Sharding分片

Sharded Cluster分片集群

The following graphic describes the interaction of components within a sharded cluster:下图描述了分片集群中组件的交互：

MongoDB shards data at the collection level, distributing the collection data across the shards in the cluster.MongoDB在集合级别对数据进行分片，将集合数据分布在集群中的分片上。

Shard Keys分片钥匙

MongoDB uses the shard key to distribute the collection's documents across shards. The shard key consists of a field or multiple fields in the documents.MongoDB使用分片键在分片之间分发集合的文档。分片键由文档中的一个或多个字段组成。

Documents in sharded collections can be missing the shard key fields. Missing shard key fields are treated as having null values when distributing the documents across shards but not when routing queries. For more information, see Missing Shard Key Fields.分片集合中的文档可能缺少分片键字段。在跨分片分发文档时，缺少的分片键字段被视为具有null值，但在路由查询时则不会。有关详细信息，请参阅缺少分片键段。

You select the shard key when sharding a collection.在对集合进行分片时，您可以选择分片键。

• Starting in MongoDB 5.0, you can reshard a collection by changing a collection's shard key.从MongoDB 5.0开始，您可以通过更改集合的分片键来重新分片集合。
• You can refine a shard key by adding a suffix field or fields to the existing shard key.您可以通过向现有分片键添加一个或多个后缀字段来细化分片键。

A document's shard key value determines its distribution across the shards. You can update a document's shard key value unless your shard key field is the immutable _id field. For more information, see Change a Document's Shard Key Value.文档的分片键值决定了它在分片中的分布。您可以更新文档的分片键值，除非分片键字段是不可变的_id字段。有关更多信息，请参阅更改文档的分片键值。

Chunks块

MongoDB partitions sharded data into chunks. Each chunk has an inclusive lower and exclusive upper range based on the shard key.MongoDB将分片数据分割成块。每个块都有一个基于分片键的包容性下限和排他性上限。

Balancer and Even Data Distribution平衡器和均匀数据分布

In an attempt to achieve an even distribution of data across all shards in the cluster, a balancer runs in the background to migrate ranges across the shards.为了在集群中的所有分片上实现数据的均匀分布，平衡器在后台运行以跨分片迁移范围。

Advantages of Sharding分片的优点

Considerations Before Sharding分片前的注意事项

Sharded cluster infrastructure requirements and complexity require careful planning, execution, and maintenance.分片化的集群基础设施要求和复杂性需要仔细的规划、执行和维护。

While you can reshard your collection later, it is important to carefully consider your shard key choice to avoid scalability and performance issues.虽然您可以稍后重新标记集合，但重要的是要仔细考虑分片键选择，以避免可扩展性和性能问题。

To understand the operational requirements and restrictions for sharding your collection, see Operational Restrictions in Sharded Clusters.要了解对集合进行分片的操作要求和限制，请参阅分片集群中的操作限制。

If queries do not include the shard key or the prefix of a compound shard key, mongos performs a broadcast operation, querying all shards in the sharded cluster. 如果查询不包括分片键或复合分片键的前缀，mongos将执行广播操作，查询分片集群中的所有分片。These scatter/gather queries can be long running operations.这些分散/聚集查询可能是长时间运行的操作。

Starting in MongoDB 5.1, when starting, restarting or adding a shard server with sh.addShard() the Cluster Wide Write Concern (CWWC) must be set.从MongoDB 5.1开始，在启动、重新启动或使用sh.addShard()添加分片服务器时，必须设置集群范围写入关注（CWWC）。

If the CWWC is not set and the shard is configured such that the default write concern is { w : 1 } the shard server will fail to start or be added and returns an error.如果未设置CWWC，并且分片配置为默认写入关注为{ w : 1 }，则分片服务器将无法启动或被添加并返回错误。

See default write concern calculations for details on how the default write concern is calculated.有关如何计算默认写入关注的详细信息，请参阅默认写入关注计算。

Sharded and Non-Sharded Collections分片和非分片集合

A database can have a mixture of sharded and unsharded collections. 数据库可以包含分片和非分片集合。Sharded collections are partitioned and distributed across the shards in the cluster. Unsharded collections can be located on any shard but cannot span across shards.分片集合被分区并分布在集群中的分片上。未分片的集合可以位于任何分片上，但不能跨越分片。

Connecting to a Sharded Cluster连接到分片集群

You must connect to a mongos router to interact with any collection in the sharded cluster. 您必须连接到mongos路由器才能与分片集群中的任何集合进行交互。This includes sharded and unsharded collections. Clients should never connect to a single shard in order to perform read or write operations.这包括分片和非分片集合。客户端永远不应该连接到单个分片来执行读取或写入操作。

You can connect to a mongos the same way you connect to a mongod using the mongosh or a MongoDB driver.您可以连接到mongos，就像使用mongosh或MongoDB驱动程序连接到mongod一样。

"You are connecting to a sharded cluster improperly by connecting directly
to a shard. Please connect to the cluster via a router (mongos)."

