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rocksdb/db/compaction_job.cc

1198 lines
44 KiB

// Copyright (c) 2013, Facebook, Inc. All rights reserved.
// This source code is licensed under the BSD-style license found in the
// LICENSE file in the root directory of this source tree. An additional grant
// of patent rights can be found in the PATENTS file in the same directory.
//
// Copyright (c) 2011 The LevelDB Authors. All rights reserved.
// Use of this source code is governed by a BSD-style license that can be
// found in the LICENSE file. See the AUTHORS file for names of contributors.
#include "db/compaction_job.h"
#ifndef __STDC_FORMAT_MACROS
#define __STDC_FORMAT_MACROS
#endif
#include <inttypes.h>
#include <algorithm>
#include <vector>
#include <memory>
#include <list>
#include "db/builder.h"
#include "db/db_iter.h"
#include "db/dbformat.h"
#include "db/event_helpers.h"
#include "db/filename.h"
#include "db/log_reader.h"
#include "db/log_writer.h"
#include "db/memtable.h"
#include "db/merge_helper.h"
#include "db/memtable_list.h"
#include "db/merge_context.h"
#include "db/version_set.h"
#include "port/port.h"
#include "port/likely.h"
#include "rocksdb/db.h"
#include "rocksdb/env.h"
#include "rocksdb/statistics.h"
#include "rocksdb/status.h"
#include "rocksdb/table.h"
#include "table/block.h"
#include "table/block_based_table_factory.h"
#include "table/merger.h"
#include "table/table_builder.h"
#include "table/two_level_iterator.h"
#include "util/coding.h"
#include "util/file_reader_writer.h"
#include "util/logging.h"
#include "util/log_buffer.h"
#include "util/mutexlock.h"
#include "util/perf_context_imp.h"
#include "util/iostats_context_imp.h"
#include "util/stop_watch.h"
#include "util/string_util.h"
#include "util/sync_point.h"
#include "util/thread_status_util.h"
namespace rocksdb {
// Maintains state for each sub-compaction
struct CompactionJob::SubCompactionState {
Compaction* const compaction;
// The boundaries of the key-range this compaction is interested in. No two
// subcompactions may have overlapping key-ranges.
// 'start' is inclusive, 'end' is exclusive, and nullptr means unbounded
Slice *start, *end;
// The return status of this compaction
Status status;
// Files produced by compaction
struct Output {
uint64_t number;
uint32_t path_id;
uint64_t file_size;
InternalKey smallest, largest;
SequenceNumber smallest_seqno, largest_seqno;
bool need_compaction;
};
// State kept for output being generated
std::vector<Output> outputs;
std::unique_ptr<WritableFileWriter> outfile;
std::unique_ptr<TableBuilder> builder;
Output* current_output() {
assert(!outputs.empty());
return &outputs.back();
}
// State during the sub-compaction
uint64_t total_bytes;
uint64_t num_input_records;
uint64_t num_output_records;
SequenceNumber earliest_snapshot;
SequenceNumber visible_at_tip;
SequenceNumber latest_snapshot;
CompactionJobStats compaction_job_stats;
// "level_ptrs" holds indices that remember which file of an associated
// level we were last checking during the last call to compaction->
// KeyNotExistsBeyondOutputLevel(). This allows future calls to the function
// to pick off where it left off since each subcompaction's key range is
// increasing so a later call to the function must be looking for a key that
// is in or beyond the last file checked during the previous call
std::vector<size_t> level_ptrs;
explicit SubCompactionState(Compaction* c, Slice* _start, Slice* _end,
SequenceNumber earliest, SequenceNumber visible,
SequenceNumber latest)
: compaction(c),
start(_start),
end(_end),
outfile(nullptr),
builder(nullptr),
total_bytes(0),
num_input_records(0),
num_output_records(0),
earliest_snapshot(earliest),
visible_at_tip(visible),
latest_snapshot(latest) {
assert(compaction != nullptr);
level_ptrs = std::vector<size_t>(compaction->number_levels(), 0);
}
};
// Maintains state for the entire compaction
struct CompactionJob::CompactionState {
Compaction* const compaction;
// REQUIRED: subcompaction states are stored in order of increasing
// key-range
std::vector<CompactionJob::SubCompactionState> sub_compact_states;
Status status;
uint64_t total_bytes;
uint64_t num_input_records;
uint64_t num_output_records;
explicit CompactionState(Compaction* c)
: compaction(c),
total_bytes(0),
num_input_records(0),
num_output_records(0) {}
size_t NumOutputFiles() {
size_t total = 0;
for (auto& s : sub_compact_states) {
total += s.outputs.size();
}
return total;
}
Slice SmallestUserKey() {
assert(!sub_compact_states.empty() &&
sub_compact_states[0].start == nullptr);
return sub_compact_states[0].outputs[0].smallest.user_key();
}
Slice LargestUserKey() {
assert(!sub_compact_states.empty() &&
sub_compact_states.back().end == nullptr);
return sub_compact_states.back().current_output()->largest.user_key();
}
};
void CompactionJob::AggregateStatistics() {
for (SubCompactionState& sc : compact_->sub_compact_states) {
compact_->total_bytes += sc.total_bytes;
compact_->num_input_records += sc.num_input_records;
compact_->num_output_records += sc.num_output_records;
if (compaction_job_stats_) {
compaction_job_stats_->Add(sc.compaction_job_stats);
}
}
}
CompactionJob::CompactionJob(
int job_id, Compaction* compaction, const DBOptions& db_options,
const EnvOptions& env_options, VersionSet* versions,
std::atomic<bool>* shutting_down, LogBuffer* log_buffer,
Directory* db_directory, Directory* output_directory, Statistics* stats,
std::vector<SequenceNumber> existing_snapshots,
std::shared_ptr<Cache> table_cache, EventLogger* event_logger,
bool paranoid_file_checks, bool measure_io_stats, const std::string& dbname,
CompactionJobStats* compaction_job_stats)
: job_id_(job_id),
compact_(new CompactionState(compaction)),
compaction_job_stats_(compaction_job_stats),
compaction_stats_(1),
dbname_(dbname),
db_options_(db_options),
env_options_(env_options),
env_(db_options.env),
versions_(versions),
shutting_down_(shutting_down),
log_buffer_(log_buffer),
db_directory_(db_directory),
output_directory_(output_directory),
stats_(stats),
existing_snapshots_(std::move(existing_snapshots)),
table_cache_(std::move(table_cache)),
event_logger_(event_logger),
paranoid_file_checks_(paranoid_file_checks),
measure_io_stats_(measure_io_stats) {
assert(log_buffer_ != nullptr);
ThreadStatusUtil::SetColumnFamily(compact_->compaction->column_family_data());
Allow GetThreadList() to report operation stage. Summary: Allow GetThreadList() to report operation stage. Test Plan: ./thread_list_test ./db_bench --benchmarks=fillrandom --num=100000 --threads=40 \ --max_background_compactions=10 --max_background_flushes=3 \ --thread_status_per_interval=1000 --key_size=16 --value_size=1000 \ --num_column_families=10 export ROCKSDB_TESTS=ThreadStatus ./db_test Sample output ThreadID ThreadType cfName Operation OP_StartTime ElapsedTime Stage State 140116265861184 Low Pri 140116270055488 Low Pri 140116274249792 High Pri column_family_name_000005 Flush 2015/03/10-14:58:11 0 us FlushJob::WriteLevel0Table 140116400078912 Low Pri column_family_name_000004 Compaction 2015/03/10-14:58:11 0 us CompactionJob::FinishCompactionOutputFile 140116358135872 Low Pri column_family_name_000006 Compaction 2015/03/10-14:58:10 1 us CompactionJob::FinishCompactionOutputFile 140116341358656 Low Pri 140116295221312 High Pri default Flush 2015/03/10-14:58:11 0 us FlushJob::WriteLevel0Table 140116324581440 Low Pri column_family_name_000009 Compaction 2015/03/10-14:58:11 0 us CompactionJob::ProcessKeyValueCompaction 140116278444096 Low Pri 140116299415616 Low Pri column_family_name_000008 Compaction 2015/03/10-14:58:11 0 us CompactionJob::FinishCompactionOutputFile 140116291027008 High Pri column_family_name_000001 Flush 2015/03/10-14:58:11 0 us FlushJob::WriteLevel0Table 140116286832704 Low Pri column_family_name_000002 Compaction 2015/03/10-14:58:11 0 us CompactionJob::FinishCompactionOutputFile 140116282638400 Low Pri Reviewers: rven, igor, sdong Reviewed By: sdong Subscribers: dhruba, leveldb Differential Revision: https://reviews.facebook.net/D34683
10 years ago
ThreadStatusUtil::SetThreadOperation(ThreadStatus::OP_COMPACTION);
Allow GetThreadList() to report basic compaction operation properties. Summary: Now we're able to show more details about a compaction in GetThreadList() :) This patch allows GetThreadList() to report basic compaction operation properties. Basic compaction properties include: 1. job id 2. compaction input / output level 3. compaction property flags (is_manual, is_deletion, .. etc) 4. total input bytes 5. the number of bytes has been read currently. 6. the number of bytes has been written currently. Flush operation properties will be done in a seperate diff. Test Plan: /db_bench --threads=30 --num=1000000 --benchmarks=fillrandom --thread_status_per_interval=1 Sample output of tracking same job: ThreadID ThreadType cfName Operation ElapsedTime Stage State OperationProperties 140664171987072 Low Pri default Compaction 31.357 ms CompactionJob::FinishCompactionOutputFile BaseInputLevel 1 | BytesRead 2264663 | BytesWritten 1934241 | IsDeletion 0 | IsManual 0 | IsTrivialMove 0 | JobID 277 | OutputLevel 2 | TotalInputBytes 3964158 | ThreadID ThreadType cfName Operation ElapsedTime Stage State OperationProperties 140664171987072 Low Pri default Compaction 59.440 ms CompactionJob::FinishCompactionOutputFile BaseInputLevel 1 | BytesRead 2264663 | BytesWritten 1934241 | IsDeletion 0 | IsManual 0 | IsTrivialMove 0 | JobID 277 | OutputLevel 2 | TotalInputBytes 3964158 | ThreadID ThreadType cfName Operation ElapsedTime Stage State OperationProperties 140664171987072 Low Pri default Compaction 226.375 ms CompactionJob::Install BaseInputLevel 1 | BytesRead 3958013 | BytesWritten 3621940 | IsDeletion 0 | IsManual 0 | IsTrivialMove 0 | JobID 277 | OutputLevel 2 | TotalInputBytes 3964158 | Reviewers: sdong, rven, igor Reviewed By: igor Subscribers: dhruba, leveldb Differential Revision: https://reviews.facebook.net/D37653
