2014-10-31 23:31:25 +00:00
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// Copyright (c) 2013, Facebook, Inc. All rights reserved.
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// This source code is licensed under the BSD-style license found in the
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// LICENSE file in the root directory of this source tree. An additional grant
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// of patent rights can be found in the PATENTS file in the same directory.
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//
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// Copyright (c) 2011 The LevelDB Authors. All rights reserved.
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// Use of this source code is governed by a BSD-style license that can be
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// found in the LICENSE file. See the AUTHORS file for names of contributors.
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#include "db/compaction_job.h"
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#ifndef __STDC_FORMAT_MACROS
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#define __STDC_FORMAT_MACROS
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#endif
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#include <inttypes.h>
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#include <algorithm>
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#include <vector>
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#include <memory>
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#include <list>
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#include "db/builder.h"
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#include "db/db_iter.h"
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#include "db/dbformat.h"
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2015-05-28 20:37:47 +00:00
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#include "db/event_helpers.h"
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2014-10-31 23:31:25 +00:00
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#include "db/filename.h"
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#include "db/log_reader.h"
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#include "db/log_writer.h"
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#include "db/memtable.h"
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#include "db/merge_helper.h"
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#include "db/memtable_list.h"
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#include "db/merge_context.h"
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#include "db/version_set.h"
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#include "port/port.h"
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#include "port/likely.h"
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#include "rocksdb/db.h"
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#include "rocksdb/env.h"
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#include "rocksdb/statistics.h"
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#include "rocksdb/status.h"
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#include "rocksdb/table.h"
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#include "table/block.h"
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#include "table/block_based_table_factory.h"
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#include "table/merger.h"
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#include "table/table_builder.h"
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#include "table/two_level_iterator.h"
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#include "util/coding.h"
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Move rate_limiter, write buffering, most perf context instrumentation and most random kill out of Env
Summary: We want to keep Env a think layer for better portability. Less platform dependent codes should be moved out of Env. In this patch, I create a wrapper of file readers and writers, and put rate limiting, write buffering, as well as most perf context instrumentation and random kill out of Env. It will make it easier to maintain multiple Env in the future.
Test Plan: Run all existing unit tests.
Reviewers: anthony, kradhakrishnan, IslamAbdelRahman, yhchiang, igor
Reviewed By: igor
Subscribers: leveldb, dhruba
Differential Revision: https://reviews.facebook.net/D42321
2015-07-17 23:16:11 +00:00
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#include "util/file_reader_writer.h"
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2014-10-31 23:31:25 +00:00
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#include "util/logging.h"
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#include "util/log_buffer.h"
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#include "util/mutexlock.h"
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#include "util/perf_context_imp.h"
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#include "util/iostats_context_imp.h"
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#include "util/stop_watch.h"
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Include bunch of more events into EventLogger
Summary:
Added these events:
* Recovery start, finish and also when recovery creates a file
* Trivial move
* Compaction start, finish and when compaction creates a file
* Flush start, finish
Also includes small fix to EventLogger
Also added option ROCKSDB_PRINT_EVENTS_TO_STDOUT which is useful when we debug things. I've spent far too much time chasing LOG files.
Still didn't get sst table properties in JSON. They are written very deeply into the stack. I'll address in separate diff.
TODO:
* Write specification. Let's first use this for a while and figure out what's good data to put here, too. After that we'll write spec
* Write tools that parse and analyze LOGs. This can be in python or go. Good intern task.
Test Plan: Ran db_bench with ROCKSDB_PRINT_EVENTS_TO_STDOUT. Here's the output: https://phabricator.fb.com/P19811976
Reviewers: sdong, yhchiang, rven, MarkCallaghan, kradhakrishnan, anthony
Reviewed By: anthony
Subscribers: dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D37521
2015-04-27 22:20:02 +00:00
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#include "util/string_util.h"
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2014-10-31 23:31:25 +00:00
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#include "util/sync_point.h"
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2015-01-13 08:04:08 +00:00
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#include "util/thread_status_util.h"
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2014-10-31 23:31:25 +00:00
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namespace rocksdb {
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2015-08-18 18:06:23 +00:00
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// Maintains state for each sub-compaction
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struct CompactionJob::SubCompactionState {
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2015-08-20 21:08:24 +00:00
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Compaction* compaction;
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2014-10-31 23:31:25 +00:00
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2015-08-18 18:06:23 +00:00
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// The boundaries of the key-range this compaction is interested in. No two
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// subcompactions may have overlapping key-ranges.
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// 'start' is inclusive, 'end' is exclusive, and nullptr means unbounded
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Slice *start, *end;
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// The return status of this compaction
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Status status;
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2014-10-31 23:31:25 +00:00
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// Files produced by compaction
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struct Output {
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uint64_t number;
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uint32_t path_id;
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uint64_t file_size;
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InternalKey smallest, largest;
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SequenceNumber smallest_seqno, largest_seqno;
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2015-06-04 19:03:40 +00:00
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bool need_compaction;
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2014-10-31 23:31:25 +00:00
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};
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// State kept for output being generated
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2015-08-18 18:06:23 +00:00
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std::vector<Output> outputs;
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Move rate_limiter, write buffering, most perf context instrumentation and most random kill out of Env
Summary: We want to keep Env a think layer for better portability. Less platform dependent codes should be moved out of Env. In this patch, I create a wrapper of file readers and writers, and put rate limiting, write buffering, as well as most perf context instrumentation and random kill out of Env. It will make it easier to maintain multiple Env in the future.
Test Plan: Run all existing unit tests.
Reviewers: anthony, kradhakrishnan, IslamAbdelRahman, yhchiang, igor
Reviewed By: igor
Subscribers: leveldb, dhruba
Differential Revision: https://reviews.facebook.net/D42321
2015-07-17 23:16:11 +00:00
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std::unique_ptr<WritableFileWriter> outfile;
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2014-10-31 23:31:25 +00:00
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std::unique_ptr<TableBuilder> builder;
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2015-08-18 18:06:23 +00:00
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Output* current_output() {
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2015-08-18 19:27:12 +00:00
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if (outputs.empty()) {
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// This subcompaction's ouptut could be empty if compaction was aborted
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// before this subcompaction had a chance to generate any output files.
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// When subcompactions are executed sequentially this is more likely and
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// will be particulalry likely for the last subcompaction to be empty.
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// Once they are run in parallel however it should be much rarer.
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return nullptr;
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} else {
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return &outputs.back();
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}
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2015-08-18 18:06:23 +00:00
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}
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2014-10-31 23:31:25 +00:00
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2015-08-18 18:06:23 +00:00
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// State during the sub-compaction
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2014-10-31 23:31:25 +00:00
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uint64_t total_bytes;
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2015-08-18 18:06:23 +00:00
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uint64_t num_input_records;
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uint64_t num_output_records;
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SequenceNumber earliest_snapshot;
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SequenceNumber visible_at_tip;
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SequenceNumber latest_snapshot;
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CompactionJobStats compaction_job_stats;
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// "level_ptrs" holds indices that remember which file of an associated
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// level we were last checking during the last call to compaction->
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// KeyNotExistsBeyondOutputLevel(). This allows future calls to the function
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// to pick off where it left off since each subcompaction's key range is
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// increasing so a later call to the function must be looking for a key that
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// is in or beyond the last file checked during the previous call
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std::vector<size_t> level_ptrs;
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2015-08-20 21:08:24 +00:00
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SubCompactionState(Compaction* c, Slice* _start, Slice* _end,
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2015-08-18 18:06:23 +00:00
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SequenceNumber earliest, SequenceNumber visible,
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SequenceNumber latest)
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: compaction(c),
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start(_start),
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end(_end),
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outfile(nullptr),
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builder(nullptr),
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total_bytes(0),
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num_input_records(0),
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num_output_records(0),
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earliest_snapshot(earliest),
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visible_at_tip(visible),
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latest_snapshot(latest) {
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assert(compaction != nullptr);
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level_ptrs = std::vector<size_t>(compaction->number_levels(), 0);
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}
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2015-08-20 21:08:24 +00:00
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SubCompactionState(SubCompactionState&& o) {
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*this = std::move(o);
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}
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SubCompactionState& operator=(SubCompactionState&& o) {
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compaction = std::move(o.compaction);
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start = std::move(o.start);
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end = std::move(o.end);
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status = std::move(o.status);
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outputs = std::move(o.outputs);
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outfile = std::move(o.outfile);
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builder = std::move(o.builder);
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total_bytes = std::move(o.total_bytes);
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num_input_records = std::move(o.num_input_records);
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num_output_records = std::move(o.num_output_records);
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earliest_snapshot = std::move(o.earliest_snapshot);
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visible_at_tip = std::move(o.visible_at_tip);
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latest_snapshot = std::move(o.latest_snapshot);
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level_ptrs = std::move(o.level_ptrs);
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return *this;
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}
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// Because member unique_ptrs do not have these.
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SubCompactionState(const SubCompactionState&) = delete;
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SubCompactionState& operator=(const SubCompactionState&) = delete;
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2015-08-18 18:06:23 +00:00
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};
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// Maintains state for the entire compaction
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struct CompactionJob::CompactionState {
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Compaction* const compaction;
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2014-10-31 23:31:25 +00:00
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2015-08-18 18:06:23 +00:00
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// REQUIRED: subcompaction states are stored in order of increasing
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// key-range
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std::vector<CompactionJob::SubCompactionState> sub_compact_states;
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Status status;
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uint64_t total_bytes;
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uint64_t num_input_records;
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uint64_t num_output_records;
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2014-10-31 23:31:25 +00:00
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2014-11-01 01:36:07 +00:00
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explicit CompactionState(Compaction* c)
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: compaction(c),
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total_bytes(0),
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num_input_records(0),
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num_output_records(0) {}
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2014-10-31 23:31:25 +00:00
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2015-08-18 18:06:23 +00:00
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size_t NumOutputFiles() {
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size_t total = 0;
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for (auto& s : sub_compact_states) {
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total += s.outputs.size();
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}
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return total;
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}
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Slice SmallestUserKey() {
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2015-08-18 19:27:12 +00:00
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for (size_t i = 0; i < sub_compact_states.size(); i++) {
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if (!sub_compact_states[i].outputs.empty()) {
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return sub_compact_states[i].outputs[0].smallest.user_key();
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}
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}
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// TODO(aekmekji): should we exit with an error if it reaches here?
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assert(0);
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return Slice(nullptr, 0);
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2015-08-18 18:06:23 +00:00
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}
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Slice LargestUserKey() {
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2015-08-18 19:27:12 +00:00
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for (int i = static_cast<int>(sub_compact_states.size() - 1); i >= 0; i--) {
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if (!sub_compact_states[i].outputs.empty()) {
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assert(sub_compact_states[i].current_output() != nullptr);
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return sub_compact_states[i].current_output()->largest.user_key();
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}
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}
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// TODO(aekmekji): should we exit with an error if it reaches here?
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assert(0);
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return Slice(nullptr, 0);
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2015-08-18 18:06:23 +00:00
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}
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2014-10-31 23:31:25 +00:00
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};
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2015-08-18 18:06:23 +00:00
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void CompactionJob::AggregateStatistics() {
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for (SubCompactionState& sc : compact_->sub_compact_states) {
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compact_->total_bytes += sc.total_bytes;
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compact_->num_input_records += sc.num_input_records;
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compact_->num_output_records += sc.num_output_records;
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if (compaction_job_stats_) {
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compaction_job_stats_->Add(sc.compaction_job_stats);
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}
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}
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}
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2014-10-31 23:31:25 +00:00
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CompactionJob::CompactionJob(
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2015-02-12 17:54:48 +00:00
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int job_id, Compaction* compaction, const DBOptions& db_options,
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2015-05-06 02:01:12 +00:00
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const EnvOptions& env_options, VersionSet* versions,
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std::atomic<bool>* shutting_down, LogBuffer* log_buffer,
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Directory* db_directory, Directory* output_directory, Statistics* stats,
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std::vector<SequenceNumber> existing_snapshots,
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2015-07-17 19:02:52 +00:00
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std::shared_ptr<Cache> table_cache, EventLogger* event_logger,
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Add options.compaction_measure_io_stats to print write I/O stats in compactions
Summary:
Add options.compaction_measure_io_stats to print out / pass to listener accumulated time spent on write calls. Example outputs in info logs:
2015/08/12-16:27:59.463944 7fd428bff700 (Original Log Time 2015/08/12-16:27:59.463922) EVENT_LOG_v1 {"time_micros": 1439422079463897, "job": 6, "event": "compaction_finished", "output_level": 1, "num_output_files": 4, "total_output_size": 6900525, "num_input_records": 111483, "num_output_records": 106877, "file_write_nanos": 15663206, "file_range_sync_nanos": 649588, "file_fsync_nanos": 349614797, "file_prepare_write_nanos": 1505812, "lsm_state": [2, 4, 0, 0, 0, 0, 0]}
Add two more counters in iostats_context.
Also add a parameter of db_bench.
Test Plan: Add a unit test. Also manually verify LOG outputs in db_bench
Subscribers: leveldb, dhruba
Differential Revision: https://reviews.facebook.net/D44115
2015-08-13 00:24:45 +00:00
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bool paranoid_file_checks, bool measure_io_stats, const std::string& dbname,
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2015-06-03 00:07:16 +00:00
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CompactionJobStats* compaction_job_stats)
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2015-02-12 17:54:48 +00:00
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: job_id_(job_id),
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compact_(new CompactionState(compaction)),
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2015-06-03 00:07:16 +00:00
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compaction_job_stats_(compaction_job_stats),
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2014-10-31 23:31:25 +00:00
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compaction_stats_(1),
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2015-06-02 21:12:23 +00:00
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dbname_(dbname),
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2014-10-31 23:31:25 +00:00
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db_options_(db_options),
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env_options_(env_options),
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env_(db_options.env),
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versions_(versions),
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shutting_down_(shutting_down),
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log_buffer_(log_buffer),
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db_directory_(db_directory),
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2015-01-26 21:59:38 +00:00
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output_directory_(output_directory),
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2014-10-31 23:31:25 +00:00
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stats_(stats),
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2015-05-06 02:01:12 +00:00
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existing_snapshots_(std::move(existing_snapshots)),
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2014-10-31 23:31:25 +00:00
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table_cache_(std::move(table_cache)),
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2015-05-06 02:01:12 +00:00
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event_logger_(event_logger),
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Add options.compaction_measure_io_stats to print write I/O stats in compactions
Summary:
Add options.compaction_measure_io_stats to print out / pass to listener accumulated time spent on write calls. Example outputs in info logs:
2015/08/12-16:27:59.463944 7fd428bff700 (Original Log Time 2015/08/12-16:27:59.463922) EVENT_LOG_v1 {"time_micros": 1439422079463897, "job": 6, "event": "compaction_finished", "output_level": 1, "num_output_files": 4, "total_output_size": 6900525, "num_input_records": 111483, "num_output_records": 106877, "file_write_nanos": 15663206, "file_range_sync_nanos": 649588, "file_fsync_nanos": 349614797, "file_prepare_write_nanos": 1505812, "lsm_state": [2, 4, 0, 0, 0, 0, 0]}
Add two more counters in iostats_context.