Sharding Strategy分片化战略

MongoDB supports two sharding strategies for distributing data across sharded clusters.MongoDB支持两种分片策略，用于在分片集群之间分发数据。

Hashed Sharding哈希分片

Hashed Sharding involves computing a hash of the shard key field's value. Each chunk is then assigned a range based on the hashed shard key values.哈希分片涉及计算分片键字段值的哈希值。然后，根据哈希的分片键值为每个块分配一个范围。

Tip

MongoDB automatically computes the hashes when resolving queries using hashed indexes. Applications do not need to compute hashes.MongoDB在使用哈希索引解析查询时会自动计算哈希值。应用程序不需要计算哈希值。

While a range of shard keys may be "close", their hashed values are unlikely to be on the same chunk. Data distribution based on hashed values facilitates more even data distribution, especially in data sets where the shard key changes monotonically.虽然一系列分片键可能“接近”，但它们的哈希值不太可能在同一块上。基于哈希值的数据分布有助于更均匀的数据分布，特别是在分片键单调变化的数据集中。

However, hashed distribution means that range-based queries on the shard key are less likely to target a single shard, resulting in more cluster wide broadcast operations然而，哈希分布意味着基于分片键的范围查询不太可能针对单个分片，从而导致更多的集群范围广播操作

See Hashed Sharding for more information.有关更多信息，请参阅哈希分片。

Ranged Sharding测距分片

Ranged sharding involves dividing data into ranges based on the shard key values. Each chunk is then assigned a range based on the shard key values.范围分片涉及根据分片键值将数据划分为范围。然后根据分片键值为每个块分配一个范围。

A range of shard keys whose values are "close" are more likely to reside on the same chunk. 值为“close”的一系列分片键更有可能位于同一块上。This allows for targeted operations as a mongos can route the operations to only the shards that contain the required data.这允许有针对性的操作，因为mongos可以将操作路由到仅包含所需数据的分片。

The efficiency of ranged sharding depends on the shard key chosen. Poorly considered shard keys can result in uneven distribution of data, which can negate some benefits of sharding or can cause performance bottlenecks. 范围分片的效率取决于所选择的分片键。考虑不周的分片键可能会导致数据分布不均，这可能会抵消分片的一些好处，或者导致性能瓶颈。See shard key selection for range-based sharding.有关基于范围的分片，请参阅分片键选择。

See Ranged Sharding for more information.有关更多信息，请参阅范围分片。

Zones in Sharded Clusters分片集群中的区域

Zones can help improve the locality of data for sharded clusters that span multiple data centers.区域可以帮助改善跨越多个数据中心的分片集群的数据局部性。

In sharded clusters, you can create zones of sharded data based on the shard key. 在分片集群中，您可以根据分片键创建分片数据区域。You can associate each zone with one or more shards in the cluster. A shard can associate with any number of zones. In a balanced cluster, MongoDB migrates chunks covered by a zone only to those shards associated with the zone.您可以将每个区域与集群中的一个或多个分片相关联。一个分片可以与任意数量的区域相关联。在平衡集群中，MongoDB只将区域覆盖的块迁移到与该区域关联的那些分片。

Each zone covers one or more ranges of shard key values. Each range a zone covers is always inclusive of its lower boundary and exclusive of its upper boundary.每个区域覆盖一个或多个分片键值范围。一个区域覆盖的每个范围总是包括其下限，不包括其上限。

You must use fields contained in the shard key when defining a new range for a zone to cover. If using a compound shard key, the range must include the prefix of the shard key. 在定义要覆盖的区域的新范围时，必须使用分片键中包含的字段。如果使用复合分片键，则范围必须包含分片键的前缀。See shard keys in zones for more information.有关更多信息，请参阅区域中的分片键。

The possible use of zones in the future should be taken into consideration when choosing a shard key.在选择分片键时，应考虑未来可能使用的区域。

See zones for more information.有关更多信息，请参阅区域。

Collations in Sharding分片整理

Use the shardCollection command with the collation : { locale : "simple" } option to shard a collection which has a default collation. Successful sharding requires that:使用shardCollection命令和collation : { locale : "simple" }选项对具有默认排序规则的集合进行分片。成功的分片需要：

• The collection must have an index whose prefix is the shard key集合必须有一个前缀为分片键的索引
• The index must have the collation { locale: "simple" }索引必须具有排序规则{ locale: "simple" }

When creating new collections with a collation, ensure these conditions are met prior to sharding the collection.在使用排序规则创建新集合时，请确保在对集合进行分片之前满足这些条件。

See shardCollection for more information about sharding and collation.有关分片和排序规则的更多信息，请参阅shardCollection。

Change Streams更改流

Change streams are available for replica sets and sharded clusters. Change streams allow applications to access real-time data changes without the complexity and risk of tailing the oplog. Applications can use change streams to subscribe to all data changes on a collection or collections.更改流可用于副本集和分片集群。变更流允许应用程序访问实时数据变更，而不会带来跟踪oplog的复杂性和风险。应用程序可以使用更改流订阅一个或多个集合上的所有数据更改。

Transactions事务

With the introduction of distributed transactions, multi-document transactions are available on sharded clusters.随着分布式事务的引入，多文档事务在分片集群上可用。

Until a transaction commits, the data changes made in the transaction are not visible outside the transaction.在事务提交之前，事务中所做的数据更改在事务外部不可见。

However, when a transaction writes to multiple shards, not all outside read operations need to wait for the result of the committed transaction to be visible across the shards. For example, if a transaction is committed and write 1 is visible on shard A but write 2 is not yet visible on shard B, an outside read at read concern "local" can read the results of write 1 without seeing write 2.然而，当一个事务写入多个分片时，并非所有外部读取操作都需要等待提交事务的结果在分片之间可见。例如，如果一个事务已提交，并且写1在分片a上可见，但写2在分片B上尚不可见，则外部读取关注"local"可以读取写1的结果，而看不到写2。

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