
CheckFileContent(k_stats, file_path, true);
|
|
|
|
|
|
|
|
// Check the access count distribution
|
|
|
|
std::vector<std::string> k_dist = {"access_count: 1 num: 2"};
|
|
|
|
file_path =
|
|
|
|
output_path + "/test-range_delete-0-accessed_key_count_distribution.txt";
|
|
|
|
CheckFileContent(k_dist, file_path, true);
|
|
|
|
|
|
|
|
// Check the trace sequence
|
|
|
|
std::vector<std::string> k_sequence = {"1", "5", "2", "3", "4", "8",
|
|
|
|
"8", "8", "8", "8", "8", "8",
|
|
|
|
"8", "8", "0", "6", "7", "0"};
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
file_path = output_path + "/test-human_readable_trace.txt";
|
|
|
|
CheckFileContent(k_sequence, file_path, false);
|
|
|
|
|
|
|
|
// Check the prefix
|
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|
std::vector<std::string> k_prefix = {"0 0 0 0.000000 0.000000 0x30",
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"1 1 1 1.000000 1.000000 0x65"};
|
|
|
|
file_path = output_path + "/test-range_delete-0-accessed_key_prefix_cut.txt";
|
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|
CheckFileContent(k_prefix, file_path, true);
|
|
|
|
|
|
|
|
// Check the time series
|
|
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|
std::vector<std::string> k_series = {"4 1533000630 0", "4 1533060100 1"};
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|
file_path = output_path + "/test-range_delete-0-time_series.txt";
|
|
|
|
CheckFileContent(k_series, file_path, false);
|
|
|
|
|
|
|
|
// Check the accessed key in whole key space
|
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|
std::vector<std::string> k_whole_access = {"4 1", "5 1"};
|
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|
file_path = output_path + "/test-range_delete-0-whole_key_stats.txt";
|
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CheckFileContent(k_whole_access, file_path, true);
|
|
|
|
|
|
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|
// Check the whole key prefix cut
|
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|
std::vector<std::string> k_whole_prefix = {"0 0x61", "1 0x62", "2 0x63",
|
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|
"3 0x64", "4 0x65", "5 0x66"};
|
|
|
|
file_path = output_path + "/test-range_delete-0-whole_key_prefix_cut.txt";
|
|
|
|
CheckFileContent(k_whole_prefix, file_path, true);
|
|
|
|
|
|
|
|
/*
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
// Check the overall qps
|
|
|
|
std::vector<std::string> all_qps = {"0 0 0 0 2 0 0 0 0 2"};
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
file_path = output_path + "/test-qps_stats.txt";
|
|
|
|
CheckFileContent(all_qps, file_path, true);
|
|
|
|
|
|
|
|
// Check the qps of DeleteRange
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
std::vector<std::string> get_qps = {"2"};
|
|
|
|
file_path = output_path + "/test-range_delete-0-qps_stats.txt";
|
|
|
|
CheckFileContent(get_qps, file_path, true);
|
|
|
|
|
|
|
|
// Check the top k qps prefix cut
|
|
|
|
std::vector<std::string> top_qps = {"At time: 0 with QPS: 2",
|
|
|
|
"The prefix: 0x65 Access count: 1",
|
