The CREATE INDEX statement creates an index for a table. Indexes improve your database's performance by helping SQL locate data without having to look through every row of a table.
The following types cannot be included in an index key, but can be stored (and used in a covered query) using the STORING or COVERING clause:
To create an index on the schemaless data in a JSONB column, use an inverted index.
Indexes are automatically created for a table's PRIMARY KEY and UNIQUE columns. When querying a table, CockroachDB uses the fastest index. For more information about that process, see Index Selection in CockroachDB.
This statement performs a schema change. For more information about how online schema changes work in CockroachDB, see Online Schema Changes.
Required privileges
The user must have the CREATE privilege on the table.
Synopsis
Standard index:
Inverted index:
Parameters
| Parameter | Description |
|---|---|
UNIQUE |
Apply the UNIQUE constraint to the indexed columns.This causes the system to check for existing duplicate values on index creation. It also applies the UNIQUE constraint at the table level, so the system checks for duplicate values when inserting or updating data. |
INVERTED |
Create an inverted index on the schemaless data in the specified JSONB column.You can also use the PostgreSQL-compatible syntax USING GIN. For more details, see Inverted Indexes. |
IF NOT EXISTS |
Create a new index only if an index of the same name does not already exist; if one does exist, do not return an error. |
opt_index_nameindex_name |
The name of the index to create, which must be unique to its table and follow these identifier rules. If you do not specify a name, CockroachDB uses the format <table>_<columns>_key/idx. key indicates the index applies the UNIQUE constraint; idx indicates it does not. Example: accounts_balance_idx |
table_name |
The name of the table you want to create the index on. |
USING name |
An optional clause for compatibility with third-party tools. Accepted values for name are btree and gin, with btree for a standard secondary index and gin as the PostgreSQL-compatible syntax for an inverted index on schemaless data in a JSONB column. |
column_name |
The name of the column you want to index. |
ASC or DESC |
Sort the column in ascending (ASC) or descending (DESC) order in the index. How columns are sorted affects query results, particularly when using LIMIT.Default: ASC |
STORING ... |
Store (but do not sort) each column whose name you include. For information on when to use STORING, see Store Columns. Note that columns that are part of a table's PRIMARY KEY cannot be specified as STORING columns in secondary indexes on the table.COVERING and INCLUDE are aliases for STORING and work identically. |
opt_interleave |
You can potentially optimize query performance by interleaving indexes, which changes how CockroachDB stores your data. Note: Hash-sharded indexes cannot be interleaved. |
opt_partition_by |
An enterprise-only option that lets you define index partitions at the row level. |
USING HASH WITH BUCKET COUNT |
New in v20.1: Creates a hash-sharded index with n_buckets number of buckets.Note: To enable hash-sharded indexes, set the experimental_enable_hash_sharded_indexes session variable to on. |
CONCURRENTLY |
New in v20.1: Optional, no-op syntax for PostgreSQL compatibility. All indexes are created concurrently in CockroachDB. |
Viewing schema changes
This schema change statement is registered as a job. You can view long-running jobs with SHOW JOBS.
Examples
Setup
The following examples use MovR, a fictional vehicle-sharing application, to demonstrate CockroachDB SQL statements. For more information about the MovR example application and dataset, see MovR: A Global Vehicle-sharing App.
To follow along, run cockroach demo to start a temporary, in-memory cluster with the movr dataset preloaded:
$ cockroach demo
Create standard indexes
To create the most efficient indexes, we recommend reviewing:
Single-column indexes
Single-column indexes sort the values of a single column.
> CREATE INDEX ON users (name);
Because each query can only use one index, single-column indexes are not typically as useful as multiple-column indexes.
Multiple-column indexes
Multiple-column indexes sort columns in the order you list them.
> CREATE INDEX ON users (name, city);
To create the most useful multiple-column indexes, we recommend reviewing our best practices.
Unique indexes
Unique indexes do not allow duplicate values among their columns.
> CREATE UNIQUE INDEX ON users (name, id);
This also applies the UNIQUE constraint at the table level, similarly to ALTER TABLE. The above example is equivalent to:
> ALTER TABLE users ADD CONSTRAINT users_name_id_key UNIQUE (name, id);
Create inverted indexes
Inverted indexes can be created on schemaless data in a JSONB column.
> CREATE INVERTED INDEX ON promo_codes (rules);
The above example is equivalent to the following PostgreSQL-compatible syntax:
> CREATE INDEX ON promo_codes USING GIN (rules);
Store columns
Storing a column improves the performance of queries that retrieve (but do not filter) its values.
