LevelDB的源码阅读(四) Compaction操作
leveldb的数据存储采用LSM的思想,将随机写入变为顺序写入,记录写入操作日志,一旦日志被以追加写的形式写入硬盘,就返回写入成功,由后台线程将写入日志作用于原有的磁盘文件生成新的磁盘数据.Leveldb在内存中维护一个数据结构memtable,采用skiplist来实现,保存当前写入的数据,当数据达到一定规模后变为不可写的内存表immutable table.新的写入操作会写入新的memtable,而immutable table会被后台线程写入到数据文件.Leveldb的数据文件是按层存放的,默认配置的最高层级是7,即level0,level1,…,level7.内存中的immutable总是写入level0,除level0之外的各个层leveli的所有数据文件的key范围都是互相不相交的.当满足一定条件时,leveli的数据文件会和leveli+1的数据文件进行merge,产生新的leveli+1层级的文件,这个磁盘文件的merge过程和immutable的dump过程叫做Compaction,在leveldb中是由一个单独的后台线程来完成的.
进行Compaction操作的条件如下:
1.产生了新的immutable table需要写入数据文件
2.某个level的数据规模过大
3.某个文件被无效查询的次数过多(在文件i中查询key,没有找到key,这次查询称为文件i的无效查询)
4.手动compaction
满足以上条件会启动Compaction过程,接下来分析详细的Compaction过程.
Leveldb进行Compaction的入口函数是db文件夹下db_impl.cc文件中的DBImpl::MaybeScheduleCompaction,该函数在每次leveldb进行读写操作时都有可能被调用.源码内容如下:
void DBImpl::MaybeScheduleCompaction() { mutex_.AssertHeld(); if (bg_compaction_scheduled_) { // Already scheduled } else if (shutting_down_.Acquire_Load()) { // DB is being deleted; no more background compactions } else if (!bg_error_.ok()) { // Already got an error; no more changes } else if (imm_ == NULL && manual_compaction_ == NULL && !versions_->NeedsCompaction()) { // No work to be done } else { bg_compaction_scheduled_ = true; env_->Schedule(&DBImpl::BGWork, this); //新建后台任务并进行调度 } }
首先调用db文件夹下version_set.h中的NeedsCompaction()判断是否需要启动Compact任务.源码内容如下:
// Returns true iff some level needs a compaction. bool NeedsCompaction() const { Version* v = current_; return (v->compaction_score_ >= 1) || (v->file_to_compact_ != NULL); }
version_set.cc中compaction_score_ 的计算如下:
void VersionSet::Finalize(Version* v) { // Precomputed best level for next compaction int best_level = -1; double best_score = -1; for (int level = 0; level < config::kNumLevels-1; level++) { double score; if (level == 0) { // We treat level-0 specially by bounding the number of files // instead of number of bytes for two reasons: // // (1) With larger write-buffer sizes, it is nice not to do too // many level-0 compactions. // // (2) The files in level-0 are merged on every read and // therefore we wish to avoid too many files when the individual // file size is small (perhaps because of a small write-buffer // setting, or very high compression ratios, or lots of // overwrites/deletions). score = v->files_[level].size() / static_cast<double>(config::kL0_CompactionTrigger); } else { // Compute the ratio of current size to size limit. const uint64_t level_bytes = TotalFileSize(v->files_[level]); score = static_cast<double>(level_bytes) / MaxBytesForLevel(level); } if (score > best_score) { best_level = level; best_score = score; } } v->compaction_level_ = best_level; v->compaction_score_ = best_score; }
注意,这里同时预计算了进行compaction的最佳level.
确认需要启动compaction之后,调用util文件夹下env_posix.cc文件中的PosixEnv::Schedule函数启动Compact过程.