|
|
|
"The prefix: 0x66 Access count: 1"};
|
|
|
|
file_path =
|
|
|
|
output_path + "/test-range_delete-0-accessed_top_k_qps_prefix_cut.txt";
|
|
|
|
CheckFileContent(top_qps, file_path, true);
|
|
|
|
*/
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
}
|
|
|
|
|
|
|
|
// Test analyzing of Iterator
|
|
|
|
TEST_F(TraceAnalyzerTest, Iterator) {
|
|
|
|
std::string trace_path = test_path_ + "/trace";
|
|
|
|
std::string output_path = test_path_ + "/iterator";
|
|
|
|
std::string file_path;
|
|
|
|
std::vector<std::string> paras = {
|
|
|
|
"-analyze_get=false", "-analyze_put=false",
|
|
|
|
"-analyze_delete=false", "-analyze_merge=false",
|
|
|
|
"-analyze_single_delete=false", "-analyze_range_delete=false",
|
|
|
|
"-analyze_iterator=true", "-analyze_multiget=false"};
|
|
|
|
paras.push_back("-output_dir=" + output_path);
|
|
|
|
paras.push_back("-trace_path=" + trace_path);
|
|
|
|
paras.push_back("-key_space_dir=" + test_path_);
|
|
|
|
AnalyzeTrace(paras, output_path, trace_path);
|
|
|
|
|
|
|
|
// Check the output of Seek
|
|
|
|
// check the key_stats file
|
|
|
|
std::vector<std::string> k_stats = {"0 10 0 1 1.000000"};
|
|
|
|
file_path = output_path + "/test-iterator_Seek-0-accessed_key_stats.txt";
|
|
|
|
CheckFileContent(k_stats, file_path, true);
|
|
|
|
|
|
|
|
// Check the access count distribution
|
|
|
|
std::vector<std::string> k_dist = {"access_count: 1 num: 1"};
|
|
|
|
file_path =
|
|
|
|
output_path + "/test-iterator_Seek-0-accessed_key_count_distribution.txt";
|
|
|
|
CheckFileContent(k_dist, file_path, true);
|
|
|
|
|
|
|
|
// Check the trace sequence
|
|
|
|
std::vector<std::string> k_sequence = {"1", "5", "2", "3", "4", "8",
|
|
|
|
"8", "8", "8", "8", "8", "8",
|
|
|
|
"8", "8", "0", "6", "7", "0"};
|
|
|
|
file_path = output_path + "/test-human_readable_trace.txt";
|
|
|
|
CheckFileContent(k_sequence, file_path, false);
|
|
|
|
|
|
|
|
// Check the prefix
|
|
|
|
std::vector<std::string> k_prefix = {"0 0 0 0.000000 0.000000 0x30"};
|
|
|
|
file_path = output_path + "/test-iterator_Seek-0-accessed_key_prefix_cut.txt";
|
|
|
|
CheckFileContent(k_prefix, file_path, true);
|
|
|
|
|
|
|
|
// Check the time series
|
|
|
|
std::vector<std::string> k_series = {"6 1 0"};
|
|
|
|
file_path = output_path + "/test-iterator_Seek-0-time_series.txt";
|
|
|
|
CheckFileContent(k_series, file_path, false);
|
|
|
|
|
|
|
|
// Check the accessed key in whole key space
|
|
|
|
std::vector<std::string> k_whole_access = {"0 1"};
|
|
|
|
file_path = output_path + "/test-iterator_Seek-0-whole_key_stats.txt";
|
|
|
|
CheckFileContent(k_whole_access, file_path, true);
|
|
|
|
|
|
|
|
// Check the whole key prefix cut
|
|
|
|
std::vector<std::string> k_whole_prefix = {"0 0x61", "1 0x62", "2 0x63",
|
|
|
|
"3 0x64", "4 0x65", "5 0x66"};
|
|
|
|
file_path = output_path + "/test-iterator_Seek-0-whole_key_prefix_cut.txt";
|
|
|
|
CheckFileContent(k_whole_prefix, file_path, true);
|
|
|
|
|
|
|
|
/*
|
|
|
|
// Check the overall qps
|
|
|
|
std::vector<std::string> all_qps = {"0 0 0 0 0 0 1 1 0 2"};
|
|
|
|
file_path = output_path + "/test-qps_stats.txt";
