CREATE INDEX

CREATE INDEX — define a new index

Synopsis

CREATE [ UNIQUE ] INDEX [ CONCURRENTLY ] [ [ IF NOT EXISTS ] [schema_name.]name ] ON [ ONLY ] table_name [ USING method ]
    ( { column_name | ( expression ) } [ COLLATE collation ] [ opclass [ ( opclass_parameter = value [, ... ] ) ] ] [ ASC | DESC ] [ NULLS { FIRST | LAST } ] [, ...] )
    [ INCLUDE ( column_name [, ...] ) ]
    [ WITH ( storage_parameter [= value] [, ... ] ) ]
    [ LOCAL | GLOBAL [ LT_HASH_PARTITION_DEPT ] ]
    [ LOGGING | NOLOGGING ]
    [ COMPRESS | NOCOMPRESS ]
    [ TABLESPACE tablespace_name ]
    [ WHERE predicate ]

Description

CREATE INDEX constructs an index on the specified column(s) of the specified relation, which can be a table. Indexes are primarily used to enhance database performance (though inappropriate use can result in slower performance).

The key field(s) for the index are specified as column names, or alternatively as expressions written in parentheses. Multiple fields can be specified if the index method supports multicolumn indexes.

An index field can be an expression computed from the values of one or more columns of the table row. This feature can be used to obtain fast access to data based on some transformation of the basic data. For example, an index computed on upper(col) would allow the clause WHERE upper(col) = 'JIM' to use an index.

LightDB provides the index methods B-tree, hash, GIN. Users can also define their own index methods, but that is fairly complicated.

When the WHERE clause is present, a partial index is created. A partial index is an index that contains entries for only a portion of a table, usually a portion that is more useful for indexing than the rest of the table. For example, if you have a table that contains both billed and unbilled orders where the unbilled orders take up a small fraction of the total table and yet that is an often used section, you can improve performance by creating an index on just that portion. Another possible application is to use WHERE with UNIQUE to enforce uniqueness over a subset of a table. See Section 12.8 for more discussion.

The expression used in the WHERE clause can refer only to columns of the underlying table, but it can use all columns, not just the ones being indexed. Presently, subqueries and aggregate expressions are also forbidden in WHERE. The same restrictions apply to index fields that are expressions.

All functions and operators used in an index definition must be immutable, that is, their results must depend only on their arguments and never on any outside influence (such as the contents of another table or the current time). This restriction ensures that the behavior of the index is well-defined. To use a user-defined function in an index expression or WHERE clause, remember to mark the function immutable when you create it.

LightDB supports automatic collection of statistics immediately after index creation. You can set the lightdb_enable_indexautoanalyze configuration variable to decide whether to automatically collect statistics.

Parameters

UNIQUE

Causes the system to check for duplicate values in the table when the index is created (if data already exist) and each time data is added. Attempts to insert or update data which would result in duplicate entries will generate an error.

Additional restrictions apply when unique indexes are applied to partitioned tables; see CREATE TABLE.

CONCURRENTLY

When this option is used, LightDB will build the index without taking any locks that prevent concurrent inserts, updates, or deletes on the table; whereas a standard index build locks out writes (but not reads) on the table until it's done. There are several caveats to be aware of when using this option — see Building Indexes Concurrently below.

For temporary tables, CREATE INDEX is always non-concurrent, as no other session can access them, and non-concurrent index creation is cheaper.

IF NOT EXISTS

Do not throw an error if a relation with the same name already exists. A notice is issued in this case. Note that there is no guarantee that the existing index is anything like the one that would have been created. Index name is required when IF NOT EXISTS is specified.

USING

The optional USING clause specifies an index type as described in Section 12.2. If not specified, a default index type will be used based on the data types of the columns.

INCLUDE

The optional INCLUDE clause specifies a list of columns which will be included in the index as non-key columns. A non-key column cannot be used in an index scan search qualification, and it is disregarded for purposes of any uniqueness or exclusion constraint enforced by the index. However, an index-only scan can return the contents of non-key columns without having to visit the index's table, since they are available directly from the index entry. Thus, addition of non-key columns allows index-only scans to be used for queries that otherwise could not use them.