10 years ago
ReportStartedCompaction(compaction);
Allow GetThreadList() to report operation stage. Summary: Allow GetThreadList() to report operation stage. Test Plan: ./thread_list_test ./db_bench --benchmarks=fillrandom --num=100000 --threads=40 \ --max_background_compactions=10 --max_background_flushes=3 \ --thread_status_per_interval=1000 --key_size=16 --value_size=1000 \ --num_column_families=10 export ROCKSDB_TESTS=ThreadStatus ./db_test Sample output ThreadID ThreadType cfName Operation OP_StartTime ElapsedTime Stage State 140116265861184 Low Pri 140116270055488 Low Pri 140116274249792 High Pri column_family_name_000005 Flush 2015/03/10-14:58:11 0 us FlushJob::WriteLevel0Table 140116400078912 Low Pri column_family_name_000004 Compaction 2015/03/10-14:58:11 0 us CompactionJob::FinishCompactionOutputFile 140116358135872 Low Pri column_family_name_000006 Compaction 2015/03/10-14:58:10 1 us CompactionJob::FinishCompactionOutputFile 140116341358656 Low Pri 140116295221312 High Pri default Flush 2015/03/10-14:58:11 0 us FlushJob::WriteLevel0Table 140116324581440 Low Pri column_family_name_000009 Compaction 2015/03/10-14:58:11 0 us CompactionJob::ProcessKeyValueCompaction 140116278444096 Low Pri 140116299415616 Low Pri column_family_name_000008 Compaction 2015/03/10-14:58:11 0 us CompactionJob::FinishCompactionOutputFile 140116291027008 High Pri column_family_name_000001 Flush 2015/03/10-14:58:11 0 us FlushJob::WriteLevel0Table 140116286832704 Low Pri column_family_name_000002 Compaction 2015/03/10-14:58:11 0 us CompactionJob::FinishCompactionOutputFile 140116282638400 Low Pri Reviewers: rven, igor, sdong Reviewed By: sdong Subscribers: dhruba, leveldb Differential Revision: https://reviews.facebook.net/D34683
10 years ago
}
CompactionJob::~CompactionJob() {
assert(compact_ == nullptr);
ThreadStatusUtil::ResetThreadStatus();
}
Allow GetThreadList() to report basic compaction operation properties. Summary: Now we're able to show more details about a compaction in GetThreadList() :) This patch allows GetThreadList() to report basic compaction operation properties. Basic compaction properties include: 1. job id 2. compaction input / output level 3. compaction property flags (is_manual, is_deletion, .. etc) 4. total input bytes 5. the number of bytes has been read currently. 6. the number of bytes has been written currently. Flush operation properties will be done in a seperate diff. Test Plan: /db_bench --threads=30 --num=1000000 --benchmarks=fillrandom --thread_status_per_interval=1 Sample output of tracking same job: ThreadID ThreadType cfName Operation ElapsedTime Stage State OperationProperties 140664171987072 Low Pri default Compaction 31.357 ms CompactionJob::FinishCompactionOutputFile BaseInputLevel 1 | BytesRead 2264663 | BytesWritten 1934241 | IsDeletion 0 | IsManual 0 | IsTrivialMove 0 | JobID 277 | OutputLevel 2 | TotalInputBytes 3964158 | ThreadID ThreadType cfName Operation ElapsedTime Stage State OperationProperties 140664171987072 Low Pri default Compaction 59.440 ms CompactionJob::FinishCompactionOutputFile BaseInputLevel 1 | BytesRead 2264663 | BytesWritten 1934241 | IsDeletion 0 | IsManual 0 | IsTrivialMove 0 | JobID 277 | OutputLevel 2 | TotalInputBytes 3964158 | ThreadID ThreadType cfName Operation ElapsedTime Stage State OperationProperties 140664171987072 Low Pri default Compaction 226.375 ms CompactionJob::Install BaseInputLevel 1 | BytesRead 3958013 | BytesWritten 3621940 | IsDeletion 0 | IsManual 0 | IsTrivialMove 0 | JobID 277 | OutputLevel 2 | TotalInputBytes 3964158 | Reviewers: sdong, rven, igor Reviewed By: igor Subscribers: dhruba, leveldb Differential Revision: https://reviews.facebook.net/D37653
10 years ago
void CompactionJob::ReportStartedCompaction(
Compaction* compaction) {
ThreadStatusUtil::SetColumnFamily(
compact_->compaction->column_family_data());
ThreadStatusUtil::SetThreadOperationProperty(
ThreadStatus::COMPACTION_JOB_ID,
job_id_);
ThreadStatusUtil::SetThreadOperationProperty(
ThreadStatus::COMPACTION_INPUT_OUTPUT_LEVEL,
(static_cast<uint64_t>(compact_->compaction->start_level()) << 32) +
compact_->compaction->output_level());
// In the current design, a CompactionJob is always created
// for non-trivial compaction.
assert(compaction->IsTrivialMove() == false ||
compaction->is_manual_compaction() == true);
Allow GetThreadList() to report basic compaction operation properties. Summary: Now we're able to show more details about a compaction in GetThreadList() :) This patch allows GetThreadList() to report basic compaction operation properties. Basic compaction properties include: 1. job id 2. compaction input / output level 3. compaction property flags (is_manual, is_deletion, .. etc) 4. total input bytes 5. the number of bytes has been read currently. 6. the number of bytes has been written currently. Flush operation properties will be done in a seperate diff. Test Plan: /db_bench --threads=30 --num=1000000 --benchmarks=fillrandom --thread_status_per_interval=1 Sample output of tracking same job: ThreadID ThreadType cfName Operation ElapsedTime Stage State OperationProperties 140664171987072 Low Pri default Compaction 31.357 ms CompactionJob::FinishCompactionOutputFile BaseInputLevel 1 | BytesRead 2264663 | BytesWritten 1934241 | IsDeletion 0 | IsManual 0 | IsTrivialMove 0 | JobID 277 | OutputLevel 2 | TotalInputBytes 3964158 | ThreadID ThreadType cfName Operation ElapsedTime Stage State OperationProperties 140664171987072 Low Pri default Compaction 59.440 ms CompactionJob::FinishCompactionOutputFile BaseInputLevel 1 | BytesRead 2264663 | BytesWritten 1934241 | IsDeletion 0 | IsManual 0 | IsTrivialMove 0 | JobID 277 | OutputLevel 2 | TotalInputBytes 3964158 | ThreadID ThreadType cfName Operation ElapsedTime Stage State OperationProperties 140664171987072 Low Pri default Compaction 226.375 ms CompactionJob::Install BaseInputLevel 1 | BytesRead 3958013 | BytesWritten 3621940 | IsDeletion 0 | IsManual 0 | IsTrivialMove 0 | JobID 277 | OutputLevel 2 | TotalInputBytes 3964158 | Reviewers: sdong, rven, igor Reviewed By: igor Subscribers: dhruba, leveldb Differential Revision: https://reviews.facebook.net/D37653
10 years ago
ThreadStatusUtil::SetThreadOperationProperty(
ThreadStatus::COMPACTION_PROP_FLAGS,
compaction->is_manual_compaction() +
(compaction->deletion_compaction() << 1));
Allow GetThreadList() to report basic compaction operation properties. Summary: Now we're able to show more details about a compaction in GetThreadList() :) This patch allows GetThreadList() to report basic compaction operation properties. Basic compaction properties include: 1. job id 2. compaction input / output level 3. compaction property flags (is_manual, is_deletion, .. etc) 4. total input bytes 5. the number of bytes has been read currently. 6. the number of bytes has been written currently. Flush operation properties will be done in a seperate diff. Test Plan: /db_bench --threads=30 --num=1000000 --benchmarks=fillrandom --thread_status_per_interval=1 Sample output of tracking same job: ThreadID ThreadType cfName Operation ElapsedTime Stage State OperationProperties 140664171987072 Low Pri default Compaction 31.357 ms CompactionJob::FinishCompactionOutputFile BaseInputLevel 1 | BytesRead 2264663 | BytesWritten 1934241 | IsDeletion 0 | IsManual 0 | IsTrivialMove 0 | JobID 277 | OutputLevel 2 | TotalInputBytes 3964158 | ThreadID ThreadType cfName Operation ElapsedTime Stage State OperationProperties 140664171987072 Low Pri default Compaction 59.440 ms CompactionJob::FinishCompactionOutputFile BaseInputLevel 1 | BytesRead 2264663 | BytesWritten 1934241 | IsDeletion 0 | IsManual 0 | IsTrivialMove 0 | JobID 277 | OutputLevel 2 | TotalInputBytes 3964158 | ThreadID ThreadType cfName Operation ElapsedTime Stage State OperationProperties 140664171987072 Low Pri default Compaction 226.375 ms CompactionJob::Install BaseInputLevel 1 | BytesRead 3958013 | BytesWritten 3621940 | IsDeletion 0 | IsManual 0 | IsTrivialMove 0 | JobID 277 | OutputLevel 2 | TotalInputBytes 3964158 | Reviewers: sdong, rven, igor Reviewed By: igor Subscribers: dhruba, leveldb Differential Revision: https://reviews.facebook.net/D37653
10 years ago
ThreadStatusUtil::SetThreadOperationProperty(
ThreadStatus::COMPACTION_TOTAL_INPUT_BYTES,
compaction->CalculateTotalInputSize());
IOSTATS_RESET(bytes_written);
IOSTATS_RESET(bytes_read);
ThreadStatusUtil::SetThreadOperationProperty(
ThreadStatus::COMPACTION_BYTES_WRITTEN, 0);
ThreadStatusUtil::SetThreadOperationProperty(
ThreadStatus::COMPACTION_BYTES_READ, 0);
// Set the thread operation after operation properties
// to ensure GetThreadList() can always show them all together.