Also add a parameter of db_bench.
Test Plan: Add a unit test. Also manually verify LOG outputs in db_bench
Subscribers: leveldb, dhruba
Differential Revision: https://reviews.facebook.net/D44115
2015-08-13 00:24:45 +00:00
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paranoid_file_checks_(paranoid_file_checks),
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measure_io_stats_(measure_io_stats) {
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2015-07-15 06:12:34 +00:00
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assert(log_buffer_ != nullptr);
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2015-05-06 02:01:12 +00:00
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ThreadStatusUtil::SetColumnFamily(compact_->compaction->column_family_data());
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2015-03-13 17:45:40 +00:00
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ThreadStatusUtil::SetThreadOperation(ThreadStatus::OP_COMPACTION);
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2015-05-07 05:50:35 +00:00
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ReportStartedCompaction(compaction);
|
2015-03-13 17:45:40 +00:00
|
|
|
}
|
|
|
|
|
|
|
|
CompactionJob::~CompactionJob() {
|
|
|
|
assert(compact_ == nullptr);
|
|
|
|
ThreadStatusUtil::ResetThreadStatus();
|
|
|
|
}
|
2014-10-31 23:31:25 +00:00
|
|
|
|
2015-05-07 05:50:35 +00:00
|
|
|
void CompactionJob::ReportStartedCompaction(
|
|
|
|
Compaction* compaction) {
|
|
|
|
ThreadStatusUtil::SetColumnFamily(
|
|
|
|
compact_->compaction->column_family_data());
|
|
|
|
|
|
|
|
ThreadStatusUtil::SetThreadOperationProperty(
|
|
|
|
ThreadStatus::COMPACTION_JOB_ID,
|
|
|
|
job_id_);
|
|
|
|
|
|
|
|
ThreadStatusUtil::SetThreadOperationProperty(
|
|
|
|
ThreadStatus::COMPACTION_INPUT_OUTPUT_LEVEL,
|
|
|
|
(static_cast<uint64_t>(compact_->compaction->start_level()) << 32) +
|
|
|
|
compact_->compaction->output_level());
|
|
|
|
|
2015-06-03 00:07:16 +00:00
|
|
|
// In the current design, a CompactionJob is always created
|
|
|
|
// for non-trivial compaction.
|
|
|
|
assert(compaction->IsTrivialMove() == false ||
|
2015-07-08 22:21:10 +00:00
|
|
|
compaction->is_manual_compaction() == true);
|
2015-06-03 00:07:16 +00:00
|
|
|
|
2015-05-07 05:50:35 +00:00
|
|
|
ThreadStatusUtil::SetThreadOperationProperty(
|
|
|
|
ThreadStatus::COMPACTION_PROP_FLAGS,
|
2015-07-13 19:11:05 +00:00
|
|
|
compaction->is_manual_compaction() +
|
2015-07-08 22:21:10 +00:00
|
|
|
(compaction->deletion_compaction() << 1));
|
2015-05-07 05:50:35 +00:00
|
|
|
|
|
|
|
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);
|
2015-06-03 00:07:16 +00:00
|
|
|
|
|
|
|
if (compaction_job_stats_) {
|
|
|
|
compaction_job_stats_->is_manual_compaction =
|
2015-07-13 19:11:05 +00:00
|
|
|
compaction->is_manual_compaction();
|
2015-06-03 00:07:16 +00:00
|
|
|
}
|
2015-05-07 05:50:35 +00:00
|
|
|
}
|
|
|
|
|
2014-10-31 23:31:25 +00:00
|
|
|
void CompactionJob::Prepare() {
|
2015-03-13 17:45:40 +00:00
|
|
|
AutoThreadOperationStageUpdater stage_updater(
|
|
|
|
ThreadStatus::STAGE_COMPACTION_PREPARE);
|
2014-10-31 23:31:25 +00:00
|
|
|
|
|
|
|
// Generate file_levels_ for compaction berfore making Iterator
|
2015-08-19 15:52:22 +00:00
|
|
|
auto* c = compact_->compaction;
|
|
|
|
assert(c->column_family_data() != nullptr);
|
|
|
|
assert(c->column_family_data()->current()->storage_info()
|
|
|
|
->NumLevelFiles(compact_->compaction->level()) > 0);
|
2014-10-31 23:31:25 +00:00
|
|
|
|
2015-08-18 18:06:23 +00:00
|
|
|
// Is this compaction producing files at the bottommost level?
|
2015-08-19 15:52:22 +00:00
|
|
|
bottommost_level_ = c->bottommost_level();
|
2015-08-18 18:06:23 +00:00
|
|
|
|
|
|
|
// Initialize subcompaction states
|
|
|
|
SequenceNumber earliest_snapshot;
|
|
|
|
SequenceNumber latest_snapshot = 0;
|
|
|
|
SequenceNumber visible_at_tip = 0;
|
|
|
|
|
2015-05-06 02:01:12 +00:00
|
|
|
if (existing_snapshots_.size() == 0) {
|
2014-10-31 23:31:25 +00:00
|
|
|
// optimize for fast path if there are no snapshots
|
2015-08-18 18:06:23 +00:00
|
|
|
visible_at_tip = versions_->LastSequence();
|
|
|
|
earliest_snapshot = visible_at_tip;
|
2014-10-31 23:31:25 +00:00
|
|
|
} else {
|
2015-08-18 18:06:23 +00:00
|
|
|
latest_snapshot = existing_snapshots_.back();
|
2014-10-31 23:31:25 +00:00
|
|
|
// Add the current seqno as the 'latest' virtual
|
|
|
|
// snapshot to the end of this list.
|
2015-05-06 02:01:12 +00:00
|
|
|
existing_snapshots_.push_back(versions_->LastSequence());
|
2015-08-18 18:06:23 +00:00
|
|
|
earliest_snapshot = existing_snapshots_[0];
|
2014-10-31 23:31:25 +00:00
|
|
|
}
|
|
|
|
|
2015-08-18 18:06:23 +00:00
|
|
|
InitializeSubCompactions(earliest_snapshot, visible_at_tip, latest_snapshot);
|
Parallelize L0-L1 Compaction: Restructure Compaction Job
Summary:
As of now compactions involving files from Level 0 and Level 1 are single
threaded because the files in L0, although sorted, are not range partitioned like
the other levels. This means that during L0-L1 compaction each file from L1
needs to be merged with potentially all the files from L0.
This attempt to parallelize the L0-L1 compaction assigns a thread and a
corresponding iterator to each L1 file that then considers only the key range
found in that L1 file and only the L0 files that have those keys (and only the
specific portion of those L0 files in which those keys are found). In this way
the overlap is minimized and potentially eliminated between different iterators
focusing on the same files.
The first step is to restructure the compaction logic to break L0-L1 compactions
into multiple, smaller, sequential compactions. Eventually each of these smaller
jobs will be run simultaneously. Areas to pay extra attention to are
# Correct aggregation of compaction job statistics across multiple threads
# Proper opening/closing of output files (make sure each thread's is unique)
# Keys that span multiple L1 files
# Skewed distributions of keys within L0 files
Test Plan: Make and run db_test (newer version has separate compaction tests) and compaction_job_stats_test
Reviewers: igor, noetzli, anthony, sdong, yhchiang
Reviewed By: yhchiang
Subscribers: MarkCallaghan, dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D42699
2015-08-03 18:32:14 +00:00
|
|
|
}
|
|
|
|
|
|
|
|
// For L0-L1 compaction, iterators work in parallel by processing
|
2015-08-18 18:06:23 +00:00
|
|
|
// different subsets of the full key range. This function sets up
|
|
|
|
// the local states used by each of these subcompactions during
|
|
|
|
// their execution
|
|
|
|
void CompactionJob::InitializeSubCompactions(const SequenceNumber& earliest,
|
|
|
|
const SequenceNumber& visible,
|
|
|
|
const SequenceNumber& latest) {
|
|
|
|
Compaction* c = compact_->compaction;
|
|
|
|
auto& bounds = sub_compaction_boundaries_;
|
Parallelize L0-L1 Compaction: Restructure Compaction Job
Summary:
As of now compactions involving files from Level 0 and Level 1 are single
threaded because the files in L0, although sorted, are not range partitioned like
the other levels. This means that during L0-L1 compaction each file from L1
needs to be merged with potentially all the files from L0.
This attempt to parallelize the L0-L1 compaction assigns a thread and a
corresponding iterator to each L1 file that then considers only the key range
found in that L1 file and only the L0 files that have those keys (and only the
specific portion of those L0 files in which those keys are found). In this way
the overlap is minimized and potentially eliminated between different iterators
focusing on the same files.
The first step is to restructure the compaction logic to break L0-L1 compactions
into multiple, smaller, sequential compactions. Eventually each of these smaller
jobs will be run simultaneously. Areas to pay extra attention to are
# Correct aggregation of compaction job statistics across multiple threads
# Proper opening/closing of output files (make sure each thread's is unique)
# Keys that span multiple L1 files
# Skewed distributions of keys within L0 files
Test Plan: Make and run db_test (newer version has separate compaction tests) and compaction_job_stats_test
Reviewers: igor, noetzli, anthony, sdong, yhchiang
Reviewed By: yhchiang
Subscribers: MarkCallaghan, dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D42699
2015-08-03 18:32:14 +00:00
|
|
|
if (c->IsSubCompaction()) {
|
2015-08-18 18:06:23 +00:00
|
|
|
auto* cmp = c->column_family_data()->user_comparator();
|
Parallelize L0-L1 Compaction: Restructure Compaction Job
Summary:
As of now compactions involving files from Level 0 and Level 1 are single
threaded because the files in L0, although sorted, are not range partitioned like
the other levels. This means that during L0-L1 compaction each file from L1
needs to be merged with potentially all the files from L0.
This attempt to parallelize the L0-L1 compaction assigns a thread and a
corresponding iterator to each L1 file that then considers only the key range
found in that L1 file and only the L0 files that have those keys (and only the
specific portion of those L0 files in which those keys are found). In this way
the overlap is minimized and potentially eliminated between different iterators
focusing on the same files.
The first step is to restructure the compaction logic to break L0-L1 compactions
into multiple, smaller, sequential compactions. Eventually each of these smaller
jobs will be run simultaneously. Areas to pay extra attention to are
# Correct aggregation of compaction job statistics across multiple threads
# Proper opening/closing of output files (make sure each thread's is unique)
# Keys that span multiple L1 files
# Skewed distributions of keys within L0 files
Test Plan: Make and run db_test (newer version has separate compaction tests) and compaction_job_stats_test
Reviewers: igor, noetzli, anthony, sdong, yhchiang
Reviewed By: yhchiang
Subscribers: MarkCallaghan, dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D42699
2015-08-03 18:32:14 +00:00
|
|
|
for (size_t which = 0; which < c->num_input_levels(); which++) {
|
|
|
|
if (c->level(which) == 1) {
|
2015-08-18 18:06:23 +00:00
|
|
|
const LevelFilesBrief* flevel = c->input_levels(which);
|
|
|
|
size_t num_files = flevel->num_files;
|
|
|
|
|
|
|
|
if (num_files > 1) {
|
2015-08-18 21:56:31 +00:00
|
|
|
std::vector<Slice> candidates;
|
2015-08-18 18:06:23 +00:00
|
|
|
auto& files = flevel->files;
|
|
|
|
Slice global_min = ExtractUserKey(files[0].smallest_key);
|
|
|
|
Slice global_max = ExtractUserKey(files[num_files - 1].largest_key);
|
|
|
|
|
|
|
|
for (size_t i = 1; i < num_files; i++) {
|
|
|
|
// Make sure the smallest key in two consecutive L1 files are
|
|
|
|
// unique before adding the smallest key as a boundary. Also ensure
|
|
|
|
// that the boundary won't lead to an empty subcompaction (happens
|
|
|
|
// if the boundary == the smallest or largest key)
|
|
|
|
Slice s1 = ExtractUserKey(files[i].smallest_key);
|
|
|
|
Slice s2 = i == num_files - 1
|
|
|
|
? Slice()
|
|
|
|
: ExtractUserKey(files[i + 1].smallest_key);
|
|
|
|
|
|
|
|
if ( (i == num_files - 1 && cmp->Compare(s1, global_max) < 0)
|
|
|
|
|| (i < num_files - 1 && cmp->Compare(s1, s2) < 0 &&
|
|
|
|
cmp->Compare(s1, global_min) > 0)) {
|
2015-08-18 21:56:31 +00:00
|
|
|
candidates.emplace_back(s1);
|
2015-08-18 18:06:23 +00:00
|
|
|
}
|
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
2015-08-03 18:32:14 +00:00
|
|
|
}
|
2015-08-18 21:56:31 +00:00
|
|
|
|
|
|
|
// Divide the potential L1 file boundaries (those that passed the
|
|
|
|
// checks above) into 'num_subcompactions' groups such that each have
|
|
|
|
// as close to an equal number of files in it as possible
|
|
|
|
// TODO(aekmekji): refine this later to depend on file size
|
|
|
|
size_t files_left = candidates.size();
|
|
|
|
size_t subcompactions_left =
|
|
|
|
static_cast<size_t>(db_options_.num_subcompactions) < files_left
|
|
|
|
? db_options_.num_subcompactions
|
|
|
|
: files_left;
|
|
|
|
|
|
|
|
size_t num_to_include;
|
|
|
|
size_t index = 0;
|
|
|
|
|
|
|
|
while (files_left > 1 && subcompactions_left > 1) {
|
|
|
|
num_to_include = files_left / subcompactions_left;
|
|
|
|
index += num_to_include;
|
|
|
|
sub_compaction_boundaries_.emplace_back(candidates[index]);
|
|
|
|
files_left -= num_to_include;
|
|
|
|
subcompactions_left--;
|
|
|
|
}
|
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
2015-08-03 18:32:14 +00:00
|
|
|
}
|
|
|
|
break;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
2015-08-18 18:06:23 +00:00
|
|
|
|
|
|
|
// Note: it's necessary for the first iterator sub-range to have
|
|
|
|
// start == nullptr and for the last to have end == nullptr
|
|
|
|
for (size_t i = 0; i <= bounds.size(); i++) {
|
|
|
|
Slice *start = i == 0 ? nullptr : &bounds[i - 1];
|
|
|
|
Slice *end = i == bounds.size() ? nullptr : &bounds[i];
|
|
|
|
compact_->sub_compact_states.emplace_back(compact_->compaction, start,
|
|
|
|
end, earliest, visible, latest);
|
|
|
|
}
|
2014-10-31 23:31:25 +00:00
|
|
|
}
|
|
|
|
|
|
|
|
Status CompactionJob::Run() {
|
2015-03-13 17:45:40 +00:00
|
|
|
AutoThreadOperationStageUpdater stage_updater(
|
|
|
|
ThreadStatus::STAGE_COMPACTION_RUN);
|
2015-03-13 18:59:00 +00:00
|
|
|
TEST_SYNC_POINT("CompactionJob::Run():Start");
|
2014-10-31 23:31:25 +00:00
|
|
|
log_buffer_->FlushBufferToLog();
|
2015-08-18 18:06:23 +00:00
|
|
|
LogCompaction();
|
Include bunch of more events into EventLogger
Summary:
Added these events:
* Recovery start, finish and also when recovery creates a file
* Trivial move
* Compaction start, finish and when compaction creates a file
* Flush start, finish
Also includes small fix to EventLogger
Also added option ROCKSDB_PRINT_EVENTS_TO_STDOUT which is useful when we debug things. I've spent far too much time chasing LOG files.