void PosixEnv::Schedule(void (*function)(void*), void* arg) { PthreadCall("lock", pthread_mutex_lock(&mu_)); // Start background thread if necessary if (!started_bgthread_) { started_bgthread_ = true; PthreadCall( "create thread", pthread_create(&bgthread_, NULL, &PosixEnv::BGThreadWrapper, this)); } // If the queue is currently empty, the background thread may currently be // waiting. if (queue_.empty()) { PthreadCall("signal", pthread_cond_signal(&bgsignal_)); } // Add to priority queue queue_.push_back(BGItem()); queue_.back().function = function; queue_.back().arg = arg; PthreadCall("unlock", pthread_mutex_unlock(&mu_)); }
如果没有后台线程,则创建后台线程,否则新建一个后台执行任务BGItem压入后台线程任务队列,然后调用PosixEnv::BGThreadWrapper唤醒后台线程:
static void* BGThreadWrapper(void* arg) { reinterpret_cast<PosixEnv*>(arg)->BGThread(); return NULL; }
BGThreadWrapper调用PosixEnv::BGThread,不断地从后台任务队列中拿到任务,然后执行任务
void PosixEnv::BGThread() { while (true) { // Wait until there is an item that is ready to run PthreadCall("lock", pthread_mutex_lock(&mu_)); while (queue_.empty()) { PthreadCall("wait", pthread_cond_wait(&bgsignal_, &mu_)); } void (*function)(void*) = queue_.front().function; void* arg = queue_.front().arg; queue_.pop_front(); PthreadCall("unlock", pthread_mutex_unlock(&mu_)); (*function)(arg); } }
回到DBImpl::MaybeScheduleCompaction,方便理解起见这里再重复一遍源码
void DBImpl::MaybeScheduleCompaction() { mutex_.AssertHeld(); if (bg_compaction_scheduled_) { // Already scheduled } else if (shutting_down_.Acquire_Load()) { // DB is being deleted; no more background compactions } else if (!bg_error_.ok()) { // Already got an error; no more changes } else if (imm_ == NULL && manual_compaction_ == NULL && !versions_->NeedsCompaction()) { // No work to be done } else { bg_compaction_scheduled_ = true; env_->Schedule(&DBImpl::BGWork, this); //新建后台任务并进行调度 } }
之前分析了env_->Schedule进行的调度过程,现在来分析实际进行后台任务的DBImpl::BGWork.DBImpl::BGWork在db文件夹下db_impl.cc文件中.
void DBImpl::BGWork(void* db) { reinterpret_cast<DBImpl*>(db)->BackgroundCall(); }
DBImpl::BGWork调用DBImpl::BackgroundCall(),合并完成后可能导致有的level的文件数过多,因此会再次调用MaybeScheduleCompaction()判断是否需要继续进行合并.
void DBImpl::BackgroundCall() { MutexLock l(&mutex_); assert(bg_compaction_scheduled_); if (shutting_down_.Acquire_Load()) { // No more background work when shutting down. } else if (!bg_error_.ok()) { // No more background work after a background error. } else { BackgroundCompaction(); } bg_compaction_scheduled_ = false; // Previous compaction may have produced too many files in a level, // so reschedule another compaction if needed. MaybeScheduleCompaction(); bg_cv_.SignalAll(); }
DBImpl::BackgroundCall()调用 BackgroundCompaction(),在BackgroundCompaction()中分别完成三种不同的Compaction:对Memtable进行合并、 trivial Compaction(直接将文件移动到下一层)以及一般的合并,调用DoCompactionWork()实现.
void DBImpl::BackgroundCompaction() { mutex_.AssertHeld(); if (imm_ != NULL) { CompactMemTable();//1、对Memtable进行合并 return; } Compaction* c; bool is_manual = (manual_compaction_ != NULL);//manual_compaction默认为NULL,则is_manual默认为false InternalKey manual_end; if (is_manual) { //取得手动compaction对象 ManualCompaction* m = manual_compaction_; c = versions_->CompactRange(m->level, m->begin, m->end); m->done = (c == NULL); if (c != NULL) { manual_end = c->input(0, c->num_input_files(0) - 1)->largest; } Log(options_.info_log, "Manual compaction at level-%d from %s .. %s; will stop at %s\n", m->level, (m->begin ? m->begin->DebugString().c_str() : "(begin)"), (m->end ? m->end->DebugString().c_str() : "(end)"), (m->done ? "(end)" : manual_end.DebugString().c_str())); } else { //取得自动compaction对象 c = versions_->PickCompaction(); } Status status; if (c == NULL) { // Nothing to do } else if (!is_manual && c->IsTrivialMove()) {//2、IsTrivialMove 返回 True,trivial Compaction,则直接将文件移入 level + 1 层即可 // Move file to next level assert(c->num_input_files(0) == 1); FileMetaData* f = c->input(0, 0); c->edit()->DeleteFile(c->level(), f->number); c->edit()->AddFile(c->level() + 1, f->number, f->file_size, f->smallest, f->largest); status = versions_->LogAndApply(c->edit(), &mutex_); if (!status.ok()) { RecordBackgroundError(status); } VersionSet::LevelSummaryStorage tmp; Log(options_.info_log, "Moved #%lld to level-%d %lld bytes %s: %s\n", static_cast<unsigned long long>(f->number), c->level() + 1, static_cast<unsigned long long>(f->file_size), status.ToString().c_str(), versions_->LevelSummary(&tmp)); } else { //3、一般的合并 CompactionState* compact = new CompactionState(c); status = DoCompactionWork(compact); //进行compaction if (!status.ok()) { RecordBackgroundError(status); } CleanupCompaction(compact); c->ReleaseInputs(); // input的文件引用计数减少1 DeleteObsoleteFiles(); //删除无用文件 } delete c; if (status.ok()) { // Done } else if (shutting_down_.Acquire_Load()) { // Ignore compaction errors found during shutting down } else { Log(options_.info_log, "Compaction error: %s", status.ToString().c_str()); } if (is_manual) { ManualCompaction* m = manual_compaction_; //标记手动compaction任务完成 if (!status.ok()) { m->done = true; } if (!m->done) { // We only compacted part of the requested range. Update *m // to the range that is left to be compacted. m->tmp_storage = manual_end; m->begin = &m->tmp_storage; } manual_compaction_ = NULL; } }
首行mutex_.AssertHeld(),Mutex的AssertHeld函数实现默认为空,在很多函数的实现内有调用,其作用如下:
As you have observed it does nothing in the default implementation. The function seems to be a placeholder for checking whether a particular thread holds a mutex and optionally abort if it doesn’t. This would be equivalent to the normal asserts we use for variables but applied on mutexes.
