Hashed Indexes
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Hashed indexes collect and store hashes of the values of the indexed field.
Hashed indexes support sharding using hashed shard keys. Hashed based sharding uses a hashed index of a field as the shard key to partition data across your sharded cluster.
Use Cases
Hashed indexing is ideal for shard keys with fields that change
monotonically like ObjectId values
or timestamps. When you use ranged sharding
with a monotonically increasing shard key value, the chunk with an upper
bound of MaxKey receives the majority incoming writes. This
behavior restricts insert operations to a single shard, which removes
the advantage of distributed writes in a sharded cluster.
For more information on choosing the best sharding approach for your application, see Hashed vs Ranged Sharding
Behavior
Floating-Point Numbers
Hashed indexes truncate floating-point numbers to 64-bit integers before
hashing. For example, a hashed index uses the same hash to store the
values 2.3, 2.2, and 2.9. This is a collision, where
multiple values are assigned to a single hash key. Collisions may
negatively impact query performance.
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.
Hashed indexes do not support floating-point numbers larger than 2 53.
Limitations
Hashed indexes have limitations for array fields and the unique property.
Array Fields
The hashing function does not support multi-key indexes. You cannot create a hashed index on a field that contains an array or insert an array into a hashed indexed field.
Unique Constraint
You cannot specify a unique constraint on a hashed index. Instead, you can create an additional non-hashed index with the unique constraint. MongoDB can use that non-hashed index to enforce uniqueness on the chosen field.
Get Started
To create a hashed index, see Create a Hashed Index.
Details
This section describes technical details for hashed indexes.
Hashing Function
Important
When MongoDB uses a hashed index to resolve a query, it uses a hashing function to automatically compute the hash values. Applications do not need to compute hashes.
To see what the hashed value would be for a key, use the
convertShardKeyToHashed() method. This method uses the same
hashing function as the hashed index.
Embedded Documents
The hashing function collapses embedded documents and computes the hash for the entire value.