Map-Reduce and Sharded Collections映射减少和分片集合¶

Sharded Collection as Input分片收集作为输入¶

When using sharded collection as the input for a map-reduce operation, mongos will automatically dispatch the map-reduce job to each shard in parallel. 当使用分片集合作为map-reduce操作的输入时，mongos将自动并行地将map-reduce作业分派给每个分片。There is no special option required. 不需要特殊选项。mongos will wait for jobs on all shards to finish.mongos将等待所有碎片上的作业完成。

Sharded Collection as Output分片集合作为输出¶

If the out field for mapReduce has the sharded value, MongoDB shards the output collection using the _id field as the shard key.如果mapReduce的out字段具有shared值，则MongoDB使用_id字段作为shard键对输出集合进行切分。

To output to a sharded collection:要输出到分片集合，请执行以下操作：

• If the output collection does not exist, create the sharded collection first.如果输出集合不存在，请首先创建分片集合。

  Starting in version 4.2, MongoDB deprecates the map-reduce option to create a new sharded collection and the use of the sharded option for map-reduce. 从4.2版开始，MongoDB不推荐使用map-reduce选项来创建新的分片集合，也不推荐使用分片选项进行map-reduce。As such, to output to a sharded collection, create the sharded collection first.因此，要输出到分片集合，请首先创建分片集合。

  If you did not create the sharded collection first, MongoDB creates and shards the collection on the _id field. 如果您没有首先创建切分集合，MongoDB将在_id字段中创建并切分集合。However, it is recommended that you create the sharded collection first.但是，建议您首先创建分片集合。

• Starting in version 4.2, MongoDB deprecates the replacement of an existing sharded collection.从版本4.2开始，MongoDB反对替换现有的分片集合。
• Starting in version 4.0, if the output collection already exists but is not sharded, map-reduce fails.从版本4.0开始，如果输出集合已经存在，但没有切分，则map reduce将失败。
• For a new or an empty sharded collection, MongoDB uses the results of the first stage of the map-reduce operation to create the initial chunks distributed among the shards.对于新的或空的分片集合，MongoDB使用map reduce操作第一阶段的结果来创建分布在分片之间的初始块。
• mongos dispatches, in parallel, a map-reduce post-processing job to every shard that owns a chunk. 并行地，将映射减少后处理作业分配给拥有块的每个碎片。During the post-processing, each shard will pull the results for its own chunks from the other shards, run the final reduce/finalize, and write locally to the output collection.在后处理过程中，每个碎片将从其他碎片中提取其自身块的结果，运行最终的reduce/finalize，并在本地写入输出集合。