I think the reason it is not implemented yet is we don’t have an equivalent light weight function to assert whether a thread holds a lock in pthread_mutex_t used in the default implementation. Some platforms which has that capability could fill this implementation as part of porting process. Searching online I did find some implementation for this function in the windows port of leveldb. I can see one way to implement it using a wrapper class over pthread_mutex_t and setting some sort of a thread id variable to indicate which thread(s) currently holds the mutex, but it will have to be carefully implemented given the race conditions that can arise.
Memtable的合并
Compaction首先检查imm_,及时将已写满的memtable写入磁盘sstable文件,对Memtable的合并,调用DBImpl::CompactMemTable()完成:
void DBImpl::CompactMemTable() { mutex_.AssertHeld(); assert(imm_ != NULL);//imm_不能为空 VersionEdit edit; Version* base = versions_->current(); base->Ref(); Status s = WriteLevel0Table(imm_, &edit, base);//将Memtable转化为.sst文件,写入level0 sst table,并写入到edit中 base->Unref(); if (s.ok()) { edit.SetPrevLogNumber(0); edit.SetLogNumber(logfile_number_); // Earlier logs no longer needed s = versions_->LogAndApply(&edit, &mutex_);//应用edit中记录的变化,来生成新的版本 } if (s.ok()) { // Commit to the new state imm_->Unref(); imm_ = NULL; has_imm_.Release_Store(NULL); DeleteObsoleteFiles(); } else { RecordBackgroundError(s); } }
其中CompactMemTable()主要调用了两个函数:WriteLevel0Table()和versions_->LogAndApply()
CompactMemTable()首先调用WriteLevel0Table(),源码内容如下:
Status DBImpl::WriteLevel0Table(MemTable* mem, VersionEdit* edit, Version* base) { mutex_.AssertHeld(); FileMetaData meta; meta.number = versions_->NewFileNumber();//获取新生成的.sst文件的编号 pending_outputs_.insert(meta.number); Iterator* iter = mem->NewIterator();//用于遍历Memtable中的数据 Status s; { mutex_.Unlock(); s = BuildTable(dbname_, env_, options_, table_cache_, iter, &meta);//创建.sst文件,并将其相关信息记录在meta中 mutex_.Lock(); } delete iter; //iter用完之后一定要删除 pending_outputs_.erase(meta.number); int level = 0; if (s.ok() && meta.file_size > 0) { const Slice min_user_key = meta.smallest.user_key(); const Slice max_user_key = meta.largest.user_key(); if (base != NULL) { level = base->PickLevelForMemTableOutput(min_user_key, max_user_key);//为合并的输出文件选择合适的level } edit->AddFile(level, meta.number, meta.file_size,meta.smallest, meta.largest);//将生成的.sst文件加入到该level } return s; }
WriteLevel0Table()首先调用BuildTable()将Immutable Memtable中所有的数据写入到一个.sst文件中,并将.sst文件的信息(文件编号,Key值范围,文件大小)记录到变量meta中.由于Memtable是基于Skiplist的,是一个有序表,因此在写入.sst文件时,Key值也是从小到大来排列的.可以发现,将Memtable中的数据转换为SSTable时,是将所有记录都写入SSTable的,要删除的记录也一样.删除操作会在更高level的Compaction中完成.因此level 0中可能会存在Key值相同的记录.