ThreadStatusUtil::SetThreadOperation(
ThreadStatus::OP_COMPACTION);
if (compaction_job_stats_) {
compaction_job_stats_->is_manual_compaction =
compaction->is_manual_compaction();
}
Allow GetThreadList() to report basic compaction operation properties. Summary: Now we're able to show more details about a compaction in GetThreadList() :) This patch allows GetThreadList() to report basic compaction operation properties. Basic compaction properties include: 1. job id 2. compaction input / output level 3. compaction property flags (is_manual, is_deletion, .. etc) 4. total input bytes 5. the number of bytes has been read currently. 6. the number of bytes has been written currently. Flush operation properties will be done in a seperate diff. Test Plan: /db_bench --threads=30 --num=1000000 --benchmarks=fillrandom --thread_status_per_interval=1 Sample output of tracking same job: ThreadID ThreadType cfName Operation ElapsedTime Stage State OperationProperties 140664171987072 Low Pri default Compaction 31.357 ms CompactionJob::FinishCompactionOutputFile BaseInputLevel 1 | BytesRead 2264663 | BytesWritten 1934241 | IsDeletion 0 | IsManual 0 | IsTrivialMove 0 | JobID 277 | OutputLevel 2 | TotalInputBytes 3964158 | ThreadID ThreadType cfName Operation ElapsedTime Stage State OperationProperties 140664171987072 Low Pri default Compaction 59.440 ms CompactionJob::FinishCompactionOutputFile BaseInputLevel 1 | BytesRead 2264663 | BytesWritten 1934241 | IsDeletion 0 | IsManual 0 | IsTrivialMove 0 | JobID 277 | OutputLevel 2 | TotalInputBytes 3964158 | ThreadID ThreadType cfName Operation ElapsedTime Stage State OperationProperties 140664171987072 Low Pri default Compaction 226.375 ms CompactionJob::Install BaseInputLevel 1 | BytesRead 3958013 | BytesWritten 3621940 | IsDeletion 0 | IsManual 0 | IsTrivialMove 0 | JobID 277 | OutputLevel 2 | TotalInputBytes 3964158 | Reviewers: sdong, rven, igor Reviewed By: igor Subscribers: dhruba, leveldb Differential Revision: https://reviews.facebook.net/D37653
10 years ago
}
void CompactionJob::Prepare() {
Allow GetThreadList() to report operation stage. Summary: Allow GetThreadList() to report operation stage. Test Plan: ./thread_list_test ./db_bench --benchmarks=fillrandom --num=100000 --threads=40 \ --max_background_compactions=10 --max_background_flushes=3 \ --thread_status_per_interval=1000 --key_size=16 --value_size=1000 \ --num_column_families=10 export ROCKSDB_TESTS=ThreadStatus ./db_test Sample output ThreadID ThreadType cfName Operation OP_StartTime ElapsedTime Stage State 140116265861184 Low Pri 140116270055488 Low Pri 140116274249792 High Pri column_family_name_000005 Flush 2015/03/10-14:58:11 0 us FlushJob::WriteLevel0Table 140116400078912 Low Pri column_family_name_000004 Compaction 2015/03/10-14:58:11 0 us CompactionJob::FinishCompactionOutputFile 140116358135872 Low Pri column_family_name_000006 Compaction 2015/03/10-14:58:10 1 us CompactionJob::FinishCompactionOutputFile 140116341358656 Low Pri 140116295221312 High Pri default Flush 2015/03/10-14:58:11 0 us FlushJob::WriteLevel0Table 140116324581440 Low Pri column_family_name_000009 Compaction 2015/03/10-14:58:11 0 us CompactionJob::ProcessKeyValueCompaction 140116278444096 Low Pri 140116299415616 Low Pri column_family_name_000008 Compaction 2015/03/10-14:58:11 0 us CompactionJob::FinishCompactionOutputFile 140116291027008 High Pri column_family_name_000001 Flush 2015/03/10-14:58:11 0 us FlushJob::WriteLevel0Table 140116286832704 Low Pri column_family_name_000002 Compaction 2015/03/10-14:58:11 0 us CompactionJob::FinishCompactionOutputFile 140116282638400 Low Pri Reviewers: rven, igor, sdong Reviewed By: sdong Subscribers: dhruba, leveldb Differential Revision: https://reviews.facebook.net/D34683
10 years ago
AutoThreadOperationStageUpdater stage_updater(
ThreadStatus::STAGE_COMPACTION_PREPARE);
// Generate file_levels_ for compaction berfore making Iterator
ColumnFamilyData* cfd = compact_->compaction->column_family_data();
assert(cfd != nullptr);
assert(cfd->current()->storage_info()->NumLevelFiles(
compact_->compaction->level()) > 0);
// Is this compaction producing files at the bottommost level?
bottommost_level_ = compact_->compaction->bottommost_level();
// Initialize subcompaction states
SequenceNumber earliest_snapshot;
SequenceNumber latest_snapshot = 0;
SequenceNumber visible_at_tip = 0;
if (existing_snapshots_.size() == 0) {
// optimize for fast path if there are no snapshots
visible_at_tip = versions_->LastSequence();
earliest_snapshot = visible_at_tip;
} else {
latest_snapshot = existing_snapshots_.back();
// Add the current seqno as the 'latest' virtual
// snapshot to the end of this list.
existing_snapshots_.push_back(versions_->LastSequence());
earliest_snapshot = existing_snapshots_[0];
}
InitializeSubCompactions(earliest_snapshot, visible_at_tip, latest_snapshot);
Parallelize L0-L1 Compaction: Restructure Compaction Job Summary: As of now compactions involving files from Level 0 and Level 1 are single threaded because the files in L0, although sorted, are not range partitioned like the other levels. This means that during L0-L1 compaction each file from L1 needs to be merged with potentially all the files from L0. This attempt to parallelize the L0-L1 compaction assigns a thread and a corresponding iterator to each L1 file that then considers only the key range found in that L1 file and only the L0 files that have those keys (and only the specific portion of those L0 files in which those keys are found). In this way the overlap is minimized and potentially eliminated between different iterators focusing on the same files. The first step is to restructure the compaction logic to break L0-L1 compactions into multiple, smaller, sequential compactions. Eventually each of these smaller jobs will be run simultaneously. Areas to pay extra attention to are # Correct aggregation of compaction job statistics across multiple threads # Proper opening/closing of output files (make sure each thread's is unique) # Keys that span multiple L1 files # Skewed distributions of keys within L0 files Test Plan: Make and run db_test (newer version has separate compaction tests) and compaction_job_stats_test Reviewers: igor, noetzli, anthony, sdong, yhchiang Reviewed By: yhchiang Subscribers: MarkCallaghan, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D42699
9 years ago
}
// For L0-L1 compaction, iterators work in parallel by processing
// different subsets of the full key range. This function sets up
// the local states used by each of these subcompactions during
// their execution
void CompactionJob::InitializeSubCompactions(const SequenceNumber& earliest,
const SequenceNumber& visible,
const SequenceNumber& latest) {
Compaction* c = compact_->compaction;
auto& bounds = sub_compaction_boundaries_;
Parallelize L0-L1 Compaction: Restructure Compaction Job Summary: As of now compactions involving files from Level 0 and Level 1 are single threaded because the files in L0, although sorted, are not range partitioned like the other levels. This means that during L0-L1 compaction each file from L1 needs to be merged with potentially all the files from L0. This attempt to parallelize the L0-L1 compaction assigns a thread and a corresponding iterator to each L1 file that then considers only the key range found in that L1 file and only the L0 files that have those keys (and only the specific portion of those L0 files in which those keys are found). In this way the overlap is minimized and potentially eliminated between different iterators focusing on the same files. The first step is to restructure the compaction logic to break L0-L1 compactions into multiple, smaller, sequential compactions. Eventually each of these smaller jobs will be run simultaneously. Areas to pay extra attention to are # Correct aggregation of compaction job statistics across multiple threads # Proper opening/closing of output files (make sure each thread's is unique) # Keys that span multiple L1 files # Skewed distributions of keys within L0 files Test Plan: Make and run db_test (newer version has separate compaction tests) and compaction_job_stats_test Reviewers: igor, noetzli, anthony, sdong, yhchiang Reviewed By: yhchiang Subscribers: MarkCallaghan, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D42699
9 years ago
if (c->IsSubCompaction()) {
// TODO(aekmekji): take the option num_subcompactions into account
// when dividing up the key range between multiple iterators instead
// of just assigning each iterator one L1 file's key range
auto* cmp = c->column_family_data()->user_comparator();
Parallelize L0-L1 Compaction: Restructure Compaction Job Summary: As of now compactions involving files from Level 0 and Level 1 are single threaded because the files in L0, although sorted, are not range partitioned like the other levels. This means that during L0-L1 compaction each file from L1 needs to be merged with potentially all the files from L0. This attempt to parallelize the L0-L1 compaction assigns a thread and a corresponding iterator to each L1 file that then considers only the key range found in that L1 file and only the L0 files that have those keys (and only the specific portion of those L0 files in which those keys are found). In this way the overlap is minimized and potentially eliminated between different iterators focusing on the same files. The first step is to restructure the compaction logic to break L0-L1 compactions into multiple, smaller, sequential compactions. Eventually each of these smaller jobs will be run simultaneously. Areas to pay extra attention to are # Correct aggregation of compaction job statistics across multiple threads # Proper opening/closing of output files (make sure each thread's is unique) # Keys that span multiple L1 files # Skewed distributions of keys within L0 files Test Plan: Make and run db_test (newer version has separate compaction tests) and compaction_job_stats_test Reviewers: igor, noetzli, anthony, sdong, yhchiang Reviewed By: yhchiang Subscribers: MarkCallaghan, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D42699
9 years ago
for (size_t which = 0; which < c->num_input_levels(); which++) {
if (c->level(which) == 1) {
const LevelFilesBrief* flevel = c->input_levels(which);
size_t num_files = flevel->num_files;
if (num_files > 1) {
auto& files = flevel->files;
Slice global_min = ExtractUserKey(files[0].smallest_key);
Slice global_max = ExtractUserKey(files[num_files - 1].largest_key);
for (size_t i = 1; i < num_files; i++) {
// Make sure the smallest key in two consecutive L1 files are
// unique before adding the smallest key as a boundary. Also ensure
// that the boundary won't lead to an empty subcompaction (happens
// if the boundary == the smallest or largest key)
Slice s1 = ExtractUserKey(files[i].smallest_key);
Slice s2 = i == num_files - 1
? Slice()
: ExtractUserKey(files[i + 1].smallest_key);
if ( (i == num_files - 1 && cmp->Compare(s1, global_max) < 0)
|| (i < num_files - 1 && cmp->Compare(s1, s2) < 0 &&
cmp->Compare(s1, global_min) > 0)) {
bounds.emplace_back(s1);
}