It's wise to be conservative about adding non-key columns to an index, especially wide columns. If an index tuple exceeds the maximum size allowed for the index type, data insertion will fail. In any case, non-key columns duplicate data from the index's table and bloat the size of the index, thus potentially slowing searches. Furthermore, B-tree deduplication is never used with indexes that have a non-key column.

Columns listed in the INCLUDE clause don't need appropriate operator classes; the clause can include columns whose data types don't have operator classes defined for a given access method.

Expressions are not supported as included columns since they cannot be used in index-only scans.

Currently, the B-tree index access methods support this feature. In B-tree indexes, the values of columns listed in the INCLUDE clause are included in leaf tuples which correspond to heap tuples, but are not included in upper-level index entries used for tree navigation.

name

The name of the index to be created. No schema name can be included here; the index is always created in the same schema as its parent table. If the name is omitted, LightDB chooses a suitable name based on the parent table's name and the indexed column name(s).

ONLY

Indicates not to recurse creating indexes on partitions, if the table is partitioned. The default is to recurse.

table_name

The name (possibly schema-qualified) of the table to be indexed.

method

The name of the index method to be used. Choices are btree, hash, gin. The default method is btree.

column_name

The name of a column of the table.

expression

An expression based on one or more columns of the table. The expression usually must be written with surrounding parentheses, as shown in the syntax. However, the parentheses can be omitted if the expression has the form of a function call.

collation

The name of the collation to use for the index. By default, the index uses the collation declared for the column to be indexed or the result collation of the expression to be indexed. Indexes with non-default collations can be useful for queries that involve expressions using non-default collations.

opclass

The name of an operator class. See below for details.

opclass_parameter

The name of an operator class parameter. See below for details.

ASC

Specifies ascending sort order (which is the default).

DESC

Specifies descending sort order.

NULLS FIRST

Specifies that nulls sort before non-nulls. This is the default when DESC is specified.

NULLS LAST

Specifies that nulls sort after non-nulls. This is the default when DESC is not specified.

storage_parameter

The name of an index-method-specific storage parameter. See Index Storage Parameters below for details.

tablespace_name

The tablespace in which to create the index. If not specified, default_tablespace is consulted, or temp_tablespaces for indexes on temporary tables.

predicate

The constraint expression for a partial index.

local

Oracle compatible syntax, no function support. It is necessary to change the configuration to Oracle compatible mode.

global

Oracle compatible syntax, no function support. It is necessary to change the configuration to Oracle compatible mode.

LT_HASH_PARTITION_DEPT

Oracle compatible syntax. Only global hash partition is available for the current implementation. It is necessary to change the configuration to Oracle compatible mode.

The syntax detail is as follows:

{ PARTITION BY HASH ( { columns } ) PARTITIONS Iconst }

Note

Iconst should be a positive integer value.

The feature is only syntax compatible for oracle, there is no implementation as that in oracle database.

COMPRESS LOGGING

Starting from LightDB 23.2, four new non-reserved keywords COMPRESS, LOGGING, NOCOMPRESS, NOLOGGING, are added to be compatible with the syntax of Oracle Database. The four new keywords are just grammatical sugar, and do not achieve specific functions. These four keywords must be used before the TABLESPACE keyword.

schema_name

Starting from LightDB 23.2, the index name of the CREATE INDEX statement supports specifying the schema name to be compatible with Oracle database syntax. This function is just a syntactic sugar, there is no specific function implementation.

Index Storage Parameters

The optional WITH clause specifies storage parameters for the index. Each index method has its own set of allowed storage parameters. The B-tree, hash index methods all accept this parameter:

fillfactor (integer)

The fillfactor for an index is a percentage that determines how full the index method will try to pack index pages. For B-trees, leaf pages are filled to this percentage during initial index build, and also when extending the index at the right (adding new largest key values). If pages subsequently become completely full, they will be split, leading to gradual degradation in the index's efficiency. B-trees use a default fillfactor of 90, but any integer value from 10 to 100 can be selected. If the table is static then fillfactor 100 is best to minimize the index's physical size, but for heavily updated tables a smaller fillfactor is better to minimize the need for page splits. The other index methods use fillfactor in different but roughly analogous ways; the default fillfactor varies between methods.

