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rocksdb/include/leveldb/options.h

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// Copyright (c) 2011 The LevelDB Authors. All rights reserved.
// Use of this source code is governed by a BSD-style license that can be
// found in the LICENSE file. See the AUTHORS file for names of contributors.
#ifndef STORAGE_LEVELDB_INCLUDE_OPTIONS_H_
#define STORAGE_LEVELDB_INCLUDE_OPTIONS_H_
#include <stddef.h>
#include <string>
#include <memory>
#include <vector>
#include <stdint.h>
#include "leveldb/slice.h"
#include "leveldb/statistics.h"
namespace leveldb {
class Cache;
class Comparator;
class Env;
class FilterPolicy;
class Logger;
class Snapshot;
using std::shared_ptr;
// DB contents are stored in a set of blocks, each of which holds a
// sequence of key,value pairs. Each block may be compressed before
// being stored in a file. The following enum describes which
// compression method (if any) is used to compress a block.
enum CompressionType {
// NOTE: do not change the values of existing entries, as these are
// part of the persistent format on disk.
kNoCompression = 0x0,
kSnappyCompression = 0x1,
kZlibCompression = 0x2,
kBZip2Compression = 0x3
};
// Compression options for different compression algorithms like Zlib
struct CompressionOptions {
int window_bits;
int level;
int strategy;
CompressionOptions():window_bits(-14),
level(-1),
strategy(0){}
CompressionOptions(int wbits, int lev, int strategy):window_bits(wbits),
level(lev),
strategy(strategy){}
};
// Options to control the behavior of a database (passed to DB::Open)
struct Options {
// -------------------
// Parameters that affect behavior
// Comparator used to define the order of keys in the table.
// Default: a comparator that uses lexicographic byte-wise ordering
//
// REQUIRES: The client must ensure that the comparator supplied
// here has the same name and orders keys *exactly* the same as the
// comparator provided to previous open calls on the same DB.
const Comparator* comparator;
// If true, the database will be created if it is missing.
// Default: false
bool create_if_missing;
// If true, an error is raised if the database already exists.
// Default: false
bool error_if_exists;
// If true, the implementation will do aggressive checking of the
// data it is processing and will stop early if it detects any
// errors. This may have unforeseen ramifications: for example, a
// corruption of one DB entry may cause a large number of entries to
// become unreadable or for the entire DB to become unopenable.
// Default: false
bool paranoid_checks;
// Use the specified object to interact with the environment,
// e.g. to read/write files, schedule background work, etc.
// Default: Env::Default()
Env* env;
// Any internal progress/error information generated by the db will
// be written to info_log if it is non-nullptr, or to a file stored
// in the same directory as the DB contents if info_log is nullptr.
// Default: nullptr
shared_ptr<Logger> info_log;
// -------------------
// Parameters that affect performance
// Amount of data to build up in memory (backed by an unsorted log
// on disk) before converting to a sorted on-disk file.
//
// Larger values increase performance, especially during bulk loads.
// Up to max_write_buffer_number write buffers may be held in memory
// at the same time,
// so you may wish to adjust this parameter to control memory usage.
// Also, a larger write buffer will result in a longer recovery time
// the next time the database is opened.
//
// Default: 4MB
size_t write_buffer_size;
// The maximum number of write buffers that are built up in memory.
// The default is 2, so that when 1 write buffer is being flushed to
// storage, new writes can continue to the other write buffer.
// Default: 2
int max_write_buffer_number;
// Number of open files that can be used by the DB. You may need to
// increase this if your database has a large working set (budget
// one open file per 2MB of working set).
//
// Default: 1000
int max_open_files;
// Control over blocks (user data is stored in a set of blocks, and
// a block is the unit of reading from disk).
// If non-NULL use the specified cache for blocks.
// If NULL, leveldb will automatically create and use an 8MB internal cache.
// Default: nullptr
shared_ptr<Cache> block_cache;
// Approximate size of user data packed per block. Note that the
// block size specified here corresponds to uncompressed data. The
// actual size of the unit read from disk may be smaller if
// compression is enabled. This parameter can be changed dynamically.
//
// Default: 4K
size_t block_size;
// Number of keys between restart points for delta encoding of keys.
// This parameter can be changed dynamically. Most clients should
// leave this parameter alone.
//
// Default: 16
int block_restart_interval;
// Compress blocks using the specified compression algorithm. This
// parameter can be changed dynamically.
//
// Default: kSnappyCompression, which gives lightweight but fast
// compression.