|
|
|
|
CheckFileContent(all_qps, file_path, true);
|
|
|
|
|
|
|
|
// Check the qps of Iterator_Seek
|
|
|
|
std::vector<std::string> get_qps = {"1"};
|
|
|
|
file_path = output_path + "/test-iterator_Seek-0-qps_stats.txt";
|
|
|
|
CheckFileContent(get_qps, file_path, true);
|
|
|
|
|
|
|
|
// Check the top k qps prefix cut
|
|
|
|
std::vector<std::string> top_qps = {"At time: 0 with QPS: 1",
|
|
|
|
"The prefix: 0x61 Access count: 1"};
|
|
|
|
file_path =
|
|
|
|
output_path + "/test-iterator_Seek-0-accessed_top_k_qps_prefix_cut.txt";
|
|
|
|
CheckFileContent(top_qps, file_path, true);
|
|
|
|
*/
|
|
|
|
|
|
|
|
// Check the output of SeekForPrev
|
|
|
|
// check the key_stats file
|
|
|
|
k_stats = {"0 10 0 1 1.000000"};
|
|
|
|
file_path =
|
|
|
|
output_path + "/test-iterator_SeekForPrev-0-accessed_key_stats.txt";
|
|
|
|
CheckFileContent(k_stats, file_path, true);
|
|
|
|
|
|
|
|
// Check the access count distribution
|
|
|
|
k_dist = {"access_count: 1 num: 1"};
|
|
|
|
file_path =
|
|
|
|
output_path +
|
|
|
|
"/test-iterator_SeekForPrev-0-accessed_key_count_distribution.txt";
|
|
|
|
CheckFileContent(k_dist, file_path, true);
|
|
|
|
|
|
|
|
// Check the prefix
|
|
|
|
k_prefix = {"0 0 0 0.000000 0.000000 0x30"};
|
|
|
|
file_path =
|
|
|
|
output_path + "/test-iterator_SeekForPrev-0-accessed_key_prefix_cut.txt";
|
|
|
|
CheckFileContent(k_prefix, file_path, true);
|
|
|
|
|
|
|
|
// Check the time series
|
|
|
|
k_series = {"7 0 0"};
|
|
|
|
file_path = output_path + "/test-iterator_SeekForPrev-0-time_series.txt";
|
|
|
|
CheckFileContent(k_series, file_path, false);
|
|
|
|
|
|
|
|
// Check the accessed key in whole key space
|
|
|
|
k_whole_access = {"1 1"};
|
|
|
|
file_path = output_path + "/test-iterator_SeekForPrev-0-whole_key_stats.txt";
|
|
|
|
CheckFileContent(k_whole_access, file_path, true);
|
|
|
|
|
|
|
|
// Check the whole key prefix cut
|
|
|
|
k_whole_prefix = {"0 0x61", "1 0x62", "2 0x63", "3 0x64", "4 0x65", "5 0x66"};
|
|
|
|
file_path =
|
|
|
|
output_path + "/test-iterator_SeekForPrev-0-whole_key_prefix_cut.txt";
|
|
|
|
CheckFileContent(k_whole_prefix, file_path, true);
|
|
|
|
|
|
|
|
/*
|
|
|
|
// Check the qps of Iterator_SeekForPrev
|
|
|
|
get_qps = {"1"};
|
|
|
|
file_path = output_path + "/test-iterator_SeekForPrev-0-qps_stats.txt";
|
|
|
|
CheckFileContent(get_qps, file_path, true);
|
|
|
|
|
|
|
|
// Check the top k qps prefix cut
|
|
|
|
top_qps = {"At time: 0 with QPS: 1", "The prefix: 0x62 Access count: 1"};
|
|
|
|
file_path = output_path +
|
|
|
|
"/test-iterator_SeekForPrev-0-accessed_top_k_qps_prefix_cut.txt";
|
|
|
|
CheckFileContent(top_qps, file_path, true);
|
|
|
|
*/
|
|
|
|
}
|
|
|
|
|
|
|
|
// Test analyzing of multiget
|
|
|
|
TEST_F(TraceAnalyzerTest, MultiGet) {
|
|
|
|
std::string trace_path = test_path_ + "/trace";
|
|
|
|
std::string output_path = test_path_ + "/multiget";
|
|
|
|
std::string file_path;
|
|
|
|
std::vector<std::string> paras = {
|
|
|
|
"-analyze_get=false", "-analyze_put=false",
|
|
|
|
"-analyze_delete=false", "-analyze_merge=false",
|
|
|
|
