In-Memory Storage Engine for Self-Managed Deployments用于自我管理部署的内存存储引擎

Specify In-Memory Storage Engine指定内存存储引擎

To select the in-memory storage engine, specify:要选择内存中的存储引擎，请指定：

• inMemory for the --storageEngine option, or the storage.engine setting if using a configuration file.inMemory中的--storageEngine选项，或使用配置文件时的storage.engine设置。
• --dbpath, or storage.dbPath if using a configuration file. Although the in-memory storage engine does not write data to the filesystem, it maintains in the --dbpath small metadata files and diagnostic data as well temporary files for building large indexes.--dbpath或storage.dbPath（如果使用配置文件）。虽然内存中的存储引擎不向文件系统写入数据，但它在--dbpath中维护了小型元数据文件和诊断数据，以及用于构建大型索引的临时文件。

For example, from the command line:例如，在命令行中：

mongod --storageEngine inMemory --dbpath <path>

Or, if using the YAML configuration file format:或者，如果使用YAML配置文件格式：

storage:
   engine: inMemory
   dbPath: <path>

See inMemory Options for configuration options specific to this storage engine. 有关此存储引擎特有的配置选项，请参阅内存选项。Most mongod configuration options are available for use with in-memory storage engine except for those options that are related to data persistence, such as journaling or encryption at rest configuration.除了与数据持久性相关的选项（如日志记录或静态加密配置）外，大多数mongod配置选项都可用于内存存储引擎。

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。

Document Level Concurrency文档级并发

The in-memory storage engine uses document-level concurrency control for write operations. As a result, multiple clients can modify different documents of a collection at the same time.内存中的存储引擎对写入操作使用文档级并发控制。因此，多个客户端可以同时修改集合的不同文档。

Memory Use内存使用

In-memory storage engine requires that all its data (including indexes, oplog if mongod instance is part of a replica set, etc.) must fit into the specified --inMemorySizeGB command-line option or storage.inMemory.engineConfig.inMemorySizeGB setting in the YAML configuration file.内存存储引擎要求其所有数据（包括索引、oplog（如果mongod实例是副本集的一部分）必须符合指定的--inMemorySizeGB命令行选项或YAML配置文件中的storage.inMemory.engineConfig.inMemorySizeGB设置。

By default, the in-memory storage engine uses 50% of physical RAM minus 1 GB.默认情况下，内存存储引擎使用50%的物理RAM减去1GB。

If a write operation would cause the data to exceed the specified memory size, MongoDB returns with the error:如果写操作会导致数据超过指定的内存大小，MongoDB将返回错误：

"WT_CACHE_FULL: operation would overflow cache"

To specify a new size, use the storage.inMemory.engineConfig.inMemorySizeGB setting in the YAML configuration file format:要指定新大小，请使用YAML配置文件格式的storage.inMemory.engineConfig.inMemorySizeGB设置：

storage:
   engine: inMemory
   dbPath: <path>
   inMemory:
      engineConfig:
         inMemorySizeGB: <newSize>

Or use the command-line option --inMemorySizeGB:或者使用命令行选项--inMemorySizeGB：

mongod --storageEngine inMemory --dbpath <path> --inMemorySizeGB <newSize>

Durability耐久性

The in-memory storage engine is non-persistent and does not write data to a persistent storage. Non-persisted data includes application data and system data, such as users, permissions, indexes, replica set configuration, sharded cluster configuration, etc.内存中的存储引擎是非持久性的，不会将数据写入持久性存储。非持久化数据包括应用程序数据和系统数据，如用户、权限、索引、副本集配置、分片集群配置等。

As such, the concept of journal or waiting for data to become durable does not apply to the in-memory storage engine.因此，日志或等待数据变得持久的概念不适用于内存中的存储引擎。

If any voting member of a replica set uses the in-memory storage engine, you must set writeConcernMajorityJournalDefault to false.如果副本集的任何投票成员使用内存中的存储引擎，则必须将writeConcernMajorityJournalDefault设置为false。

With writeConcernMajorityJournalDefault set to false, MongoDB does not wait for w: "majority" writes to be written to the on-disk journal before acknowledging the writes. 当writeConcernMajorityJournalDefault设置为false时，MongoDB不会在确认写入之前等待w: "majority"写入写入到磁盘日志中。As such, "majority" write operations could possibly roll back in the event of a transient loss (e.g. crash and restart) of a majority of nodes in a given replica set.因此，在给定副本集中的大多数节点暂时丢失（例如崩溃和重启）的情况下，"majority"写操作可能会回滚。

Write operations that specify a write concern journaled are acknowledged immediately. 指定日志记录的写入关注journaled的写入操作会立即得到确认。When an mongod instance shuts down, either as result of the shutdown command or due to a system error, recovery of in-memory data is impossible.当mongod实例因shutdown命令或系统错误而关闭时，无法恢复内存中的数据。

Transactions事务

Transactions are supported on replica sets and sharded clusters where:在以下情况下，副本集和分片集群支持事务：

• the primary uses the WiredTiger storage engine, and主要使用WiredTiger存储引擎，以及
• the secondary members use either the WiredTiger storage engine or the in-memory storage engines.次要成员使用WiredTiger存储引擎或内存中存储引擎。

Deployment Architectures部署架构

In addition to running as standalones, mongod instances that use in-memory storage engine can run as part of a replica set or part of a sharded cluster.除了作为独立运行外，使用内存存储引擎的mongod实例还可以作为副本集的一部分或分片集群的一部分运行。

sh.addShardTag("shardC", "inmem")

sh.addShardTag("shardA", "persisted")
sh.addShardTag("shardB", "persisted")

sh.addTagRange("test.analytics", { shardKey: MinKey }, { shardKey: MaxKey }, "inmem")

sh.addTagRange("salesdb.orders", { shardKey: MinKey }, { shardKey: MaxKey }, "persisted")