//
// Typical speeds of kSnappyCompression on an Intel(R) Core(TM)2 2.4GHz:
// ~200-500MB/s compression
// ~400-800MB/s decompression
// Note that these speeds are significantly faster than most
// persistent storage speeds, and therefore it is typically never
// worth switching to kNoCompression. Even if the input data is
// incompressible, the kSnappyCompression implementation will
// efficiently detect that and will switch to uncompressed mode.
CompressionType compression;
Allow having different compression algorithms on different levels. Summary: The leveldb API is enhanced to support different compression algorithms at different levels. This adds the option min_level_to_compress to db_bench that specifies the minimum level for which compression should be done when compression is enabled. This can be used to disable compression for levels 0 and 1 which are likely to suffer from stalls because of the CPU load for memtable flushes and (L0,L1) compaction. Level 0 is special as it gets frequent memtable flushes. Level 1 is special as it frequently gets all:all file compactions between it and level 0. But all other levels could be the same. For any level N where N > 1, the rate of sequential IO for that level should be the same. The last level is the exception because it might not be full and because files from it are not read to compact with the next larger level. The same amount of time will be spent doing compaction at any level N excluding N=0, 1 or the last level. By this standard all of those levels should use the same compression. The difference is that the loss (using more disk space) from a faster compression algorithm is less significant for N=2 than for N=3. So we might be willing to trade disk space for faster write rates with no compression for L0 and L1, snappy for L2, zlib for L3. Using a faster compression algorithm for the mid levels also allows us to reclaim some cpu without trading off much loss in disk space overhead. Also note that little is to be gained by compressing levels 0 and 1. For a 4-level tree they account for 10% of the data. For a 5-level tree they account for 1% of the data. With compression enabled: * memtable flush rate is ~18MB/second * (L0,L1) compaction rate is ~30MB/second With compression enabled but min_level_to_compress=2 * memtable flush rate is ~320MB/second * (L0,L1) compaction rate is ~560MB/second This practicaly takes the same code from https://reviews.facebook.net/D6225 but makes the leveldb api more general purpose with a few additional lines of code. Test Plan: make check Differential Revision: https://reviews.facebook.net/D6261
12 years ago
// Different levels can have different compression policies. There
// are cases where most lower levels would like to quick compression
// algorithm while the higher levels (which have more data) use
// compression algorithms that have better compression but could
// be slower. This array, if non nullptr, should have an entry for
// each level of the database. This array, if non nullptr, overides the
Allow having different compression algorithms on different levels. Summary: The leveldb API is enhanced to support different compression algorithms at different levels. This adds the option min_level_to_compress to db_bench that specifies the minimum level for which compression should be done when compression is enabled. This can be used to disable compression for levels 0 and 1 which are likely to suffer from stalls because of the CPU load for memtable flushes and (L0,L1) compaction. Level 0 is special as it gets frequent memtable flushes. Level 1 is special as it frequently gets all:all file compactions between it and level 0. But all other levels could be the same. For any level N where N > 1, the rate of sequential IO for that level should be the same. The last level is the exception because it might not be full and because files from it are not read to compact with the next larger level. The same amount of time will be spent doing compaction at any level N excluding N=0, 1 or the last level. By this standard all of those levels should use the same compression. The difference is that the loss (using more disk space) from a faster compression algorithm is less significant for N=2 than for N=3. So we might be willing to trade disk space for faster write rates with no compression for L0 and L1, snappy for L2, zlib for L3. Using a faster compression algorithm for the mid levels also allows us to reclaim some cpu without trading off much loss in disk space overhead. Also note that little is to be gained by compressing levels 0 and 1. For a 4-level tree they account for 10% of the data. For a 5-level tree they account for 1% of the data. With compression enabled: * memtable flush rate is ~18MB/second * (L0,L1) compaction rate is ~30MB/second With compression enabled but min_level_to_compress=2 * memtable flush rate is ~320MB/second * (L0,L1) compaction rate is ~560MB/second This practicaly takes the same code from https://reviews.facebook.net/D6225 but makes the leveldb api more general purpose with a few additional lines of code. Test Plan: make check Differential Revision: https://reviews.facebook.net/D6261
12 years ago
// value specified in the previous field 'compression'. The caller is
// reponsible for allocating memory and initializing the values in it
// before invoking Open(). The caller is responsible for freeing this
// array and it could be freed anytime after the return from Open().