Status BuildTable(const std::string& dbname, Env* env, const Options& options, TableCache* table_cache, Iterator* iter, FileMetaData* meta) { Status s; meta->file_size = 0; iter->SeekToFirst(); std::string fname = TableFileName(dbname, meta->number);//获得新建表名字 if (iter->Valid()) { WritableFile* file; s = env->NewWritableFile(fname, &file); //建立新的表文件,后续写入数据 if (!s.ok()) { return s; } TableBuilder* builder = new TableBuilder(options, file); //建立TableBuilder meta->smallest.DecodeFrom(iter->key()); for (; iter->Valid(); iter->Next()) { //将key/value对加入builder Slice key = iter->key(); meta->largest.DecodeFrom(key); builder->Add(key, iter->value()); } // Finish and check for builder errors s = builder->Finish(); //构建indexhandler,metahandler,写入文件 if (s.ok()) { meta->file_size = builder->FileSize(); assert(meta->file_size > 0); } delete builder; // Finish and check for file errors if (s.ok()) { s = file->Sync(); //写入文件 } if (s.ok()) { s = file->Close(); } delete file; file = NULL; if (s.ok()) { // Verify that the table is usable Iterator* it = table_cache->NewIterator(ReadOptions(), meta->number, meta->file_size); //将表结构加入表缓存 s = it->status(); delete it; } } // Check for input iterator errors if (!iter->status().ok()) { s = iter->status(); } if (s.ok() && meta->file_size > 0) { // Keep it } else { env->DeleteFile(fname); } return s; }
该函数利用iter向TableBuilder中加入key/value对,然后写入文件并同步,将新生成的Table结构加入tablecache以备后用.
table_builder文件在table文件夹下,其中TableBuilder::Add函数流程如下:
void TableBuilder::Add(const Slice& key, const Slice& value) { Rep* r = rep_; assert(!r->closed); if (!ok()) return; if (r->num_entries > 0) { assert(r->options.comparator->Compare(key, Slice(r->last_key)) > 0); } if (r->pending_index_entry) {//新的block开始 assert(r->data_block.empty()); r->options.comparator->FindShortestSeparator(&r->last_key, key); std::string handle_encoding; r->pending_handle.EncodeTo(&handle_encoding); r->index_block.Add(r->last_key, Slice(handle_encoding)); r->pending_index_entry = false; } //计算filter if (r->filter_block != NULL) { r->filter_block->AddKey(key); } //加入blockbuilder r->last_key.assign(key.data(), key.size()); r->num_entries++; r->data_block.Add(key, value); // block大于配置的尺寸(默认为4k)则结束该block,输出后开启新的Block。 const size_t estimated_block_size = r->data_block.CurrentSizeEstimate(); if (estimated_block_size >= r->options.block_size) { Flush(); } }
将Block结构写入文件的TableBuilder::WriteBlock函数流程如下:
void TableBuilder::WriteBlock(BlockBuilder* block, BlockHandle* handle) { // File format contains a sequence of blocks where each block has: // block_data: uint8[n] // type: uint8 // crc: uint32 assert(ok()); Rep* r = rep_; Slice raw = block->Finish(); //取得block格式化数据 Slice block_contents; //获取是否压缩配置选项 CompressionType type = r->options.compression; // TODO(postrelease): Support more compression options: zlib? switch (type) { case kNoCompression: block_contents = raw; break; case kSnappyCompression: { std::string* compressed = &r->compressed_output; if (port::Snappy_Compress(raw.data(), raw.size(), compressed) && compressed->size() < raw.size() - (raw.size() / 8u)) { block_contents = *compressed; } else { // Snappy not supported, or compressed less than 12.5%, so just // store uncompressed form block_contents = raw; type = kNoCompression; } break; } } //进行压缩后,然后写入文件,blockdata+type+crc32 WriteRawBlock(block_contents, type, handle); r->compressed_output.clear(); block->Reset(); }
而TableBuilder::Finish的函数定义如下:
Status TableBuilder::Finish() { Rep* r = rep_; Flush();//将block数据写入,可能不是满的block assert(!r->closed); r->closed = true; BlockHandle filter_block_handle, metaindex_block_handle, index_block_handle; // Write filter block if (ok() && r->filter_block != NULL) { WriteRawBlock(r->filter_block->Finish(), kNoCompression, &filter_block_handle); } // Write metaindex block if (ok()) { BlockBuilder meta_index_block(&r->options); if (r->filter_block != NULL) { // Add mapping from "filter.Name" to location of filter data std::string key = "filter."; key.append(r->options.filter_policy->Name()); std::string handle_encoding; filter_block_handle.EncodeTo(&handle_encoding); meta_index_block.Add(key, handle_encoding); } // TODO(postrelease): Add stats and other meta blocks WriteBlock(&meta_index_block, &metaindex_block_handle); } // Write index block if (ok()) { if (r->pending_index_entry) { r->options.comparator->FindShortSuccessor(&r->last_key); std::string handle_encoding; r->pending_handle.EncodeTo(&handle_encoding); r->index_block.Add(r->last_key, Slice(handle_encoding)); r->pending_index_entry = false; } WriteBlock(&r->index_block, &index_block_handle); } // Write footer if (ok()) { Footer footer; footer.set_metaindex_handle(metaindex_block_handle); footer.set_index_handle(index_block_handle); std::string footer_encoding; footer.EncodeTo(&footer_encoding); r->status = r->file->Append(footer_encoding); if (r->status.ok()) { r->offset += footer_encoding.size(); } } return r->status; }
以上代码中调用的flush源码内容如下:
void TableBuilder::Flush() { Rep* r = rep_; assert(!r->closed); if (!ok()) return; if (r->data_block.empty()) return; assert(!r->pending_index_entry); WriteBlock(&r->data_block, &r->pending_handle); if (ok()) { r->pending_index_entry = true; r->status = r->file->Flush(); } if (r->filter_block != NULL) { r->filter_block->StartBlock(r->offset); } }
然后WriteLevel0Table()调用PickLevelForMemTableOutput()为Memtable合并的输出文件选择合适的level,并调用edit->AddFile()将生成的.sst文件加入到该level中.
WriteLevel0Table()结束后,CompactMemTable()调用db文件夹下version_set.cc文件中的versions_->LogAndApply()基于当前版本和更改edit来得到一个新版本.之后会对versions_->LogAndApply()进行分析.
Trivial Compaction
由之前的分析可知,is_manual默认为false,会调用PickCompaction()来选出要进行合并的level和相应的输入文件.当c->IsTrivialMove()满足时,则直接将文件移动到下一level.
c = versions_->PickCompaction(); Status status; if (c == NULL) { // Nothing to do } else if (!is_manual && c->IsTrivialMove()) { // Move file to next level assert(c->num_input_files(0) == 1); FileMetaData* f = c->input(0, 0); c->edit()->DeleteFile(c->level(), f->number); //将文件从该层删除 c->edit()->AddFile(c->level() + 1, f->number, f->file_size, //将该文件加入到下一level f->smallest, f->largest); status = versions_->LogAndApply(c->edit(), &mutex_); //应用更改,创建新的Version }
首先调用db文件夹下version_set.cc文件中的VersionSet::PickCompaction()为接下来的Compaction操作准备输入数据,由之前对Compaction的数据结构分析可知,Compaction操作有两种触发方式:某一level的文件数太多和某一文件的查找次数超过允许值,在进行合并时,将优先考虑文件数过多的情况.
Compaction* VersionSet::PickCompaction() { Compaction* c; int level; const bool size_compaction = (current_->compaction_score_ >= 1);//文件数过多 const bool seek_compaction = (current_->file_to_compact_ != NULL);//某一文件的查找次数太多 if (size_compaction) {//文件数太多优先考虑 level = current_->compaction_level_; //要进行Compaction的level c = new Compaction(level); //每一层有一个compact_pointer,用于记录compaction key,这样可以进行循环compaction for (size_t i = 0; i < current_->files_[level].size(); i++) { //从待合并的level中选择合适的文件完成合并操作 FileMetaData* f = current_->files_[level][i]; //level层中的第i个文件 if (compact_pointer_[level].empty() || //compact_pointer_中记录的是下次合并的起始Key值,为空时都可以进行合并 icmp_.Compare(f->largest.Encode(), compact_pointer_[level]) > 0) { //或者f的最大Key值大于起始值 c->inputs_[0].push_back(f);//则该文件可以参与合并,将其加入到level输入文件中 break; } } if (c->inputs_[0].empty()) { //若level输入为空,则将level的第一个文件加入到输入中 c->inputs_[0].push_back(current_->files_[level][0]); } } else if (seek_compaction) {//然后考虑查找次数过多的情况 level = current_->file_to_compact_level_; c = new Compaction(level); c->inputs_[0].push_back(current_->file_to_compact_);//将待合并的文件作为level层的输入 } else { return NULL; } c->input_version_ = current_; c->input_version_->Ref(); //level 0中的Key值是可以重复的,因此Key值范围可能相互覆盖,把所有重叠都找出来,一起做compaction if (level == 0) { InternalKey smallest, largest; GetRange(c->inputs_[0], &smallest, &largest);//待合并的level层的文件的Key值范围 current_->GetOverlappingInputs(0, &smallest, &largest, &c->inputs_[0]); assert(!c->inputs_[0].empty()); } SetupOtherInputs(c);//获取待合并的level+1层的输入 return c; }