Still didn't get sst table properties in JSON. They are written very deeply into the stack. I'll address in separate diff.
TODO:
* Write specification. Let's first use this for a while and figure out what's good data to put here, too. After that we'll write spec
* Write tools that parse and analyze LOGs. This can be in python or go. Good intern task.
Test Plan: Ran db_bench with ROCKSDB_PRINT_EVENTS_TO_STDOUT. Here's the output: https://phabricator.fb.com/P19811976
Reviewers: sdong, yhchiang, rven, MarkCallaghan, kradhakrishnan, anthony
Reviewed By: anthony
Subscribers: dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D37521
2015-04-27 22:20:02 +00:00
|
|
|
|
2015-08-18 18:06:23 +00:00
|
|
|
// Run each subcompaction sequentially
|
|
|
|
const uint64_t start_micros = env_->NowMicros();
|
|
|
|
for (size_t i = 0; i < compact_->sub_compact_states.size(); i++) {
|
|
|
|
ProcessKeyValueCompaction(&compact_->sub_compact_states[i]);
|
|
|
|
}
|
|
|
|
compaction_stats_.micros = env_->NowMicros() - start_micros;
|
|
|
|
MeasureTime(stats_, COMPACTION_TIME, compaction_stats_.micros);
|
Parallelize L0-L1 Compaction: Restructure Compaction Job
Summary:
As of now compactions involving files from Level 0 and Level 1 are single
threaded because the files in L0, although sorted, are not range partitioned like
the other levels. This means that during L0-L1 compaction each file from L1
needs to be merged with potentially all the files from L0.
This attempt to parallelize the L0-L1 compaction assigns a thread and a
corresponding iterator to each L1 file that then considers only the key range
found in that L1 file and only the L0 files that have those keys (and only the
specific portion of those L0 files in which those keys are found). In this way
the overlap is minimized and potentially eliminated between different iterators
focusing on the same files.
The first step is to restructure the compaction logic to break L0-L1 compactions
into multiple, smaller, sequential compactions. Eventually each of these smaller
jobs will be run simultaneously. Areas to pay extra attention to are
# Correct aggregation of compaction job statistics across multiple threads
# Proper opening/closing of output files (make sure each thread's is unique)
# Keys that span multiple L1 files
# Skewed distributions of keys within L0 files
Test Plan: Make and run db_test (newer version has separate compaction tests) and compaction_job_stats_test
Reviewers: igor, noetzli, anthony, sdong, yhchiang
Reviewed By: yhchiang
Subscribers: MarkCallaghan, dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D42699
2015-08-03 18:32:14 +00:00
|
|
|
|
2015-08-18 18:06:23 +00:00
|
|
|
// Determine if any of the subcompactions failed
|
|
|
|
Status status;
|
|
|
|
for (const auto& state : compact_->sub_compact_states) {
|
|
|
|
if (!state.status.ok()) {
|
|
|
|
status = state.status;
|
Parallelize L0-L1 Compaction: Restructure Compaction Job
Summary:
As of now compactions involving files from Level 0 and Level 1 are single
threaded because the files in L0, although sorted, are not range partitioned like
the other levels. This means that during L0-L1 compaction each file from L1
needs to be merged with potentially all the files from L0.
This attempt to parallelize the L0-L1 compaction assigns a thread and a
corresponding iterator to each L1 file that then considers only the key range
found in that L1 file and only the L0 files that have those keys (and only the
specific portion of those L0 files in which those keys are found). In this way
the overlap is minimized and potentially eliminated between different iterators
focusing on the same files.
The first step is to restructure the compaction logic to break L0-L1 compactions
into multiple, smaller, sequential compactions. Eventually each of these smaller
jobs will be run simultaneously. Areas to pay extra attention to are
# Correct aggregation of compaction job statistics across multiple threads
# Proper opening/closing of output files (make sure each thread's is unique)
# Keys that span multiple L1 files
# Skewed distributions of keys within L0 files
Test Plan: Make and run db_test (newer version has separate compaction tests) and compaction_job_stats_test
Reviewers: igor, noetzli, anthony, sdong, yhchiang
Reviewed By: yhchiang
Subscribers: MarkCallaghan, dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D42699
2015-08-03 18:32:14 +00:00
|
|
|
break;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
2015-08-18 18:06:23 +00:00
|
|
|
// 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
2015-08-03 18:32:14 +00:00
|
|
|
UpdateCompactionStats();
|
|
|
|
RecordCompactionIOStats();
|
|
|
|
LogFlush(db_options_.info_log);
|
|
|
|
TEST_SYNC_POINT("CompactionJob::Run():End");
|
|
|
|
|
2015-08-18 18:06:23 +00:00
|
|
|
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
2015-08-03 18:32:14 +00:00
|
|
|
return status;
|
|
|
|
}
|
|
|
|
|
2015-08-18 18:06:23 +00:00
|
|
|
Status CompactionJob::Install(const MutableCFOptions& mutable_cf_options,
|
|
|
|
InstrumentedMutex* db_mutex) {
|
2015-03-13 17:45:40 +00:00
|
|
|
AutoThreadOperationStageUpdater stage_updater(
|
|
|
|
ThreadStatus::STAGE_COMPACTION_INSTALL);
|
2014-11-07 23:44:12 +00:00
|
|
|
db_mutex->AssertHeld();
|
2015-08-18 18:06:23 +00:00
|
|
|
Status status = compact_->status;
|
2014-10-31 23:31:25 +00:00
|
|
|
ColumnFamilyData* cfd = compact_->compaction->column_family_data();
|
|
|
|
cfd->internal_stats()->AddCompactionStats(
|
|
|
|
compact_->compaction->output_level(), compaction_stats_);
|
|
|
|
|
2015-08-18 18:06:23 +00:00
|
|
|
if (status.ok()) {
|
|
|
|
status = InstallCompactionResults(mutable_cf_options, db_mutex);
|
2014-10-31 23:31:25 +00:00
|
|
|
}
|
|
|
|
VersionStorageInfo::LevelSummaryStorage tmp;
|
Include bunch of more events into EventLogger
Summary:
Added these events:
* Recovery start, finish and also when recovery creates a file
* Trivial move
* Compaction start, finish and when compaction creates a file
* Flush start, finish
Also includes small fix to EventLogger
Also added option ROCKSDB_PRINT_EVENTS_TO_STDOUT which is useful when we debug things. I've spent far too much time chasing LOG files.
Still didn't get sst table properties in JSON. They are written very deeply into the stack. I'll address in separate diff.
TODO:
* Write specification. Let's first use this for a while and figure out what's good data to put here, too. After that we'll write spec
* Write tools that parse and analyze LOGs. This can be in python or go. Good intern task.
Test Plan: Ran db_bench with ROCKSDB_PRINT_EVENTS_TO_STDOUT. Here's the output: https://phabricator.fb.com/P19811976
Reviewers: sdong, yhchiang, rven, MarkCallaghan, kradhakrishnan, anthony
Reviewed By: anthony
Subscribers: dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D37521
2015-04-27 22:20:02 +00:00
|
|
|
auto vstorage = cfd->current()->storage_info();
|
2014-10-31 23:31:25 +00:00
|
|
|
const auto& stats = compaction_stats_;
|
2015-06-18 06:40:34 +00:00
|
|
|
LogToBuffer(
|
|
|
|
log_buffer_,
|
|
|
|
"[%s] compacted to: %s, MB/sec: %.1f rd, %.1f wr, level %d, "
|
|
|
|
"files in(%d, %d) out(%d) "
|
|
|
|
"MB in(%.1f, %.1f) out(%.1f), read-write-amplify(%.1f) "
|
|
|
|
"write-amplify(%.1f) %s, records in: %d, records dropped: %d\n",
|
|
|
|
cfd->GetName().c_str(), vstorage->LevelSummary(&tmp),
|
|
|
|
(stats.bytes_read_non_output_levels + stats.bytes_read_output_level) /
|
|
|
|
static_cast<double>(stats.micros),
|
|
|
|
stats.bytes_written / static_cast<double>(stats.micros),
|
|
|
|
compact_->compaction->output_level(),
|
|
|
|
stats.num_input_files_in_non_output_levels,
|
|
|
|
stats.num_input_files_in_output_level,
|
|
|
|
stats.num_output_files,
|
|
|
|
stats.bytes_read_non_output_levels / 1048576.0,
|
|
|
|
stats.bytes_read_output_level / 1048576.0,
|
|
|
|
stats.bytes_written / 1048576.0,
|
|
|
|
(stats.bytes_written + stats.bytes_read_output_level +
|
|
|
|
stats.bytes_read_non_output_levels) /
|
|
|
|
static_cast<double>(stats.bytes_read_non_output_levels),
|
|
|
|
stats.bytes_written /
|
|
|
|
static_cast<double>(stats.bytes_read_non_output_levels),
|
2015-08-18 18:06:23 +00:00
|
|
|
status.ToString().c_str(), stats.num_input_records,
|
2015-06-18 06:40:34 +00:00
|
|
|
stats.num_dropped_records);
|
2014-10-31 23:31:25 +00:00
|
|
|
|
2015-06-03 00:07:16 +00:00
|
|
|
UpdateCompactionJobStats(stats);
|
|
|
|
|
Include bunch of more events into EventLogger
Summary:
Added these events:
* Recovery start, finish and also when recovery creates a file
* Trivial move
* Compaction start, finish and when compaction creates a file
* Flush start, finish
Also includes small fix to EventLogger
Also added option ROCKSDB_PRINT_EVENTS_TO_STDOUT which is useful when we debug things. I've spent far too much time chasing LOG files.
Still didn't get sst table properties in JSON. They are written very deeply into the stack. I'll address in separate diff.
TODO:
* Write specification. Let's first use this for a while and figure out what's good data to put here, too. After that we'll write spec
* Write tools that parse and analyze LOGs. This can be in python or go. Good intern task.
Test Plan: Ran db_bench with ROCKSDB_PRINT_EVENTS_TO_STDOUT. Here's the output: https://phabricator.fb.com/P19811976
Reviewers: sdong, yhchiang, rven, MarkCallaghan, kradhakrishnan, anthony
Reviewed By: anthony
Subscribers: dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D37521
2015-04-27 22:20:02 +00:00
|
|
|
auto stream = event_logger_->LogToBuffer(log_buffer_);
|
|
|
|
stream << "job" << job_id_ << "event"
|
|
|
|
<< "compaction_finished"
|
|
|
|
<< "output_level" << compact_->compaction->output_level()
|
2015-08-18 18:06:23 +00:00
|
|
|
<< "num_output_files" << compact_->NumOutputFiles()
|
2015-06-18 06:40:34 +00:00
|
|
|
<< "total_output_size" << compact_->total_bytes
|
|
|
|
<< "num_input_records" << compact_->num_input_records
|
|
|
|
<< "num_output_records" << compact_->num_output_records;
|
Add options.compaction_measure_io_stats to print write I/O stats in compactions
Summary:
Add options.compaction_measure_io_stats to print out / pass to listener accumulated time spent on write calls. Example outputs in info logs:
2015/08/12-16:27:59.463944 7fd428bff700 (Original Log Time 2015/08/12-16:27:59.463922) EVENT_LOG_v1 {"time_micros": 1439422079463897, "job": 6, "event": "compaction_finished", "output_level": 1, "num_output_files": 4, "total_output_size": 6900525, "num_input_records": 111483, "num_output_records": 106877, "file_write_nanos": 15663206, "file_range_sync_nanos": 649588, "file_fsync_nanos": 349614797, "file_prepare_write_nanos": 1505812, "lsm_state": [2, 4, 0, 0, 0, 0, 0]}
Add two more counters in iostats_context.
Also add a parameter of db_bench.
Test Plan: Add a unit test. Also manually verify LOG outputs in db_bench
Subscribers: leveldb, dhruba
Differential Revision: https://reviews.facebook.net/D44115
2015-08-13 00:24:45 +00:00
|
|
|
|
|
|
|
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;
|
|
|
|
}
|
|
|
|
|
Include bunch of more events into EventLogger
Summary:
Added these events:
* Recovery start, finish and also when recovery creates a file
* Trivial move
* Compaction start, finish and when compaction creates a file
* Flush start, finish
Also includes small fix to EventLogger
Also added option ROCKSDB_PRINT_EVENTS_TO_STDOUT which is useful when we debug things. I've spent far too much time chasing LOG files.
Still didn't get sst table properties in JSON. They are written very deeply into the stack. I'll address in separate diff.
TODO:
* Write specification. Let's first use this for a while and figure out what's good data to put here, too. After that we'll write spec
* Write tools that parse and analyze LOGs. This can be in python or go. Good intern task.
