WiredTiger Storage EngineWiredTiger存储引擎

Operation and Limitations操作和限制

The following operational notes and limitations apply to the WiredTiger engine:以下操作注意事项和限制适用于WiredTiger发动机：

• You can't pin documents to the WiredTiger cache.您无法将文档固定到WiredTiger缓存。
• WiredTiger doesn't reserve a portion of the cache for reads and another for writes.WiredTiger不保留缓存的一部分用于读取，另一部分用于写入。
• WiredTiger allocates its cache to the entire mongod instance. WiredTiger doesn't allocate cache on a per-database or per-collection level.WiredTiger将其缓存分配给整个mongod实例。WiredTiger不会在每个数据库或每个集合级别分配缓存。

Transaction (Read and Write) Concurrency事务（读写）并发

Starting in version 7.0, MongoDB uses a default algorithm to dynamically adjust the maximum number of concurrent storage engine transactions, or read and write tickets. The dynamic concurrent storage engine transaction algorithm optimizes database throughput during cluster overload.从7.0版本开始，MongoDB使用默认算法动态调整并发存储引擎事务或读写票证的最大数量。动态并发存储引擎事务算法在集群过载期间优化了数据库吞吐量。

The maximum number of concurrent storage engine transactions, or read and write tickets, never exceeds 128 read tickets and 128 write tickets and may differ across nodes in a cluster. The maximum number of read tickets and write tickets within a single node are always equal.并发存储引擎事务或读写票证的最大数量永远不会超过128个读票证和128个写票证，并且可能因集群中的节点而异。单个节点内读取票和写入票的最大数量始终相等。

To specify a maximum number of read and write transactions, or read and write tickets, that the dynamic maximum can not exceed, use storageEngineConcurrentReadTransactions and storageEngineConcurrentWriteTransactions.要指定动态最大值不能超过的最大读写事务数或读写票证数，请使用storageEngineConcurrentReadTransactions和storageEngineConcurrentWriteTransactions。

If you want to disable the dynamic concurrent storage engine transactions algorithm, file a support request to work with a MongoDB Technical Services Engineer.如果你想禁用动态并发存储引擎事务算法，请提交支持请求，与MongoDB技术服务工程师合作。

To view the number of concurrent read transactions (read tickets) and write transactions (write tickets) allowed in the WiredTiger storage engine, use the serverStatus command and see the queues.execution response document.要查看WiredTiger存储引擎中允许的并发读取事务（读取票）和写入事务（写入票）的数量，请使用serverStatus命令并查看queues.execution响应文档。

Document Level Concurrency

WiredTiger uses document-level concurrency control for write operations. As a result, multiple clients can modify different documents of a collection at the same time.

For most read and write operations, WiredTiger uses optimistic concurrency control. WiredTiger uses only intent locks at the global, database and collection levels. When the storage engine detects conflicts between two operations, one will incur a write conflict causing MongoDB to transparently retry that operation.

Some global operations, typically short lived operations involving multiple databases, still require a global "instance-wide" lock. Some other operations, such as renameCollection, still require an exclusive database lock in certain circumstances.

Snapshots and Checkpoints

WiredTiger uses MultiVersion Concurrency Control (MVCC). At the start of an operation, WiredTiger provides a point-in-time snapshot of the data to the operation. A snapshot presents a consistent view of the in-memory data.

When writing to disk, WiredTiger writes all the data in a snapshot to disk in a consistent way across all data files. The now-durable data act as a checkpoint in the data files. The checkpoint ensures that the data files are consistent up to and including the last checkpoint; i.e. checkpoints can act as recovery points.

MongoDB configures WiredTiger to create checkpoints, specifically, writing the snapshot data to disk at intervals of 60 seconds.

During the write of a new checkpoint, the previous checkpoint is still valid. As such, even if MongoDB terminates or encounters an error while writing a new checkpoint, upon restart, MongoDB can recover from the last valid checkpoint.

The new checkpoint becomes accessible and permanent when WiredTiger's metadata table is atomically updated to reference the new checkpoint. Once the new checkpoint is accessible, WiredTiger frees pages from the old checkpoints.

Journal

WiredTiger uses a write-ahead log (i.e. journal) in combination with checkpoints to ensure data durability.