"-analyze_single_delete=false", "-analyze_range_delete=true",
|
|
|
|
"-analyze_iterator=false", "-analyze_multiget=true"};
|
|
|
|
paras.push_back("-output_dir=" + output_path);
|
|
|
|
paras.push_back("-trace_path=" + trace_path);
|
|
|
|
paras.push_back("-key_space_dir=" + test_path_);
|
|
|
|
AnalyzeTrace(paras, output_path, trace_path);
|
|
|
|
|
|
|
|
// check the key_stats file
|
|
|
|
std::vector<std::string> k_stats = {"0 10 0 2 1.000000", "0 10 1 2 1.000000",
|
|
|
|
"0 10 2 1 1.000000", "0 10 3 2 1.000000",
|
|
|
|
"0 10 4 2 1.000000"};
|
|
|
|
file_path = output_path + "/test-multiget-0-accessed_key_stats.txt";
|
|
|
|
CheckFileContent(k_stats, file_path, true);
|
|
|
|
|
|
|
|
// Check the access count distribution
|
|
|
|
std::vector<std::string> k_dist = {"access_count: 1 num: 1",
|
|
|
|
"access_count: 2 num: 4"};
|
|
|
|
file_path =
|
|
|
|
output_path + "/test-multiget-0-accessed_key_count_distribution.txt";
|
|
|
|
CheckFileContent(k_dist, file_path, true);
|
|
|
|
|
|
|
|
// Check the trace sequence
|
|
|
|
std::vector<std::string> k_sequence = {"1", "5", "2", "3", "4", "8",
|
|
|
|
"8", "8", "8", "8", "8", "8",
|
|
|
|
"8", "8", "0", "6", "7", "0"};
|
|
|
|
file_path = output_path + "/test-human_readable_trace.txt";
|
|
|
|
CheckFileContent(k_sequence, file_path, false);
|
|
|
|
|
|
|
|
// Check the prefix
|
|
|
|
std::vector<std::string> k_prefix = {
|
|
|
|
"0 0 0 0.000000 0.000000 0x30", "1 2 1 2.000000 1.000000 0x61",
|
|
|
|
"2 2 1 2.000000 1.000000 0x62", "3 1 1 1.000000 1.000000 0x64",
|
|
|
|
"4 2 1 2.000000 1.000000 0x67"};
|
|
|
|
file_path = output_path + "/test-multiget-0-accessed_key_prefix_cut.txt";
|
|
|
|
CheckFileContent(k_prefix, file_path, true);
|
|
|
|
|
|
|
|
// Check the time series
|
|
|
|
std::vector<std::string> k_series = {"8 0 0", "8 0 1", "8 0 2",
|
|
|
|
"8 0 3", "8 0 4", "8 0 0",
|
|
|
|
"8 0 1", "8 0 3", "8 0 4"};
|
|
|
|
file_path = output_path + "/test-multiget-0-time_series.txt";
|
|
|
|
CheckFileContent(k_series, file_path, false);
|
|
|
|
|
|
|
|
// Check the accessed key in whole key space
|
|
|
|
std::vector<std::string> k_whole_access = {"0 2", "1 2"};
|
|
|
|
file_path = output_path + "/test-multiget-0-whole_key_stats.txt";
|
|
|
|
CheckFileContent(k_whole_access, file_path, true);
|
|
|
|
|
|
|
|
// Check the whole key prefix cut
|
|
|
|
std::vector<std::string> k_whole_prefix = {"0 0x61", "1 0x62", "2 0x63",
|
|
|
|
"3 0x64", "4 0x65", "5 0x66"};
|
|
|
|
file_path = output_path + "/test-multiget-0-whole_key_prefix_cut.txt";
|
|
|
|
CheckFileContent(k_whole_prefix, file_path, true);
|
|
|
|
|
|
|
|
/*
|
|
|
|
// Check the overall qps. We have 3 MultiGet queries and it requested 9 keys
|
|
|
|
// in total
|
|
|
|
std::vector<std::string> all_qps = {"0 0 0 0 2 0 0 0 9 11"};
|
|
|
|
file_path = output_path + "/test-qps_stats.txt";
|
|
|
|
CheckFileContent(all_qps, file_path, true);
|
|
|
|
|
|
|
|
// Check the qps of DeleteRange
|
|
|
|
std::vector<std::string> get_qps = {"9"};
|
|
|
|
file_path = output_path + "/test-multiget-0-qps_stats.txt";
|
|
|
|
CheckFileContent(get_qps, file_path, true);
|
|