Test Plan: Ran db_bench with ROCKSDB_PRINT_EVENTS_TO_STDOUT. Here's the output: https://phabricator.fb.com/P19811976
Reviewers: sdong, yhchiang, rven, MarkCallaghan, kradhakrishnan, anthony
Reviewed By: anthony
Subscribers: dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D37521
2015-04-27 22:20:02 +00:00
|
|
|
stream << "lsm_state";
|
|
|
|
stream.StartArray();
|
|
|
|
for (int level = 0; level < vstorage->num_levels(); ++level) {
|
|
|
|
stream << vstorage->NumLevelFiles(level);
|
|
|
|
}
|
|
|
|
stream.EndArray();
|
|
|
|
|
2015-08-18 18:06:23 +00:00
|
|
|
CleanupCompaction();
|
|
|
|
return status;
|
2014-10-31 23:31:25 +00:00
|
|
|
}
|
|
|
|
|
2015-08-18 18:06:23 +00:00
|
|
|
void CompactionJob::ProcessKeyValueCompaction(SubCompactionState* sub_compact) {
|
|
|
|
assert(sub_compact != nullptr);
|
|
|
|
std::unique_ptr<Iterator> input_ptr(
|
|
|
|
versions_->MakeInputIterator(sub_compact->compaction));
|
|
|
|
Iterator* input = input_ptr.get();
|
|
|
|
|
2015-03-13 17:45:40 +00:00
|
|
|
AutoThreadOperationStageUpdater stage_updater(
|
|
|
|
ThreadStatus::STAGE_COMPACTION_PROCESS_KV);
|
2015-08-18 18:06:23 +00:00
|
|
|
|
|
|
|
// I/O measurement variables
|
|
|
|
PerfLevel prev_perf_level = PerfLevel::kEnableTime;
|
|
|
|
uint64_t prev_write_nanos = 0;
|
|
|
|
uint64_t prev_fsync_nanos = 0;
|
|
|
|
uint64_t prev_range_sync_nanos = 0;
|
|
|
|
uint64_t prev_prepare_write_nanos = 0;
|
|
|
|
if (measure_io_stats_) {
|
|
|
|
prev_perf_level = GetPerfLevel();
|
|
|
|
SetPerfLevel(PerfLevel::kEnableTime);
|
|
|
|
prev_write_nanos = iostats_context.write_nanos;
|
|
|
|
prev_fsync_nanos = iostats_context.fsync_nanos;
|
|
|
|
prev_range_sync_nanos = iostats_context.range_sync_nanos;
|
|
|
|
prev_prepare_write_nanos = iostats_context.prepare_write_nanos;
|
|
|
|
}
|
|
|
|
|
|
|
|
// Variables used inside the loop
|
2014-10-31 23:31:25 +00:00
|
|
|
Status status;
|
|
|
|
std::string compaction_filter_value;
|
|
|
|
ParsedInternalKey ikey;
|
|
|
|
IterKey current_user_key;
|
|
|
|
bool has_current_user_key = false;
|
|
|
|
IterKey delete_key;
|
2015-08-18 18:06:23 +00:00
|
|
|
|
2015-08-19 15:52:22 +00:00
|
|
|
SequenceNumber last_sequence_for_key __attribute__((unused)) =
|
|
|
|
kMaxSequenceNumber;
|
2014-10-31 23:31:25 +00:00
|
|
|
SequenceNumber visible_in_snapshot = kMaxSequenceNumber;
|
2015-08-18 18:06:23 +00:00
|
|
|
ColumnFamilyData* cfd = sub_compact->compaction->column_family_data();
|
2014-10-31 23:31:25 +00:00
|
|
|
MergeHelper merge(cfd->user_comparator(), cfd->ioptions()->merge_operator,
|
|
|
|
db_options_.info_log.get(),
|
|
|
|
cfd->ioptions()->min_partial_merge_operands,
|
|
|
|
false /* internal key corruption is expected */);
|
|
|
|
auto compaction_filter = cfd->ioptions()->compaction_filter;
|
|
|
|
std::unique_ptr<CompactionFilter> compaction_filter_from_factory = nullptr;
|
2015-07-29 02:21:55 +00:00
|
|
|
if (compaction_filter == nullptr) {
|
2014-10-31 23:31:25 +00:00
|
|
|
compaction_filter_from_factory =
|
2015-08-18 18:06:23 +00:00
|
|
|
sub_compact->compaction->CreateCompactionFilter();
|
2014-10-31 23:31:25 +00:00
|
|
|
compaction_filter = compaction_filter_from_factory.get();
|
|
|
|
}
|
|
|
|
|
2015-03-14 15:21:53 +00:00
|
|
|
TEST_SYNC_POINT("CompactionJob::Run():Inprogress");
|
2015-03-11 17:31:02 +00:00
|
|
|
|
2014-10-31 23:31:25 +00:00
|
|
|
int64_t key_drop_user = 0;
|
|
|
|
int64_t key_drop_newer_entry = 0;
|
|
|
|
int64_t key_drop_obsolete = 0;
|
|
|
|
int64_t loop_cnt = 0;
|
2015-03-03 18:59:36 +00:00
|
|
|
|
|
|
|
StopWatchNano timer(env_, stats_ != nullptr);
|
|
|
|
uint64_t total_filter_time = 0;
|
2015-07-29 02:21:55 +00:00
|
|
|
|
2015-08-18 18:06:23 +00:00
|
|
|
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
2015-08-03 18:32:14 +00:00
|
|
|
if (start != nullptr) {
|
|
|
|
IterKey start_iter;
|
|
|
|
start_iter.SetInternalKey(*start, kMaxSequenceNumber, kValueTypeForSeek);
|
|
|
|
Slice start_key = start_iter.GetKey();
|
|
|
|
input->Seek(start_key);
|
|
|
|
} else {
|
|
|
|
input->SeekToFirst();
|
|
|
|
}
|
|
|
|
|
2015-07-29 02:21:55 +00:00
|
|
|
// TODO(noetzli): check whether we could check !shutting_down_->... only
|
|
|
|
// only occasionally (see diff D42687)
|
2014-10-31 23:31:25 +00:00
|
|
|
while (input->Valid() && !shutting_down_->load(std::memory_order_acquire) &&
|
|
|
|
!cfd->IsDropped() && status.ok()) {
|
Parallelize L0-L1 Compaction: Restructure Compaction Job
Summary:
As of now compactions involving files from Level 0 and Level 1 are single
threaded because the files in L0, although sorted, are not range partitioned like
the other levels. This means that during L0-L1 compaction each file from L1
needs to be merged with potentially all the files from L0.
This attempt to parallelize the L0-L1 compaction assigns a thread and a
corresponding iterator to each L1 file that then considers only the key range
found in that L1 file and only the L0 files that have those keys (and only the
specific portion of those L0 files in which those keys are found). In this way
the overlap is minimized and potentially eliminated between different iterators
focusing on the same files.
The first step is to restructure the compaction logic to break L0-L1 compactions
into multiple, smaller, sequential compactions. Eventually each of these smaller
jobs will be run simultaneously. Areas to pay extra attention to are
# Correct aggregation of compaction job statistics across multiple threads
# Proper opening/closing of output files (make sure each thread's is unique)
# Keys that span multiple L1 files
# Skewed distributions of keys within L0 files
Test Plan: Make and run db_test (newer version has separate compaction tests) and compaction_job_stats_test
Reviewers: igor, noetzli, anthony, sdong, yhchiang
Reviewed By: yhchiang
Subscribers: MarkCallaghan, dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D42699
2015-08-03 18:32:14 +00:00
|
|
|
Slice key = input->key();
|
|
|
|
Slice value = input->value();
|
|
|
|
|
|
|
|
// First check that the key is parseable before performing the comparison
|
2015-08-18 18:06:23 +00:00
|
|
|
// to determine if it's within the range we want. Parsing may fail if the
|
|
|
|
// key being passed in is a user key without any internal key component
|
Parallelize L0-L1 Compaction: Restructure Compaction Job
Summary:
As of now compactions involving files from Level 0 and Level 1 are single
threaded because the files in L0, although sorted, are not range partitioned like
the other levels. This means that during L0-L1 compaction each file from L1
needs to be merged with potentially all the files from L0.
This attempt to parallelize the L0-L1 compaction assigns a thread and a
corresponding iterator to each L1 file that then considers only the key range
found in that L1 file and only the L0 files that have those keys (and only the
specific portion of those L0 files in which those keys are found). In this way
the overlap is minimized and potentially eliminated between different iterators
focusing on the same files.
The first step is to restructure the compaction logic to break L0-L1 compactions
into multiple, smaller, sequential compactions. Eventually each of these smaller
jobs will be run simultaneously. Areas to pay extra attention to are
# Correct aggregation of compaction job statistics across multiple threads
# Proper opening/closing of output files (make sure each thread's is unique)
# Keys that span multiple L1 files
# Skewed distributions of keys within L0 files
Test Plan: Make and run db_test (newer version has separate compaction tests) and compaction_job_stats_test
Reviewers: igor, noetzli, anthony, sdong, yhchiang
Reviewed By: yhchiang
Subscribers: MarkCallaghan, dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D42699
2015-08-03 18:32:14 +00:00
|
|
|
if (!ParseInternalKey(key, &ikey)) {
|
|
|
|
// Do not hide error keys
|
|
|
|
// TODO: error key stays in db forever? Figure out the rationale
|
|
|
|
// v10 error v8 : we cannot hide v8 even though it's pretty obvious.
|
|
|
|
current_user_key.Clear();
|
|
|
|
has_current_user_key = false;
|
|
|
|
last_sequence_for_key = kMaxSequenceNumber;
|
|
|
|
visible_in_snapshot = kMaxSequenceNumber;
|
2015-08-18 18:06:23 +00:00
|
|
|
sub_compact->compaction_job_stats.num_corrupt_keys++;
|
Parallelize L0-L1 Compaction: Restructure Compaction Job
Summary:
As of now compactions involving files from Level 0 and Level 1 are single
threaded because the files in L0, although sorted, are not range partitioned like
the other levels. This means that during L0-L1 compaction each file from L1
needs to be merged with potentially all the files from L0.
This attempt to parallelize the L0-L1 compaction assigns a thread and a
corresponding iterator to each L1 file that then considers only the key range
found in that L1 file and only the L0 files that have those keys (and only the
specific portion of those L0 files in which those keys are found). In this way
the overlap is minimized and potentially eliminated between different iterators
focusing on the same files.
The first step is to restructure the compaction logic to break L0-L1 compactions
into multiple, smaller, sequential compactions. Eventually each of these smaller
jobs will be run simultaneously. Areas to pay extra attention to are
# Correct aggregation of compaction job statistics across multiple threads
# Proper opening/closing of output files (make sure each thread's is unique)
# Keys that span multiple L1 files
# Skewed distributions of keys within L0 files
Test Plan: Make and run db_test (newer version has separate compaction tests) and compaction_job_stats_test
Reviewers: igor, noetzli, anthony, sdong, yhchiang
Reviewed By: yhchiang
Subscribers: MarkCallaghan, dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D42699
2015-08-03 18:32:14 +00:00
|
|
|
|
2015-08-18 18:06:23 +00:00
|
|
|
status = WriteKeyValue(key, value, ikey, input->status(), sub_compact);
|
Parallelize L0-L1 Compaction: Restructure Compaction Job
Summary:
As of now compactions involving files from Level 0 and Level 1 are single
threaded because the files in L0, although sorted, are not range partitioned like
the other levels. This means that during L0-L1 compaction each file from L1
needs to be merged with potentially all the files from L0.
This attempt to parallelize the L0-L1 compaction assigns a thread and a
corresponding iterator to each L1 file that then considers only the key range
found in that L1 file and only the L0 files that have those keys (and only the
specific portion of those L0 files in which those keys are found). In this way
the overlap is minimized and potentially eliminated between different iterators
focusing on the same files.
The first step is to restructure the compaction logic to break L0-L1 compactions
into multiple, smaller, sequential compactions. Eventually each of these smaller
jobs will be run simultaneously. Areas to pay extra attention to are
# Correct aggregation of compaction job statistics across multiple threads
# Proper opening/closing of output files (make sure each thread's is unique)
# Keys that span multiple L1 files
# Skewed distributions of keys within L0 files
Test Plan: Make and run db_test (newer version has separate compaction tests) and compaction_job_stats_test
Reviewers: igor, noetzli, anthony, sdong, yhchiang
Reviewed By: yhchiang
Subscribers: MarkCallaghan, dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D42699
2015-08-03 18:32:14 +00:00
|
|
|
input->Next();
|
|
|
|
continue;
|
|
|
|
}
|
|
|
|
|
2015-08-18 18:06:23 +00:00
|
|
|
// 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
2015-08-03 18:32:14 +00:00
|
|
|
if (end != nullptr &&
|
|
|
|
cfd->user_comparator()->Compare(ikey.user_key, *end) >= 0) {
|
|
|
|
break;
|
|
|
|
}
|
|
|
|
|
2015-08-18 18:06:23 +00:00
|
|
|
sub_compact->num_input_records++;
|
2014-10-31 23:31:25 +00:00
|
|
|
if (++loop_cnt > 1000) {
|
2015-08-18 18:06:23 +00:00
|
|
|
RecordDroppedKeys(&key_drop_user, &key_drop_newer_entry,
|
|
|
|
&key_drop_obsolete,
|
|
|
|
&sub_compact->compaction_job_stats);
|
2014-10-31 23:31:25 +00:00
|
|
|
RecordCompactionIOStats();
|
|
|
|
loop_cnt = 0;
|
|
|
|
}
|
|
|
|
|
2015-08-18 18:06:23 +00:00
|
|
|
sub_compact->compaction_job_stats.total_input_raw_key_bytes += key.size();
|
|
|
|
sub_compact->compaction_job_stats.total_input_raw_value_bytes +=
|
|
|
|
value.size();
|
2015-06-03 00:07:16 +00:00
|
|
|
|
2015-08-18 18:06:23 +00:00
|
|
|
if (sub_compact->compaction->ShouldStopBefore(key) &&
|
|
|
|
sub_compact->builder != nullptr) {
|
|
|
|
status = FinishCompactionOutputFile(input->status(), sub_compact);
|
2014-10-31 23:31:25 +00:00
|
|
|
if (!status.ok()) {
|
|
|
|
break;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
2015-08-18 18:06:23 +00:00
|
|
|
if (ikey.type == kTypeDeletion) {
|
|
|
|
sub_compact->compaction_job_stats.num_input_deletion_records++;
|
2015-07-29 02:21:55 +00:00
|
|
|
}
|
|
|
|
|
|
|
|
if (!has_current_user_key ||
|
|
|
|
cfd->user_comparator()->Compare(ikey.user_key,
|
|
|
|
current_user_key.GetKey()) != 0) {
|
|
|
|
// First occurrence of this user key
|
|
|
|
current_user_key.SetKey(ikey.user_key);
|
|
|
|
has_current_user_key = true;
|
|
|
|
last_sequence_for_key = kMaxSequenceNumber;
|
|
|
|
visible_in_snapshot = kMaxSequenceNumber;
|
|
|
|
// apply the compaction filter to the first occurrence of the user key
|
|
|
|
if (compaction_filter && ikey.type == kTypeValue &&
|
2015-08-18 18:06:23 +00:00
|
|
|
(sub_compact->visible_at_tip ||
|
|
|
|
ikey.sequence > sub_compact->latest_snapshot)) {
|
2015-07-29 02:21:55 +00:00
|
|
|
// If the user has specified a compaction filter and the sequence
|
|
|
|
// number is greater than any external snapshot, then invoke the
|
2015-08-18 18:06:23 +00:00
|
|
|
// filter. If the return value of the compaction filter is true,
|
|
|
|
// replace the entry with a deletion marker.
