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rocksdb/db/compaction_job.cc

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// Copyright (c) 2011-present, Facebook, Inc. All rights reserved.
// This source code is licensed under both the GPLv2 (found in the
// COPYING file in the root directory) and Apache 2.0 License
// (found in the LICENSE.Apache file in the root 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 <functional>
#include <list>
#include <memory>
#include <random>
#include <set>
#include <thread>
#include <utility>
#include <vector>
#include "db/builder.h"
#include "db/db_iter.h"
#include "db/dbformat.h"
#include "db/event_helpers.h"
#include "db/log_reader.h"
#include "db/log_writer.h"
#include "db/memtable.h"
#include "db/memtable_list.h"
#include "db/merge_context.h"
#include "db/merge_helper.h"
#include "db/version_set.h"
#include "monitoring/iostats_context_imp.h"
#include "monitoring/perf_context_imp.h"
#include "monitoring/thread_status_util.h"
#include "port/port.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/merging_iterator.h"
#include "table/table_builder.h"
#include "util/coding.h"
#include "util/file_reader_writer.h"
#include "util/filename.h"
#include "util/log_buffer.h"
#include "util/logging.h"
#include "util/mutexlock.h"
#include "util/random.h"
#include "util/sst_file_manager_impl.h"
#include "util/stop_watch.h"
#include "util/string_util.h"
#include "util/sync_point.h"
namespace rocksdb {
// Maintains state for each sub-compaction
struct CompactionJob::SubcompactionState {
const Compaction* compaction;
std::unique_ptr<CompactionIterator> c_iter;
// 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 subcompaction
Status status;
// Files produced by this subcompaction
struct Output {
FileMetaData meta;
bool finished;
std::shared_ptr<const TableProperties> table_properties;
};
// State kept for output being generated
std::vector<Output> outputs;
std::unique_ptr<WritableFileWriter> outfile;
std::unique_ptr<TableBuilder> builder;
Output* current_output() {
if (outputs.empty()) {
// This subcompaction's outptut could be empty if compaction was aborted
// before this subcompaction had a chance to generate any output files.
// When subcompactions are executed sequentially this is more likely and
// will be particulalry likely for the later subcompactions to be empty.
// Once they are run in parallel however it should be much rarer.
return nullptr;
} else {
return &outputs.back();
}
}
uint64_t current_output_file_size;
// State during the subcompaction
uint64_t total_bytes;
uint64_t num_input_records;
uint64_t num_output_records;
CompactionJobStats compaction_job_stats;
uint64_t approx_size;
// An index that used to speed up ShouldStopBefore().
size_t grandparent_index = 0;
// The number of bytes overlapping between the current output and
// grandparent files used in ShouldStopBefore().
uint64_t overlapped_bytes = 0;
// A flag determine whether the key has been seen in ShouldStopBefore()
bool seen_key = false;
std::string compression_dict;
SubcompactionState(Compaction* c, Slice* _start, Slice* _end,
uint64_t size = 0)
: compaction(c),
start(_start),
end(_end),
outfile(nullptr),
builder(nullptr),
current_output_file_size(0),
total_bytes(0),
num_input_records(0),
num_output_records(0),
approx_size(size),
grandparent_index(0),
overlapped_bytes(0),
seen_key(false),
compression_dict() {
assert(compaction != nullptr);
}
SubcompactionState(SubcompactionState&& o) { *this = std::move(o); }
SubcompactionState& operator=(SubcompactionState&& o) {
compaction = std::move(o.compaction);
start = std::move(o.start);
end = std::move(o.end);
status = std::move(o.status);
outputs = std::move(o.outputs);
outfile = std::move(o.outfile);
builder = std::move(o.builder);
current_output_file_size = std::move(o.current_output_file_size);
total_bytes = std::move(o.total_bytes);
num_input_records = std::move(o.num_input_records);
num_output_records = std::move(o.num_output_records);
compaction_job_stats = std::move(o.compaction_job_stats);
approx_size = std::move(o.approx_size);
grandparent_index = std::move(o.grandparent_index);
overlapped_bytes = std::move(o.overlapped_bytes);
seen_key = std::move(o.seen_key);
compression_dict = std::move(o.compression_dict);
return *this;
}
// Because member unique_ptrs do not have these.
SubcompactionState(const SubcompactionState&) = delete;
SubcompactionState& operator=(const SubcompactionState&) = delete;
// Returns true iff we should stop building the current output
// before processing "internal_key".
bool ShouldStopBefore(const Slice& internal_key, uint64_t curr_file_size) {
const InternalKeyComparator* icmp =
&compaction->column_family_data()->internal_comparator();
const std::vector<FileMetaData*>& grandparents = compaction->grandparents();
// Scan to find earliest grandparent file that contains key.
while (grandparent_index < grandparents.size() &&
icmp->Compare(internal_key,
grandparents[grandparent_index]->largest.Encode()) >
0) {
if (seen_key) {
overlapped_bytes += grandparents[grandparent_index]->fd.GetFileSize();
}
assert(grandparent_index + 1 >= grandparents.size() ||
icmp->Compare(
grandparents[grandparent_index]->largest.Encode(),
grandparents[grandparent_index + 1]->smallest.Encode()) <= 0);
grandparent_index++;
}
seen_key = true;
if (overlapped_bytes + curr_file_size >
compaction->max_compaction_bytes()) {
// Too much overlap for current output; start new output
overlapped_bytes = 0;
return true;
}
return false;
}
};
// 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() {
for (const auto& sub_compact_state : sub_compact_states) {
if (!sub_compact_state.outputs.empty() &&
sub_compact_state.outputs[0].finished) {
return sub_compact_state.outputs[0].meta.smallest.user_key();
}
}
// If there is no finished output, return an empty slice.
return Slice(nullptr, 0);
}
Slice LargestUserKey() {
for (auto it = sub_compact_states.rbegin(); it < sub_compact_states.rend();
++it) {
if (!it->outputs.empty() && it->current_output()->finished) {
assert(it->current_output() != nullptr);
return it->current_output()->meta.largest.user_key();
}
}
// If there is no finished output, return an empty slice.
return Slice(nullptr, 0);
}
};
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_) {
for (SubcompactionState& sc : compact_->sub_compact_states) {
compaction_job_stats_->Add(sc.compaction_job_stats);
}
}
}
CompactionJob::CompactionJob(
int job_id, Compaction* compaction, const ImmutableDBOptions& db_options,
const EnvOptions env_options, VersionSet* versions,
Added support for differential snapshots Summary: The motivation for this PR is to add to RocksDB support for differential (incremental) snapshots, as snapshot of the DB changes between two points in time (one can think of it as diff between to sequence numbers, or the diff D which can be thought of as an SST file or just set of KVs that can be applied to sequence number S1 to get the database to the state at sequence number S2). This feature would be useful for various distributed storages layers built on top of RocksDB, as it should help reduce resources (time and network bandwidth) needed to recover and rebuilt DB instances as replicas in the context of distributed storages. From the API standpoint that would like client app requesting iterator between (start seqnum) and current DB state, and reading the "diff". This is a very draft PR for initial review in the discussion on the approach, i'm going to rework some parts and keep updating the PR. For now, what's done here according to initial discussions: Preserving deletes: - We want to be able to optionally preserve recent deletes for some defined period of time, so that if a delete came in recently and might need to be included in the next incremental snapshot it would't get dropped by a compaction. This is done by adding new param to Options (preserve deletes flag) and new variable to DB Impl where we keep track of the sequence number after which we don't want to drop tombstones, even if they are otherwise eligible for deletion. - I also added a new API call for clients to be able to advance this cutoff seqnum after which we drop deletes; i assume it's more flexible to let clients control this, since otherwise we'd need to keep some kind of timestamp < -- > seqnum mapping inside the DB, which sounds messy and painful to support. Clients could make use of it by periodically calling GetLatestSequenceNumber(), noting the timestamp, doing some calculation and figuring out by how much we need to advance the cutoff seqnum. - Compaction codepath in compaction_iterator.cc has been modified to avoid dropping tombstones with seqnum > cutoff seqnum. Iterator changes: - couple params added to ReadOptions, to optionally allow client to request internal keys instead of user keys (so that client can get the latest value of a key, be it delete marker or a put), as well as min timestamp and min seqnum. TableCache changes: - I modified table_cache code to be able to quickly exclude SST files from iterators heep if creation_time on the file is less then iter_start_ts as passed in ReadOptions. That would help a lot in some DB settings (like reading very recent data only or using FIFO compactions), but not so much for universal compaction with more or less long iterator time span. What's left: - Still looking at how to best plug that inside DBIter codepath. So far it seems that FindNextUserKeyInternal only parses values as UserKeys, and iter->key() call generally returns user key. Can we add new API to DBIter as internal_key(), and modify this internal method to optionally set saved_key_ to point to the full internal key? I don't need to store actual seqnum there, but I do need to store type. Closes https://github.com/facebook/rocksdb/pull/2999 Differential Revision: D6175602 Pulled By: mikhail-antonov fbshipit-source-id: c779a6696ee2d574d86c69cec866a3ae095aa900