Parallelize L0-L1 Compaction: Restructure Compaction Job Summary: As of now compactions involving files from Level 0 and Level 1 are single threaded because the files in L0, although sorted, are not range partitioned like the other levels. This means that during L0-L1 compaction each file from L1 needs to be merged with potentially all the files from L0. This attempt to parallelize the L0-L1 compaction assigns a thread and a corresponding iterator to each L1 file that then considers only the key range found in that L1 file and only the L0 files that have those keys (and only the specific portion of those L0 files in which those keys are found). In this way the overlap is minimized and potentially eliminated between different iterators focusing on the same files. The first step is to restructure the compaction logic to break L0-L1 compactions into multiple, smaller, sequential compactions. Eventually each of these smaller jobs will be run simultaneously. Areas to pay extra attention to are # Correct aggregation of compaction job statistics across multiple threads # Proper opening/closing of output files (make sure each thread's is unique) # Keys that span multiple L1 files # Skewed distributions of keys within L0 files Test Plan: Make and run db_test (newer version has separate compaction tests) and compaction_job_stats_test Reviewers: igor, noetzli, anthony, sdong, yhchiang Reviewed By: yhchiang Subscribers: MarkCallaghan, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D42699
9 years ago
}
}
break;
}
}
}
// Note: it's necessary for the first iterator sub-range to have
// start == nullptr and for the last to have end == nullptr
for (size_t i = 0; i <= bounds.size(); i++) {
Slice *start = i == 0 ? nullptr : &bounds[i - 1];
Slice *end = i == bounds.size() ? nullptr : &bounds[i];
compact_->sub_compact_states.emplace_back(compact_->compaction, start,
end, earliest, visible, latest);
}
}
Status CompactionJob::Run() {
Allow GetThreadList() to report operation stage. Summary: Allow GetThreadList() to report operation stage. Test Plan: ./thread_list_test ./db_bench --benchmarks=fillrandom --num=100000 --threads=40 \ --max_background_compactions=10 --max_background_flushes=3 \ --thread_status_per_interval=1000 --key_size=16 --value_size=1000 \ --num_column_families=10 export ROCKSDB_TESTS=ThreadStatus ./db_test Sample output ThreadID ThreadType cfName Operation OP_StartTime ElapsedTime Stage State 140116265861184 Low Pri 140116270055488 Low Pri 140116274249792 High Pri column_family_name_000005 Flush 2015/03/10-14:58:11 0 us FlushJob::WriteLevel0Table 140116400078912 Low Pri column_family_name_000004 Compaction 2015/03/10-14:58:11 0 us CompactionJob::FinishCompactionOutputFile 140116358135872 Low Pri column_family_name_000006 Compaction 2015/03/10-14:58:10 1 us CompactionJob::FinishCompactionOutputFile 140116341358656 Low Pri 140116295221312 High Pri default Flush 2015/03/10-14:58:11 0 us FlushJob::WriteLevel0Table 140116324581440 Low Pri column_family_name_000009 Compaction 2015/03/10-14:58:11 0 us CompactionJob::ProcessKeyValueCompaction 140116278444096 Low Pri 140116299415616 Low Pri column_family_name_000008 Compaction 2015/03/10-14:58:11 0 us CompactionJob::FinishCompactionOutputFile 140116291027008 High Pri column_family_name_000001 Flush 2015/03/10-14:58:11 0 us FlushJob::WriteLevel0Table 140116286832704 Low Pri column_family_name_000002 Compaction 2015/03/10-14:58:11 0 us CompactionJob::FinishCompactionOutputFile 140116282638400 Low Pri Reviewers: rven, igor, sdong Reviewed By: sdong Subscribers: dhruba, leveldb Differential Revision: https://reviews.facebook.net/D34683
10 years ago
AutoThreadOperationStageUpdater stage_updater(
ThreadStatus::STAGE_COMPACTION_RUN);
TEST_SYNC_POINT("CompactionJob::Run():Start");
log_buffer_->FlushBufferToLog();
LogCompaction();
// Run each subcompaction sequentially
const uint64_t start_micros = env_->NowMicros();
for (size_t i = 0; i < compact_->sub_compact_states.size(); i++) {
ProcessKeyValueCompaction(&compact_->sub_compact_states[i]);
}
compaction_stats_.micros = env_->NowMicros() - start_micros;
MeasureTime(stats_, COMPACTION_TIME, compaction_stats_.micros);
Parallelize L0-L1 Compaction: Restructure Compaction Job Summary: As of now compactions involving files from Level 0 and Level 1 are single threaded because the files in L0, although sorted, are not range partitioned like the other levels. This means that during L0-L1 compaction each file from L1 needs to be merged with potentially all the files from L0. This attempt to parallelize the L0-L1 compaction assigns a thread and a corresponding iterator to each L1 file that then considers only the key range found in that L1 file and only the L0 files that have those keys (and only the specific portion of those L0 files in which those keys are found). In this way the overlap is minimized and potentially eliminated between different iterators focusing on the same files. The first step is to restructure the compaction logic to break L0-L1 compactions into multiple, smaller, sequential compactions. Eventually each of these smaller jobs will be run simultaneously. Areas to pay extra attention to are # Correct aggregation of compaction job statistics across multiple threads # Proper opening/closing of output files (make sure each thread's is unique) # Keys that span multiple L1 files # Skewed distributions of keys within L0 files Test Plan: Make and run db_test (newer version has separate compaction tests) and compaction_job_stats_test Reviewers: igor, noetzli, anthony, sdong, yhchiang Reviewed By: yhchiang Subscribers: MarkCallaghan, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D42699
9 years ago
// Determine if any of the subcompactions failed
Status status;
for (const auto& state : compact_->sub_compact_states) {
if (!state.status.ok()) {
status = state.status;
Parallelize L0-L1 Compaction: Restructure Compaction Job Summary: As of now compactions involving files from Level 0 and Level 1 are single threaded because the files in L0, although sorted, are not range partitioned like the other levels. This means that during L0-L1 compaction each file from L1 needs to be merged with potentially all the files from L0. This attempt to parallelize the L0-L1 compaction assigns a thread and a corresponding iterator to each L1 file that then considers only the key range found in that L1 file and only the L0 files that have those keys (and only the specific portion of those L0 files in which those keys are found). In this way the overlap is minimized and potentially eliminated between different iterators focusing on the same files. The first step is to restructure the compaction logic to break L0-L1 compactions into multiple, smaller, sequential compactions. Eventually each of these smaller jobs will be run simultaneously. Areas to pay extra attention to are # Correct aggregation of compaction job statistics across multiple threads # Proper opening/closing of output files (make sure each thread's is unique) # Keys that span multiple L1 files # Skewed distributions of keys within L0 files Test Plan: Make and run db_test (newer version has separate compaction tests) and compaction_job_stats_test Reviewers: igor, noetzli, anthony, sdong, yhchiang Reviewed By: yhchiang Subscribers: MarkCallaghan, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D42699
9 years ago
break;
}
}
// Finish up all book-keeping to unify the subcompaction results
AggregateStatistics();
Parallelize L0-L1 Compaction: Restructure Compaction Job Summary: As of now compactions involving files from Level 0 and Level 1 are single threaded because the files in L0, although sorted, are not range partitioned like the other levels. This means that during L0-L1 compaction each file from L1 needs to be merged with potentially all the files from L0. This attempt to parallelize the L0-L1 compaction assigns a thread and a corresponding iterator to each L1 file that then considers only the key range found in that L1 file and only the L0 files that have those keys (and only the specific portion of those L0 files in which those keys are found). In this way the overlap is minimized and potentially eliminated between different iterators focusing on the same files. The first step is to restructure the compaction logic to break L0-L1 compactions into multiple, smaller, sequential compactions. Eventually each of these smaller jobs will be run simultaneously. Areas to pay extra attention to are # Correct aggregation of compaction job statistics across multiple threads # Proper opening/closing of output files (make sure each thread's is unique) # Keys that span multiple L1 files # Skewed distributions of keys within L0 files Test Plan: Make and run db_test (newer version has separate compaction tests) and compaction_job_stats_test Reviewers: igor, noetzli, anthony, sdong, yhchiang Reviewed By: yhchiang Subscribers: MarkCallaghan, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D42699
9 years ago
UpdateCompactionStats();
RecordCompactionIOStats();
LogFlush(db_options_.info_log);
TEST_SYNC_POINT("CompactionJob::Run():End");
compact_->status = status;
Parallelize L0-L1 Compaction: Restructure Compaction Job Summary: As of now compactions involving files from Level 0 and Level 1 are single threaded because the files in L0, although sorted, are not range partitioned like the other levels. This means that during L0-L1 compaction each file from L1 needs to be merged with potentially all the files from L0. This attempt to parallelize the L0-L1 compaction assigns a thread and a corresponding iterator to each L1 file that then considers only the key range found in that L1 file and only the L0 files that have those keys (and only the specific portion of those L0 files in which those keys are found). In this way the overlap is minimized and potentially eliminated between different iterators focusing on the same files. The first step is to restructure the compaction logic to break L0-L1 compactions into multiple, smaller, sequential compactions. Eventually each of these smaller jobs will be run simultaneously. Areas to pay extra attention to are # Correct aggregation of compaction job statistics across multiple threads # Proper opening/closing of output files (make sure each thread's is unique) # Keys that span multiple L1 files # Skewed distributions of keys within L0 files Test Plan: Make and run db_test (newer version has separate compaction tests) and compaction_job_stats_test Reviewers: igor, noetzli, anthony, sdong, yhchiang Reviewed By: yhchiang Subscribers: MarkCallaghan, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D42699
9 years ago
return status;
}
Status CompactionJob::Install(const MutableCFOptions& mutable_cf_options,
InstrumentedMutex* db_mutex) {
Allow GetThreadList() to report operation stage. Summary: Allow GetThreadList() to report operation stage. Test Plan: ./thread_list_test ./db_bench --benchmarks=fillrandom --num=100000 --threads=40 \ --max_background_compactions=10 --max_background_flushes=3 \ --thread_status_per_interval=1000 --key_size=16 --value_size=1000 \ --num_column_families=10 export ROCKSDB_TESTS=ThreadStatus ./db_test Sample output ThreadID ThreadType cfName Operation OP_StartTime ElapsedTime Stage State 140116265861184 Low Pri 140116270055488 Low Pri 140116274249792 High Pri column_family_name_000005 Flush 2015/03/10-14:58:11 0 us FlushJob::WriteLevel0Table 140116400078912 Low Pri column_family_name_000004 Compaction 2015/03/10-14:58:11 0 us CompactionJob::FinishCompactionOutputFile 140116358135872 Low Pri column_family_name_000006 Compaction 2015/03/10-14:58:10 1 us CompactionJob::FinishCompactionOutputFile 140116341358656 Low Pri 140116295221312 High Pri default Flush 2015/03/10-14:58:11 0 us FlushJob::WriteLevel0Table 140116324581440 Low Pri column_family_name_000009 Compaction 2015/03/10-14:58:11 0 us CompactionJob::ProcessKeyValueCompaction 140116278444096 Low Pri 140116299415616 Low Pri column_family_name_000008 Compaction 2015/03/10-14:58:11 0 us CompactionJob::FinishCompactionOutputFile 140116291027008 High Pri column_family_name_000001 Flush 2015/03/10-14:58:11 0 us FlushJob::WriteLevel0Table 140116286832704 Low Pri column_family_name_000002 Compaction 2015/03/10-14:58:11 0 us CompactionJob::FinishCompactionOutputFile 140116282638400 Low Pri Reviewers: rven, igor, sdong Reviewed By: sdong Subscribers: dhruba, leveldb Differential Revision: https://reviews.facebook.net/D34683
10 years ago