然后判断是否为trivial Compaction,当为trivial Compaction时,只需要简单的将level层的文件移动到level +1 层即可
bool Compaction::IsTrivialMove() const { return (num_input_files(0) == 1 && //level层只有1个文件 num_input_files(1) == 0 && //level+1层没有文件 TotalFileSize(grandparents_) <= kMaxGrandParentOverlapBytes);//level+2层文件总大小不超过最大覆盖范围,否则会导致后面的merge需要很大的开销 }
最终完成完成Compaction操作
c->edit()->DeleteFile(c->level(), f->number); c->edit()->AddFile(c->level() + 1, f->number, f->file_size,f->smallest, f->largest); status = versions_->LogAndApply(c->edit(), &mutex_);
一般的合并
一般的合并调用DBImpl::DoCompactionWork()完成,compact是调用VersionSet::PickCompacttion()得到的,与之前的trivial Compaction相同.不同level之间,可能存在Key值相同的记录,但是记录的seq不同.由之前的分析可知,最新的数据存放在较低的level中,其对应的seq也一定比level+1中的记录的seq要大,因此当出现相同Key值的记录时,只需要记录第一条记录,后面的都可以丢弃.level 0中也可能存在Key值相同的数据,其后面的seq也不同.数据越新,其对应的seq越大,且记录在level 0中的记录是按照user_key递增,seq递减的方式存储的,则相同user_key对应的记录是聚集在一起的,且按照seq递减的方式存放的.在更高层的Compaction时,只需要处理第一条出现的user_key相同的记录即可,后面的相同user_key的记录都可以丢弃.因此合并后的level +1层的文件中不会存在Key值相同的记录.删除记录的操作也会在此时完成,删除数据的记录会被丢弃,而不会被写入到更高level的文件中.
Status DBImpl::DoCompactionWork(CompactionState* compact) { if (snapshots_.empty()) { compact->smallest_snapshot = versions_->LastSequence(); } else { compact->smallest_snapshot = snapshots_.oldest()->number_; } mutex_.Unlock(); //生成iterator:遍历要compaction的数据 Iterator* input = versions_->MakeInputIterator(compact->compaction);//用于遍历待合并的每一个文件 input->SeekToFirst(); Status status; ParsedInternalKey ikey; std::string current_user_key; bool has_current_user_key = false; SequenceNumber last_sequence_for_key = kMaxSequenceNumber; for (; input->Valid() && !shutting_down_.Acquire_Load(); ) { if (has_imm_.NoBarrier_Load() != NULL) { //immutable memtable的优先级最高 mutex_.Lock(); if (imm_ != NULL) { //当imm_非空时,合并Memtable CompactMemTable(); bg_cv_.SignalAll(); // Wakeup MakeRoomForWrite() if necessary } mutex_.Unlock(); } Slice key = input->key(); if (compact->compaction->ShouldStopBefore(key) && //是否需要停止Compaction,中途输出compaction的结果,避免compaction结果和level N+2 files有过多的重叠 compact->builder != NULL) { status = FinishCompactionOutputFile(compact, input); } bool drop = false; if (!ParseInternalKey(key, &ikey)) { current_user_key.clear(); has_current_user_key = false; last_sequence_for_key = kMaxSequenceNumber; } else { if (!has_current_user_key || //获取当前的user_key和sequence user_comparator()->Compare(ikey.user_key, Slice(current_user_key)) != 0) { //可能存在Key值相同但seq不同的记录 // 此时是这个Key第一次出现 current_user_key.assign(ikey.user_key.data(), ikey.user_key.size()); has_current_user_key = true; last_sequence_for_key = kMaxSequenceNumber;//则将其seq设为最大值,表示第一次出现 } if (last_sequence_for_key <= compact->smallest_snapshot) {//表示key已经出现过,否则seq应为KMaxSequenceNumber drop = true; // (A) //之前已经存在Key值相同的记录,丢弃 } else if (ikey.type == kTypeDeletion && //要删除该记录 ikey.sequence <= compact->smallest_snapshot && //记录的序号比数据库之前的最小序号还小 compact->compaction->IsBaseLevelForKey(ikey.user_key)) { //高的level中没有数据 drop = true; //此时要丢弃该记录 } last_sequence_for_key = ikey.sequence;//上次出现的记录对应的sequence,用于判断后面出现相同Key值的情况 } if (!drop) { //如果不需要丢弃该记录 if (compact->builder == NULL) { status = OpenCompactionOutputFile(compact);//若需要,则创建一个.sst文件,用于存放合并后的数据 } if (compact->builder->NumEntries() == 