|
2015-07-29 02:21:55 +00:00
|
|
|
bool value_changed = false;
|
|
|
|
compaction_filter_value.clear();
|
|
|
|
if (stats_ != nullptr) {
|
|
|
|
timer.Start();
|
2014-10-31 23:31:25 +00:00
|
|
|
}
|
2015-07-29 02:21:55 +00:00
|
|
|
bool to_delete = compaction_filter->Filter(
|
2015-08-18 18:06:23 +00:00
|
|
|
sub_compact->compaction->level(), ikey.user_key, value,
|
2015-07-29 02:21:55 +00:00
|
|
|
&compaction_filter_value, &value_changed);
|
|
|
|
total_filter_time += timer.ElapsedNanos();
|
|
|
|
if (to_delete) {
|
|
|
|
// make a copy of the original key and convert it to a delete
|
|
|
|
delete_key.SetInternalKey(ExtractUserKey(key), ikey.sequence,
|
|
|
|
kTypeDeletion);
|
|
|
|
// anchor the key again
|
|
|
|
key = delete_key.GetKey();
|
|
|
|
// needed because ikey is backed by key
|
2014-10-31 23:31:25 +00:00
|
|
|
ParseInternalKey(key, &ikey);
|
2015-07-29 02:21:55 +00:00
|
|
|
// no value associated with delete
|
|
|
|
value.clear();
|
|
|
|
++key_drop_user;
|
|
|
|
} else if (value_changed) {
|
|
|
|
value = compaction_filter_value;
|
2014-10-31 23:31:25 +00:00
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
2015-07-29 02:21:55 +00:00
|
|
|
// If there are no snapshots, then this kv affect visibility at tip.
|
|
|
|
// Otherwise, search though all existing snapshots to find
|
|
|
|
// the earlist snapshot that is affected by this kv.
|
|
|
|
SequenceNumber prev_snapshot = 0; // 0 means no previous snapshot
|
|
|
|
SequenceNumber visible =
|
2015-08-18 18:06:23 +00:00
|
|
|
sub_compact->visible_at_tip
|
|
|
|
? sub_compact->visible_at_tip
|
|
|
|
: findEarliestVisibleSnapshot(ikey.sequence, &prev_snapshot);
|
2015-07-29 02:21:55 +00:00
|
|
|
|
|
|
|
if (visible_in_snapshot == visible) {
|
|
|
|
// If the earliest snapshot is which this key is visible in
|
|
|
|
// is the same as the visibily of a previous instance of the
|
|
|
|
// same key, then this kv is not visible in any snapshot.
|
|
|
|
// Hidden by an newer entry for same user key
|
|
|
|
// TODO: why not > ?
|
|
|
|
assert(last_sequence_for_key >= ikey.sequence);
|
|
|
|
++key_drop_newer_entry;
|
|
|
|
input->Next(); // (A)
|
|
|
|
} else if (ikey.type == kTypeDeletion &&
|
2015-08-18 18:06:23 +00:00
|
|
|
ikey.sequence <= sub_compact->earliest_snapshot &&
|
|
|
|
sub_compact->compaction->KeyNotExistsBeyondOutputLevel(
|
|
|
|
ikey.user_key, &sub_compact->level_ptrs)) {
|
2015-07-29 02:21:55 +00:00
|
|
|
// For this user key:
|
|
|
|
// (1) there is no data in higher levels
|
|
|
|
// (2) data in lower levels will have larger sequence numbers
|
|
|
|
// (3) data in layers that are being compacted here and have
|
|
|
|
// smaller sequence numbers will be dropped in the next
|
|
|
|
// few iterations of this loop (by rule (A) above).
|
|
|
|
// Therefore this deletion marker is obsolete and can be dropped.
|
|
|
|
++key_drop_obsolete;
|
|
|
|
input->Next();
|
|
|
|
} else if (ikey.type == kTypeMerge) {
|
|
|
|
if (!merge.HasOperator()) {
|
|
|
|
LogToBuffer(log_buffer_, "Options::merge_operator is null.");
|
|
|
|
status = Status::InvalidArgument(
|
|
|
|
"merge_operator is not properly initialized.");
|
|
|
|
break;
|
|
|
|
}
|
|
|
|
// We know the merge type entry is not hidden, otherwise we would
|
|
|
|
// have hit (A)
|
|
|
|
// We encapsulate the merge related state machine in a different
|
|
|
|
// object to minimize change to the existing flow. Turn out this
|
|
|
|
// logic could also be nicely re-used for memtable flush purge
|
|
|
|
// optimization in BuildTable.
|
|
|
|
merge.MergeUntil(input, prev_snapshot, bottommost_level_,
|
|
|
|
db_options_.statistics.get(), env_);
|
|
|
|
|
Simplify querying of merge results
Summary:
While working on supporting mixing merge operators with
single deletes ( https://reviews.facebook.net/D43179 ),
I realized that returning and dealing with merge results
can be made simpler. Submitting this as a separate diff
because it is not directly related to single deletes.
Before, callers of merge helper had to retrieve the merge
result in one of two ways depending on whether the merge
was successful or not (success = result of merge was single
kTypeValue). For successful merges, the caller could query
the resulting key/value pair and for unsuccessful merges,
the result could be retrieved in the form of two deques of
keys and values. However, with single deletes, a successful merge
does not return a single key/value pair (if merge
operands are merged with a single delete, we have to generate
a value and keep the original single delete around to make
sure that we are not accidentially producing a key overwrite).
In addition, the two existing call sites of the merge
helper were taking the same actions independently from whether
the merge was successful or not, so this patch simplifies that.
Test Plan: make clean all check
Reviewers: rven, sdong, yhchiang, anthony, igor
Reviewed By: igor
Subscribers: dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D43353
2015-08-18 00:34:38 +00:00
|
|
|
// NOTE: key, value, and ikey refer to old entries.
|
|
|
|
// These will be correctly set below.
|
|
|
|
const auto& keys = merge.keys();
|
|
|
|
const auto& values = merge.values();
|
|
|
|
assert(!keys.empty());
|
|
|
|
assert(keys.size() == values.size());
|
|
|
|
|
|
|
|
// We have a list of keys to write, write all keys in the list.
|
|
|
|
for (auto key_iter = keys.rbegin(), value_iter = values.rbegin();
|
|
|
|
!status.ok() || key_iter != keys.rend(); key_iter++, value_iter++) {
|
|
|
|
key = Slice(*key_iter);
|
|
|
|
value = Slice(*value_iter);
|
|
|
|
bool valid_key __attribute__((__unused__)) =
|
|
|
|
ParseInternalKey(key, &ikey);
|
|
|
|
// MergeUntil stops when it encounters a corrupt key and does not
|
|
|
|
// include them in the result, so we expect the keys here to valid.
|
|
|
|
assert(valid_key);
|
2015-08-18 18:06:23 +00:00
|
|
|
status = WriteKeyValue(key, value, ikey, input->status(), sub_compact);
|
2015-07-15 16:55:45 +00:00
|
|
|
}
|
2015-07-29 02:21:55 +00:00
|
|
|
} else {
|
2015-08-18 18:06:23 +00:00
|
|
|
status = WriteKeyValue(key, value, ikey, input->status(), sub_compact);
|
2014-10-31 23:31:25 +00:00
|
|
|
input->Next();
|
|
|
|
}
|
2015-07-29 02:21:55 +00:00
|
|
|
|
|
|
|
last_sequence_for_key = ikey.sequence;
|
|
|
|
visible_in_snapshot = visible;
|
2014-10-31 23:31:25 +00:00
|
|
|
}
|
2015-07-29 02:21:55 +00:00
|
|
|
|
2015-03-03 18:59:36 +00:00
|
|
|
RecordTick(stats_, FILTER_OPERATION_TOTAL_TIME, total_filter_time);
|
2015-08-18 18:06:23 +00:00
|
|
|
RecordDroppedKeys(&key_drop_user, &key_drop_newer_entry, &key_drop_obsolete,
|
|
|
|
&sub_compact->compaction_job_stats);
|
2014-10-31 23:31:25 +00:00
|
|
|
RecordCompactionIOStats();
|
|
|
|
|
2015-07-29 02:21:55 +00:00
|
|
|
if (status.ok() &&
|
|
|
|
(shutting_down_->load(std::memory_order_acquire) || cfd->IsDropped())) {
|
|
|
|
status = Status::ShutdownInProgress(
|
|
|
|
"Database shutdown or Column family drop during compaction");
|
|
|
|
}
|
2015-08-18 18:06:23 +00:00
|
|
|
if (status.ok() && sub_compact->builder != nullptr) {
|
|
|
|
status = FinishCompactionOutputFile(input->status(), sub_compact);
|
2015-07-29 02:21:55 +00:00
|
|
|
}
|
|
|
|
if (status.ok()) {
|
|
|
|
status = input->status();
|
|
|
|
}
|
2015-08-18 18:06:23 +00:00
|
|
|
if (output_directory_ && !db_options_.disableDataSync) {
|
|
|
|
// TODO(aekmekji): Maybe only call once after all subcompactions complete?
|
|
|
|
output_directory_->Fsync();
|
|
|
|
}
|
2015-07-29 02:21:55 +00:00
|
|
|
|
2015-08-18 18:06:23 +00:00
|
|
|
if (measure_io_stats_) {
|
|
|
|
sub_compact->compaction_job_stats.file_write_nanos +=
|
|
|
|
iostats_context.write_nanos - prev_write_nanos;
|
|
|
|
sub_compact->compaction_job_stats.file_fsync_nanos +=
|
|
|
|
iostats_context.fsync_nanos - prev_fsync_nanos;
|
|
|
|
sub_compact->compaction_job_stats.file_range_sync_nanos +=
|
|
|
|
iostats_context.range_sync_nanos - prev_range_sync_nanos;
|
|
|
|
sub_compact->compaction_job_stats.file_prepare_write_nanos +=
|
|
|
|
iostats_context.prepare_write_nanos - prev_prepare_write_nanos;
|
|
|
|
if (prev_perf_level != PerfLevel::kEnableTime) {
|
|
|
|
SetPerfLevel(prev_perf_level);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
input_ptr.reset();
|
|
|
|
sub_compact->status = status;
|
2014-10-31 23:31:25 +00:00
|
|
|
}
|
|
|
|
|
2015-07-15 16:55:45 +00:00
|
|
|
Status CompactionJob::WriteKeyValue(const Slice& key, const Slice& value,
|
2015-08-18 18:06:23 +00:00
|
|
|
const ParsedInternalKey& ikey, const Status& input_status,
|
|
|
|
SubCompactionState* sub_compact) {
|
|
|
|
|
2015-07-15 16:55:45 +00:00
|
|
|
Slice newkey(key.data(), key.size());
|
|
|
|
std::string kstr;
|
|
|
|
|
|
|
|
// Zeroing out the sequence number leads to better compression.
|
|
|
|
// If this is the bottommost level (no files in lower levels)
|
|
|
|
// and the earliest snapshot is larger than this seqno
|
|
|
|
// then we can squash the seqno to zero.