// This could have been a std::vector but that makes the equivalent
Allow having different compression algorithms on different levels. Summary: The leveldb API is enhanced to support different compression algorithms at different levels. This adds the option min_level_to_compress to db_bench that specifies the minimum level for which compression should be done when compression is enabled. This can be used to disable compression for levels 0 and 1 which are likely to suffer from stalls because of the CPU load for memtable flushes and (L0,L1) compaction. Level 0 is special as it gets frequent memtable flushes. Level 1 is special as it frequently gets all:all file compactions between it and level 0. But all other levels could be the same. For any level N where N > 1, the rate of sequential IO for that level should be the same. The last level is the exception because it might not be full and because files from it are not read to compact with the next larger level. The same amount of time will be spent doing compaction at any level N excluding N=0, 1 or the last level. By this standard all of those levels should use the same compression. The difference is that the loss (using more disk space) from a faster compression algorithm is less significant for N=2 than for N=3. So we might be willing to trade disk space for faster write rates with no compression for L0 and L1, snappy for L2, zlib for L3. Using a faster compression algorithm for the mid levels also allows us to reclaim some cpu without trading off much loss in disk space overhead. Also note that little is to be gained by compressing levels 0 and 1. For a 4-level tree they account for 10% of the data. For a 5-level tree they account for 1% of the data. With compression enabled: * memtable flush rate is ~18MB/second * (L0,L1) compaction rate is ~30MB/second With compression enabled but min_level_to_compress=2 * memtable flush rate is ~320MB/second * (L0,L1) compaction rate is ~560MB/second This practicaly takes the same code from https://reviews.facebook.net/D6225 but makes the leveldb api more general purpose with a few additional lines of code. Test Plan: make check Differential Revision: https://reviews.facebook.net/D6261
12 years ago
// java/C api hard to construct.
std::vector<CompressionType> compression_per_level;
Allow having different compression algorithms on different levels. Summary: The leveldb API is enhanced to support different compression algorithms at different levels. This adds the option min_level_to_compress to db_bench that specifies the minimum level for which compression should be done when compression is enabled. This can be used to disable compression for levels 0 and 1 which are likely to suffer from stalls because of the CPU load for memtable flushes and (L0,L1) compaction. Level 0 is special as it gets frequent memtable flushes. Level 1 is special as it frequently gets all:all file compactions between it and level 0. But all other levels could be the same. For any level N where N > 1, the rate of sequential IO for that level should be the same. The last level is the exception because it might not be full and because files from it are not read to compact with the next larger level. The same amount of time will be spent doing compaction at any level N excluding N=0, 1 or the last level. By this standard all of those levels should use the same compression. The difference is that the loss (using more disk space) from a faster compression algorithm is less significant for N=2 than for N=3. So we might be willing to trade disk space for faster write rates with no compression for L0 and L1, snappy for L2, zlib for L3. Using a faster compression algorithm for the mid levels also allows us to reclaim some cpu without trading off much loss in disk space overhead. Also note that little is to be gained by compressing levels 0 and 1. For a 4-level tree they account for 10% of the data. For a 5-level tree they account for 1% of the data. With compression enabled: * memtable flush rate is ~18MB/second * (L0,L1) compaction rate is ~30MB/second With compression enabled but min_level_to_compress=2 * memtable flush rate is ~320MB/second * (L0,L1) compaction rate is ~560MB/second This practicaly takes the same code from https://reviews.facebook.net/D6225 but makes the leveldb api more general purpose with a few additional lines of code. Test Plan: make check Differential Revision: https://reviews.facebook.net/D6261
12 years ago
//different options for compression algorithms
CompressionOptions compression_opts;
// If non-nullptr, use the specified filter policy to reduce disk reads.
// Many applications will benefit from passing the result of
// NewBloomFilterPolicy() here.
//
// Default: nullptr
const FilterPolicy* filter_policy;
// Number of levels for this database
int num_levels;
// Number of files to trigger level-0 compaction. A value <0 means that
// level-0 compaction will not be triggered by number of files at all.
int level0_file_num_compaction_trigger;
// Soft limit on number of level-0 files. We slow down writes at this point.
// A value <0 means that no writing slow down will be triggered by number
// of files in level-0.
int level0_slowdown_writes_trigger;
// Maximum number of level-0 files. We stop writes at this point.
int level0_stop_writes_trigger;
// Maximum level to which a new compacted memtable is pushed if it
// does not create overlap. We try to push to level 2 to avoid the
// relatively expensive level 0=>1 compactions and to avoid some
// expensive manifest file operations. We do not push all the way to
// the largest level since that can generate a lot of wasted disk
// space if the same key space is being repeatedly overwritten.
int max_mem_compaction_level;
// Target file size for compaction.
// target_file_size_base is per-file size for level-1.
// Target file size for level L can be calculated by
// target_file_size_base * (target_file_size_multiplier ^ (L-1))
// For example, if target_file_size_base is 2MB and
// target_file_size_multiplier is 10, then each file on level-1 will
// be 2MB, and each file on level 2 will be 20MB,
// and each file on level-3 will be 200MB.