AutoThreadOperationStageUpdater stage_updater(
ThreadStatus::STAGE_COMPACTION_INSTALL);
db_mutex->AssertHeld();
Status status = compact_->status;
ColumnFamilyData* cfd = compact_->compaction->column_family_data();
cfd->internal_stats()->AddCompactionStats(
compact_->compaction->output_level(), compaction_stats_);
if (status.ok()) {
status = InstallCompactionResults(mutable_cf_options, db_mutex);
}
VersionStorageInfo::LevelSummaryStorage tmp;
auto vstorage = cfd->current()->storage_info();
const auto& stats = compaction_stats_;
LogToBuffer(
log_buffer_,
"[%s] compacted to: %s, MB/sec: %.1f rd, %.1f wr, level %d, "
"files in(%d, %d) out(%d) "
"MB in(%.1f, %.1f) out(%.1f), read-write-amplify(%.1f) "
"write-amplify(%.1f) %s, records in: %d, records dropped: %d\n",
cfd->GetName().c_str(), vstorage->LevelSummary(&tmp),
(stats.bytes_read_non_output_levels + stats.bytes_read_output_level) /
static_cast<double>(stats.micros),
stats.bytes_written / static_cast<double>(stats.micros),
compact_->compaction->output_level(),
stats.num_input_files_in_non_output_levels,
stats.num_input_files_in_output_level,
stats.num_output_files,
stats.bytes_read_non_output_levels / 1048576.0,
stats.bytes_read_output_level / 1048576.0,
stats.bytes_written / 1048576.0,
(stats.bytes_written + stats.bytes_read_output_level +
stats.bytes_read_non_output_levels) /
static_cast<double>(stats.bytes_read_non_output_levels),
stats.bytes_written /
static_cast<double>(stats.bytes_read_non_output_levels),
status.ToString().c_str(), stats.num_input_records,
stats.num_dropped_records);
UpdateCompactionJobStats(stats);
auto stream = event_logger_->LogToBuffer(log_buffer_);
stream << "job" << job_id_ << "event"
<< "compaction_finished"
<< "output_level" << compact_->compaction->output_level()
<< "num_output_files" << compact_->NumOutputFiles()
<< "total_output_size" << compact_->total_bytes
<< "num_input_records" << compact_->num_input_records
<< "num_output_records" << compact_->num_output_records;
if (measure_io_stats_ && compaction_job_stats_ != nullptr) {
stream << "file_write_nanos" << compaction_job_stats_->file_write_nanos;
stream << "file_range_sync_nanos"
<< compaction_job_stats_->file_range_sync_nanos;
stream << "file_fsync_nanos" << compaction_job_stats_->file_fsync_nanos;
stream << "file_prepare_write_nanos"
<< compaction_job_stats_->file_prepare_write_nanos;
}
stream << "lsm_state";
stream.StartArray();
for (int level = 0; level < vstorage->num_levels(); ++level) {
stream << vstorage->NumLevelFiles(level);
}
stream.EndArray();
CleanupCompaction();
return status;
}
void CompactionJob::ProcessKeyValueCompaction(SubCompactionState* sub_compact) {
assert(sub_compact != nullptr);
std::unique_ptr<Iterator> input_ptr(
versions_->MakeInputIterator(sub_compact->compaction));
Iterator* input = input_ptr.get();
Allow GetThreadList() to report operation stage. Summary: Allow GetThreadList() to report operation stage. Test Plan: ./thread_list_test ./db_bench --benchmarks=fillrandom --num=100000 --threads=40 \ --max_background_compactions=10 --max_background_flushes=3 \ --thread_status_per_interval=1000 --key_size=16 --value_size=1000 \ --num_column_families=10 export ROCKSDB_TESTS=ThreadStatus ./db_test Sample output ThreadID ThreadType cfName Operation OP_StartTime ElapsedTime Stage State 140116265861184 Low Pri 140116270055488 Low Pri 140116274249792 High Pri column_family_name_000005 Flush 2015/03/10-14:58:11 0 us FlushJob::WriteLevel0Table 140116400078912 Low Pri column_family_name_000004 Compaction 2015/03/10-14:58:11 0 us CompactionJob::FinishCompactionOutputFile 140116358135872 Low Pri column_family_name_000006 Compaction 2015/03/10-14:58:10 1 us CompactionJob::FinishCompactionOutputFile 140116341358656 Low Pri 140116295221312 High Pri default Flush 2015/03/10-14:58:11 0 us FlushJob::WriteLevel0Table 140116324581440 Low Pri column_family_name_000009 Compaction 2015/03/10-14:58:11 0 us CompactionJob::ProcessKeyValueCompaction 140116278444096 Low Pri 140116299415616 Low Pri column_family_name_000008 Compaction 2015/03/10-14:58:11 0 us CompactionJob::FinishCompactionOutputFile 140116291027008 High Pri column_family_name_000001 Flush 2015/03/10-14:58:11 0 us FlushJob::WriteLevel0Table 140116286832704 Low Pri column_family_name_000002 Compaction 2015/03/10-14:58:11 0 us CompactionJob::FinishCompactionOutputFile 140116282638400 Low Pri Reviewers: rven, igor, sdong Reviewed By: sdong Subscribers: dhruba, leveldb Differential Revision: https://reviews.facebook.net/D34683
10 years ago
AutoThreadOperationStageUpdater stage_updater(
ThreadStatus::STAGE_COMPACTION_PROCESS_KV);
// I/O measurement variables
PerfLevel prev_perf_level = PerfLevel::kEnableTime;
uint64_t prev_write_nanos = 0;
uint64_t prev_fsync_nanos = 0;
uint64_t prev_range_sync_nanos = 0;
uint64_t prev_prepare_write_nanos = 0;
if (measure_io_stats_) {
prev_perf_level = GetPerfLevel();
SetPerfLevel(PerfLevel::kEnableTime);
prev_write_nanos = iostats_context.write_nanos;
prev_fsync_nanos = iostats_context.fsync_nanos;
prev_range_sync_nanos = iostats_context.range_sync_nanos;
prev_prepare_write_nanos = iostats_context.prepare_write_nanos;
}
// Variables used inside the loop
Status status;
std::string compaction_filter_value;
ParsedInternalKey ikey;
IterKey current_user_key;
bool has_current_user_key = false;
IterKey delete_key;
SequenceNumber last_sequence_for_key = kMaxSequenceNumber;
SequenceNumber visible_in_snapshot = kMaxSequenceNumber;
ColumnFamilyData* cfd = sub_compact->compaction->column_family_data();
MergeHelper merge(cfd->user_comparator(), cfd->ioptions()->merge_operator,
db_options_.info_log.get(),
cfd->ioptions()->min_partial_merge_operands,
false /* internal key corruption is expected */);
auto compaction_filter = cfd->ioptions()->compaction_filter;
std::unique_ptr<CompactionFilter> compaction_filter_from_factory = nullptr;
if (compaction_filter == nullptr) {
compaction_filter_from_factory =
sub_compact->compaction->CreateCompactionFilter();
compaction_filter = compaction_filter_from_factory.get();
}
TEST_SYNC_POINT("CompactionJob::Run():Inprogress");
int64_t key_drop_user = 0;
int64_t key_drop_newer_entry = 0;
int64_t key_drop_obsolete = 0;
int64_t loop_cnt = 0;
StopWatchNano timer(env_, stats_ != nullptr);
uint64_t total_filter_time = 0;
Slice* start = sub_compact->start;
Slice* end = sub_compact->end;
Parallelize L0-L1 Compaction: Restructure Compaction Job Summary: As of now compactions involving files from Level 0 and Level 1 are single threaded because the files in L0, although sorted, are not range partitioned like the other levels. This means that during L0-L1 compaction each file from L1 needs to be merged with potentially all the files from L0. This attempt to parallelize the L0-L1 compaction assigns a thread and a corresponding iterator to each L1 file that then considers only the key range found in that L1 file and only the L0 files that have those keys (and only the specific portion of those L0 files in which those keys are found). In this way the overlap is minimized and potentially eliminated between different iterators focusing on the same files. The first step is to restructure the compaction logic to break L0-L1 compactions into multiple, smaller, sequential compactions. Eventually each of these smaller jobs will be run simultaneously. Areas to pay extra attention to are # Correct aggregation of compaction job statistics across multiple threads # Proper opening/closing of output files (make sure each thread's is unique) # Keys that span multiple L1 files # Skewed distributions of keys within L0 files Test Plan: Make and run db_test (newer version has separate compaction tests) and compaction_job_stats_test Reviewers: igor, noetzli, anthony, sdong, yhchiang Reviewed By: yhchiang Subscribers: MarkCallaghan, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D42699
9 years ago
if (start != nullptr) {
IterKey start_iter;
start_iter.SetInternalKey(*start, kMaxSequenceNumber, kValueTypeForSeek);
Slice start_key = start_iter.GetKey();
input->Seek(start_key);
} else {
input->SeekToFirst();
}
// TODO(noetzli): check whether we could check !shutting_down_->... only
// only occasionally (see diff D42687)
while (input->Valid() && !shutting_down_->load(std::memory_order_acquire) &&
!cfd->IsDropped() && status.ok()) {
Parallelize L0-L1 Compaction: Restructure Compaction Job Summary: As of now compactions involving files from Level 0 and Level 1 are single threaded because the files in L0, although sorted, are not range partitioned like the other levels. This means that during L0-L1 compaction each file from L1 needs to be merged with potentially all the files from L0. This attempt to parallelize the L0-L1 compaction assigns a thread and a corresponding iterator to each L1 file that then considers only the key range found in that L1 file and only the L0 files that have those keys (and only the specific portion of those L0 files in which those keys are found). In this way the overlap is minimized and potentially eliminated between different iterators focusing on the same files. The first step is to restructure the compaction logic to break L0-L1 compactions into multiple, smaller, sequential compactions. Eventually each of these smaller jobs will be run simultaneously. Areas to pay extra attention to are # Correct aggregation of compaction job statistics across multiple threads # Proper opening/closing of output files (make sure each thread's is unique) # Keys that span multiple L1 files # Skewed distributions of keys within L0 files Test Plan: Make and run db_test (newer version has separate compaction tests) and compaction_job_stats_test Reviewers: igor, noetzli, anthony, sdong, yhchiang Reviewed By: yhchiang Subscribers: MarkCallaghan, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D42699
9 years ago
Slice key = input->key();
Slice value = input->value();
// First check that the key is parseable before performing the comparison
// to determine if it's within the range we want. Parsing may fail if the
// key being passed in is a user key without any internal key component
Parallelize L0-L1 Compaction: Restructure Compaction Job Summary: As of now compactions involving files from Level 0 and Level 1 are single threaded because the files in L0, although sorted, are not range partitioned like the other levels. This means that during L0-L1 compaction each file from L1 needs to be merged with potentially all the files from L0. This attempt to parallelize the L0-L1 compaction assigns a thread and a corresponding iterator to each L1 file that then considers only the key range found in that L1 file and only the L0 files that have those keys (and only the specific portion of those L0 files in which those keys are found). In this way the overlap is minimized and potentially eliminated between different iterators focusing on the same files. The first step is to restructure the compaction logic to break L0-L1 compactions into multiple, smaller, sequential compactions. Eventually each of these smaller jobs will be run simultaneously. Areas to pay extra attention to are # Correct aggregation of compaction job statistics across multiple threads # Proper opening/closing of output files (make sure each thread's is unique) # Keys that span multiple L1 files # Skewed distributions of keys within L0 files Test Plan: Make and run db_test (newer version has separate compaction tests) and compaction_job_stats_test Reviewers: igor, noetzli, anthony, sdong, yhchiang Reviewed By: yhchiang Subscribers: MarkCallaghan, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D42699
9 years ago
if (!ParseInternalKey(key, &ikey)) {
// Do not hide error keys
// TODO: error key stays in db forever? Figure out the rationale
// v10 error v8 : we cannot hide v8 even though it's pretty obvious.
