Hashed Indexes哈希索引

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Hashed indexes maintain entries with hashes of the values of the indexed field.散列索引使用索引字段的值的散列来维护条目。

Hashed indexes support sharding using hashed shard keys. 哈希索引支持使用哈希分片键进行分片。Hashed based sharding uses a hashed index of a field as the shard key to partition data across your sharded cluster.基于哈希的分片使用字段的哈希索引作为分片键，在分片集群中对数据进行分区。

Using a hashed shard key to shard a collection results in a more even distribution of data. 使用哈希分片键对集合进行分片会导致数据分布更加均匀。See Hashed Sharding for more details.有关更多详细信息，请参阅哈希分片。

Hashing Function哈希函数

Hashed indexes use a hashing function to compute the hash of the value of the index field. 哈希索引使用哈希函数计算索引字段值的哈希。[1] The hashing function collapses embedded documents and computes the hash for the entire value but does not support multi-key (i.e. arrays) indexes. 散列函数折叠嵌入的文档并计算整个值的散列，但不支持多键（即数组）索引。Specifically, creating a hashed index on a field that contains an array or attempting to insert an array into a hashed indexed field returns an error.具体而言，在包含数组的字段上创建哈希索引或尝试将数组插入哈希索引字段会返回错误。

Tip提示

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

[1] Starting in version 4.0, mongosh provides the method convertShardKeyToHashed(). 从版本4.0开始，mongosh提供了convertShardKeyToHashed()方法。This method uses the same hashing function as the hashed index and can be used to see what the hashed value would be for a key.此方法使用与散列索引相同的散列函数，并可用于查看键的散列值。

Create a Hashed Index创建哈希索引

To create a hashed index, specify hashed as the value of the index key, as in the following example:要创建哈希索引，请指定hashed作为索引键的值，如下例所示：

db.collection.createIndex( { _id: "hashed" } )

Create a Compound Hashed Index创建复合哈希索引

New in version 4.4.在版本4.4中新增。

Starting with MongoDB 4.4, MongoDB supports creating compound indexes that include a single hashed field. 从MongoDB 4.4开始，MongoDB支持创建包含单个哈希字段的复合索引。To create a compound hashed index, specify hashed as the value of any single index key when creating the index:要创建复合哈希索引，请在创建索引时将hashed指定为任何单个索引键的值：

db.collection.createIndex( { "fieldA" : 1, "fieldB" : "hashed", "fieldC" : -1 } )

Compound hashed indexes require featureCompatibilityVersion set to 4.4.复合哈希索引需要将featureCompatibilityVersion设置为4.4。

Tip提示
See also: 参阅：

Hashed Sharding哈希分片

Considerations注意事项

Embedded Documents嵌入的文档

The hashing function collapses embedded documents and computes the hash for the entire value, but does not support multi-key (i.e. arrays) indexes. 哈希函数折叠嵌入的文档并计算整个值的哈希，但不支持多键（即数组）索引。Specifically, creating a hashed index on a field that contains an array or attempting to insert an array to a hashed indexed field returns an error.具体而言，在包含数组的字段上创建哈希索引或尝试将数组插入哈希索引字段会返回错误。

Unique Constraint唯一约束条件

MongoDB does not support specifying a unique constraint on a hashed index. MongoDB不支持在哈希索引上指定唯一约束。You can instead create an additional non-hashed index with the unique constraint on that field. 相反，您可以在该字段上创建一个具有唯一约束的附加非哈希索引。MongoDB can use that non-hashed index for enforcing uniqueness on the field.MongoDB可以使用该非哈希索引来强制字段的唯一性。

2 53 Limit

Warning警告

MongoDB hashed indexes truncate floating point numbers to 64-bit integers before hashing. MongoDBhashed索引在哈希之前将浮点数截断为64位整数。For example, a hashed index would store the same value for a field that held a value of 2.3, 2.2, and 2.9. 例如，hashed索引将为一个值为2.3、2.2和2.9的字段存储相同的值。To prevent collisions, do not use a hashed index for floating point numbers that cannot be reliably converted to 64-bit integers (and then back to floating point). 为防止冲突，请勿对无法可靠转换为64位整数（然后再转换回浮点）的浮点数使用hashed索引。MongoDB hashed indexes do not support floating point values larger than 2 53.MongoDB hashed索引不支持大于253的浮点值。

To see what the hashed value would be for a key, see convertShardKeyToHashed().要查看键的哈希值，请参阅convertShardKeyToHashed()。

PowerPC and 2 63

For hashed indexes, MongoDB 4.2 ensures that the hashed value for the floating point value 2 63 on PowerPC is consistent with other platforms.对于哈希索引，MongoDB 4.2确保PowerPC上浮点值263的哈希值与其他平台一致。

Although hashed indexes on a field that may contain floating point values greater than 2 53 is an unsupported configuration, clients may still insert documents where the indexed field has the value 2 63.虽然对可能包含大于253的浮点值的字段进行哈希索引是不受支持的配置，但客户端仍可以插入索引字段值为263的文档。

To list all hashed indexes for all collections in your deployment, you can use the following operation in mongosh:要列出部署中所有集合的所有hashed索引，可以在mongosh中使用以下操作：

db.adminCommand("listDatabases").databases.forEach(function(d){
   let mdb = db.getSiblingDB(d.name);
   mdb.getCollectionInfos({ type: "collection" }).forEach(function(c){
      let currentCollection = mdb.getCollection(c.name);
      currentCollection.getIndexes().forEach(function(idx){
        let idxValues = Object.values(Object.assign({}, idx.key));
        if (idxValues.includes("hashed")) {
          print("Hashed index: " + idx.name + " on " + d.name + "." + c.name);
          printjson(idx);
        };
      });
   });
});

To check if the indexed field contains the value 2 63, run the following operation for the collection and the indexed field:要检查索引字段是否包含值2 63，请对集合和索引字段运行以下操作：

  • If the indexed field type is a scalar and never a document:如果索引字段类型是标量而不是文档：

    // substitute the actual collection name for <collection>
// substitute the actual indexed field name for <indexfield>
db.<collection>.find( { <indexfield>: Math.pow(2,63) } );

  • If the indexed field type is a document (or a scalar), you can run:如果索引字段类型是文档（或标量），则可以运行：

    // substitute the actual collection name for <collection>
// substitute the actual indexed field name for <indexfield>
db.<collection>.find({
    $where: function() {
        function findVal(obj, val) {
            if (obj === val)
                return true;
            for (const child in obj) {
                if (findVal(obj[child], val)) {
                    return true;
                }
            }
            return false;
        }
        return findVal(this.<indexfield>, Math.pow(2, 63));
    }
})
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