The WiredTiger journal persists all data modifications between checkpoints. If MongoDB exits between checkpoints, it uses the journal to replay all data modified since the last checkpoint. For information on the frequency with which MongoDB writes the journal data to disk, see Journaling Process.

WiredTiger journal is compressed using the snappy compression library. To specify a different compression algorithm or no compression, use the storage.wiredTiger.engineConfig.journalCompressor setting. For details on changing the journal compressor, see Change WiredTiger Journal Compressor.

Compression

With WiredTiger, MongoDB supports compression for all collections and indexes. Compression minimizes storage use at the expense of additional CPU.

By default, WiredTiger uses block compression with the snappy compression library for most collections and prefix compression for all indexes. However, the default block compression for time-series collections is zstd.

For collections, the following block compression libraries are also available:

• zlib
• zstd

To specify an alternate compression algorithm or no compression, use the storage.wiredTiger.collectionConfig.blockCompressor setting.

For indexes, to disable prefix compression, use the storage.wiredTiger.indexConfig.prefixCompression setting.

Compression settings are also configurable on a per-collection and per-index basis during collection and index creation. See Specify Storage Engine Options and db.collection.createIndex() storageEngine option.

For most workloads, the default compression settings balance storage efficiency and processing requirements.

The WiredTiger journal is also compressed by default. For information on journal compression, see Journal.

Memory Use内存使用

With WiredTiger, MongoDB utilizes both the WiredTiger internal cache and the filesystem cache.使用WiredTiger，MongoDB同时利用WiredTigeer内部缓存和文件系统缓存。

The default WiredTiger internal cache size is the larger of either:默认的WiredTiger内部缓存大小是以下两者中的较大值：

• 50% of (RAM - 1 GB), or
• 256 MB.

For example, on a system with a total of 4GB of RAM the WiredTiger cache uses 1.5GB of RAM (0.5 * (4 GB - 1 GB) = 1.5 GB). Conversely, on a system with a total of 1.25 GB of RAM WiredTiger allocates 256 MB to the WiredTiger cache because that is more than half of the total RAM minus one gigabyte (0.5 * (1.25 GB - 1 GB) = 128 MB < 256 MB).

By default, WiredTiger uses Snappy block compression for all collections and prefix compression for all indexes. Compression defaults are configurable at a global level and can also be set on a per-collection and per-index basis during collection and index creation.默认情况下，WiredTiger对所有集合使用Snappy块压缩，对所有索引使用前缀压缩。压缩默认值可以在全局级别进行配置，也可以在集合和索引创建期间根据每个集合和每个索引进行设置。

Different representations are used for data in the WiredTiger internal cache versus the on-disk format:与磁盘格式相比，WiredTiger内部缓存中的数据使用了不同的表示方式：

• Data in the filesystem cache is the same as the on-disk format, including benefits of any compression for data files. The filesystem cache is used by the operating system to reduce disk I/O.文件系统缓存中的数据与磁盘上的格式相同，包括对数据文件进行任何压缩的好处。操作系统使用文件系统缓存来减少磁盘I/O。
• Indexes loaded in the WiredTiger internal cache have a different data representation to the on-disk format, but can still take advantage of index prefix compression to reduce RAM usage. Index prefix compression deduplicates common prefixes from indexed fields.加载在WiredTiger内部缓存中的索引具有与磁盘上格式不同的数据表示形式，但仍然可以利用索引前缀压缩来减少RAM使用。索引前缀压缩可消除索引字段中的常见前缀的重复。
• Collection data in the WiredTiger internal cache is uncompressed and uses a different representation from the on-disk format. Block compression can provide significant on-disk storage savings, but data must be uncompressed to be manipulated by the server.WiredTiger内部缓存中的集合数据是未压缩的，并使用与磁盘格式不同的表示形式。块压缩可以显著节省磁盘存储空间，但数据必须解压缩才能由服务器操作。

With the filesystem cache, MongoDB automatically uses all free memory that is not used by the WiredTiger cache or by other processes.使用文件系统缓存，MongoDB会自动使用WiredTiger缓存或其他进程未使用的所有空闲内存。

To adjust the size of the WiredTiger internal cache, see --wiredTigerCacheSizeGB and storage.wiredTiger.engineConfig.cacheSizeGB. Avoid increasing the WiredTiger internal cache size above its default value. If your use case requires increased internal cache size, see --wiredTigerCacheSizePct and storage.wiredTiger.engineConfig.cacheSizePct.