current_user_key.Clear();
has_current_user_key = false;
last_sequence_for_key = kMaxSequenceNumber;
visible_in_snapshot = kMaxSequenceNumber;
sub_compact->compaction_job_stats.num_corrupt_keys++;
Parallelize L0-L1 Compaction: Restructure Compaction Job Summary: As of now compactions involving files from Level 0 and Level 1 are single threaded because the files in L0, although sorted, are not range partitioned like the other levels. This means that during L0-L1 compaction each file from L1 needs to be merged with potentially all the files from L0. This attempt to parallelize the L0-L1 compaction assigns a thread and a corresponding iterator to each L1 file that then considers only the key range found in that L1 file and only the L0 files that have those keys (and only the specific portion of those L0 files in which those keys are found). In this way the overlap is minimized and potentially eliminated between different iterators focusing on the same files. The first step is to restructure the compaction logic to break L0-L1 compactions into multiple, smaller, sequential compactions. Eventually each of these smaller jobs will be run simultaneously. Areas to pay extra attention to are # Correct aggregation of compaction job statistics across multiple threads # Proper opening/closing of output files (make sure each thread's is unique) # Keys that span multiple L1 files # Skewed distributions of keys within L0 files Test Plan: Make and run db_test (newer version has separate compaction tests) and compaction_job_stats_test Reviewers: igor, noetzli, anthony, sdong, yhchiang Reviewed By: yhchiang Subscribers: MarkCallaghan, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D42699
9 years ago
status = WriteKeyValue(key, value, ikey, input->status(), sub_compact);
Parallelize L0-L1 Compaction: Restructure Compaction Job Summary: As of now compactions involving files from Level 0 and Level 1 are single threaded because the files in L0, although sorted, are not range partitioned like the other levels. This means that during L0-L1 compaction each file from L1 needs to be merged with potentially all the files from L0. This attempt to parallelize the L0-L1 compaction assigns a thread and a corresponding iterator to each L1 file that then considers only the key range found in that L1 file and only the L0 files that have those keys (and only the specific portion of those L0 files in which those keys are found). In this way the overlap is minimized and potentially eliminated between different iterators focusing on the same files. The first step is to restructure the compaction logic to break L0-L1 compactions into multiple, smaller, sequential compactions. Eventually each of these smaller jobs will be run simultaneously. Areas to pay extra attention to are # Correct aggregation of compaction job statistics across multiple threads # Proper opening/closing of output files (make sure each thread's is unique) # Keys that span multiple L1 files # Skewed distributions of keys within L0 files Test Plan: Make and run db_test (newer version has separate compaction tests) and compaction_job_stats_test Reviewers: igor, noetzli, anthony, sdong, yhchiang Reviewed By: yhchiang Subscribers: MarkCallaghan, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D42699
9 years ago
input->Next();
continue;
}
// If an end key (exclusive) is specified, check if the current key is
// >= than it and exit if it is because the iterator is out of its range
Parallelize L0-L1 Compaction: Restructure Compaction Job Summary: As of now compactions involving files from Level 0 and Level 1 are single threaded because the files in L0, although sorted, are not range partitioned like the other levels. This means that during L0-L1 compaction each file from L1 needs to be merged with potentially all the files from L0. This attempt to parallelize the L0-L1 compaction assigns a thread and a corresponding iterator to each L1 file that then considers only the key range found in that L1 file and only the L0 files that have those keys (and only the specific portion of those L0 files in which those keys are found). In this way the overlap is minimized and potentially eliminated between different iterators focusing on the same files. The first step is to restructure the compaction logic to break L0-L1 compactions into multiple, smaller, sequential compactions. Eventually each of these smaller jobs will be run simultaneously. Areas to pay extra attention to are # Correct aggregation of compaction job statistics across multiple threads # Proper opening/closing of output files (make sure each thread's is unique) # Keys that span multiple L1 files # Skewed distributions of keys within L0 files Test Plan: Make and run db_test (newer version has separate compaction tests) and compaction_job_stats_test Reviewers: igor, noetzli, anthony, sdong, yhchiang Reviewed By: yhchiang Subscribers: MarkCallaghan, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D42699
9 years ago
if (end != nullptr &&
cfd->user_comparator()->Compare(ikey.user_key, *end) >= 0) {
break;
}
sub_compact->num_input_records++;
if (++loop_cnt > 1000) {
RecordDroppedKeys(&key_drop_user, &key_drop_newer_entry,
&key_drop_obsolete,
&sub_compact->compaction_job_stats);
RecordCompactionIOStats();
loop_cnt = 0;
}
sub_compact->compaction_job_stats.total_input_raw_key_bytes += key.size();
sub_compact->compaction_job_stats.total_input_raw_value_bytes +=
value.size();
if (sub_compact->compaction->ShouldStopBefore(key) &&
sub_compact->builder != nullptr) {
status = FinishCompactionOutputFile(input->status(), sub_compact);
if (!status.ok()) {
break;
}
}
if (ikey.type == kTypeDeletion) {
sub_compact->compaction_job_stats.num_input_deletion_records++;
}
if (!has_current_user_key ||
cfd->user_comparator()->Compare(ikey.user_key,
current_user_key.GetKey()) != 0) {
// First occurrence of this user key
current_user_key.SetKey(ikey.user_key);
has_current_user_key = true;
last_sequence_for_key = kMaxSequenceNumber;
visible_in_snapshot = kMaxSequenceNumber;
// apply the compaction filter to the first occurrence of the user key
if (compaction_filter && ikey.type == kTypeValue &&
(sub_compact->visible_at_tip ||
ikey.sequence > sub_compact->latest_snapshot)) {
// If the user has specified a compaction filter and the sequence
// number is greater than any external snapshot, then invoke the
// filter. If the return value of the compaction filter is true,
// replace the entry with a deletion marker.
bool value_changed = false;
compaction_filter_value.clear();
if (stats_ != nullptr) {
timer.Start();
}
bool to_delete = compaction_filter->Filter(
sub_compact->compaction->level(), ikey.user_key, value,
&compaction_filter_value, &value_changed);
total_filter_time += timer.ElapsedNanos();
if (to_delete) {
// make a copy of the original key and convert it to a delete
delete_key.SetInternalKey(ExtractUserKey(key), ikey.sequence,
kTypeDeletion);
// anchor the key again
key = delete_key.GetKey();
// needed because ikey is backed by key
ParseInternalKey(key, &ikey);
// no value associated with delete
value.clear();
++key_drop_user;
} else if (value_changed) {
value = compaction_filter_value;
}
}
}
// If there are no snapshots, then this kv affect visibility at tip.
// Otherwise, search though all existing snapshots to find
// the earlist snapshot that is affected by this kv.
SequenceNumber prev_snapshot = 0; // 0 means no previous snapshot
SequenceNumber visible =
sub_compact->visible_at_tip
? sub_compact->visible_at_tip
: findEarliestVisibleSnapshot(ikey.sequence, &prev_snapshot);
if (visible_in_snapshot == visible) {
// If the earliest snapshot is which this key is visible in
// is the same as the visibily of a previous instance of the
// same key, then this kv is not visible in any snapshot.
// Hidden by an newer entry for same user key
// TODO: why not > ?
assert(last_sequence_for_key >= ikey.sequence);
++key_drop_newer_entry;
input->Next(); // (A)
} else if (ikey.type == kTypeDeletion &&
ikey.sequence <= sub_compact->earliest_snapshot &&
sub_compact->compaction->KeyNotExistsBeyondOutputLevel(
ikey.user_key, &sub_compact->level_ptrs)) {
// For this user key:
// (1) there is no data in higher levels
// (2) data in lower levels will have larger sequence numbers
// (3) data in layers that are being compacted here and have
// smaller sequence numbers will be dropped in the next
// few iterations of this loop (by rule (A) above).
// Therefore this deletion marker is obsolete and can be dropped.
++key_drop_obsolete;
input->Next();
} else if (ikey.type == kTypeMerge) {
if (!merge.HasOperator()) {
LogToBuffer(log_buffer_, "Options::merge_operator is null.");
status = Status::InvalidArgument(
"merge_operator is not properly initialized.");
break;
}
// We know the merge type entry is not hidden, otherwise we would
// have hit (A)
// We encapsulate the merge related state machine in a different
// object to minimize change to the existing flow. Turn out this
// logic could also be nicely re-used for memtable flush purge
// optimization in BuildTable.
merge.MergeUntil(input, prev_snapshot, bottommost_level_,
db_options_.statistics.get(), env_);
// NOTE: key, value, and ikey refer to old entries.
// These will be correctly set below.
const auto& keys = merge.keys();
const auto& values = merge.values();
assert(!keys.empty());
assert(keys.size() == values.size());
// We have a list of keys to write, write all keys in the list.
for (auto key_iter = keys.rbegin(), value_iter = values.rbegin();
!status.ok() || key_iter != keys.rend(); key_iter++, value_iter++) {
key = Slice(*key_iter);
value = Slice(*value_iter);
bool valid_key __attribute__((__unused__)) =
ParseInternalKey(key, &ikey);
// MergeUntil stops when it encounters a corrupt key and does not
// include them in the result, so we expect the keys here to valid.
assert(valid_key);
status = WriteKeyValue(key, value, ikey, input->status(), sub_compact);
}
} else {
status = WriteKeyValue(key, value, ikey, input->status(), sub_compact);
input->Next();
}
last_sequence_for_key = ikey.sequence;
visible_in_snapshot = visible;
}
RecordTick(stats_, FILTER_OPERATION_TOTAL_TIME, total_filter_time);
RecordDroppedKeys(&key_drop_user, &key_drop_newer_entry, &key_drop_obsolete,
&sub_compact->compaction_job_stats);
RecordCompactionIOStats();
if (status.ok() &&
(shutting_down_->load(std::memory_order_acquire) || cfd->IsDropped())) {
status = Status::ShutdownInProgress(
"Database shutdown or Column family drop during compaction");
}
if (status.ok() && sub_compact->builder != nullptr) {
status = FinishCompactionOutputFile(input->status(), sub_compact);
}
if (status.ok()) {
status = input->status();
}
if (output_directory_ && !db_options_.disableDataSync) {
// TODO(aekmekji): Maybe only call once after all subcompactions complete?
output_directory_->Fsync();
}
if (measure_io_stats_) {
sub_compact->compaction_job_stats.file_write_nanos +=
iostats_context.write_nanos - prev_write_nanos;
sub_compact->compaction_job_stats.file_fsync_nanos +=
iostats_context.fsync_nanos - prev_fsync_nanos;
sub_compact->compaction_job_stats.file_range_sync_nanos +=
iostats_context.range_sync_nanos - prev_range_sync_nanos;
sub_compact->compaction_job_stats.file_prepare_write_nanos +=
iostats_context.prepare_write_nanos - prev_prepare_write_nanos;
if (prev_perf_level != PerfLevel::kEnableTime) {
SetPerfLevel(prev_perf_level);
}
}
input_ptr.reset();
sub_compact->status = status;
}
Status CompactionJob::WriteKeyValue(const Slice& key, const Slice& value,
const ParsedInternalKey& ikey, const Status& input_status,
SubCompactionState* sub_compact) {
Slice newkey(key.data(), key.size());
std::string kstr;
// Zeroing out the sequence number leads to better compression.