> CREATE INDEX ON users (city) STORING (name);
However, to use stored columns, queries must filter another column in the same index. For example, SQL can retrieve name values from the above index only when a query's WHERE clause filters city.
Change column sort order
To sort columns in descending order, you must explicitly set the option when creating the index. (Ascending order is the default.)
> CREATE INDEX ON users (city DESC, name);
Note that how a column is ordered in the index will affect the ordering of the index keys, and may affect the efficiency of queries that include an ORDER BY clause.
Query specific indexes
Normally, CockroachDB selects the index that it calculates will scan the fewest rows. However, you can override that selection and specify the name of the index you want to use. To find the name, use SHOW INDEX.
> SHOW INDEX FROM users;
table_name | index_name | non_unique | seq_in_index | column_name | direction | storing | implicit
+------------+----------------+------------+--------------+-------------+-----------+---------+----------+
users | primary | false | 1 | city | ASC | false | false
users | primary | false | 2 | id | ASC | false | false
users | users_name_idx | true | 1 | name | ASC | false | false
users | users_name_idx | true | 2 | city | ASC | false | true
users | users_name_idx | true | 3 | id | ASC | false | true
(5 rows)
> SELECT name FROM users@users_name_idx WHERE city='new york';
name
+------------------+
Catherine Nelson
Devin Jordan
James Hamilton
Judy White
Robert Murphy
(5 rows)
Create a hash-sharded secondary index
For performance reasons, we discourage indexing on sequential keys. If, however, you are working with a table that must be indexed on sequential keys, you should use hash-sharded indexes. Hash-sharded indexes distribute sequential traffic uniformly across ranges, eliminating single-range hotspots and improving write performance on sequentially-keyed indexes at a small cost to read performance.
> CREATE TABLE events (
product_id INT8,
owner UUID,
serial_number VARCHAR,
event_id UUID,
ts TIMESTAMP,
data JSONB,
PRIMARY KEY (product_id, owner, serial_number, ts, event_id)
);
> SET experimental_enable_hash_sharded_indexes=on;
> CREATE INDEX ON events(ts) USING HASH WITH BUCKET_COUNT=8;
> SHOW INDEX FROM events;
table_name | index_name | non_unique | seq_in_index | column_name | direction | storing | implicit
-------------+----------------------------------------+------------+--------------+--------------------------+-----------+---------+-----------
events | primary | false | 1 | product_id | ASC | false | false
events | primary | false | 2 | owner | ASC | false | false
events | primary | false | 3 | serial_number | ASC | false | false
events | primary | false | 4 | ts | ASC | false | false
events | primary | false | 5 | event_id | ASC | false | false
events | events_crdb_internal_ts_shard_8_ts_idx | true | 1 | crdb_internal_ts_shard_8 | ASC | false | false
events | events_crdb_internal_ts_shard_8_ts_idx | true | 2 | ts | ASC | false | false
events | events_crdb_internal_ts_shard_8_ts_idx | true | 3 | product_id | ASC | false | true
events | events_crdb_internal_ts_shard_8_ts_idx | true | 4 | owner | ASC | false | true
events | events_crdb_internal_ts_shard_8_ts_idx | true | 5 | serial_number | ASC | false | true
events | events_crdb_internal_ts_shard_8_ts_idx | true | 6 | event_id | ASC | false | true
(11 rows)
> SHOW COLUMNS FROM events;
column_name | data_type | is_nullable | column_default | generation_expression | indices | is_hidden
---------------------------+-----------+-------------+----------------+-----------------------------------+--------------------------------------------------+------------
product_id | INT8 | false | NULL | | {primary,events_crdb_internal_ts_shard_8_ts_idx} | false
owner | UUID | false | NULL | | {primary,events_crdb_internal_ts_shard_8_ts_idx} | false
serial_number | VARCHAR | false | NULL | | {primary,events_crdb_internal_ts_shard_8_ts_idx} | false
event_id | UUID | false | NULL | | {primary,events_crdb_internal_ts_shard_8_ts_idx} | false
ts | TIMESTAMP | false | NULL | | {primary,events_crdb_internal_ts_shard_8_ts_idx} | false
data | JSONB | true | NULL | | {} | false
crdb_internal_ts_shard_8 | INT4 | false | NULL | mod(fnv32(CAST(ts AS STRING)), 8) | {events_crdb_internal_ts_shard_8_ts_idx} | true
(7 rows)
See also
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