7 years ago
const std::atomic<bool>* shutting_down,
const SequenceNumber preserve_deletes_seqnum, LogBuffer* log_buffer,
Directory* db_directory, Directory* output_directory, Statistics* stats,
InstrumentedMutex* db_mutex, Status* db_bg_error,
std::vector<SequenceNumber> existing_snapshots,
SequenceNumber earliest_write_conflict_snapshot,
const SnapshotChecker* snapshot_checker, 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),
env_optiosn_for_read_(
env_->OptimizeForCompactionTableRead(env_options, db_options_)),
versions_(versions),
shutting_down_(shutting_down),
Added support for differential snapshots Summary: The motivation for this PR is to add to RocksDB support for differential (incremental) snapshots, as snapshot of the DB changes between two points in time (one can think of it as diff between to sequence numbers, or the diff D which can be thought of as an SST file or just set of KVs that can be applied to sequence number S1 to get the database to the state at sequence number S2). This feature would be useful for various distributed storages layers built on top of RocksDB, as it should help reduce resources (time and network bandwidth) needed to recover and rebuilt DB instances as replicas in the context of distributed storages. From the API standpoint that would like client app requesting iterator between (start seqnum) and current DB state, and reading the "diff". This is a very draft PR for initial review in the discussion on the approach, i'm going to rework some parts and keep updating the PR. For now, what's done here according to initial discussions: Preserving deletes: - We want to be able to optionally preserve recent deletes for some defined period of time, so that if a delete came in recently and might need to be included in the next incremental snapshot it would't get dropped by a compaction. This is done by adding new param to Options (preserve deletes flag) and new variable to DB Impl where we keep track of the sequence number after which we don't want to drop tombstones, even if they are otherwise eligible for deletion. - I also added a new API call for clients to be able to advance this cutoff seqnum after which we drop deletes; i assume it's more flexible to let clients control this, since otherwise we'd need to keep some kind of timestamp < -- > seqnum mapping inside the DB, which sounds messy and painful to support. Clients could make use of it by periodically calling GetLatestSequenceNumber(), noting the timestamp, doing some calculation and figuring out by how much we need to advance the cutoff seqnum. - Compaction codepath in compaction_iterator.cc has been modified to avoid dropping tombstones with seqnum > cutoff seqnum. Iterator changes: - couple params added to ReadOptions, to optionally allow client to request internal keys instead of user keys (so that client can get the latest value of a key, be it delete marker or a put), as well as min timestamp and min seqnum. TableCache changes: - I modified table_cache code to be able to quickly exclude SST files from iterators heep if creation_time on the file is less then iter_start_ts as passed in ReadOptions. That would help a lot in some DB settings (like reading very recent data only or using FIFO compactions), but not so much for universal compaction with more or less long iterator time span. What's left: - Still looking at how to best plug that inside DBIter codepath. So far it seems that FindNextUserKeyInternal only parses values as UserKeys, and iter->key() call generally returns user key. Can we add new API to DBIter as internal_key(), and modify this internal method to optionally set saved_key_ to point to the full internal key? I don't need to store actual seqnum there, but I do need to store type. Closes https://github.com/facebook/rocksdb/pull/2999 Differential Revision: D6175602 Pulled By: mikhail-antonov fbshipit-source-id: c779a6696ee2d574d86c69cec866a3ae095aa900
7 years ago
preserve_deletes_seqnum_(preserve_deletes_seqnum),
log_buffer_(log_buffer),
db_directory_(db_directory),
output_directory_(output_directory),
stats_(stats),
db_mutex_(db_mutex),
db_bg_error_(db_bg_error),
existing_snapshots_(std::move(existing_snapshots)),
earliest_write_conflict_snapshot_(earliest_write_conflict_snapshot),
snapshot_checker_(snapshot_checker),
table_cache_(std::move(table_cache)),
event_logger_(event_logger),
bottommost_level_(false),
paranoid_file_checks_(paranoid_file_checks),
measure_io_stats_(measure_io_stats),
write_hint_(Env::WLTH_NOT_SET) {
assert(log_buffer_ != nullptr);
const auto* cfd = compact_->compaction->column_family_data();
ThreadStatusUtil::SetColumnFamily(cfd, cfd->ioptions()->env,
db_options_.enable_thread_tracking);
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) {
const auto* cfd = compact_->compaction->column_family_data();
ThreadStatusUtil::SetColumnFamily(cfd, cfd->ioptions()->env,
db_options_.enable_thread_tracking);
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_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
auto* c = compact_->compaction;
assert(c->column_family_data() != nullptr);
assert(c->column_family_data()->current()->storage_info()
->NumLevelFiles(compact_->compaction->level()) > 0);
write_hint_ = c->column_family_data()->CalculateSSTWriteHint(
c->output_level());
// Is this compaction producing files at the bottommost level?
bottommost_level_ = c->bottommost_level();
if (c->ShouldFormSubcompactions()) {
const uint64_t start_micros = env_->NowMicros();
GenSubcompactionBoundaries();
MeasureTime(stats_, SUBCOMPACTION_SETUP_TIME,
env_->NowMicros() - start_micros);
assert(sizes_.size() == boundaries_.size() + 1);
for (size_t i = 0; i <= boundaries_.size(); i++) {
Slice* start = i == 0 ? nullptr : &boundaries_[i - 1];
Slice* end = i == boundaries_.size() ? nullptr : &boundaries_[i];
compact_->sub_compact_states.emplace_back(c, start, end, sizes_[i]);
}
MeasureTime(stats_, NUM_SUBCOMPACTIONS_SCHEDULED,
compact_->sub_compact_states.size());
} else {
compact_->sub_compact_states.emplace_back(c, nullptr, nullptr);
}
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
}
struct RangeWithSize {
Range range;
uint64_t size;
RangeWithSize(const Slice& a, const Slice& b, uint64_t s = 0)
: range(a, b), size(s) {}
};
// Generates a histogram representing potential divisions of key ranges from
// the input. It adds the starting and/or ending keys of certain input files
// to the working set and then finds the approximate size of data in between
// each consecutive pair of slices. Then it divides these ranges into
// consecutive groups such that each group has a similar size.
void CompactionJob::GenSubcompactionBoundaries() {
auto* c = compact_->compaction;
auto* cfd = c->column_family_data();
const Comparator* cfd_comparator = cfd->user_comparator();
std::vector<Slice> bounds;
int start_lvl = c->start_level();
int out_lvl = c->output_level();
// Add the starting and/or ending key of certain input files as a potential
// boundary
for (size_t lvl_idx = 0; lvl_idx < c->num_input_levels(); lvl_idx++) {
int lvl = c->level(lvl_idx);
if (lvl >= start_lvl && lvl <= out_lvl) {
const LevelFilesBrief* flevel = c->input_levels(lvl_idx);
size_t num_files = flevel->num_files;
if (num_files == 0) {
continue;
}
if (lvl == 0) {
// For level 0 add the starting and ending key of each file since the
// files may have greatly differing key ranges (not range-partitioned)
for (size_t i = 0; i < num_files; i++) {
bounds.emplace_back(flevel->files[i].smallest_key);
bounds.emplace_back(flevel->files[i].largest_key);
}
} else {
// For all other levels add the smallest/largest key in the level to
// encompass the range covered by that level
bounds.emplace_back(flevel->files[0].smallest_key);
bounds.emplace_back(flevel->files[num_files - 1].largest_key);
if (lvl == out_lvl) {
// For the last level include the starting keys of all files since
// the last level is the largest and probably has the widest key
// range. Since it's range partitioned, the ending key of one file
// and the starting key of the next are very close (or identical).