|
2015-08-18 18:06:23 +00:00
|
|
|
if (bottommost_level_ && ikey.sequence < sub_compact->earliest_snapshot &&
|
2015-07-15 16:55:45 +00:00
|
|
|
ikey.type != kTypeMerge) {
|
|
|
|
assert(ikey.type != kTypeDeletion);
|
|
|
|
// make a copy because updating in place would cause problems
|
|
|
|
// with the priority queue that is managing the input key iterator
|
|
|
|
kstr.assign(key.data(), key.size());
|
|
|
|
UpdateInternalKey(&kstr, (uint64_t)0, ikey.type);
|
|
|
|
newkey = Slice(kstr);
|
|
|
|
}
|
|
|
|
|
|
|
|
// Open output file if necessary
|
2015-08-18 18:06:23 +00:00
|
|
|
if (sub_compact->builder == nullptr) {
|
|
|
|
Status status = OpenCompactionOutputFile(sub_compact);
|
2015-07-15 16:55:45 +00:00
|
|
|
if (!status.ok()) {
|
|
|
|
return status;
|
|
|
|
}
|
|
|
|
}
|
2015-08-18 18:06:23 +00:00
|
|
|
assert(sub_compact->builder != nullptr);
|
2015-08-18 19:27:12 +00:00
|
|
|
assert(sub_compact->current_output() != nullptr);
|
2015-07-15 16:55:45 +00:00
|
|
|
|
|
|
|
SequenceNumber seqno = GetInternalKeySeqno(newkey);
|
2015-08-18 18:06:23 +00:00
|
|
|
if (sub_compact->builder->NumEntries() == 0) {
|
|
|
|
sub_compact->current_output()->smallest.DecodeFrom(newkey);
|
|
|
|
sub_compact->current_output()->smallest_seqno = seqno;
|
2015-07-15 16:55:45 +00:00
|
|
|
} else {
|
2015-08-18 18:06:23 +00:00
|
|
|
sub_compact->current_output()->smallest_seqno =
|
|
|
|
std::min(sub_compact->current_output()->smallest_seqno, seqno);
|
2015-07-15 16:55:45 +00:00
|
|
|
}
|
2015-08-18 18:06:23 +00:00
|
|
|
sub_compact->current_output()->largest.DecodeFrom(newkey);
|
|
|
|
sub_compact->builder->Add(newkey, value);
|
|
|
|
sub_compact->num_output_records++;
|
|
|
|
sub_compact->current_output()->largest_seqno =
|
|
|
|
std::max(sub_compact->current_output()->largest_seqno, seqno);
|
2015-07-15 16:55:45 +00:00
|
|
|
|
|
|
|
// Close output file if it is big enough
|
|
|
|
Status status;
|
2015-08-18 18:06:23 +00:00
|
|
|
if (sub_compact->builder->FileSize() >=
|
|
|
|
sub_compact->compaction->max_output_file_size()) {
|
|
|
|
status = FinishCompactionOutputFile(input_status, sub_compact);
|
2015-07-15 16:55:45 +00:00
|
|
|
}
|
|
|
|
|
|
|
|
return status;
|
|
|
|
}
|
|
|
|
|
2015-06-03 00:07:16 +00:00
|
|
|
void CompactionJob::RecordDroppedKeys(
|
|
|
|
int64_t* key_drop_user,
|
|
|
|
int64_t* key_drop_newer_entry,
|
2015-08-18 18:06:23 +00:00
|
|
|
int64_t* key_drop_obsolete,
|
|
|
|
CompactionJobStats* compaction_job_stats) {
|
2015-06-03 00:07:16 +00:00
|
|
|
if (*key_drop_user > 0) {
|
|
|
|
RecordTick(stats_, COMPACTION_KEY_DROP_USER, *key_drop_user);
|
|
|
|
*key_drop_user = 0;
|
|
|
|
}
|
|
|
|
if (*key_drop_newer_entry > 0) {
|
|
|
|
RecordTick(stats_, COMPACTION_KEY_DROP_NEWER_ENTRY, *key_drop_newer_entry);
|
2015-08-18 18:06:23 +00:00
|
|
|
if (compaction_job_stats) {
|
|
|
|
compaction_job_stats->num_records_replaced += *key_drop_newer_entry;
|
2015-06-03 00:07:16 +00:00
|
|
|
}
|
|
|
|
*key_drop_newer_entry = 0;
|
|
|
|
}
|
|
|
|
if (*key_drop_obsolete > 0) {
|
|
|
|
RecordTick(stats_, COMPACTION_KEY_DROP_OBSOLETE, *key_drop_obsolete);
|
2015-08-18 18:06:23 +00:00
|
|
|
if (compaction_job_stats) {
|
|
|
|
compaction_job_stats->num_expired_deletion_records += *key_drop_obsolete;
|
2015-07-13 22:51:38 +00:00
|
|
|
}
|
2015-06-03 00:07:16 +00:00
|
|
|
*key_drop_obsolete = 0;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
2015-08-18 18:06:23 +00:00
|
|
|
Status CompactionJob::FinishCompactionOutputFile(const Status& input_status,
|
|
|
|
SubCompactionState* sub_compact) {
|
2015-03-13 17:45:40 +00:00
|
|
|
AutoThreadOperationStageUpdater stage_updater(
|
|
|
|
ThreadStatus::STAGE_COMPACTION_SYNC_FILE);
|
2015-08-18 18:06:23 +00:00
|
|
|
assert(sub_compact != nullptr);
|
|
|
|
assert(sub_compact->outfile);
|
|
|
|
assert(sub_compact->builder != nullptr);
|
2015-08-18 19:27:12 +00:00
|
|
|
assert(sub_compact->current_output() != nullptr);
|
2014-10-31 23:31:25 +00:00
|
|
|
|
2015-08-18 18:06:23 +00:00
|
|
|
const uint64_t output_number = sub_compact->current_output()->number;
|
|
|
|
const uint32_t output_path_id = sub_compact->current_output()->path_id;
|
2014-10-31 23:31:25 +00:00
|
|
|
assert(output_number != 0);
|
|
|
|
|
Add more table properties to EventLogger
Summary:
Example output:
{"time_micros": 1431463794310521, "job": 353, "event": "table_file_creation", "file_number": 387, "file_size": 86937, "table_info": {"data_size": "81801", "index_size": "9751", "filter_size": "0", "raw_key_size": "23448", "raw_average_key_size": "24.000000", "raw_value_size": "990571", "raw_average_value_size": "1013.890481", "num_data_blocks": "245", "num_entries": "977", "filter_policy_name": "", "kDeletedKeys": "0"}}
Also fixed a bug where BuildTable() in recovery was passing Env::IOHigh argument into paranoid_checks_file parameter.
Test Plan: make check + check out the output in the log
Reviewers: sdong, rven, yhchiang
Reviewed By: yhchiang
Subscribers: dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D38343
2015-05-12 22:53:55 +00:00
|
|
|
TableProperties table_properties;
|
2014-10-31 23:31:25 +00:00
|
|
|
// Check for iterator errors
|
2015-07-15 16:55:45 +00:00
|
|
|
Status s = input_status;
|
2015-08-18 18:06:23 +00:00
|
|
|
const uint64_t current_entries = sub_compact->builder->NumEntries();
|
|
|
|
sub_compact->current_output()->need_compaction =
|
|
|
|
sub_compact->builder->NeedCompact();
|
2014-10-31 23:31:25 +00:00
|
|
|
if (s.ok()) {
|
2015-08-18 18:06:23 +00:00
|
|
|
s = sub_compact->builder->Finish();
|
2014-10-31 23:31:25 +00:00
|
|
|
} else {
|
2015-08-18 18:06:23 +00:00
|
|
|
sub_compact->builder->Abandon();
|
2014-10-31 23:31:25 +00:00
|
|
|
}
|
2015-08-18 18:06:23 +00:00
|
|
|
const uint64_t current_bytes = sub_compact->builder->FileSize();
|
|
|
|
sub_compact->current_output()->file_size = current_bytes;
|
|
|
|
sub_compact->total_bytes += current_bytes;
|
2014-10-31 23:31:25 +00:00
|
|
|
|
|
|
|
// Finish and check for file errors
|
|
|
|
if (s.ok() && !db_options_.disableDataSync) {
|
Move rate_limiter, write buffering, most perf context instrumentation and most random kill out of Env
Summary: We want to keep Env a think layer for better portability. Less platform dependent codes should be moved out of Env. In this patch, I create a wrapper of file readers and writers, and put rate limiting, write buffering, as well as most perf context instrumentation and random kill out of Env. It will make it easier to maintain multiple Env in the future.
Test Plan: Run all existing unit tests.
Reviewers: anthony, kradhakrishnan, IslamAbdelRahman, yhchiang, igor
Reviewed By: igor
Subscribers: leveldb, dhruba
Differential Revision: https://reviews.facebook.net/D42321
2015-07-17 23:16:11 +00:00
|
|
|
StopWatch sw(env_, stats_, COMPACTION_OUTFILE_SYNC_MICROS);
|
2015-08-18 18:06:23 +00:00
|
|
|
s = sub_compact->outfile->Sync(db_options_.use_fsync);
|
2014-10-31 23:31:25 +00:00
|
|
|
}
|
|
|
|
if (s.ok()) {
|
2015-08-18 18:06:23 +00:00
|
|
|
s = sub_compact->outfile->Close();
|
2014-10-31 23:31:25 +00:00
|
|
|
}
|
2015-08-18 18:06:23 +00:00
|
|
|
sub_compact->outfile.reset();
|
2014-10-31 23:31:25 +00:00
|
|
|
|
|
|
|
if (s.ok() && current_entries > 0) {
|
|
|
|
// Verify that the table is usable
|
2015-08-18 18:06:23 +00:00
|
|
|
ColumnFamilyData* cfd = sub_compact->compaction->column_family_data();
|
2014-10-31 23:31:25 +00:00
|
|
|
FileDescriptor fd(output_number, output_path_id, current_bytes);
|
|
|
|
Iterator* iter = cfd->table_cache()->NewIterator(
|
2015-08-05 19:11:30 +00:00
|
|
|
ReadOptions(), env_options_, cfd->internal_comparator(), fd, nullptr,
|
Measure file read latency histogram per level
Summary: In internal stats, remember read latency histogram, if statistics is enabled. It can be retrieved from DB::GetProperty() with "rocksdb.dbstats" property, if it is enabled.
Test Plan: Manually run db_bench and prints out "rocksdb.dbstats" by hand and make sure it prints out as expected
Reviewers: igor, IslamAbdelRahman, rven, kradhakrishnan, anthony, yhchiang
Reviewed By: yhchiang
Subscribers: MarkCallaghan, leveldb, dhruba
Differential Revision: https://reviews.facebook.net/D44193
2015-08-13 21:35:54 +00:00
|
|
|
cfd->internal_stats()->GetFileReadHist(
|
|
|
|
compact_->compaction->output_level()),
|
|
|
|
false);
|
2014-10-31 23:31:25 +00:00
|
|
|
s = iter->status();
|
2015-04-17 22:26:50 +00:00
|
|
|
|
2015-05-06 02:01:12 +00:00
|
|
|
if (s.ok() && paranoid_file_checks_) {
|
2015-04-17 22:26:50 +00:00
|
|
|
for (iter->SeekToFirst(); iter->Valid(); iter->Next()) {}
|
|
|
|
s = iter->status();
|
|
|
|
}
|
|
|
|
|
2014-10-31 23:31:25 +00:00
|
|
|
delete iter;
|
|
|
|
if (s.ok()) {
|
2015-08-18 18:06:23 +00:00
|
|
|
TableFileCreationInfo info(sub_compact->builder->GetTableProperties());
|
2015-06-02 21:12:23 +00:00
|
|
|
info.db_name = dbname_;
|
|
|
|
info.cf_name = cfd->GetName();
|
|
|
|
info.file_path = TableFileName(cfd->ioptions()->db_paths,
|
|
|
|
fd.GetNumber(), fd.GetPathId());
|
|
|
|
info.file_size = fd.GetFileSize();
|
|
|
|
info.job_id = job_id_;
|
2015-02-12 17:54:48 +00:00
|
|
|
Log(InfoLogLevel::INFO_LEVEL, db_options_.info_log,
|
|
|
|
"[%s] [JOB %d] Generated table #%" PRIu64 ": %" PRIu64
|
Print info message about files need compaction for debuging purpose
Summary:
When there are files marked for compaction after compactions, print extra messages to help debugging. Example:
2015/06/08-23:12:55.212855 7ff5013ff700 [default] [JOB 121] Generated table #75: 54 keys, 4807 bytes (need compaction)
2015/06/08-23:12:55.556194 7ff5013ff700 (Original Log Time 2015/06/08-23:12:55.556160) [default] compacted to: base level 1 max bytes base
10240 files[0 1 9 32 12 0 0 0] max score 0.96 (2 files need compaction), MB/sec: 0.0 rd, 0.1 wr, level 2, files in(1, 3) out(5) MB in(0.0,
0.0) out(0.0), read-write-amplify(11.3) write-amplify(5.7) OK, records in: 40, records dropped: 0
Test Plan:
Run test and see LOG files.
valgrind test DBTest.TablePropertiesNeedCompactTest
Reviewers: rven, yhchiang, kradhakrishnan, IslamAbdelRahman, igor
Reviewed By: igor
Subscribers: yoshinorim, maykov, leveldb, dhruba
Differential Revision: https://reviews.facebook.net/D39771
2015-06-09 06:14:13 +00:00
|
|
|
" keys, %" PRIu64 " bytes%s",
|
2015-02-12 17:54:48 +00:00
|
|
|
cfd->GetName().c_str(), job_id_, output_number, current_entries,
|
Print info message about files need compaction for debuging purpose
Summary:
When there are files marked for compaction after compactions, print extra messages to help debugging. Example:
2015/06/08-23:12:55.212855 7ff5013ff700 [default] [JOB 121] Generated table #75: 54 keys, 4807 bytes (need compaction)
2015/06/08-23:12:55.556194 7ff5013ff700 (Original Log Time 2015/06/08-23:12:55.556160) [default] compacted to: base level 1 max bytes base
10240 files[0 1 9 32 12 0 0 0] max score 0.96 (2 files need compaction), MB/sec: 0.0 rd, 0.1 wr, level 2, files in(1, 3) out(5) MB in(0.0,
0.0) out(0.0), read-write-amplify(11.3) write-amplify(5.7) OK, records in: 40, records dropped: 0
Test Plan:
Run test and see LOG files.
valgrind test DBTest.TablePropertiesNeedCompactTest
Reviewers: rven, yhchiang, kradhakrishnan, IslamAbdelRahman, igor
Reviewed By: igor
Subscribers: yoshinorim, maykov, leveldb, dhruba
Differential Revision: https://reviews.facebook.net/D39771
2015-06-09 06:14:13 +00:00
|
|
|
current_bytes,
|
2015-08-18 18:06:23 +00:00
|
|
|
sub_compact->current_output()->need_compaction ? " (need compaction)"
|
Print info message about files need compaction for debuging purpose
Summary:
When there are files marked for compaction after compactions, print extra messages to help debugging. Example:
2015/06/08-23:12:55.212855 7ff5013ff700 [default] [JOB 121] Generated table #75: 54 keys, 4807 bytes (need compaction)
2015/06/08-23:12:55.556194 7ff5013ff700 (Original Log Time 2015/06/08-23:12:55.556160) [default] compacted to: base level 1 max bytes base
10240 files[0 1 9 32 12 0 0 0] max score 0.96 (2 files need compaction), MB/sec: 0.0 rd, 0.1 wr, level 2, files in(1, 3) out(5) MB in(0.0,
0.0) out(0.0), read-write-amplify(11.3) write-amplify(5.7) OK, records in: 40, records dropped: 0
Test Plan:
Run test and see LOG files.
valgrind test DBTest.TablePropertiesNeedCompactTest
Reviewers: rven, yhchiang, kradhakrishnan, IslamAbdelRahman, igor
Reviewed By: igor
Subscribers: yoshinorim, maykov, leveldb, dhruba
Differential Revision: https://reviews.facebook.net/D39771
2015-06-09 06:14:13 +00:00
|
|
|
: "");
|
2015-06-02 21:12:23 +00:00
|
|
|
EventHelpers::LogAndNotifyTableFileCreation(
|
|
|
|
event_logger_, cfd->ioptions()->listeners, fd, info);
|
2014-10-31 23:31:25 +00:00
|
|
|
}
|
|
|
|
}
|
2015-08-18 18:06:23 +00:00
|
|
|
sub_compact->builder.reset();
|
2014-10-31 23:31:25 +00:00
|
|
|
return s;
|
|
|
|
}
|
|
|
|
|
2015-05-06 02:01:12 +00:00
|
|
|
Status CompactionJob::InstallCompactionResults(
|
2015-08-18 18:06:23 +00:00
|
|
|
const MutableCFOptions& mutable_cf_options, InstrumentedMutex* db_mutex) {
|
2014-11-07 23:44:12 +00:00
|
|
|
db_mutex->AssertHeld();
|
2014-10-31 23:31:25 +00:00
|
|
|
|
options.level_compaction_dynamic_level_bytes to allow RocksDB to pick size bases of levels dynamically.