0) { compact->current_output()->smallest.DecodeFrom(key); } compact->current_output()->largest.DecodeFrom(key); compact->builder->Add(key, input->value());//将记录写入.sst文件 if (compact->builder->FileSize() >= compact->compaction->MaxOutputFileSize()) { //当.sst文件超过最大值时 status = FinishCompactionOutputFile(compact, input);//完成Compaction输出文件 } } input->Next(); //处理下一个文件 } if (status.ok() && compact->builder != NULL) { status = FinishCompactionOutputFile(compact, input); } if (status.ok()) { status = input->status(); } delete input; input = NULL; //更新compaction的一些统计数据 CompactionStats stats; stats.micros = env_->NowMicros() - start_micros - imm_micros; for (int which = 0; which < 2; which++) { for (int i = 0; i < compact->compaction->num_input_files(which); i++) { stats.bytes_read += compact->compaction->input(which, i)->file_size; } } for (size_t i = 0; i < compact->outputs.size(); i++) { stats.bytes_written += compact->outputs[i].file_size; } mutex_.Lock(); stats_[compact->compaction->level() + 1].Add(stats); if (status.ok()) { status = InstallCompactionResults(compact);//完成合并 } if (!status.ok()) { RecordBackgroundError(status); } VersionSet::LevelSummaryStorage tmp; Log(options_.info_log, "compacted to: %s", versions_->LevelSummary(&tmp)); return status; }
首先将可以留下的记录写入到.sst文件中,并将相关信息保存在变量compact中,然后调用InstallCompactionResults()将所做的改动加入到VersionEdit中,再调用LogAndApply()来得到新的版本.
Status DBImpl::InstallCompactionResults(CompactionState* compact) { mutex_.AssertHeld(); Log(options_.info_log, "Compacted %d@%d + %d@%d files => %lld bytes", compact->compaction->num_input_files(0), compact->compaction->level(), compact->compaction->num_input_files(1), compact->compaction->level() + 1, static_cast<long long>(compact->total_bytes)); // Add compaction outputs compact->compaction->AddInputDeletions(compact->compaction->edit()); const int level = compact->compaction->level(); for (size_t i = 0; i < compact->outputs.size(); i++) { const CompactionState::Output& out = compact->outputs[i]; compact->compaction->edit()->AddFile( level + 1, out.number, out.file_size, out.smallest, out.largest); } return versions_->LogAndApply(compact->compaction->edit(), &mutex_); }
LogAndApply()
在上面三种不同的Compaction操作中,最终当对当前版本的更改VersionEdit全部完成后,都会调用VersionSet::LogAndApply()来应用更改,创建新版本.edit中保存了level和level+1层要删除和增加的文件.
Status VersionSet::LogAndApply(VersionEdit* edit, port::Mutex* mu) { Version* v = new Version(this); //创建一个新Version { Builder builder(this, current_);//基于当前Version创建一个builder变量 builder.Apply(edit);//将edit中记录的要增加、删除的文件加入到builder类中 builder.SaveTo(v);//然后将edit中的记录保存到新创建的Version中,这样就得到了一个新的版本 } Finalize(v);//根据各层文件数来判断是否还需要进行Compaction std::string new_manifest_file; Status s; if (descriptor_log_ == NULL) { //只会在第一次调用时进入 assert(descriptor_file_ == NULL); new_manifest_file = DescriptorFileName(dbname_, manifest_file_number_);//创建一个新的Manifest文件 edit->SetNextFile(next_file_number_); s = env_->NewWritableFile(new_manifest_file, &descriptor_file_); if (s.ok()) { descriptor_log_ = new log::Writer(descriptor_file_); s = WriteSnapshot(descriptor_log_);//快照,系统开始时完整记录数据库的所有信息 } } { mu->Unlock(); if (s.ok()) { std::string record; edit->EncodeTo(&record); s = descriptor_log_->AddRecord(record);//将数据库的变化记录到Manifest文件中 if (s.ok()) { s = descriptor_file_->Sync(); } } if (s.ok() && !new_manifest_file.empty()) { s = SetCurrentFile(env_, dbname_, manifest_file_number_); } mu->Lock(); } if (s.ok()) { AppendVersion(v); //将新得到的Version插入到所有Version形成的双向链表的尾部 log_number_ = edit->log_number_; prev_log_number_ = edit->prev_log_number_; } } return s; }
为了重启之后能恢复数据库之前的状态,就需要将数据库的历史变化信息记录下来,这些信息都是记录在Manifest文件中的.为了节省空间和时间,leveldb采用的是在系统开始完整的所有数据库的信息(WriteSnapShot()),以后则只记录数据库的变化,即VersionEdit中的信息(descriptor_log_->AddRecord()).恢复时,只需要根据Manifest中的信息就可以一步步的恢复到上次的状态.