for (size_t i = 1; i < num_files; i++) {
bounds.emplace_back(flevel->files[i].smallest_key);
}
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
}
}
}
}
std::sort(bounds.begin(), bounds.end(),
[cfd_comparator] (const Slice& a, const Slice& b) -> bool {
return cfd_comparator->Compare(ExtractUserKey(a), ExtractUserKey(b)) < 0;
});
// Remove duplicated entries from bounds
bounds.erase(std::unique(bounds.begin(), bounds.end(),
[cfd_comparator] (const Slice& a, const Slice& b) -> bool {
return cfd_comparator->Compare(ExtractUserKey(a), ExtractUserKey(b)) == 0;
}), bounds.end());
// Combine consecutive pairs of boundaries into ranges with an approximate
// size of data covered by keys in that range
uint64_t sum = 0;
std::vector<RangeWithSize> ranges;
auto* v = cfd->current();
for (auto it = bounds.begin();;) {
const Slice a = *it;
it++;
if (it == bounds.end()) {
break;
}
const Slice b = *it;
uint64_t size = versions_->ApproximateSize(v, a, b, start_lvl, out_lvl + 1);
ranges.emplace_back(a, b, size);
sum += size;
}
// Group the ranges into subcompactions
const double min_file_fill_percent = 4.0 / 5;
uint64_t max_output_files = static_cast<uint64_t>(
std::ceil(sum / min_file_fill_percent /
c->mutable_cf_options()->MaxFileSizeForLevel(out_lvl)));
uint64_t subcompactions =
std::min({static_cast<uint64_t>(ranges.size()),
static_cast<uint64_t>(db_options_.max_subcompactions),
max_output_files});
if (subcompactions > 1) {
double mean = sum * 1.0 / subcompactions;
// Greedily add ranges to the subcompaction until the sum of the ranges'
// sizes becomes >= the expected mean size of a subcompaction
sum = 0;
for (size_t i = 0; i < ranges.size() - 1; i++) {
sum += ranges[i].size;
if (subcompactions == 1) {
// If there's only one left to schedule then it goes to the end so no
// need to put an end boundary
continue;
}
if (sum >= mean) {
boundaries_.emplace_back(ExtractUserKey(ranges[i].range.limit));
sizes_.emplace_back(sum);
subcompactions--;
sum = 0;
}
}
sizes_.emplace_back(sum + ranges.back().size);
} else {
// Only one range so its size is the total sum of sizes computed above
sizes_.emplace_back(sum);
}
}
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();
const size_t num_threads = compact_->sub_compact_states.size();
assert(num_threads > 0);
const uint64_t start_micros = env_->NowMicros();
// Launch a thread for each of subcompactions 1...num_threads-1
std::vector<port::Thread> thread_pool;
thread_pool.reserve(num_threads - 1);
for (size_t i = 1; i < compact_->sub_compact_states.size(); i++) {
thread_pool.emplace_back(&CompactionJob::ProcessKeyValueCompaction, this,
&compact_->sub_compact_states[i]);
}
// Always schedule the first subcompaction (whether or not there are also
// others) in the current thread to be efficient with resources
ProcessKeyValueCompaction(&compact_->sub_compact_states[0]);
// Wait for all other threads (if there are any) to finish execution
for (auto& thread : thread_pool) {
thread.join();
}
if (output_directory_) {
output_directory_->Fsync();
}
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
// Check if any thread encountered an error during execution
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;
}
}
TablePropertiesCollection tp;
for (const auto& state : compact_->sub_compact_states) {
for (const auto& output : state.outputs) {
auto fn = TableFileName(db_options_.db_paths, output.meta.fd.GetNumber(),
output.meta.fd.GetPathId());
tp[fn] = output.table_properties;
}
}
compact_->compaction->SetOutputTableProperties(std::move(tp));
// 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) {
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);
}
VersionStorageInfo::LevelSummaryStorage tmp;
auto vstorage = cfd->current()->storage_info();
const auto& stats = compaction_stats_;
double read_write_amp = 0.0;
double write_amp = 0.0;
double bytes_read_per_sec = 0;
double bytes_written_per_sec = 0;
if (stats.bytes_read_non_output_levels > 0) {
read_write_amp = (stats.bytes_written + stats.bytes_read_output_level +
stats.bytes_read_non_output_levels) /
static_cast<double>(stats.bytes_read_non_output_levels);
write_amp = stats.bytes_written /
static_cast<double>(stats.bytes_read_non_output_levels);
}
if (stats.micros > 0) {
bytes_read_per_sec =
(stats.bytes_read_non_output_levels + stats.bytes_read_output_level) /
static_cast<double>(stats.micros);
bytes_written_per_sec =
stats.bytes_written / static_cast<double>(stats.micros);
}
ROCKS_LOG_BUFFER(
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: %" PRIu64
", records dropped: %" PRIu64 " output_compression: %s\n",
cfd->GetName().c_str(), vstorage->LevelSummary(&tmp), bytes_read_per_sec,
bytes_written_per_sec, 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, read_write_amp, write_amp,
status.ToString().c_str(), stats.num_input_records,
stats.num_dropped_records,
CompressionTypeToString(compact_->compaction->output_compression())
.c_str());
UpdateCompactionJobStats(stats);
auto stream = event_logger_->LogToBuffer(log_buffer_);
stream << "job" << job_id_ << "event"
<< "compaction_finished"
<< "compaction_time_micros" << compaction_stats_.micros
<< "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 << "num_subcompactions"
<< compact_->sub_compact_states.size() << "output_compression"
<< CompressionTypeToString(compact_->compaction->output_compression());
if (compaction_job_stats_ != nullptr) {
stream << "num_single_delete_mismatches"
<< compaction_job_stats_->num_single_del_mismatch;
stream << "num_single_delete_fallthrough"
<< compaction_job_stats_->num_single_del_fallthru;
}
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);
Compaction Support for Range Deletion Summary: This diff introduces RangeDelAggregator, which takes ownership of iterators provided to it via AddTombstones(). The tombstones are organized in a two-level map (snapshot stripe -> begin key -> tombstone). Tombstone creation avoids data copy by holding Slices returned by the iterator, which remain valid thanks to pinning. For compaction, we create a hierarchical range tombstone iterator with structure matching the iterator over compaction input data. An aggregator based on that iterator is used by CompactionIterator to determine which keys are covered by range tombstones. In case of merge operand, the same aggregator is used by MergeHelper. Upon finishing each file in the compaction, relevant range tombstones are added to the output file's range tombstone metablock and file boundaries are updated accordingly. To check whether a key is covered by range tombstone, RangeDelAggregator::ShouldDelete() considers tombstones in the key's snapshot stripe. When this function is used outside of compaction, it also checks newer stripes, which can contain covering tombstones. Currently the intra-stripe check involves a linear scan; however, in the future we plan to collapse ranges within a stripe such that binary search can be used. RangeDelAggregator::AddToBuilder() adds all range tombstones in the table's key-range to a new table's range tombstone meta-block. Since range tombstones may fall in the gap between files, we may need to extend some files' key-ranges. The strategy is (1) first file extends as far left as possible and other files do not extend left, (2) all files extend right until either the start of the next file or the end of the last range tombstone in the gap, whichever comes first. One other notable change is adding release/move semantics to ScopedArenaIterator such that it can be used to transfer ownership of an arena-allocated iterator, similar to how unique_ptr is used for malloc'd data. Depends on D61473 Test Plan: compaction_iterator_test, mock_table, end-to-end tests in D63927 Reviewers: sdong, IslamAbdelRahman, wanning, yhchiang, lightmark Reviewed By: lightmark Subscribers: andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D62205
8 years ago
ColumnFamilyData* cfd = sub_compact->compaction->column_family_data();
std::unique_ptr<RangeDelAggregator> range_del_agg(
new RangeDelAggregator(cfd->internal_comparator(), existing_snapshots_));
std::unique_ptr<InternalIterator> input(versions_->MakeInputIterator(
sub_compact->compaction, range_del_agg.get(), env_optiosn_for_read_));
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;
const uint64_t kRecordStatsEvery = 1000;
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(write_nanos);
prev_fsync_nanos = IOSTATS(fsync_nanos);
prev_range_sync_nanos = IOSTATS(range_sync_nanos);
prev_prepare_write_nanos = IOSTATS(prepare_write_nanos);
}
const MutableCFOptions* mutable_cf_options =
sub_compact->compaction->mutable_cf_options();
// To build compression dictionary, we sample the first output file, assuming
// it'll reach the maximum length. We optionally pass these samples through
// zstd's dictionary trainer, or just use them directly. Then, the dictionary
// is used for compressing subsequent output files in the same subcompaction.
const bool kUseZstdTrainer =
cfd->ioptions()->compression_opts.zstd_max_train_bytes > 0;
const size_t kSampleBytes =
kUseZstdTrainer ? cfd->ioptions()->compression_opts.zstd_max_train_bytes
: cfd->ioptions()->compression_opts.max_dict_bytes;
const int kSampleLenShift = 6; // 2^6 = 64-byte samples
std::set<size_t> sample_begin_offsets;
if (bottommost_level_ && kSampleBytes > 0) {
const size_t kMaxSamples = kSampleBytes >> kSampleLenShift;
const size_t kOutFileLen = static_cast<size_t>(
mutable_cf_options->MaxFileSizeForLevel(
compact_->compaction->output_level()));
if (kOutFileLen != port::kMaxSizet) {
const size_t kOutFileNumSamples = kOutFileLen >> kSampleLenShift;
Random64 generator{versions_->NewFileNumber()};
for (size_t i = 0; i < kMaxSamples; ++i) {
sample_begin_offsets.insert(
static_cast<size_t>(generator.Uniform(kOutFileNumSamples))
<< kSampleLenShift);
}
}
}
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();
}
MergeHelper merge(
env_, cfd->user_comparator(), cfd->ioptions()->merge_operator,
compaction_filter, db_options_.info_log.get(),
false /* internal key corruption is expected */,
existing_snapshots_.empty() ? 0 : existing_snapshots_.back(),
snapshot_checker_, compact_->compaction->level(),
db_options_.statistics.get(), shutting_down_);
TEST_SYNC_POINT("CompactionJob::Run():Inprogress");
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);
input->Seek(start_iter.GetInternalKey());
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
} else {
input->SeekToFirst();
}
Status status;
sub_compact->c_iter.reset(new CompactionIterator(
input.get(), cfd->user_comparator(), &merge, versions_->LastSequence(),
&existing_snapshots_, earliest_write_conflict_snapshot_,
snapshot_checker_, env_, false, range_del_agg.get(),
sub_compact->compaction, compaction_filter, shutting_down_,
preserve_deletes_seqnum_));
auto c_iter = sub_compact->c_iter.get();
c_iter->SeekToFirst();
if (c_iter->Valid() &&
sub_compact->compaction->output_level() != 0) {
// ShouldStopBefore() maintains state based on keys processed so far. The
// compaction loop always calls it on the "next" key, thus won't tell it the
// first key. So we do that here.
sub_compact->ShouldStopBefore(
c_iter->key(), sub_compact->current_output_file_size);
}
const auto& c_iter_stats = c_iter->iter_stats();
auto sample_begin_offset_iter = sample_begin_offsets.cbegin();
// data_begin_offset and dict_sample_data are only valid while generating
// dictionary from the first output file.
size_t data_begin_offset = 0;
std::string dict_sample_data;
dict_sample_data.reserve(kSampleBytes);
while (status.ok() && !cfd->IsDropped() && c_iter->Valid()) {
// Invariant: c_iter.status() is guaranteed to be OK if c_iter->Valid()
// returns true.