Summary:
When having fixed max_bytes_for_level_base, the ratio of size of largest level and the second one can range from 0 to the multiplier. This makes LSM tree frequently irregular and unpredictable. It can also cause poor space amplification in some cases.
In this improvement (proposed by Igor Kabiljo), we introduce a parameter option.level_compaction_use_dynamic_max_bytes. When turning it on, RocksDB is free to pick a level base in the range of (options.max_bytes_for_level_base/options.max_bytes_for_level_multiplier, options.max_bytes_for_level_base] so that real level ratios are close to options.max_bytes_for_level_multiplier.
Test Plan: New unit tests and pass tests suites including valgrind.
Reviewers: MarkCallaghan, rven, yhchiang, igor, ikabiljo
Reviewed By: ikabiljo
Subscribers: yoshinorim, ikabiljo, dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D31437
2015-02-05 19:44:17 +00:00
|
|
|
auto* compaction = compact_->compaction;
|
2014-10-31 23:31:25 +00:00
|
|
|
// 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_.
|
options.level_compaction_dynamic_level_bytes to allow RocksDB to pick size bases of levels dynamically.
Summary:
When having fixed max_bytes_for_level_base, the ratio of size of largest level and the second one can range from 0 to the multiplier. This makes LSM tree frequently irregular and unpredictable. It can also cause poor space amplification in some cases.
In this improvement (proposed by Igor Kabiljo), we introduce a parameter option.level_compaction_use_dynamic_max_bytes. When turning it on, RocksDB is free to pick a level base in the range of (options.max_bytes_for_level_base/options.max_bytes_for_level_multiplier, options.max_bytes_for_level_base] so that real level ratios are close to options.max_bytes_for_level_multiplier.
Test Plan: New unit tests and pass tests suites including valgrind.
Reviewers: MarkCallaghan, rven, yhchiang, igor, ikabiljo
Reviewed By: ikabiljo
Subscribers: yoshinorim, ikabiljo, dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D31437
2015-02-05 19:44:17 +00:00
|
|
|
if (!versions_->VerifyCompactionFileConsistency(compaction)) {
|
|
|
|
Compaction::InputLevelSummaryBuffer inputs_summary;
|
|
|
|
|
2014-11-04 19:07:11 +00:00
|
|
|
Log(InfoLogLevel::ERROR_LEVEL, db_options_.info_log,
|
options.level_compaction_dynamic_level_bytes to allow RocksDB to pick size bases of levels dynamically.
Summary:
When having fixed max_bytes_for_level_base, the ratio of size of largest level and the second one can range from 0 to the multiplier. This makes LSM tree frequently irregular and unpredictable. It can also cause poor space amplification in some cases.
In this improvement (proposed by Igor Kabiljo), we introduce a parameter option.level_compaction_use_dynamic_max_bytes. When turning it on, RocksDB is free to pick a level base in the range of (options.max_bytes_for_level_base/options.max_bytes_for_level_multiplier, options.max_bytes_for_level_base] so that real level ratios are close to options.max_bytes_for_level_multiplier.
Test Plan: New unit tests and pass tests suites including valgrind.
Reviewers: MarkCallaghan, rven, yhchiang, igor, ikabiljo
Reviewed By: ikabiljo
Subscribers: yoshinorim, ikabiljo, dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D31437
2015-02-05 19:44:17 +00:00
|
|
|
"[%s] [JOB %d] Compaction %s aborted",
|
|
|
|
compaction->column_family_data()->GetName().c_str(), job_id_,
|
|
|
|
compaction->InputLevelSummary(&inputs_summary));
|
2014-10-31 23:31:25 +00:00
|
|
|
return Status::Corruption("Compaction input files inconsistent");
|
|
|
|
}
|
|
|
|
|
options.level_compaction_dynamic_level_bytes to allow RocksDB to pick size bases of levels dynamically.
Summary:
When having fixed max_bytes_for_level_base, the ratio of size of largest level and the second one can range from 0 to the multiplier. This makes LSM tree frequently irregular and unpredictable. It can also cause poor space amplification in some cases.
In this improvement (proposed by Igor Kabiljo), we introduce a parameter option.level_compaction_use_dynamic_max_bytes. When turning it on, RocksDB is free to pick a level base in the range of (options.max_bytes_for_level_base/options.max_bytes_for_level_multiplier, options.max_bytes_for_level_base] so that real level ratios are close to options.max_bytes_for_level_multiplier.
Test Plan: New unit tests and pass tests suites including valgrind.
Reviewers: MarkCallaghan, rven, yhchiang, igor, ikabiljo
Reviewed By: ikabiljo
Subscribers: yoshinorim, ikabiljo, dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D31437
2015-02-05 19:44:17 +00:00
|
|
|
{
|
|
|
|
Compaction::InputLevelSummaryBuffer inputs_summary;
|
|
|
|
Log(InfoLogLevel::INFO_LEVEL, db_options_.info_log,
|
|
|
|
"[%s] [JOB %d] Compacted %s => %" PRIu64 " bytes",
|
|
|
|
compaction->column_family_data()->GetName().c_str(), job_id_,
|
|
|
|
compaction->InputLevelSummary(&inputs_summary), compact_->total_bytes);
|
|
|
|
}
|
2014-10-31 23:31:25 +00:00
|
|
|
|
|
|
|
// Add compaction outputs
|
options.level_compaction_dynamic_level_bytes to allow RocksDB to pick size bases of levels dynamically.
Summary:
When having fixed max_bytes_for_level_base, the ratio of size of largest level and the second one can range from 0 to the multiplier. This makes LSM tree frequently irregular and unpredictable. It can also cause poor space amplification in some cases.
In this improvement (proposed by Igor Kabiljo), we introduce a parameter option.level_compaction_use_dynamic_max_bytes. When turning it on, RocksDB is free to pick a level base in the range of (options.max_bytes_for_level_base/options.max_bytes_for_level_multiplier, options.max_bytes_for_level_base] so that real level ratios are close to options.max_bytes_for_level_multiplier.
Test Plan: New unit tests and pass tests suites including valgrind.
Reviewers: MarkCallaghan, rven, yhchiang, igor, ikabiljo
Reviewed By: ikabiljo
Subscribers: yoshinorim, ikabiljo, dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D31437
2015-02-05 19:44:17 +00:00
|
|
|
compaction->AddInputDeletions(compact_->compaction->edit());
|
2015-08-18 18:06:23 +00:00
|
|
|
|
|
|
|
for (SubCompactionState& sub_compact : compact_->sub_compact_states) {
|
|
|
|
for (size_t i = 0; i < sub_compact.outputs.size(); i++) {
|
|
|
|
const SubCompactionState::Output& out = sub_compact.outputs[i];
|
|
|
|
compaction->edit()->AddFile(compaction->output_level(), out.number,
|
|
|
|
out.path_id, out.file_size, out.smallest,
|
|
|
|
out.largest, out.smallest_seqno,
|
|
|
|
out.largest_seqno, out.need_compaction);
|
|
|
|
}
|
options.level_compaction_dynamic_level_bytes to allow RocksDB to pick size bases of levels dynamically.
Summary:
When having fixed max_bytes_for_level_base, the ratio of size of largest level and the second one can range from 0 to the multiplier. This makes LSM tree frequently irregular and unpredictable. It can also cause poor space amplification in some cases.
In this improvement (proposed by Igor Kabiljo), we introduce a parameter option.level_compaction_use_dynamic_max_bytes. When turning it on, RocksDB is free to pick a level base in the range of (options.max_bytes_for_level_base/options.max_bytes_for_level_multiplier, options.max_bytes_for_level_base] so that real level ratios are close to options.max_bytes_for_level_multiplier.
Test Plan: New unit tests and pass tests suites including valgrind.
Reviewers: MarkCallaghan, rven, yhchiang, igor, ikabiljo
Reviewed By: ikabiljo
Subscribers: yoshinorim, ikabiljo, dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D31437
2015-02-05 19:44:17 +00:00
|
|
|
}
|
|
|
|
return versions_->LogAndApply(compaction->column_family_data(),
|
2015-05-06 02:01:12 +00:00
|
|
|
mutable_cf_options, compaction->edit(),
|
options.level_compaction_dynamic_level_bytes to allow RocksDB to pick size bases of levels dynamically.
Summary:
When having fixed max_bytes_for_level_base, the ratio of size of largest level and the second one can range from 0 to the multiplier. This makes LSM tree frequently irregular and unpredictable. It can also cause poor space amplification in some cases.
In this improvement (proposed by Igor Kabiljo), we introduce a parameter option.level_compaction_use_dynamic_max_bytes. When turning it on, RocksDB is free to pick a level base in the range of (options.max_bytes_for_level_base/options.max_bytes_for_level_multiplier, options.max_bytes_for_level_base] so that real level ratios are close to options.max_bytes_for_level_multiplier.
Test Plan: New unit tests and pass tests suites including valgrind.
Reviewers: MarkCallaghan, rven, yhchiang, igor, ikabiljo
Reviewed By: ikabiljo
Subscribers: yoshinorim, ikabiljo, dhruba, leveldb
Differential Revision: https://reviews.facebook.net/D31437
2015-02-05 19:44:17 +00:00
|
|
|
db_mutex, db_directory_);
|
2014-10-31 23:31:25 +00:00
|
|
|
}
|
|
|
|
|
|
|
|
// Given a sequence number, return the sequence number of the
|
|
|
|
// earliest snapshot that this sequence number is visible in.
|
|
|
|
// The snapshots themselves are arranged in ascending order of
|
|
|
|
// sequence numbers.
|
|
|
|
// Employ a sequential search because the total number of
|
|
|
|
// snapshots are typically small.
|
|
|
|
inline SequenceNumber CompactionJob::findEarliestVisibleSnapshot(
|
2015-08-18 18:06:23 +00:00
|
|
|
SequenceNumber in, SequenceNumber* prev_snapshot) {
|
|
|
|
assert(existing_snapshots_.size());
|
2014-10-31 23:31:25 +00:00
|
|
|
SequenceNumber prev __attribute__((unused)) = 0;
|
2015-08-18 18:06:23 +00:00
|
|
|
for (const auto cur : existing_snapshots_) {
|
2014-10-31 23:31:25 +00:00
|
|
|
assert(prev <= cur);
|
|
|
|
if (cur >= in) {
|
|
|
|
*prev_snapshot = prev;
|
|
|
|
return cur;
|
|
|
|
}
|
|
|
|
prev = cur; // assignment
|
|
|
|
assert(prev);
|
|
|
|
}
|
2014-11-04 19:07:11 +00:00
|
|
|
Log(InfoLogLevel::WARN_LEVEL, db_options_.info_log,
|
|
|
|
"CompactionJob is not able to find snapshot"
|
|
|
|
" with SeqId later than %" PRIu64
|
|
|
|
": current MaxSeqId is %" PRIu64 "",
|
2015-08-18 18:06:23 +00:00
|
|
|
in, existing_snapshots_[existing_snapshots_.size() - 1]);
|
2014-10-31 23:31:25 +00:00
|
|
|
assert(0);
|
|
|
|
return 0;
|
|
|
|
}
|
|
|
|
|
|
|
|
void CompactionJob::RecordCompactionIOStats() {
|
|
|
|
RecordTick(stats_, COMPACT_READ_BYTES, IOSTATS(bytes_read));
|
2015-05-07 05:50:35 +00:00
|
|
|
ThreadStatusUtil::IncreaseThreadOperationProperty(
|
|
|
|
ThreadStatus::COMPACTION_BYTES_READ, IOSTATS(bytes_read));
|
2014-10-31 23:31:25 +00:00
|
|
|
IOSTATS_RESET(bytes_read);
|
|
|
|
RecordTick(stats_, COMPACT_WRITE_BYTES, IOSTATS(bytes_written));
|
2015-05-07 05:50:35 +00:00
|
|
|
ThreadStatusUtil::IncreaseThreadOperationProperty(
|
|
|
|
ThreadStatus::COMPACTION_BYTES_WRITTEN, IOSTATS(bytes_written));
|
2014-10-31 23:31:25 +00:00
|
|
|
IOSTATS_RESET(bytes_written);
|
|
|
|
}
|
|
|
|
|
2015-08-18 18:06:23 +00:00
|
|
|
Status CompactionJob::OpenCompactionOutputFile(SubCompactionState*
|
|
|
|
sub_compact) {
|
|
|
|
assert(sub_compact != nullptr);
|
|
|
|
assert(sub_compact->builder == nullptr);
|
2014-11-07 23:44:12 +00:00
|
|
|
// no need to lock because VersionSet::next_file_number_ is atomic
|
|
|
|
uint64_t file_number = versions_->NewFileNumber();
|
2014-10-31 23:31:25 +00:00
|
|
|
// Make the output file
|
Move rate_limiter, write buffering, most perf context instrumentation and most random kill out of Env
Summary: We want to keep Env a think layer for better portability. Less platform dependent codes should be moved out of Env. In this patch, I create a wrapper of file readers and writers, and put rate limiting, write buffering, as well as most perf context instrumentation and random kill out of Env. It will make it easier to maintain multiple Env in the future.
Test Plan: Run all existing unit tests.
Reviewers: anthony, kradhakrishnan, IslamAbdelRahman, yhchiang, igor
Reviewed By: igor
Subscribers: leveldb, dhruba
Differential Revision: https://reviews.facebook.net/D42321
2015-07-17 23:16:11 +00:00
|
|
|
unique_ptr<WritableFile> writable_file;
|
2014-10-31 23:31:25 +00:00
|
|
|
std::string fname = TableFileName(db_options_.db_paths, file_number,
|
2015-08-18 18:06:23 +00:00
|
|
|
sub_compact->compaction->output_path_id());
|
Move rate_limiter, write buffering, most perf context instrumentation and most random kill out of Env
Summary: We want to keep Env a think layer for better portability. Less platform dependent codes should be moved out of Env. In this patch, I create a wrapper of file readers and writers, and put rate limiting, write buffering, as well as most perf context instrumentation and random kill out of Env. It will make it easier to maintain multiple Env in the future.