// by default target_file_size_base is 2MB.
int target_file_size_base;
// by default target_file_size_multiplier is 1, which means
// by default files in different levels will have similar size.
int target_file_size_multiplier;
// Control maximum total data size for a level.
// max_bytes_for_level_base is the max total for level-1.
// Maximum number of bytes for level L can be calculated as
// (max_bytes_for_level_base) * (max_bytes_for_level_multiplier ^ (L-1))
// For example, if max_bytes_for_level_base is 20MB, and if
// max_bytes_for_level_multiplier is 10, total data size for level-1
// will be 20MB, total file size for level-2 will be 200MB,
// and total file size for level-3 will be 2GB.
// by default 'max_bytes_for_level_base' is 10MB.
uint64_t max_bytes_for_level_base;
// by default 'max_bytes_for_level_base' is 10.
int max_bytes_for_level_multiplier;
// Maximum number of bytes in all compacted files. We avoid expanding
// the lower level file set of a compaction if it would make the
// total compaction cover more than
// (expanded_compaction_factor * targetFileSizeLevel()) many bytes.
int expanded_compaction_factor;
// Maximum number of bytes in all source files to be compacted in a
// single compaction run. We avoid picking too many files in the
// source level so that we do not exceed the total source bytes
// for compaction to exceed
// (source_compaction_factor * targetFileSizeLevel()) many bytes.
// Default:1, i.e. pick maxfilesize amount of data as the source of
// a compaction.
int source_compaction_factor;
// Control maximum bytes of overlaps in grandparent (i.e., level+2) before we
// stop building a single file in a level->level+1 compaction.
int max_grandparent_overlap_factor;
// If non-null, then we should collect metrics about database operations
// Statistics objects should not be shared between DB instances as
// it does not use any locks to prevent concurrent updates.
shared_ptr<Statistics> statistics;
// If true, then the contents of data files are not synced
// to stable storage. Their contents remain in the OS buffers till the
// OS decides to flush them. This option is good for bulk-loading
// of data. Once the bulk-loading is complete, please issue a
// sync to the OS to flush all dirty buffesrs to stable storage.
// Default: false
bool disableDataSync;
// If true, then every store to stable storage will issue a fsync.
// If false, then every store to stable storage will issue a fdatasync.
// This parameter should be set to true while storing data to
// filesystem like ext3 which can lose files after a reboot.
// Default: false
bool use_fsync;
// This number controls how often a new scribe log about
// db deploy stats is written out.
// -1 indicates no logging at all.
// Default value is 1800 (half an hour).
int db_stats_log_interval;
// This specifies the log dir.
// If it is empty, the log files will be in the same dir as data.
// If it is non empty, the log files will be in the specified dir,
// and the db data dir's absolute path will be used as the log file
// name's prefix.
std::string db_log_dir;
// Disable compaction triggered by seek.
// With bloomfilter and fast storage, a miss on one level
// is very cheap if the file handle is cached in table cache
// (which is true if max_open_files is large).
bool disable_seek_compaction;
// The periodicity when obsolete files get deleted. The default
// value is 0 which means that obsolete files get removed after
// every compaction run.
uint64_t delete_obsolete_files_period_micros;
// Maximum number of concurrent background compactions.
// Default: 1
int max_background_compactions;
// Specify the maximal size of the info log file. If the log file
// is larger than `max_log_file_size`, a new info log file will
// be created.
// If max_log_file_size == 0, all logs will be written to one
// log file.
size_t max_log_file_size;
// Time for the info log file to roll (in seconds).
// If specified with non-zero value, log file will be rolled
// if it has been active longer than `log_file_time_to_roll`.
// Default: 0 (disabled)
size_t log_file_time_to_roll;
// Maximal info log files to be kept.
// Default: 1000
size_t keep_log_file_num;
// Puts are delayed when any level has a compaction score that
// exceeds rate_limit. This is ignored when <= 1.0.
double rate_limit;
// Max time a put will be stalled when rate_limit is enforced
unsigned int rate_limit_delay_milliseconds;
// manifest file is rolled over on reaching this limit.
// The older manifest file be deleted.
// The default value is MAX_INT so that roll-over does not take place.
uint64_t max_manifest_file_size;
// Disable block cache. If this is set to false,
// then no block cache should be used, and the block_cache should
// point to a nullptr object.
bool no_block_cache;
// Number of shards used for table cache.
int table_cache_numshardbits;
// Create an Options object with default values for all fields.
Options();
void Dump(Logger* log) const;
// Set appropriate parameters for bulk loading.