const Slice& key = c_iter->key();
const Slice& value = c_iter->value();
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 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(c_iter->user_key(), *end) >= 0) {
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;
}
if (c_iter_stats.num_input_records % kRecordStatsEvery ==
kRecordStatsEvery - 1) {
RecordDroppedKeys(c_iter_stats, &sub_compact->compaction_job_stats);
c_iter->ResetRecordCounts();
RecordCompactionIOStats();
}
// Open output file if necessary
if (sub_compact->builder == nullptr) {
status = OpenCompactionOutputFile(sub_compact);
if (!status.ok()) {
break;
}
}
assert(sub_compact->builder != nullptr);
assert(sub_compact->current_output() != nullptr);
sub_compact->builder->Add(key, value);
sub_compact->current_output_file_size = sub_compact->builder->FileSize();
sub_compact->current_output()->meta.UpdateBoundaries(
key, c_iter->ikey().sequence);
sub_compact->num_output_records++;
if (sub_compact->outputs.size() == 1) { // first output file
// Check if this key/value overlaps any sample intervals; if so, appends
// overlapping portions to the dictionary.
for (const auto& data_elmt : {key, value}) {
size_t data_end_offset = data_begin_offset + data_elmt.size();
while (sample_begin_offset_iter != sample_begin_offsets.cend() &&
*sample_begin_offset_iter < data_end_offset) {
size_t sample_end_offset =
*sample_begin_offset_iter + (1 << kSampleLenShift);
// Invariant: Because we advance sample iterator while processing the
// data_elmt containing the sample's last byte, the current sample
// cannot end before the current data_elmt.
assert(data_begin_offset < sample_end_offset);
size_t data_elmt_copy_offset, data_elmt_copy_len;
if (*sample_begin_offset_iter <= data_begin_offset) {
// The sample starts before data_elmt starts, so take bytes starting
// at the beginning of data_elmt.
data_elmt_copy_offset = 0;
} else {
// data_elmt starts before the sample starts, so take bytes starting
// at the below offset into data_elmt.
data_elmt_copy_offset =
*sample_begin_offset_iter - data_begin_offset;
}
if (sample_end_offset <= data_end_offset) {
// The sample ends before data_elmt ends, so take as many bytes as
// needed.
data_elmt_copy_len =
sample_end_offset - (data_begin_offset + data_elmt_copy_offset);
} else {
// data_elmt ends before the sample ends, so take all remaining
// bytes in data_elmt.
data_elmt_copy_len =
data_end_offset - (data_begin_offset + data_elmt_copy_offset);
}
dict_sample_data.append(&data_elmt.data()[data_elmt_copy_offset],
data_elmt_copy_len);
if (sample_end_offset > data_end_offset) {
// Didn't finish sample. Try to finish it with the next data_elmt.
break;
}
// Next sample may require bytes from same data_elmt.
sample_begin_offset_iter++;
}
data_begin_offset = data_end_offset;
}
}
// Close output file if it is big enough. Two possibilities determine it's
// time to close it: (1) the current key should be this file's last key, (2)
// the next key should not be in this file.
//
// TODO(aekmekji): determine if file should be closed earlier than this
// during subcompactions (i.e. if output size, estimated by input size, is
// going to be 1.2MB and max_output_file_size = 1MB, prefer to have 0.6MB
// and 0.6MB instead of 1MB and 0.2MB)
bool output_file_ended = false;
Status input_status;
if (sub_compact->compaction->output_level() != 0 &&
sub_compact->current_output_file_size >=
sub_compact->compaction->max_output_file_size()) {
// (1) this key terminates the file. For historical reasons, the iterator
// status before advancing will be given to FinishCompactionOutputFile().
input_status = input->status();
output_file_ended = true;
}
c_iter->Next();
if (!output_file_ended && c_iter->Valid() &&
sub_compact->compaction->output_level() != 0 &&
sub_compact->ShouldStopBefore(
c_iter->key(), sub_compact->current_output_file_size) &&
sub_compact->builder != nullptr) {
// (2) this key belongs to the next file. For historical reasons, the
// iterator status after advancing will be given to
// FinishCompactionOutputFile().
input_status = input->status();
output_file_ended = true;
}
if (output_file_ended) {
Compaction Support for Range Deletion Summary: This diff introduces RangeDelAggregator, which takes ownership of iterators provided to it via AddTombstones(). The tombstones are organized in a two-level map (snapshot stripe -> begin key -> tombstone). Tombstone creation avoids data copy by holding Slices returned by the iterator, which remain valid thanks to pinning. For compaction, we create a hierarchical range tombstone iterator with structure matching the iterator over compaction input data. An aggregator based on that iterator is used by CompactionIterator to determine which keys are covered by range tombstones. In case of merge operand, the same aggregator is used by MergeHelper. Upon finishing each file in the compaction, relevant range tombstones are added to the output file's range tombstone metablock and file boundaries are updated accordingly. To check whether a key is covered by range tombstone, RangeDelAggregator::ShouldDelete() considers tombstones in the key's snapshot stripe. When this function is used outside of compaction, it also checks newer stripes, which can contain covering tombstones. Currently the intra-stripe check involves a linear scan; however, in the future we plan to collapse ranges within a stripe such that binary search can be used. RangeDelAggregator::AddToBuilder() adds all range tombstones in the table's key-range to a new table's range tombstone meta-block. Since range tombstones may fall in the gap between files, we may need to extend some files' key-ranges. The strategy is (1) first file extends as far left as possible and other files do not extend left, (2) all files extend right until either the start of the next file or the end of the last range tombstone in the gap, whichever comes first. One other notable change is adding release/move semantics to ScopedArenaIterator such that it can be used to transfer ownership of an arena-allocated iterator, similar to how unique_ptr is used for malloc'd data. Depends on D61473 Test Plan: compaction_iterator_test, mock_table, end-to-end tests in D63927 Reviewers: sdong, IslamAbdelRahman, wanning, yhchiang, lightmark Reviewed By: lightmark Subscribers: andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D62205
8 years ago
const Slice* next_key = nullptr;
if (c_iter->Valid()) {
next_key = &c_iter->key();
}
CompactionIterationStats range_del_out_stats;
Compaction Support for Range Deletion Summary: This diff introduces RangeDelAggregator, which takes ownership of iterators provided to it via AddTombstones(). The tombstones are organized in a two-level map (snapshot stripe -> begin key -> tombstone). Tombstone creation avoids data copy by holding Slices returned by the iterator, which remain valid thanks to pinning. For compaction, we create a hierarchical range tombstone iterator with structure matching the iterator over compaction input data. An aggregator based on that iterator is used by CompactionIterator to determine which keys are covered by range tombstones. In case of merge operand, the same aggregator is used by MergeHelper. Upon finishing each file in the compaction, relevant range tombstones are added to the output file's range tombstone metablock and file boundaries are updated accordingly. To check whether a key is covered by range tombstone, RangeDelAggregator::ShouldDelete() considers tombstones in the key's snapshot stripe. When this function is used outside of compaction, it also checks newer stripes, which can contain covering tombstones. Currently the intra-stripe check involves a linear scan; however, in the future we plan to collapse ranges within a stripe such that binary search can be used. RangeDelAggregator::AddToBuilder() adds all range tombstones in the table's key-range to a new table's range tombstone meta-block. Since range tombstones may fall in the gap between files, we may need to extend some files' key-ranges. The strategy is (1) first file extends as far left as possible and other files do not extend left, (2) all files extend right until either the start of the next file or the end of the last range tombstone in the gap, whichever comes first. One other notable change is adding release/move semantics to ScopedArenaIterator such that it can be used to transfer ownership of an arena-allocated iterator, similar to how unique_ptr is used for malloc'd data. Depends on D61473 Test Plan: compaction_iterator_test, mock_table, end-to-end tests in D63927 Reviewers: sdong, IslamAbdelRahman, wanning, yhchiang, lightmark Reviewed By: lightmark Subscribers: andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D62205
8 years ago
status = FinishCompactionOutputFile(input_status, sub_compact,
range_del_agg.get(),
&range_del_out_stats, next_key);
RecordDroppedKeys(range_del_out_stats,
&sub_compact->compaction_job_stats);
if (sub_compact->outputs.size() == 1) {
// Use samples from first output file to create dictionary for
// compression of subsequent files.