VersionSet::LogAndApply首先创建一个新的Version,然后调用builder.Apply(edit)将edit中所有要删除、增加的文件编号记录下来,其源码如下:
// Apply all of the edits in *edit to the current state. void Apply(VersionEdit* edit) { // 更新每一层下次合并的起始Key值 for (size_t i = 0; i < edit->compact_pointers_.size(); i++) { const int level = edit->compact_pointers_[i].first; vset_->compact_pointer_[level] = edit->compact_pointers_[i].second.Encode().ToString(); } //将所有要删除的文件加入到levels_[level].deleted_files变量中 const VersionEdit::DeletedFileSet& del = edit->deleted_files_; for (VersionEdit::DeletedFileSet::const_iterator iter = del.begin(); iter != del.end();++iter) { const int level = iter->first; const uint64_t number = iter->second; levels_[level].deleted_files.insert(number); } // 将所有新增加的文件加入到levels_[level].added_files中 for (size_t i = 0; i < edit->new_files_.size(); i++) { const int level = edit->new_files_[i].first; FileMetaData* f = new FileMetaData(edit->new_files_[i].second); f->refs = 1; f->allowed_seeks = (f->file_size / 16384); if (f->allowed_seeks < 100) f->allowed_seeks = 100; levels_[level].deleted_files.erase(f->number); levels_[level].added_files->insert(f); } }
然后VersionSet::LogAndApply再调用builder.SaveTo(v)将更改保存到新的Version中,其源码如下:
void SaveTo(Version* v) { BySmallestKey cmp; cmp.internal_comparator = &vset_->icmp_; for (int level = 0; level < config::kNumLevels; level++) { const std::vector<FileMetaData*>& base_files = base_->files_[level];//当前Version中原有的各个level的.sst文件 std::vector<FileMetaData*>::const_iterator base_iter = base_files.begin(); std::vector<FileMetaData*>::const_iterator base_end = base_files.end(); const FileSet* added = levels_[level].added_files;//对应level新增加的文件 v->files_[level].reserve(base_files.size() + added->size()); for (FileSet::const_iterator added_iter = added->begin(); added_iter != added->end();++added_iter) { // 将原有文件中编号比added小的加入到新的Version for (std::vector<FileMetaData*>::const_iterator bpos = std::upper_bound(base_iter, base_end, *added_iter, cmp); base_iter != bpos;++base_iter) { MaybeAddFile(v, level, *base_iter); } MaybeAddFile(v, level, *added_iter);//再将新增的文件依次加入到新的Version } for (; base_iter != base_end; ++base_iter) { MaybeAddFile(v, level, *base_iter);//再将原有文件中剩余的部分加入到新的Version } } }
bpos = std::upper_bound(base_iter,base_end,*added_iter,cmp); // 返回base_iter到base_end之间,第一个大于*added_iter的iter.假设原有文件的编号为1、3、4、6、8,新增文件的编号为2、5、7,则第一次循环时,bpos为3对应的迭代器,因此base_iter只遍历一个元素,即将编号1加入到新的Version中.总体对新增文件来说,就是首先加入base中编号比它小的,然后再将其加入,然后再继续比那里下一个新增文件,因此最终得到的文件编号顺序是 1、2、3、4、5、6、7、8,即每一层的.sst文件都是按照编号从小到大排列的.这样就得到了新的Version的每一层的所有文件.
参考文献:
1.http://blog.csdn.net/u012658346/article/details/45787233
2.http://blog.csdn.net/u012658346/article/details/45788939
3.http://blog.csdn.net/joeyon1985/article/details/47154249
4.http://www.blogjava.net/sandy/archive/2012/03/15/leveldb6.html
5.http://www.pandademo.com/2016/04/compaction-of-sstable-leveldb-part-1-source-dissect-9/