Test Plan: Run all existing unit tests.
Reviewers: anthony, kradhakrishnan, IslamAbdelRahman, yhchiang, igor
Reviewed By: igor
Subscribers: leveldb, dhruba
Differential Revision: https://reviews.facebook.net/D42321
2015-07-17 23:16:11 +00:00
|
|
|
Status s = env_->NewWritableFile(fname, &writable_file, env_options_);
|
2014-10-31 23:31:25 +00:00
|
|
|
if (!s.ok()) {
|
|
|
|
Log(InfoLogLevel::ERROR_LEVEL, db_options_.info_log,
|
2015-02-12 17:54:48 +00:00
|
|
|
"[%s] [JOB %d] OpenCompactionOutputFiles for table #%" PRIu64
|
2014-11-04 19:07:11 +00:00
|
|
|
" fails at NewWritableFile with status %s",
|
2015-08-18 18:06:23 +00:00
|
|
|
sub_compact->compaction->column_family_data()->GetName().c_str(),
|
|
|
|
job_id_, file_number, s.ToString().c_str());
|
2014-10-31 23:31:25 +00:00
|
|
|
LogFlush(db_options_.info_log);
|
|
|
|
return s;
|
|
|
|
}
|
2015-08-18 18:06:23 +00:00
|
|
|
SubCompactionState::Output out;
|
2014-10-31 23:31:25 +00:00
|
|
|
out.number = file_number;
|
2015-08-18 18:06:23 +00:00
|
|
|
out.path_id = sub_compact->compaction->output_path_id();
|
2014-10-31 23:31:25 +00:00
|
|
|
out.smallest.Clear();
|
|
|
|
out.largest.Clear();
|
|
|
|
out.smallest_seqno = out.largest_seqno = 0;
|
|
|
|
|
2015-08-18 18:06:23 +00:00
|
|
|
sub_compact->outputs.push_back(out);
|
Move rate_limiter, write buffering, most perf context instrumentation and most random kill out of Env
Summary: We want to keep Env a think layer for better portability. Less platform dependent codes should be moved out of Env. In this patch, I create a wrapper of file readers and writers, and put rate limiting, write buffering, as well as most perf context instrumentation and random kill out of Env. It will make it easier to maintain multiple Env in the future.
Test Plan: Run all existing unit tests.
Reviewers: anthony, kradhakrishnan, IslamAbdelRahman, yhchiang, igor
Reviewed By: igor
Subscribers: leveldb, dhruba
Differential Revision: https://reviews.facebook.net/D42321
2015-07-17 23:16:11 +00:00
|
|
|
writable_file->SetIOPriority(Env::IO_LOW);
|
2015-08-18 18:06:23 +00:00
|
|
|
writable_file->SetPreallocationBlockSize(static_cast<size_t>(
|
|
|
|
sub_compact->compaction->OutputFilePreallocationSize()));
|
|
|
|
sub_compact->outfile.reset(
|
Move rate_limiter, write buffering, most perf context instrumentation and most random kill out of Env
Summary: We want to keep Env a think layer for better portability. Less platform dependent codes should be moved out of Env. In this patch, I create a wrapper of file readers and writers, and put rate limiting, write buffering, as well as most perf context instrumentation and random kill out of Env. It will make it easier to maintain multiple Env in the future.
Test Plan: Run all existing unit tests.
Reviewers: anthony, kradhakrishnan, IslamAbdelRahman, yhchiang, igor
Reviewed By: igor
Subscribers: leveldb, dhruba
Differential Revision: https://reviews.facebook.net/D42321
2015-07-17 23:16:11 +00:00
|
|
|
new WritableFileWriter(std::move(writable_file), env_options_));
|
2014-10-31 23:31:25 +00:00
|
|
|
|
2015-08-18 18:06:23 +00:00
|
|
|
ColumnFamilyData* cfd = sub_compact->compaction->column_family_data();
|
2015-02-17 16:03:45 +00:00
|
|
|
bool skip_filters = false;
|
|
|
|
|
|
|
|
// If the Column family flag is to only optimize filters for hits,
|
|
|
|
// we can skip creating filters if this is the bottommost_level where
|
|
|
|
// data is going to be found
|
|
|
|
//
|
|
|
|
if (cfd->ioptions()->optimize_filters_for_hits && bottommost_level_) {
|
|
|
|
skip_filters = true;
|
|
|
|
}
|
|
|
|
|
2015-08-18 18:06:23 +00:00
|
|
|
sub_compact->builder.reset(NewTableBuilder(
|
A new call back to TablePropertiesCollector to allow users know the entry is add, delete or merge
Summary:
Currently users have no idea a key is add, delete or merge from TablePropertiesCollector call back. Add a new function to add it.
Also refactor the codes so that
(1) make table property collector and internal table property collector two separate data structures with the later one now exposed
(2) table builders only receive internal table properties
Test Plan: Add cases in table_properties_collector_test to cover both of old and new ways of using TablePropertiesCollector.
Reviewers: yhchiang, igor.sugak, rven, igor
Reviewed By: rven, igor
Subscribers: meyering, yoshinorim, maykov, leveldb, dhruba
Differential Revision: https://reviews.facebook.net/D35373
2015-04-06 17:04:30 +00:00
|
|
|
*cfd->ioptions(), cfd->internal_comparator(),
|
2015-08-18 18:06:23 +00:00
|
|
|
cfd->int_tbl_prop_collector_factories(), sub_compact->outfile.get(),
|
|
|
|
sub_compact->compaction->output_compression(),
|
2015-02-17 16:03:45 +00:00
|
|
|
cfd->ioptions()->compression_opts, skip_filters));
|
2014-10-31 23:31:25 +00:00
|
|
|
LogFlush(db_options_.info_log);
|
|
|
|
return s;
|
|
|
|
}
|
|
|
|
|
2015-08-18 18:06:23 +00:00
|
|
|
void CompactionJob::CleanupCompaction() {
|
|
|
|
for (SubCompactionState& sub_compact : compact_->sub_compact_states) {
|
|
|
|
const auto& sub_status = sub_compact.status;
|
2014-10-31 23:31:25 +00:00
|
|
|
|
2015-08-18 18:06:23 +00:00
|
|
|
if (sub_compact.builder != nullptr) {
|
|
|
|
// May happen if we get a shutdown call in the middle of compaction
|
|
|
|
sub_compact.builder->Abandon();
|
|
|
|
sub_compact.builder.reset();
|
|
|
|
} else {
|
|
|
|
assert(!sub_status.ok() || sub_compact.outfile == nullptr);
|
|
|
|
}
|
|
|
|
for (size_t i = 0; i < sub_compact.outputs.size(); i++) {
|
|
|
|
const SubCompactionState::Output& out = sub_compact.outputs[i];
|
|
|
|
|
|
|
|
// If this file was inserted into the table cache then remove
|
|
|
|
// them here because this compaction was not committed.
|
|
|
|
if (!sub_status.ok()) {
|
|
|
|
TableCache::Evict(table_cache_.get(), out.number);
|
|
|
|
}
|
2014-10-31 23:31:25 +00:00
|
|
|
}
|
|
|
|
}
|
|
|
|
delete compact_;
|
|
|
|
compact_ = nullptr;
|
|
|
|
}
|
|
|
|
|
2015-06-03 00:07:16 +00:00
|
|
|
#ifndef ROCKSDB_LITE
|
|
|
|
namespace {
|
|
|
|
void CopyPrefix(
|
2015-06-04 19:31:12 +00:00
|
|
|
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);
|
2015-06-03 00:07:16 +00:00
|
|
|
}
|
|
|
|
} // namespace
|
|
|
|
|
|
|
|
#endif // !ROCKSDB_LITE
|
|
|
|
|
2015-07-14 07:09:20 +00:00
|
|
|
void CompactionJob::UpdateCompactionStats() {
|
2015-06-18 06:40:34 +00:00
|
|
|
Compaction* compaction = compact_->compaction;
|
|
|
|
compaction_stats_.num_input_files_in_non_output_levels = 0;
|
|
|
|
compaction_stats_.num_input_files_in_output_level = 0;
|
|
|
|
for (int input_level = 0;
|
|
|
|
input_level < static_cast<int>(compaction->num_input_levels());
|
|
|
|
++input_level) {
|
|
|
|
if (compaction->start_level() + input_level
|
|
|
|
!= compaction->output_level()) {
|
|
|
|
UpdateCompactionInputStatsHelper(
|
|
|
|
&compaction_stats_.num_input_files_in_non_output_levels,
|
|
|
|
&compaction_stats_.bytes_read_non_output_levels,
|
|
|
|
input_level);
|
|
|
|
} else {
|
|
|
|
UpdateCompactionInputStatsHelper(
|
|
|
|
&compaction_stats_.num_input_files_in_output_level,
|
|
|
|
&compaction_stats_.bytes_read_output_level,
|
|
|
|
input_level);
|
|
|
|
}
|
|
|
|
}
|
2015-07-14 07:09:20 +00:00
|
|
|
|
2015-08-18 18:06:23 +00:00
|
|
|
for (const auto& sub_compact : compact_->sub_compact_states) {
|
|
|
|
size_t num_output_files = sub_compact.outputs.size();
|
|
|
|
if (sub_compact.builder != nullptr) {
|
|
|
|
// An error occurred so ignore the last output.
|
|
|
|
assert(num_output_files > 0);
|
|
|
|
--num_output_files;
|
|
|
|
}
|
|
|
|
compaction_stats_.num_output_files += static_cast<int>(num_output_files);
|
|
|
|
|
|
|
|
for (size_t i = 0; i < num_output_files; i++) {
|
|
|
|
compaction_stats_.bytes_written += sub_compact.outputs[i].file_size;
|
|
|
|
}
|
|
|
|
if (sub_compact.num_input_records > sub_compact.num_output_records) {
|
|
|
|
compaction_stats_.num_dropped_records +=
|
|
|
|
sub_compact.num_input_records - sub_compact.num_output_records;
|
|
|
|
}
|
2015-07-14 07:09:20 +00:00
|
|
|
}
|
2015-06-18 06:40:34 +00:00
|
|
|
}
|
|
|
|
|
|
|
|
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);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
2015-06-03 00:07:16 +00:00
|
|
|
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 =
|
2015-06-18 06:40:34 +00:00
|
|
|
stats.bytes_read_non_output_levels +
|
|
|
|
stats.bytes_read_output_level;
|
|
|
|
compaction_job_stats_->num_input_records =
|
|
|
|
compact_->num_input_records;
|
2015-06-03 00:07:16 +00:00
|
|
|
compaction_job_stats_->num_input_files =
|
2015-06-18 06:40:34 +00:00
|
|
|
stats.num_input_files_in_non_output_levels +
|
|
|
|
stats.num_input_files_in_output_level;
|
2015-06-03 00:07:16 +00:00
|
|
|
compaction_job_stats_->num_input_files_at_output_level =
|
2015-06-18 06:40:34 +00:00
|
|
|
stats.num_input_files_in_output_level;
|
2015-06-03 00:07:16 +00:00
|
|
|
|
|
|
|
// output information
|
|
|
|
compaction_job_stats_->total_output_bytes = stats.bytes_written;
|
|
|
|
compaction_job_stats_->num_output_records =
|
|
|
|
compact_->num_output_records;
|
2015-06-18 06:40:34 +00:00
|
|
|
compaction_job_stats_->num_output_files = stats.num_output_files;
|
2015-06-03 00:07:16 +00:00
|
|
|
|
2015-08-18 18:06:23 +00:00
|
|
|
if (compact_->NumOutputFiles() > 0U) {
|
2015-06-03 00:07:16 +00:00
|
|
|
CopyPrefix(
|
2015-08-18 18:06:23 +00:00
|
|
|
compact_->SmallestUserKey(),
|
2015-06-04 19:31:12 +00:00
|
|
|
CompactionJobStats::kMaxPrefixLength,
|
|
|
|
&compaction_job_stats_->smallest_output_key_prefix);
|
2015-06-03 00:07:16 +00:00
|
|
|
CopyPrefix(
|
2015-08-18 18:06:23 +00:00
|
|
|
compact_->LargestUserKey(),
|
2015-06-04 19:31:12 +00:00
|
|
|
CompactionJobStats::kMaxPrefixLength,
|
|
|
|
&compaction_job_stats_->largest_output_key_prefix);
|
2015-06-03 00:07:16 +00:00
|
|
|
}
|
|
|
|
}
|
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#endif // !ROCKSDB_LITE
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}
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2015-08-18 18:06:23 +00:00
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void CompactionJob::LogCompaction() {
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Compaction* compaction = compact_->compaction;
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ColumnFamilyData* cfd = compaction->column_family_data();
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2015-07-14 07:09:20 +00:00
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// Let's check if anything will get logged. Don't prepare all the info if
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// we're not logging
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if (db_options_.info_log_level <= InfoLogLevel::INFO_LEVEL) {
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Compaction::InputLevelSummaryBuffer inputs_summary;
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Log(InfoLogLevel::INFO_LEVEL, db_options_.info_log,
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"[%s] [JOB %d] Compacting %s, score %.2f", cfd->GetName().c_str(),
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job_id_, compaction->InputLevelSummary(&inputs_summary),
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compaction->score());
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char scratch[2345];
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compaction->Summary(scratch, sizeof(scratch));
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Log(InfoLogLevel::INFO_LEVEL, db_options_.info_log,
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"[%s] Compaction start summary: %s\n", cfd->GetName().c_str(), scratch);
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// build event logger report
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auto stream = event_logger_->Log();
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stream << "job" << job_id_ << "event"
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<< "compaction_started";
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for (size_t i = 0; i < compaction->num_input_levels(); ++i) {
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stream << ("files_L" + ToString(compaction->level(i)));
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stream.StartArray();
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for (auto f : *compaction->inputs(i)) {
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stream << f->fd.GetNumber();
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}
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stream.EndArray();
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}
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stream << "score" << compaction->score() << "input_data_size"
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<< compaction->CalculateTotalInputSize();
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}
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}
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2014-10-31 23:31:25 +00:00
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} // namespace rocksdb
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