if (kUseZstdTrainer) {
sub_compact->compression_dict = ZSTD_TrainDictionary(
dict_sample_data, kSampleLenShift,
cfd->ioptions()->compression_opts.max_dict_bytes);
} else {
sub_compact->compression_dict = std::move(dict_sample_data);
}
}
}
}
sub_compact->num_input_records = c_iter_stats.num_input_records;
sub_compact->compaction_job_stats.num_input_deletion_records =
c_iter_stats.num_input_deletion_records;
sub_compact->compaction_job_stats.num_corrupt_keys =
c_iter_stats.num_input_corrupt_records;
sub_compact->compaction_job_stats.num_single_del_fallthru =
c_iter_stats.num_single_del_fallthru;
sub_compact->compaction_job_stats.num_single_del_mismatch =
c_iter_stats.num_single_del_mismatch;
sub_compact->compaction_job_stats.total_input_raw_key_bytes +=
c_iter_stats.total_input_raw_key_bytes;
sub_compact->compaction_job_stats.total_input_raw_value_bytes +=
c_iter_stats.total_input_raw_value_bytes;
RecordTick(stats_, FILTER_OPERATION_TOTAL_TIME,
c_iter_stats.total_filter_time);
RecordDroppedKeys(c_iter_stats, &sub_compact->compaction_job_stats);
RecordCompactionIOStats();
if (status.ok() && (shutting_down_->load(std::memory_order_relaxed) ||
cfd->IsDropped())) {
status = Status::ShutdownInProgress(
"Database shutdown or Column family drop during compaction");
}
if (status.ok()) {
status = input->status();
}
if (status.ok()) {
status = c_iter->status();
}
Compaction Support for Range Deletion Summary: This diff introduces RangeDelAggregator, which takes ownership of iterators provided to it via AddTombstones(). The tombstones are organized in a two-level map (snapshot stripe -> begin key -> tombstone). Tombstone creation avoids data copy by holding Slices returned by the iterator, which remain valid thanks to pinning. For compaction, we create a hierarchical range tombstone iterator with structure matching the iterator over compaction input data. An aggregator based on that iterator is used by CompactionIterator to determine which keys are covered by range tombstones. In case of merge operand, the same aggregator is used by MergeHelper. Upon finishing each file in the compaction, relevant range tombstones are added to the output file's range tombstone metablock and file boundaries are updated accordingly. To check whether a key is covered by range tombstone, RangeDelAggregator::ShouldDelete() considers tombstones in the key's snapshot stripe. When this function is used outside of compaction, it also checks newer stripes, which can contain covering tombstones. Currently the intra-stripe check involves a linear scan; however, in the future we plan to collapse ranges within a stripe such that binary search can be used. RangeDelAggregator::AddToBuilder() adds all range tombstones in the table's key-range to a new table's range tombstone meta-block. Since range tombstones may fall in the gap between files, we may need to extend some files' key-ranges. The strategy is (1) first file extends as far left as possible and other files do not extend left, (2) all files extend right until either the start of the next file or the end of the last range tombstone in the gap, whichever comes first. One other notable change is adding release/move semantics to ScopedArenaIterator such that it can be used to transfer ownership of an arena-allocated iterator, similar to how unique_ptr is used for malloc'd data. Depends on D61473 Test Plan: compaction_iterator_test, mock_table, end-to-end tests in D63927 Reviewers: sdong, IslamAbdelRahman, wanning, yhchiang, lightmark Reviewed By: lightmark Subscribers: andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D62205
8 years ago
if (status.ok() && sub_compact->builder == nullptr &&
sub_compact->outputs.size() == 0 &&
Compaction Support for Range Deletion Summary: This diff introduces RangeDelAggregator, which takes ownership of iterators provided to it via AddTombstones(). The tombstones are organized in a two-level map (snapshot stripe -> begin key -> tombstone). Tombstone creation avoids data copy by holding Slices returned by the iterator, which remain valid thanks to pinning. For compaction, we create a hierarchical range tombstone iterator with structure matching the iterator over compaction input data. An aggregator based on that iterator is used by CompactionIterator to determine which keys are covered by range tombstones. In case of merge operand, the same aggregator is used by MergeHelper. Upon finishing each file in the compaction, relevant range tombstones are added to the output file's range tombstone metablock and file boundaries are updated accordingly. To check whether a key is covered by range tombstone, RangeDelAggregator::ShouldDelete() considers tombstones in the key's snapshot stripe. When this function is used outside of compaction, it also checks newer stripes, which can contain covering tombstones. Currently the intra-stripe check involves a linear scan; however, in the future we plan to collapse ranges within a stripe such that binary search can be used. RangeDelAggregator::AddToBuilder() adds all range tombstones in the table's key-range to a new table's range tombstone meta-block. Since range tombstones may fall in the gap between files, we may need to extend some files' key-ranges. The strategy is (1) first file extends as far left as possible and other files do not extend left, (2) all files extend right until either the start of the next file or the end of the last range tombstone in the gap, whichever comes first. One other notable change is adding release/move semantics to ScopedArenaIterator such that it can be used to transfer ownership of an arena-allocated iterator, similar to how unique_ptr is used for malloc'd data. Depends on D61473 Test Plan: compaction_iterator_test, mock_table, end-to-end tests in D63927 Reviewers: sdong, IslamAbdelRahman, wanning, yhchiang, lightmark Reviewed By: lightmark Subscribers: andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D62205
8 years ago
range_del_agg->ShouldAddTombstones(bottommost_level_)) {
// handle subcompaction containing only range deletions
Compaction Support for Range Deletion Summary: This diff introduces RangeDelAggregator, which takes ownership of iterators provided to it via AddTombstones(). The tombstones are organized in a two-level map (snapshot stripe -> begin key -> tombstone). Tombstone creation avoids data copy by holding Slices returned by the iterator, which remain valid thanks to pinning. For compaction, we create a hierarchical range tombstone iterator with structure matching the iterator over compaction input data. An aggregator based on that iterator is used by CompactionIterator to determine which keys are covered by range tombstones. In case of merge operand, the same aggregator is used by MergeHelper. Upon finishing each file in the compaction, relevant range tombstones are added to the output file's range tombstone metablock and file boundaries are updated accordingly. To check whether a key is covered by range tombstone, RangeDelAggregator::ShouldDelete() considers tombstones in the key's snapshot stripe. When this function is used outside of compaction, it also checks newer stripes, which can contain covering tombstones. Currently the intra-stripe check involves a linear scan; however, in the future we plan to collapse ranges within a stripe such that binary search can be used. RangeDelAggregator::AddToBuilder() adds all range tombstones in the table's key-range to a new table's range tombstone meta-block. Since range tombstones may fall in the gap between files, we may need to extend some files' key-ranges. The strategy is (1) first file extends as far left as possible and other files do not extend left, (2) all files extend right until either the start of the next file or the end of the last range tombstone in the gap, whichever comes first. One other notable change is adding release/move semantics to ScopedArenaIterator such that it can be used to transfer ownership of an arena-allocated iterator, similar to how unique_ptr is used for malloc'd data. Depends on D61473 Test Plan: compaction_iterator_test, mock_table, end-to-end tests in D63927 Reviewers: sdong, IslamAbdelRahman, wanning, yhchiang, lightmark Reviewed By: lightmark Subscribers: andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D62205
8 years ago
status = OpenCompactionOutputFile(sub_compact);
}
// Call FinishCompactionOutputFile() even if status is not ok: it needs to
// close the output file.
if (sub_compact->builder != nullptr) {
CompactionIterationStats range_del_out_stats;
Status s = FinishCompactionOutputFile(
status, sub_compact, range_del_agg.get(), &range_del_out_stats);
if (status.ok()) {
status = s;
}
RecordDroppedKeys(range_del_out_stats, &sub_compact->compaction_job_stats);
}
if (measure_io_stats_) {
sub_compact->compaction_job_stats.file_write_nanos +=
IOSTATS(write_nanos) - prev_write_nanos;
sub_compact->compaction_job_stats.file_fsync_nanos +=
IOSTATS(fsync_nanos) - prev_fsync_nanos;
sub_compact->compaction_job_stats.file_range_sync_nanos +=
IOSTATS(range_sync_nanos) - prev_range_sync_nanos;
sub_compact->compaction_job_stats.file_prepare_write_nanos +=
IOSTATS(prepare_write_nanos) - prev_prepare_write_nanos;
if (prev_perf_level != PerfLevel::kEnableTime) {
SetPerfLevel(prev_perf_level);
}
}
sub_compact->c_iter.reset();
input.reset();
sub_compact->status = status;
}
void CompactionJob::RecordDroppedKeys(
const CompactionIterationStats& c_iter_stats,
CompactionJobStats* compaction_job_stats) {
if (c_iter_stats.num_record_drop_user > 0) {
RecordTick(stats_, COMPACTION_KEY_DROP_USER,
c_iter_stats.num_record_drop_user);
}
if (c_iter_stats.num_record_drop_hidden > 0) {
RecordTick(stats_, COMPACTION_KEY_DROP_NEWER_ENTRY,
c_iter_stats.num_record_drop_hidden);
if (compaction_job_stats) {
compaction_job_stats->num_records_replaced +=
c_iter_stats.num_record_drop_hidden;
}
}
if (c_iter_stats.num_record_drop_obsolete > 0) {
RecordTick(stats_, COMPACTION_KEY_DROP_OBSOLETE,
c_iter_stats.num_record_drop_obsolete);
if (compaction_job_stats) {
compaction_job_stats->num_expired_deletion_records +=
c_iter_stats.num_record_drop_obsolete;
}
}
if (c_iter_stats.num_record_drop_range_del > 0) {
RecordTick(stats_, COMPACTION_KEY_DROP_RANGE_DEL,
c_iter_stats.num_record_drop_range_del);
}
if (c_iter_stats.num_range_del_drop_obsolete > 0) {
RecordTick(stats_, COMPACTION_RANGE_DEL_DROP_OBSOLETE,
c_iter_stats.num_range_del_drop_obsolete);
}
if (c_iter_stats.num_optimized_del_drop_obsolete > 0) {
RecordTick(stats_, COMPACTION_OPTIMIZED_DEL_DROP_OBSOLETE,
c_iter_stats.num_optimized_del_drop_obsolete);
}
}
Status CompactionJob::FinishCompactionOutputFile(