// If this is the bottommost level (no files in lower levels)
// and the earliest snapshot is larger than this seqno
// then we can squash the seqno to zero.
if (bottommost_level_ && ikey.sequence < sub_compact->earliest_snapshot &&
ikey.type != kTypeMerge) {
assert(ikey.type != kTypeDeletion);
// make a copy because updating in place would cause problems
// with the priority queue that is managing the input key iterator
kstr.assign(key.data(), key.size());
UpdateInternalKey(&kstr, (uint64_t)0, ikey.type);
newkey = Slice(kstr);
}
// Open output file if necessary
if (sub_compact->builder == nullptr) {
Status status = OpenCompactionOutputFile(sub_compact);
if (!status.ok()) {
return status;
}
}
assert(sub_compact->builder != nullptr);
SequenceNumber seqno = GetInternalKeySeqno(newkey);
if (sub_compact->builder->NumEntries() == 0) {
sub_compact->current_output()->smallest.DecodeFrom(newkey);
sub_compact->current_output()->smallest_seqno = seqno;
} else {
sub_compact->current_output()->smallest_seqno =
std::min(sub_compact->current_output()->smallest_seqno, seqno);
}
sub_compact->current_output()->largest.DecodeFrom(newkey);
sub_compact->builder->Add(newkey, value);
sub_compact->num_output_records++;
sub_compact->current_output()->largest_seqno =
std::max(sub_compact->current_output()->largest_seqno, seqno);
// Close output file if it is big enough
Status status;
if (sub_compact->builder->FileSize() >=
sub_compact->compaction->max_output_file_size()) {
status = FinishCompactionOutputFile(input_status, sub_compact);
}
return status;
}
void CompactionJob::RecordDroppedKeys(
int64_t* key_drop_user,
int64_t* key_drop_newer_entry,
int64_t* key_drop_obsolete,
CompactionJobStats* compaction_job_stats) {
if (*key_drop_user > 0) {
RecordTick(stats_, COMPACTION_KEY_DROP_USER, *key_drop_user);
*key_drop_user = 0;
}
if (*key_drop_newer_entry > 0) {
RecordTick(stats_, COMPACTION_KEY_DROP_NEWER_ENTRY, *key_drop_newer_entry);
if (compaction_job_stats) {
compaction_job_stats->num_records_replaced += *key_drop_newer_entry;
}
*key_drop_newer_entry = 0;
}
if (*key_drop_obsolete > 0) {
RecordTick(stats_, COMPACTION_KEY_DROP_OBSOLETE, *key_drop_obsolete);
if (compaction_job_stats) {
compaction_job_stats->num_expired_deletion_records += *key_drop_obsolete;
}
*key_drop_obsolete = 0;
}
}
Status CompactionJob::FinishCompactionOutputFile(const Status& input_status,
SubCompactionState* sub_compact) {
Allow GetThreadList() to report operation stage. Summary: Allow GetThreadList() to report operation stage. Test Plan: ./thread_list_test ./db_bench --benchmarks=fillrandom --num=100000 --threads=40 \ --max_background_compactions=10 --max_background_flushes=3 \ --thread_status_per_interval=1000 --key_size=16 --value_size=1000 \ --num_column_families=10 export ROCKSDB_TESTS=ThreadStatus ./db_test Sample output ThreadID ThreadType cfName Operation OP_StartTime ElapsedTime Stage State 140116265861184 Low Pri 140116270055488 Low Pri 140116274249792 High Pri column_family_name_000005 Flush 2015/03/10-14:58:11 0 us FlushJob::WriteLevel0Table 140116400078912 Low Pri column_family_name_000004 Compaction 2015/03/10-14:58:11 0 us CompactionJob::FinishCompactionOutputFile 140116358135872 Low Pri column_family_name_000006 Compaction 2015/03/10-14:58:10 1 us CompactionJob::FinishCompactionOutputFile 140116341358656 Low Pri 140116295221312 High Pri default Flush 2015/03/10-14:58:11 0 us FlushJob::WriteLevel0Table 140116324581440 Low Pri column_family_name_000009 Compaction 2015/03/10-14:58:11 0 us CompactionJob::ProcessKeyValueCompaction 140116278444096 Low Pri 140116299415616 Low Pri column_family_name_000008 Compaction 2015/03/10-14:58:11 0 us CompactionJob::FinishCompactionOutputFile 140116291027008 High Pri column_family_name_000001 Flush 2015/03/10-14:58:11 0 us FlushJob::WriteLevel0Table 140116286832704 Low Pri column_family_name_000002 Compaction 2015/03/10-14:58:11 0 us CompactionJob::FinishCompactionOutputFile 140116282638400 Low Pri Reviewers: rven, igor, sdong Reviewed By: sdong Subscribers: dhruba, leveldb Differential Revision: https://reviews.facebook.net/D34683
10 years ago
AutoThreadOperationStageUpdater stage_updater(
ThreadStatus::STAGE_COMPACTION_SYNC_FILE);
assert(sub_compact != nullptr);
assert(sub_compact->outfile);
assert(sub_compact->builder != nullptr);
const uint64_t output_number = sub_compact->current_output()->number;
const uint32_t output_path_id = sub_compact->current_output()->path_id;
assert(output_number != 0);
TableProperties table_properties;
// Check for iterator errors
Status s = input_status;
const uint64_t current_entries = sub_compact->builder->NumEntries();
sub_compact->current_output()->need_compaction =
sub_compact->builder->NeedCompact();
if (s.ok()) {
s = sub_compact->builder->Finish();
} else {
sub_compact->builder->Abandon();
}
const uint64_t current_bytes = sub_compact->builder->FileSize();
sub_compact->current_output()->file_size = current_bytes;
sub_compact->total_bytes += current_bytes;
// Finish and check for file errors
if (s.ok() && !db_options_.disableDataSync) {
StopWatch sw(env_, stats_, COMPACTION_OUTFILE_SYNC_MICROS);
s = sub_compact->outfile->Sync(db_options_.use_fsync);
}
if (s.ok()) {
s = sub_compact->outfile->Close();
}
sub_compact->outfile.reset();
if (s.ok() && current_entries > 0) {
// Verify that the table is usable
ColumnFamilyData* cfd = sub_compact->compaction->column_family_data();
FileDescriptor fd(output_number, output_path_id, current_bytes);
Iterator* iter = cfd->table_cache()->NewIterator(
ReadOptions(), env_options_, cfd->internal_comparator(), fd, nullptr,
cfd->internal_stats()->GetFileReadHist(
compact_->compaction->output_level()),
false);
s = iter->status();
if (s.ok() && paranoid_file_checks_) {
for (iter->SeekToFirst(); iter->Valid(); iter->Next()) {}
s = iter->status();
}
delete iter;
if (s.ok()) {
TableFileCreationInfo info(sub_compact->builder->GetTableProperties());
info.db_name = dbname_;
info.cf_name = cfd->GetName();
info.file_path = TableFileName(cfd->ioptions()->db_paths,
fd.GetNumber(), fd.GetPathId());
info.file_size = fd.GetFileSize();
info.job_id = job_id_;
Log(InfoLogLevel::INFO_LEVEL, db_options_.info_log,
"[%s] [JOB %d] Generated table #%" PRIu64 ": %" PRIu64
" keys, %" PRIu64 " bytes%s",
cfd->GetName().c_str(), job_id_, output_number, current_entries,
current_bytes,
sub_compact->current_output()->need_compaction ? " (need compaction)"
: "");
EventHelpers::LogAndNotifyTableFileCreation(
event_logger_, cfd->ioptions()->listeners, fd, info);
}
}
sub_compact->builder.reset();
return s;
}
Status CompactionJob::InstallCompactionResults(
const MutableCFOptions& mutable_cf_options, InstrumentedMutex* db_mutex) {
db_mutex->AssertHeld();
auto* compaction = compact_->compaction;
// paranoia: verify that the files that we started with
// still exist in the current version and in the same original level.
// This ensures that a concurrent compaction did not erroneously
// pick the same files to compact_.
if (!versions_->VerifyCompactionFileConsistency(compaction)) {
Compaction::InputLevelSummaryBuffer inputs_summary;
Log(InfoLogLevel::ERROR_LEVEL, db_options_.info_log,
"[%s] [JOB %d] Compaction %s aborted",
compaction->column_family_data()->GetName().c_str(), job_id_,
compaction->InputLevelSummary(&inputs_summary));
return Status::Corruption("Compaction input files inconsistent");
}
{
Compaction::InputLevelSummaryBuffer inputs_summary;
Log(InfoLogLevel::INFO_LEVEL, db_options_.info_log,
"[%s] [JOB %d] Compacted %s => %" PRIu64 " bytes",
compaction->column_family_data()->GetName().c_str(), job_id_,
compaction->InputLevelSummary(&inputs_summary), compact_->total_bytes);
}
// Add compaction outputs
compaction->AddInputDeletions(compact_->compaction->edit());
for (SubCompactionState& sub_compact : compact_->sub_compact_states) {
for (size_t i = 0; i < sub_compact.outputs.size(); i++) {
const SubCompactionState::Output& out = sub_compact.outputs[i];
compaction->edit()->AddFile(compaction->output_level(), out.number,
out.path_id, out.file_size, out.smallest,
out.largest, out.smallest_seqno,
out.largest_seqno, out.need_compaction);
}
}
return versions_->LogAndApply(compaction->column_family_data(),
mutable_cf_options, compaction->edit(),
db_mutex, db_directory_);
}
// Given a sequence number, return the sequence number of the
// earliest snapshot that this sequence number is visible in.
// The snapshots themselves are arranged in ascending order of
// sequence numbers.
// Employ a sequential search because the total number of
// snapshots are typically small.