|
|
|
|
|
|
// Check the top k qps prefix cut
|
|
|
|
std::vector<std::string> top_qps = {
|
|
|
|
"At time: 0 with QPS: 9", "The prefix: 0x61 Access count: 2",
|
|
|
|
"The prefix: 0x62 Access count: 2", "The prefix: 0x64 Access count: 1",
|
|
|
|
"The prefix: 0x67 Access count: 2", "The prefix: 0x68 Access count: 2"};
|
|
|
|
file_path =
|
|
|
|
output_path + "/test-multiget-0-accessed_top_k_qps_prefix_cut.txt";
|
|
|
|
CheckFileContent(top_qps, file_path, true);
|
|
|
|
*/
|
|
|
|
}
|
|
|
|
|
|
|
|
} // namespace ROCKSDB_NAMESPACE
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
|
|
|
|
int main(int argc, char** argv) {
|
|
|
|
ROCKSDB_NAMESPACE::port::InstallStackTraceHandler();
|
RocksDB Trace Analyzer (#4091)
Summary:
A framework of trace analyzing for RocksDB
After collecting the trace by using the tool of [PR #3837](https://github.com/facebook/rocksdb/pull/3837). User can use the Trace Analyzer to interpret, analyze, and characterize the collected workload.
**Input:**
1. trace file
2. Whole keys space file
**Statistics:**
1. Access count of each operation (Get, Put, Delete, SingleDelete, DeleteRange, Merge) in each column family.
2. Key hotness (access count) of each one
3. Key space separation based on given prefix
4. Key size distribution
5. Value size distribution if appliable
6. Top K accessed keys
7. QPS statistics including the average QPS and peak QPS
8. Top K accessed prefix
9. The query correlation analyzing, output the number of X after Y and the corresponding average time
intervals
**Output:**
1. key access heat map (either in the accessed key space or whole key space)
2. trace sequence file (interpret the raw trace file to line base text file for future use)
3. Time serial (The key space ID and its access time)
4. Key access count distritbution
5. Key size distribution
6. Value size distribution (in each intervals)
7. whole key space separation by the prefix
8. Accessed key space separation by the prefix
9. QPS of each operation and each column family
10. Top K QPS and their accessed prefix range
**Test:**
1. Added the unit test of analyzing Get, Put, Delete, SingleDelete, DeleteRange, Merge
2. Generated the trace and analyze the trace
**Implemented but not tested (due to the limitation of trace_replay):**
1. Analyzing Iterator, supporting Seek() and SeekForPrev() analyzing
2. Analyzing the number of Key found by Get
**Future Work:**
1. Support execution time analyzing of each requests
2. Support cache hit situation and block read situation of Get
Pull Request resolved: https://github.com/facebook/rocksdb/pull/4091
Differential Revision: D9256157
Pulled By: zhichao-cao
fbshipit-source-id: f0ceacb7eedbc43a3eee6e85b76087d7832a8fe6
6 years ago
|
|
|
::testing::InitGoogleTest(&argc, argv);
|
|
|
|
return RUN_ALL_TESTS();
|
|
|
|
}
|
|
|
|
#endif // GFLAG
|
|
|
|
#else
|
|
|
|
#include <stdio.h>
|
|
|
|
|
|
|
|
int main(int /*argc*/, char** /*argv*/) {
|
|
|
|
fprintf(stderr, "Trace_analyzer test is not supported in ROCKSDB_LITE\n");
|
|
|
|
return 0;
|
|
|
|
}
|
|
|
|
|
|
|
|
#endif // !ROCKSDB_LITE return RUN_ALL_TESTS();
|