Compaction Support for Range Deletion Summary: This diff introduces RangeDelAggregator, which takes ownership of iterators provided to it via AddTombstones(). The tombstones are organized in a two-level map (snapshot stripe -> begin key -> tombstone). Tombstone creation avoids data copy by holding Slices returned by the iterator, which remain valid thanks to pinning. For compaction, we create a hierarchical range tombstone iterator with structure matching the iterator over compaction input data. An aggregator based on that iterator is used by CompactionIterator to determine which keys are covered by range tombstones. In case of merge operand, the same aggregator is used by MergeHelper. Upon finishing each file in the compaction, relevant range tombstones are added to the output file's range tombstone metablock and file boundaries are updated accordingly. To check whether a key is covered by range tombstone, RangeDelAggregator::ShouldDelete() considers tombstones in the key's snapshot stripe. When this function is used outside of compaction, it also checks newer stripes, which can contain covering tombstones. Currently the intra-stripe check involves a linear scan; however, in the future we plan to collapse ranges within a stripe such that binary search can be used. RangeDelAggregator::AddToBuilder() adds all range tombstones in the table's key-range to a new table's range tombstone meta-block. Since range tombstones may fall in the gap between files, we may need to extend some files' key-ranges. The strategy is (1) first file extends as far left as possible and other files do not extend left, (2) all files extend right until either the start of the next file or the end of the last range tombstone in the gap, whichever comes first. One other notable change is adding release/move semantics to ScopedArenaIterator such that it can be used to transfer ownership of an arena-allocated iterator, similar to how unique_ptr is used for malloc'd data. Depends on D61473 Test Plan: compaction_iterator_test, mock_table, end-to-end tests in D63927 Reviewers: sdong, IslamAbdelRahman, wanning, yhchiang, lightmark Reviewed By: lightmark Subscribers: andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D62205
8 years ago
const Status& input_status, SubcompactionState* sub_compact,
RangeDelAggregator* range_del_agg,
CompactionIterationStats* range_del_out_stats,
Compaction Support for Range Deletion Summary: This diff introduces RangeDelAggregator, which takes ownership of iterators provided to it via AddTombstones(). The tombstones are organized in a two-level map (snapshot stripe -> begin key -> tombstone). Tombstone creation avoids data copy by holding Slices returned by the iterator, which remain valid thanks to pinning. For compaction, we create a hierarchical range tombstone iterator with structure matching the iterator over compaction input data. An aggregator based on that iterator is used by CompactionIterator to determine which keys are covered by range tombstones. In case of merge operand, the same aggregator is used by MergeHelper. Upon finishing each file in the compaction, relevant range tombstones are added to the output file's range tombstone metablock and file boundaries are updated accordingly. To check whether a key is covered by range tombstone, RangeDelAggregator::ShouldDelete() considers tombstones in the key's snapshot stripe. When this function is used outside of compaction, it also checks newer stripes, which can contain covering tombstones. Currently the intra-stripe check involves a linear scan; however, in the future we plan to collapse ranges within a stripe such that binary search can be used. RangeDelAggregator::AddToBuilder() adds all range tombstones in the table's key-range to a new table's range tombstone meta-block. Since range tombstones may fall in the gap between files, we may need to extend some files' key-ranges. The strategy is (1) first file extends as far left as possible and other files do not extend left, (2) all files extend right until either the start of the next file or the end of the last range tombstone in the gap, whichever comes first. One other notable change is adding release/move semantics to ScopedArenaIterator such that it can be used to transfer ownership of an arena-allocated iterator, similar to how unique_ptr is used for malloc'd data. Depends on D61473 Test Plan: compaction_iterator_test, mock_table, end-to-end tests in D63927 Reviewers: sdong, IslamAbdelRahman, wanning, yhchiang, lightmark Reviewed By: lightmark Subscribers: andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D62205
8 years ago
const Slice* next_table_min_key /* = nullptr */) {
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);
assert(sub_compact->current_output() != nullptr);
uint64_t output_number = sub_compact->current_output()->meta.fd.GetNumber();
assert(output_number != 0);
// Check for iterator errors
Status s = input_status;
auto meta = &sub_compact->current_output()->meta;
Compaction Support for Range Deletion Summary: This diff introduces RangeDelAggregator, which takes ownership of iterators provided to it via AddTombstones(). The tombstones are organized in a two-level map (snapshot stripe -> begin key -> tombstone). Tombstone creation avoids data copy by holding Slices returned by the iterator, which remain valid thanks to pinning. For compaction, we create a hierarchical range tombstone iterator with structure matching the iterator over compaction input data. An aggregator based on that iterator is used by CompactionIterator to determine which keys are covered by range tombstones. In case of merge operand, the same aggregator is used by MergeHelper. Upon finishing each file in the compaction, relevant range tombstones are added to the output file's range tombstone metablock and file boundaries are updated accordingly. To check whether a key is covered by range tombstone, RangeDelAggregator::ShouldDelete() considers tombstones in the key's snapshot stripe. When this function is used outside of compaction, it also checks newer stripes, which can contain covering tombstones. Currently the intra-stripe check involves a linear scan; however, in the future we plan to collapse ranges within a stripe such that binary search can be used. RangeDelAggregator::AddToBuilder() adds all range tombstones in the table's key-range to a new table's range tombstone meta-block. Since range tombstones may fall in the gap between files, we may need to extend some files' key-ranges. The strategy is (1) first file extends as far left as possible and other files do not extend left, (2) all files extend right until either the start of the next file or the end of the last range tombstone in the gap, whichever comes first. One other notable change is adding release/move semantics to ScopedArenaIterator such that it can be used to transfer ownership of an arena-allocated iterator, similar to how unique_ptr is used for malloc'd data. Depends on D61473 Test Plan: compaction_iterator_test, mock_table, end-to-end tests in D63927 Reviewers: sdong, IslamAbdelRahman, wanning, yhchiang, lightmark Reviewed By: lightmark Subscribers: andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D62205
8 years ago
if (s.ok()) {
Slice lower_bound_guard, upper_bound_guard;
std::string smallest_user_key;
const Slice *lower_bound, *upper_bound;
if (sub_compact->outputs.size() == 1) {
// For the first output table, include range tombstones before the min key
// but after the subcompaction boundary.
lower_bound = sub_compact->start;
} else if (meta->smallest.size() > 0) {
// For subsequent output tables, only include range tombstones from min
// key onwards since the previous file was extended to contain range
// tombstones falling before min key.
smallest_user_key = meta->smallest.user_key().ToString(false /*hex*/);
lower_bound_guard = Slice(smallest_user_key);
lower_bound = &lower_bound_guard;
} else {
lower_bound = nullptr;
}
if (next_table_min_key != nullptr) {
// This isn't the last file in the subcompaction, so extend until the next
// file starts.
upper_bound_guard = ExtractUserKey(*next_table_min_key);
upper_bound = &upper_bound_guard;
} else {
// This is the last file in the subcompaction, so extend until the
// subcompaction ends.
upper_bound = sub_compact->end;
}
range_del_agg->AddToBuilder(sub_compact->builder.get(), lower_bound,
upper_bound, meta, range_del_out_stats,
bottommost_level_);
meta->marked_for_compaction = sub_compact->builder->NeedCompact();
Compaction Support for Range Deletion Summary: This diff introduces RangeDelAggregator, which takes ownership of iterators provided to it via AddTombstones(). The tombstones are organized in a two-level map (snapshot stripe -> begin key -> tombstone). Tombstone creation avoids data copy by holding Slices returned by the iterator, which remain valid thanks to pinning. For compaction, we create a hierarchical range tombstone iterator with structure matching the iterator over compaction input data. An aggregator based on that iterator is used by CompactionIterator to determine which keys are covered by range tombstones. In case of merge operand, the same aggregator is used by MergeHelper. Upon finishing each file in the compaction, relevant range tombstones are added to the output file's range tombstone metablock and file boundaries are updated accordingly. To check whether a key is covered by range tombstone, RangeDelAggregator::ShouldDelete() considers tombstones in the key's snapshot stripe. When this function is used outside of compaction, it also checks newer stripes, which can contain covering tombstones. Currently the intra-stripe check involves a linear scan; however, in the future we plan to collapse ranges within a stripe such that binary search can be used. RangeDelAggregator::AddToBuilder() adds all range tombstones in the table's key-range to a new table's range tombstone meta-block. Since range tombstones may fall in the gap between files, we may need to extend some files' key-ranges. The strategy is (1) first file extends as far left as possible and other files do not extend left, (2) all files extend right until either the start of the next file or the end of the last range tombstone in the gap, whichever comes first. One other notable change is adding release/move semantics to ScopedArenaIterator such that it can be used to transfer ownership of an arena-allocated iterator, similar to how unique_ptr is used for malloc'd data. Depends on D61473 Test Plan: compaction_iterator_test, mock_table, end-to-end tests in D63927 Reviewers: sdong, IslamAbdelRahman, wanning, yhchiang, lightmark Reviewed By: lightmark Subscribers: andrewkr, dhruba, leveldb Differential Revision: https://reviews.facebook.net/D62205
8 years ago
}
const uint64_t current_entries = sub_compact->builder->NumEntries();
if (s.ok()) {
s = sub_compact->builder->Finish();
} else {
sub_compact->builder->Abandon();
}
const uint64_t current_bytes = sub_compact->builder->FileSize();
if (s.ok()) {
meta->fd.file_size = current_bytes;
}
sub_compact->current_output()->finished = true;
sub_compact->total_bytes += current_bytes;
// Finish and check for file errors
if (s.ok()) {
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) {
// If there is nothing to output, no necessary to generate a sst file.