// The reason that this is a function that returns "this" instead of a
// constructor is to enable chaining of multiple similar calls in the future.
//
// All data will be in level 0 without any automatic compaction.
// It's recommended to manually call CompactRange(NULL, NULL) before reading
// from the database, because otherwise the read can be very slow.
Options* PrepareForBulkLoad();
// This method allows an application to modify/delete a key-value at
// the time of compaction. The compaction process invokes this
// method for kv that is being compacted. A return value
// of false indicates that the kv should be preserved in the
// output of this compaction run and a return value of true
// indicates that this key-value should be removed from the
// output of the compaction. The application can inspect
// the existing value of the key and make decision based on it.
// When the value is to be preserved, the application has the option
// to modify the existing_value and pass it back through new_value.
// value_changed needs to be set to true in this case.
// The compaction_filter_args, if specified here, are passed
// back to the invocation of the CompactionFilter.
void* compaction_filter_args;
bool (*CompactionFilter)(void* compaction_filter_args,
int level, const Slice& key,
const Slice& existing_value,
std::string* new_value,
bool* value_changed);
// Disable automatic compactions. Manual compactions can still
// be issued on this database.
bool disable_auto_compactions;
// The number of seconds a WAL(write ahead log) should be kept after it has
// been marked as Not Live. If the value is set. The WAL files are moved to
// the archive direcotory and deleted after the given TTL.
// If set to 0, WAL files are deleted as soon as they are not required by
// the database.
// If set to std::numeric_limits<uint64_t>::max() the WAL files will never be
// deleted.
// Default : 0
uint64_t WAL_ttl_seconds;
// Number of bytes to preallocate (via fallocate) the manifest
// files. Default is 4mb, which is reasonable to reduce random IO
// as well as prevent overallocation for mounts that preallocate
// large amounts of data (such as xfs's allocsize option).
size_t manifest_preallocation_size;
// Purge duplicate/deleted keys when a memtable is flushed to storage.
// Default: true
bool purge_redundant_kvs_while_flush;
// Data being read from file storage may be buffered in the OS
// Default: true
bool allow_os_buffer;
// Reading a single block from a file can cause the OS/FS to start
// readaheads of other blocks from the file. Default: true
bool allow_readahead;
// The reads triggered by compaction allows data to be readahead
// by the OS/FS. This overrides the setting of 'allow_readahead'
// for compaction-reads. Default: true
bool allow_readahead_compactions;
// Allow the OS to mmap file for reading. Default: false
bool allow_mmap_reads;
// Allow the OS to mmap file for writing. Default: true
bool allow_mmap_writes;
// Disable child process inherit open files. Default: true
bool is_fd_close_on_exec;
};
// Options that control read operations
struct ReadOptions {
// If true, all data read from underlying storage will be
// verified against corresponding checksums.
// Default: false
bool verify_checksums;
// Should the data read for this iteration be cached in memory?
// Callers may wish to set this field to false for bulk scans.
// Default: true
bool fill_cache;
// If "snapshot" is non-nullptr, read as of the supplied snapshot
// (which must belong to the DB that is being read and which must
// not have been released). If "snapshot" is nullptr, use an impliicit
// snapshot of the state at the beginning of this read operation.
// Default: nullptr
const Snapshot* snapshot;
ReadOptions()
: verify_checksums(false),
fill_cache(true),
snapshot(nullptr) {
}
ReadOptions(bool cksum, bool cache) :
verify_checksums(cksum), fill_cache(cache),
snapshot(nullptr) {
}
};
// Options that control write operations
struct WriteOptions {
// If true, the write will be flushed from the operating system
// buffer cache (by calling WritableFile::Sync()) before the write
// is considered complete. If this flag is true, writes will be
// slower.
//
// If this flag is false, and the machine crashes, some recent
// writes may be lost. Note that if it is just the process that
// crashes (i.e., the machine does not reboot), no writes will be
// lost even if sync==false.
//
// In other words, a DB write with sync==false has similar
// crash semantics as the "write()" system call. A DB write
// with sync==true has similar crash semantics to a "write()"
// system call followed by "fsync()".
//
// Default: false
bool sync;
// If true, writes will not first go to the write ahead log,
// and the write may got lost after a crash.
bool disableWAL;
WriteOptions()
: sync(false),
disableWAL(false) {
}
};
// Options that control flush operations
struct FlushOptions {
// If true, the flush will wait until the flush is done.
// Default: true
bool wait;
FlushOptions()
: wait(true) {
}
};
} // namespace leveldb
#endif // STORAGE_LEVELDB_INCLUDE_OPTIONS_H_