inline SequenceNumber CompactionJob::findEarliestVisibleSnapshot(
SequenceNumber in, SequenceNumber* prev_snapshot) {
assert(existing_snapshots_.size());
SequenceNumber prev __attribute__((unused)) = 0;
for (const auto cur : existing_snapshots_) {
assert(prev <= cur);
if (cur >= in) {
*prev_snapshot = prev;
return cur;
}
prev = cur; // assignment
assert(prev);
}
Log(InfoLogLevel::WARN_LEVEL, db_options_.info_log,
"CompactionJob is not able to find snapshot"
" with SeqId later than %" PRIu64
": current MaxSeqId is %" PRIu64 "",
in, existing_snapshots_[existing_snapshots_.size() - 1]);
assert(0);
return 0;
}
void CompactionJob::RecordCompactionIOStats() {
RecordTick(stats_, COMPACT_READ_BYTES, IOSTATS(bytes_read));
Allow GetThreadList() to report basic compaction operation properties. Summary: Now we're able to show more details about a compaction in GetThreadList() :) This patch allows GetThreadList() to report basic compaction operation properties. Basic compaction properties include: 1. job id 2. compaction input / output level 3. compaction property flags (is_manual, is_deletion, .. etc) 4. total input bytes 5. the number of bytes has been read currently. 6. the number of bytes has been written currently. Flush operation properties will be done in a seperate diff. Test Plan: /db_bench --threads=30 --num=1000000 --benchmarks=fillrandom --thread_status_per_interval=1 Sample output of tracking same job: ThreadID ThreadType cfName Operation ElapsedTime Stage State OperationProperties 140664171987072 Low Pri default Compaction 31.357 ms CompactionJob::FinishCompactionOutputFile BaseInputLevel 1 | BytesRead 2264663 | BytesWritten 1934241 | IsDeletion 0 | IsManual 0 | IsTrivialMove 0 | JobID 277 | OutputLevel 2 | TotalInputBytes 3964158 | ThreadID ThreadType cfName Operation ElapsedTime Stage State OperationProperties 140664171987072 Low Pri default Compaction 59.440 ms CompactionJob::FinishCompactionOutputFile BaseInputLevel 1 | BytesRead 2264663 | BytesWritten 1934241 | IsDeletion 0 | IsManual 0 | IsTrivialMove 0 | JobID 277 | OutputLevel 2 | TotalInputBytes 3964158 | ThreadID ThreadType cfName Operation ElapsedTime Stage State OperationProperties 140664171987072 Low Pri default Compaction 226.375 ms CompactionJob::Install BaseInputLevel 1 | BytesRead 3958013 | BytesWritten 3621940 | IsDeletion 0 | IsManual 0 | IsTrivialMove 0 | JobID 277 | OutputLevel 2 | TotalInputBytes 3964158 | Reviewers: sdong, rven, igor Reviewed By: igor Subscribers: dhruba, leveldb Differential Revision: https://reviews.facebook.net/D37653
10 years ago
ThreadStatusUtil::IncreaseThreadOperationProperty(
ThreadStatus::COMPACTION_BYTES_READ, IOSTATS(bytes_read));
IOSTATS_RESET(bytes_read);
RecordTick(stats_, COMPACT_WRITE_BYTES, IOSTATS(bytes_written));
Allow GetThreadList() to report basic compaction operation properties. Summary: Now we're able to show more details about a compaction in GetThreadList() :) This patch allows GetThreadList() to report basic compaction operation properties. Basic compaction properties include: 1. job id 2. compaction input / output level 3. compaction property flags (is_manual, is_deletion, .. etc) 4. total input bytes 5. the number of bytes has been read currently. 6. the number of bytes has been written currently. Flush operation properties will be done in a seperate diff. Test Plan: /db_bench --threads=30 --num=1000000 --benchmarks=fillrandom --thread_status_per_interval=1 Sample output of tracking same job: ThreadID ThreadType cfName Operation ElapsedTime Stage State OperationProperties 140664171987072 Low Pri default Compaction 31.357 ms CompactionJob::FinishCompactionOutputFile BaseInputLevel 1 | BytesRead 2264663 | BytesWritten 1934241 | IsDeletion 0 | IsManual 0 | IsTrivialMove 0 | JobID 277 | OutputLevel 2 | TotalInputBytes 3964158 | ThreadID ThreadType cfName Operation ElapsedTime Stage State OperationProperties 140664171987072 Low Pri default Compaction 59.440 ms CompactionJob::FinishCompactionOutputFile BaseInputLevel 1 | BytesRead 2264663 | BytesWritten 1934241 | IsDeletion 0 | IsManual 0 | IsTrivialMove 0 | JobID 277 | OutputLevel 2 | TotalInputBytes 3964158 | ThreadID ThreadType cfName Operation ElapsedTime Stage State OperationProperties 140664171987072 Low Pri default Compaction 226.375 ms CompactionJob::Install BaseInputLevel 1 | BytesRead 3958013 | BytesWritten 3621940 | IsDeletion 0 | IsManual 0 | IsTrivialMove 0 | JobID 277 | OutputLevel 2 | TotalInputBytes 3964158 | Reviewers: sdong, rven, igor Reviewed By: igor Subscribers: dhruba, leveldb Differential Revision: https://reviews.facebook.net/D37653
10 years ago
ThreadStatusUtil::IncreaseThreadOperationProperty(
ThreadStatus::COMPACTION_BYTES_WRITTEN, IOSTATS(bytes_written));
IOSTATS_RESET(bytes_written);
}
Status CompactionJob::OpenCompactionOutputFile(SubCompactionState*
sub_compact) {
assert(sub_compact != nullptr);
assert(sub_compact->builder == nullptr);
// no need to lock because VersionSet::next_file_number_ is atomic
uint64_t file_number = versions_->NewFileNumber();
// Make the output file
unique_ptr<WritableFile> writable_file;
std::string fname = TableFileName(db_options_.db_paths, file_number,
sub_compact->compaction->output_path_id());
Status s = env_->NewWritableFile(fname, &writable_file, env_options_);
if (!s.ok()) {
Log(InfoLogLevel::ERROR_LEVEL, db_options_.info_log,
"[%s] [JOB %d] OpenCompactionOutputFiles for table #%" PRIu64
" fails at NewWritableFile with status %s",
sub_compact->compaction->column_family_data()->GetName().c_str(),
job_id_, file_number, s.ToString().c_str());
LogFlush(db_options_.info_log);
return s;
}
SubCompactionState::Output out;
out.number = file_number;
out.path_id = sub_compact->compaction->output_path_id();
out.smallest.Clear();
out.largest.Clear();
out.smallest_seqno = out.largest_seqno = 0;
sub_compact->outputs.push_back(out);
writable_file->SetIOPriority(Env::IO_LOW);
writable_file->SetPreallocationBlockSize(static_cast<size_t>(
sub_compact->compaction->OutputFilePreallocationSize()));
sub_compact->outfile.reset(
new WritableFileWriter(std::move(writable_file), env_options_));
ColumnFamilyData* cfd = sub_compact->compaction->column_family_data();
bool skip_filters = false;
// If the Column family flag is to only optimize filters for hits,
// we can skip creating filters if this is the bottommost_level where
// data is going to be found
//
if (cfd->ioptions()->optimize_filters_for_hits && bottommost_level_) {
skip_filters = true;
}
sub_compact->builder.reset(NewTableBuilder(
*cfd->ioptions(), cfd->internal_comparator(),
cfd->int_tbl_prop_collector_factories(), sub_compact->outfile.get(),
sub_compact->compaction->output_compression(),
cfd->ioptions()->compression_opts, skip_filters));
LogFlush(db_options_.info_log);
return s;
}
void CompactionJob::CleanupCompaction() {
for (SubCompactionState& sub_compact : compact_->sub_compact_states) {
const auto& sub_status = sub_compact.status;
if (sub_compact.builder != nullptr) {
// May happen if we get a shutdown call in the middle of compaction
sub_compact.builder->Abandon();
sub_compact.builder.reset();
} else {
assert(!sub_status.ok() || sub_compact.outfile == nullptr);
}
for (size_t i = 0; i < sub_compact.outputs.size(); i++) {
const SubCompactionState::Output& out = sub_compact.outputs[i];
// If this file was inserted into the table cache then remove
// them here because this compaction was not committed.
if (!sub_status.ok()) {
TableCache::Evict(table_cache_.get(), out.number);
}
}
}
delete compact_;
compact_ = nullptr;
}
#ifndef ROCKSDB_LITE
namespace {
void CopyPrefix(
const Slice& src, size_t prefix_length, std::string* dst) {
assert(prefix_length > 0);
size_t length = src.size() > prefix_length ? prefix_length : src.size();
dst->assign(src.data(), length);
}
} // namespace
#endif // !ROCKSDB_LITE
void CompactionJob::UpdateCompactionStats() {
Compaction* compaction = compact_->compaction;
compaction_stats_.num_input_files_in_non_output_levels = 0;
compaction_stats_.num_input_files_in_output_level = 0;
for (int input_level = 0;
input_level < static_cast<int>(compaction->num_input_levels());
++input_level) {
if (compaction->start_level() + input_level
!= compaction->output_level()) {
UpdateCompactionInputStatsHelper(
&compaction_stats_.num_input_files_in_non_output_levels,
&compaction_stats_.bytes_read_non_output_levels,
input_level);
} else {
UpdateCompactionInputStatsHelper(
&compaction_stats_.num_input_files_in_output_level,
&compaction_stats_.bytes_read_output_level,
input_level);
}
}
for (const auto& sub_compact : compact_->sub_compact_states) {
size_t num_output_files = sub_compact.outputs.size();
if (sub_compact.builder != nullptr) {
// An error occurred so ignore the last output.
assert(num_output_files > 0);
--num_output_files;
}
compaction_stats_.num_output_files += static_cast<int>(num_output_files);
for (size_t i = 0; i < num_output_files; i++) {
compaction_stats_.bytes_written += sub_compact.outputs[i].file_size;
}
if (sub_compact.num_input_records > sub_compact.num_output_records) {
compaction_stats_.num_dropped_records +=
sub_compact.num_input_records - sub_compact.num_output_records;
}
}
}
void CompactionJob::UpdateCompactionInputStatsHelper(
int* num_files, uint64_t* bytes_read, int input_level) {
const Compaction* compaction = compact_->compaction;
auto num_input_files = compaction->num_input_files(input_level);
*num_files += static_cast<int>(num_input_files);
for (size_t i = 0; i < num_input_files; ++i) {
const auto* file_meta = compaction->input(input_level, i);
*bytes_read += file_meta->fd.GetFileSize();
compaction_stats_.num_input_records +=
static_cast<uint64_t>(file_meta->num_entries);
}
}
void CompactionJob::UpdateCompactionJobStats(
const InternalStats::CompactionStats& stats) const {
#ifndef ROCKSDB_LITE
if (compaction_job_stats_) {
compaction_job_stats_->elapsed_micros = stats.micros;
// input information
compaction_job_stats_->total_input_bytes =
stats.bytes_read_non_output_levels +
stats.bytes_read_output_level;
compaction_job_stats_->num_input_records =
compact_->num_input_records;
compaction_job_stats_->num_input_files =
stats.num_input_files_in_non_output_levels +
stats.num_input_files_in_output_level;
compaction_job_stats_->num_input_files_at_output_level =
stats.num_input_files_in_output_level;
// output information
compaction_job_stats_->total_output_bytes = stats.bytes_written;
compaction_job_stats_->num_output_records =
compact_->num_output_records;
compaction_job_stats_->num_output_files = stats.num_output_files;
if (compact_->NumOutputFiles() > 0U) {
CopyPrefix(
compact_->SmallestUserKey(),
CompactionJobStats::kMaxPrefixLength,
&compaction_job_stats_->smallest_output_key_prefix);
CopyPrefix(
compact_->LargestUserKey(),
CompactionJobStats::kMaxPrefixLength,
&compaction_job_stats_->largest_output_key_prefix);
}
}
#endif // !ROCKSDB_LITE
}
void CompactionJob::LogCompaction() {
Compaction* compaction = compact_->compaction;
ColumnFamilyData* cfd = compaction->column_family_data();
// Let's check if anything will get logged. Don't prepare all the info if
// we're not logging
if (db_options_.info_log_level <= InfoLogLevel::INFO_LEVEL) {
Compaction::InputLevelSummaryBuffer inputs_summary;
Log(InfoLogLevel::INFO_LEVEL, db_options_.info_log,
"[%s] [JOB %d] Compacting %s, score %.2f", cfd->GetName().c_str(),
job_id_, compaction->InputLevelSummary(&inputs_summary),
compaction->score());
char scratch[2345];
compaction->Summary(scratch, sizeof(scratch));
Log(InfoLogLevel::INFO_LEVEL, db_options_.info_log,
"[%s] Compaction start summary: %s\n", cfd->GetName().c_str(), scratch);
// build event logger report
auto stream = event_logger_->Log();
stream << "job" << job_id_ << "event"
<< "compaction_started";
for (size_t i = 0; i < compaction->num_input_levels(); ++i) {
stream << ("files_L" + ToString(compaction->level(i)));
stream.StartArray();
for (auto f : *compaction->inputs(i)) {
stream << f->fd.GetNumber();
}
stream.EndArray();
}
stream << "score" << compaction->score() << "input_data_size"
<< compaction->CalculateTotalInputSize();
}
}
} // namespace rocksdb