// This happens when the output level is bottom level, at the same time
// the sub_compact output nothing.
std::string fname = TableFileName(
db_options_.db_paths, meta->fd.GetNumber(), meta->fd.GetPathId());
env_->DeleteFile(fname);
// Also need to remove the file from outputs, or it will be added to the
// VersionEdit.
assert(!sub_compact->outputs.empty());
sub_compact->outputs.pop_back();
sub_compact->builder.reset();
sub_compact->current_output_file_size = 0;
return s;
}
ColumnFamilyData* cfd = sub_compact->compaction->column_family_data();
TableProperties tp;
if (s.ok() && current_entries > 0) {
// Verify that the table is usable
// We set for_compaction to false and don't OptimizeForCompactionTableRead
// here because this is a special case after we finish the table building
// No matter whether use_direct_io_for_flush_and_compaction is true,
// we will regrad this verification as user reads since the goal is
// to cache it here for further user reads
InternalIterator* iter = cfd->table_cache()->NewIterator(
ReadOptions(), env_options_, cfd->internal_comparator(), meta->fd,
nullptr /* range_del_agg */, nullptr,
cfd->internal_stats()->GetFileReadHist(
compact_->compaction->output_level()),
false, nullptr /* arena */, false /* skip_filters */,
compact_->compaction->output_level());
s = iter->status();
if (s.ok() && paranoid_file_checks_) {
for (iter->SeekToFirst(); iter->Valid(); iter->Next()) {}
s = iter->status();
}
delete iter;
// Output to event logger and fire events.
if (s.ok()) {
tp = sub_compact->builder->GetTableProperties();
sub_compact->current_output()->table_properties =
std::make_shared<TableProperties>(tp);
ROCKS_LOG_INFO(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,
meta->marked_for_compaction ? " (need compaction)" : "");
}
}
std::string fname;
FileDescriptor output_fd;
if (meta != nullptr) {
fname = TableFileName(db_options_.db_paths, meta->fd.GetNumber(),
meta->fd.GetPathId());
output_fd = meta->fd;
} else {
fname = "(nil)";
}
EventHelpers::LogAndNotifyTableFileCreationFinished(
event_logger_, cfd->ioptions()->listeners, dbname_, cfd->GetName(), fname,
job_id_, output_fd, tp, TableFileCreationReason::kCompaction, s);
#ifndef ROCKSDB_LITE
// Report new file to SstFileManagerImpl
auto sfm =
static_cast<SstFileManagerImpl*>(db_options_.sst_file_manager.get());
if (sfm && meta != nullptr && meta->fd.GetPathId() == 0) {
auto fn = TableFileName(cfd->ioptions()->db_paths, meta->fd.GetNumber(),
meta->fd.GetPathId());
sfm->OnAddFile(fn);
if (sfm->IsMaxAllowedSpaceReached()) {
// TODO(ajkr): should we return OK() if max space was reached by the final
// compaction output file (similarly to how flush works when full)?
s = Status::IOError("Max allowed space was reached");
TEST_SYNC_POINT(
"CompactionJob::FinishCompactionOutputFile:"
"MaxAllowedSpaceReached");
InstrumentedMutexLock l(db_mutex_);
if (db_bg_error_->ok()) {
Status new_bg_error = s;
// may temporarily unlock and lock the mutex.
EventHelpers::NotifyOnBackgroundError(
cfd->ioptions()->listeners, BackgroundErrorReason::kCompaction,
&new_bg_error, db_mutex_);
if (!new_bg_error.ok()) {
*db_bg_error_ = new_bg_error;
}
}
}
}
#endif
sub_compact->builder.reset();
sub_compact->current_output_file_size = 0;
return s;
}
Status CompactionJob::InstallCompactionResults(
const MutableCFOptions& mutable_cf_options) {
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;
ROCKS_LOG_ERROR(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;
ROCKS_LOG_INFO(
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 (const auto& sub_compact : compact_->sub_compact_states) {
for (const auto& out : sub_compact.outputs) {
compaction->edit()->AddFile(compaction->output_level(), out.meta);
}
}
return versions_->LogAndApply(compaction->column_family_data(),
mutable_cf_options, compaction->edit(),
db_mutex_, db_directory_);
}
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();
std::string fname = TableFileName(db_options_.db_paths, file_number,
sub_compact->compaction->output_path_id());
// Fire events.
ColumnFamilyData* cfd = sub_compact->compaction->column_family_data();
#ifndef ROCKSDB_LITE
EventHelpers::NotifyTableFileCreationStarted(
cfd->ioptions()->listeners, dbname_, cfd->GetName(), fname, job_id_,
TableFileCreationReason::kCompaction);
#endif // !ROCKSDB_LITE
// Make the output file
unique_ptr<WritableFile> writable_file;
#ifndef NDEBUG
bool syncpoint_arg = env_options_.use_direct_writes;
TEST_SYNC_POINT_CALLBACK("CompactionJob::OpenCompactionOutputFile",
&syncpoint_arg);
#endif
Status s = NewWritableFile(env_, fname, &writable_file, env_options_);
if (!s.ok()) {
ROCKS_LOG_ERROR(
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);
EventHelpers::LogAndNotifyTableFileCreationFinished(
event_logger_, cfd->ioptions()->listeners, dbname_, cfd->GetName(),
fname, job_id_, FileDescriptor(), TableProperties(),
TableFileCreationReason::kCompaction, s);
return s;
}
SubcompactionState::Output out;
out.meta.fd =
FileDescriptor(file_number, sub_compact->compaction->output_path_id(), 0);
out.finished = false;
sub_compact->outputs.push_back(out);
writable_file->SetIOPriority(Env::IO_LOW);
writable_file->SetWriteLifeTimeHint(write_hint_);
writable_file->SetPreallocationBlockSize(static_cast<size_t>(
sub_compact->compaction->OutputFilePreallocationSize()));
sub_compact->outfile.reset(new WritableFileWriter(
std::move(writable_file), env_options_, db_options_.statistics.get()));
// 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
bool skip_filters =
cfd->ioptions()->optimize_filters_for_hits && bottommost_level_;
FIFO Compaction with TTL Summary: Introducing FIFO compactions with TTL. FIFO compaction is based on size only which makes it tricky to enable in production as use cases can have organic growth. A user requested an option to drop files based on the time of their creation instead of the total size. To address that request: - Added a new TTL option to FIFO compaction options. - Updated FIFO compaction score to take TTL into consideration. - Added a new table property, creation_time, to keep track of when the SST file is created. - Creation_time is set as below: - On Flush: Set to the time of flush. - On Compaction: Set to the max creation_time of all the files involved in the compaction. - On Repair and Recovery: Set to the time of repair/recovery. - Old files created prior to this code change will have a creation_time of 0. - FIFO compaction with TTL is enabled when ttl > 0. All files older than ttl will be deleted during compaction. i.e. `if (file.creation_time < (current_time - ttl)) then delete(file)`. This will enable cases where you might want to delete all files older than, say, 1 day. - FIFO compaction will fall back to the prior way of deleting files based on size if: - the creation_time of all files involved in compaction is 0. - the total size (of all SST files combined) does not drop below `compaction_options_fifo.max_table_files_size` even if the files older than ttl are deleted. This feature is not supported if max_open_files != -1 or with table formats other than Block-based. **Test Plan:** Added tests. **Benchmark results:** Base: FIFO with max size: 100MB :: ``` svemuri@dev15905 ~/rocksdb (fifo-compaction) $ TEST_TMPDIR=/dev/shm ./db_bench --benchmarks=readwhilewriting --num=5000000 --threads=16 --compaction_style=2 --fifo_compaction_max_table_files_size_mb=100 readwhilewriting : 1.924 micros/op 519858 ops/sec; 13.6 MB/s (1176277 of 5000000 found) ``` With TTL (a low one for testing) :: ``` svemuri@dev15905 ~/rocksdb (fifo-compaction) $ TEST_TMPDIR=/dev/shm ./db_bench --benchmarks=readwhilewriting --num=5000000 --threads=16 --compaction_style=2 --fifo_compaction_max_table_files_size_mb=100 --fifo_compaction_ttl=20 readwhilewriting : 1.902 micros/op 525817 ops/sec; 13.7 MB/s (1185057 of 5000000 found) ``` Example Log lines: ``` 2017/06/26-15:17:24.609249 7fd5a45ff700 (Original Log Time 2017/06/26-15:17:24.609177) [db/compaction_picker.cc:1471] [default] FIFO compaction: picking file 40 with creation time 1498515423 for deletion 2017/06/26-15:17:24.609255 7fd5a45ff700 (Original Log Time 2017/06/26-15:17:24.609234) [db/db_impl_compaction_flush.cc:1541] [default] Deleted 1 files ... 2017/06/26-15:17:25.553185 7fd5a61a5800 [DEBUG] [db/db_impl_files.cc:309] [JOB 0] Delete /dev/shm/dbbench/000040.sst type=2 #40 -- OK 2017/06/26-15:17:25.553205 7fd5a61a5800 EVENT_LOG_v1 {"time_micros": 1498515445553199, "job": 0, "event": "table_file_deletion", "file_number": 40} ``` SST Files remaining in the dbbench dir, after db_bench execution completed: ``` svemuri@dev15905 ~/rocksdb (fifo-compaction) $ ls -l /dev/shm//dbbench/*.sst -rw-r--r--. 1 svemuri users 30749887 Jun 26 15:17 /dev/shm//dbbench/000042.sst -rw-r--r--. 1 svemuri users 30768779 Jun 26 15:17 /dev/shm//dbbench/000044.sst -rw-r--r--. 1 svemuri users 30757481 Jun 26 15:17 /dev/shm//dbbench/000046.sst ``` Closes https://github.com/facebook/rocksdb/pull/2480 Differential Revision: D5305116 Pulled By: sagar0 fbshipit-source-id: 3e5cfcf5dd07ed2211b5b37492eb235b45139174
7 years ago
uint64_t output_file_creation_time =
sub_compact->compaction->MaxInputFileCreationTime();
if (output_file_creation_time == 0) {
int64_t _current_time = 0;
auto status = db_options_.env->GetCurrentTime(&_current_time);
// Safe to proceed even if GetCurrentTime fails. So, log and proceed.
if (!status.ok()) {
ROCKS_LOG_WARN(
db_options_.info_log,
"Failed to get current time to populate creation_time property. "
"Status: %s",
status.ToString().c_str());
}
FIFO Compaction with TTL Summary: Introducing FIFO compactions with TTL. FIFO compaction is based on size only which makes it tricky to enable in production as use cases can have organic growth. A user requested an option to drop files based on the time of their creation instead of the total size. To address that request: - Added a new TTL option to FIFO compaction options. - Updated FIFO compaction score to take TTL into consideration. - Added a new table property, creation_time, to keep track of when the SST file is created. - Creation_time is set as below: - On Flush: Set to the time of flush. - On Compaction: Set to the max creation_time of all the files involved in the compaction. - On Repair and Recovery: Set to the time of repair/recovery. - Old files created prior to this code change will have a creation_time of 0. - FIFO compaction with TTL is enabled when ttl > 0. All files older than ttl will be deleted during compaction. i.e. `if (file.creation_time < (current_time - ttl)) then delete(file)`. This will enable cases where you might want to delete all files older than, say, 1 day. - FIFO compaction will fall back to the prior way of deleting files based on size if: - the creation_time of all files involved in compaction is 0. - the total size (of all SST files combined) does not drop below `compaction_options_fifo.max_table_files_size` even if the files older than ttl are deleted. This feature is not supported if max_open_files != -1 or with table formats other than Block-based. **Test Plan:** Added tests. **Benchmark results:** Base: FIFO with max size: 100MB :: ``` svemuri@dev15905 ~/rocksdb (fifo-compaction) $ TEST_TMPDIR=/dev/shm ./db_bench --benchmarks=readwhilewriting --num=5000000 --threads=16 --compaction_style=2 --fifo_compaction_max_table_files_size_mb=100 readwhilewriting : 1.924 micros/op 519858 ops/sec; 13.6 MB/s (1176277 of 5000000 found) ``` With TTL (a low one for testing) :: ``` svemuri@dev15905 ~/rocksdb (fifo-compaction) $ TEST_TMPDIR=/dev/shm ./db_bench --benchmarks=readwhilewriting --num=5000000 --threads=16 --compaction_style=2 --fifo_compaction_max_table_files_size_mb=100 --fifo_compaction_ttl=20 readwhilewriting : 1.902 micros/op 525817 ops/sec; 13.7 MB/s (1185057 of 5000000 found) ``` Example Log lines: ``` 2017/06/26-15:17:24.609249 7fd5a45ff700 (Original Log Time 2017/06/26-15:17:24.609177) [db/compaction_picker.cc:1471] [default] FIFO compaction: picking file 40 with creation time 1498515423 for deletion 2017/06/26-15:17:24.609255 7fd5a45ff700 (Original Log Time 2017/06/26-15:17:24.609234) [db/db_impl_compaction_flush.cc:1541] [default] Deleted 1 files ... 2017/06/26-15:17:25.553185 7fd5a61a5800 [DEBUG] [db/db_impl_files.cc:309] [JOB 0] Delete /dev/shm/dbbench/000040.sst type=2 #40 -- OK 2017/06/26-15:17:25.553205 7fd5a61a5800 EVENT_LOG_v1 {"time_micros": 1498515445553199, "job": 0, "event": "table_file_deletion", "file_number": 40} ``` SST Files remaining in the dbbench dir, after db_bench execution completed: ``` svemuri@dev15905 ~/rocksdb (fifo-compaction) $ ls -l /dev/shm//dbbench/*.sst -rw-r--r--. 1 svemuri users 30749887 Jun 26 15:17 /dev/shm//dbbench/000042.sst -rw-r--r--. 1 svemuri users 30768779 Jun 26 15:17 /dev/shm//dbbench/000044.sst -rw-r--r--. 1 svemuri users 30757481 Jun 26 15:17 /dev/shm//dbbench/000046.sst ``` Closes https://github.com/facebook/rocksdb/pull/2480 Differential Revision: D5305116 Pulled By: sagar0 fbshipit-source-id: 3e5cfcf5dd07ed2211b5b37492eb235b45139174
7 years ago
output_file_creation_time = static_cast<uint64_t>(_current_time);
}
sub_compact->builder.reset(NewTableBuilder(
*cfd->ioptions(), cfd->internal_comparator(),
cfd->int_tbl_prop_collector_factories(), cfd->GetID(), cfd->GetName(),
sub_compact->outfile.get(), sub_compact->compaction->output_compression(),
cfd->ioptions()->compression_opts,
FIFO Compaction with TTL Summary: Introducing FIFO compactions with TTL. FIFO compaction is based on size only which makes it tricky to enable in production as use cases can have organic growth. A user requested an option to drop files based on the time of their creation instead of the total size. To address that request: - Added a new TTL option to FIFO compaction options. - Updated FIFO compaction score to take TTL into consideration. - Added a new table property, creation_time, to keep track of when the SST file is created. - Creation_time is set as below: - On Flush: Set to the time of flush. - On Compaction: Set to the max creation_time of all the files involved in the compaction. - On Repair and Recovery: Set to the time of repair/recovery. - Old files created prior to this code change will have a creation_time of 0. - FIFO compaction with TTL is enabled when ttl > 0. All files older than ttl will be deleted during compaction. i.e. `if (file.creation_time < (current_time - ttl)) then delete(file)`. This will enable cases where you might want to delete all files older than, say, 1 day. - FIFO compaction will fall back to the prior way of deleting files based on size if: - the creation_time of all files involved in compaction is 0. - the total size (of all SST files combined) does not drop below `compaction_options_fifo.max_table_files_size` even if the files older than ttl are deleted. This feature is not supported if max_open_files != -1 or with table formats other than Block-based. **Test Plan:** Added tests. **Benchmark results:** Base: FIFO with max size: 100MB :: ``` svemuri@dev15905 ~/rocksdb (fifo-compaction) $ TEST_TMPDIR=/dev/shm ./db_bench --benchmarks=readwhilewriting --num=5000000 --threads=16 --compaction_style=2 --fifo_compaction_max_table_files_size_mb=100 readwhilewriting : 1.924 micros/op 519858 ops/sec; 13.6 MB/s (1176277 of 5000000 found) ``` With TTL (a low one for testing) :: ``` svemuri@dev15905 ~/rocksdb (fifo-compaction) $ TEST_TMPDIR=/dev/shm ./db_bench --benchmarks=readwhilewriting --num=5000000 --threads=16 --compaction_style=2 --fifo_compaction_max_table_files_size_mb=100 --fifo_compaction_ttl=20 readwhilewriting : 1.902 micros/op 525817 ops/sec; 13.7 MB/s (1185057 of 5000000 found) ``` Example Log lines: ``` 2017/06/26-15:17:24.609249 7fd5a45ff700 (Original Log Time 2017/06/26-15:17:24.609177) [db/compaction_picker.cc:1471] [default] FIFO compaction: picking file 40 with creation time 1498515423 for deletion 2017/06/26-15:17:24.609255 7fd5a45ff700 (Original Log Time 2017/06/26-15:17:24.609234) [db/db_impl_compaction_flush.cc:1541] [default] Deleted 1 files ... 2017/06/26-15:17:25.553185 7fd5a61a5800 [DEBUG] [db/db_impl_files.cc:309] [JOB 0] Delete /dev/shm/dbbench/000040.sst type=2 #40 -- OK 2017/06/26-15:17:25.553205 7fd5a61a5800 EVENT_LOG_v1 {"time_micros": 1498515445553199, "job": 0, "event": "table_file_deletion", "file_number": 40} ``` SST Files remaining in the dbbench dir, after db_bench execution completed: ``` svemuri@dev15905 ~/rocksdb (fifo-compaction) $ ls -l /dev/shm//dbbench/*.sst -rw-r--r--. 1 svemuri users 30749887 Jun 26 15:17 /dev/shm//dbbench/000042.sst -rw-r--r--. 1 svemuri users 30768779 Jun 26 15:17 /dev/shm//dbbench/000044.sst -rw-r--r--. 1 svemuri users 30757481 Jun 26 15:17 /dev/shm//dbbench/000046.sst ``` Closes https://github.com/facebook/rocksdb/pull/2480 Differential Revision: D5305116 Pulled By: sagar0 fbshipit-source-id: 3e5cfcf5dd07ed2211b5b37492eb235b45139174
7 years ago
sub_compact->compaction->output_level(), &sub_compact->compression_dict,
skip_filters, output_file_creation_time));
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 (const auto& out : sub_compact.outputs) {
// 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.meta.fd.GetNumber());
}
}
}
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->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 (const auto& out : sub_compact.outputs) {
compaction_stats_.bytes_written += out.meta.fd.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;
ROCKS_LOG_INFO(
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));
ROCKS_LOG_INFO(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