B-tree indexes additionally accept this parameter:

deduplicate_items (boolean)

Controls usage of the B-tree deduplication technique described in Section 59.4.2. Set to ON or OFF to enable or disable the optimization. (Alternative spellings of ON and OFF are allowed as described in Section 18.1.) The default is ON.

Note

Turning deduplicate_items off via ALTER INDEX prevents future insertions from triggering deduplication, but does not in itself make existing posting list tuples use the standard tuple representation.

GIN indexes accept different parameters:

fastupdate (boolean)

This setting controls usage of the fast update technique described in Section 60.4.1. It is a Boolean parameter: ON enables fast update, OFF disables it. The default is ON.

Note

Turning fastupdate off via ALTER INDEX prevents future insertions from going into the list of pending index entries, but does not in itself flush previous entries. You might want to VACUUM the table or call gin_clean_pending_list function afterward to ensure the pending list is emptied.

gin_pending_list_limit (integer)

Custom gin_pending_list_limit parameter. This value is specified in kilobytes.

Building Indexes Concurrently

Creating an index can interfere with regular operation of a database. Normally LightDB locks the table to be indexed against writes and performs the entire index build with a single scan of the table. Other transactions can still read the table, but if they try to insert, update, or delete rows in the table they will block until the index build is finished. This could have a severe effect if the system is a live production database. Very large tables can take many hours to be indexed, and even for smaller tables, an index build can lock out writers for periods that are unacceptably long for a production system.

LightDB supports building indexes without locking out writes. This method is invoked by specifying the CONCURRENTLY option of CREATE INDEX. When this option is used, LightDB must perform two scans of the table, and in addition it must wait for all existing transactions that could potentially modify or use the index to terminate. Thus this method requires more total work than a standard index build and takes significantly longer to complete. However, since it allows normal operations to continue while the index is built, this method is useful for adding new indexes in a production environment. Of course, the extra CPU and I/O load imposed by the index creation might slow other operations.

In a concurrent index build, the index is actually entered into the system catalogs in one transaction, then two table scans occur in two more transactions. Before each table scan, the index build must wait for existing transactions that have modified the table to terminate. After the second scan, the index build must wait for any transactions that have a snapshot (see Chapter 14) predating the second scan to terminate, including transactions used by any phase of concurrent index builds on other tables. Then finally the index can be marked ready for use, and the CREATE INDEX command terminates. Even then, however, the index may not be immediately usable for queries: in the worst case, it cannot be used as long as transactions exist that predate the start of the index build.

If a problem arises while scanning the table, such as a deadlock or a uniqueness violation in a unique index, the CREATE INDEX command will fail but leave behind an invalid index. This index will be ignored for querying purposes because it might be incomplete; however it will still consume update overhead. The ltsql \d command will report such an index as INVALID:

lightdb@postgres=# \d tab
       Table "public.tab"
 Column |  Type   | Collation | Nullable | Default 
--------+---------+-----------+----------+---------
 col    | integer |           |          | 
Indexes:
    "idx" btree (col) INVALID

The recommended recovery method in such cases is to drop the index and try again to perform CREATE INDEX CONCURRENTLY. (Another possibility is to rebuild the index with REINDEX INDEX CONCURRENTLY).

Another caveat when building a unique index concurrently is that the uniqueness constraint is already being enforced against other transactions when the second table scan begins. This means that constraint violations could be reported in other queries prior to the index becoming available for use, or even in cases where the index build eventually fails. Also, if a failure does occur in the second scan, the invalid index continues to enforce its uniqueness constraint afterwards.

Concurrent builds of expression indexes and partial indexes are supported. Errors occurring in the evaluation of these expressions could cause behavior similar to that described above for unique constraint violations.

Regular index builds permit other regular index builds on the same table to occur simultaneously, but only one concurrent index build can occur on a table at a time. In either case, schema modification of the table is not allowed while the index is being built. Another difference is that a regular CREATE INDEX command can be performed within a transaction block, but CREATE INDEX CONCURRENTLY cannot.

Concurrent builds for indexes on partitioned tables are currently not supported. However, you may concurrently build the index on each partition individually and then finally create the partitioned index non-concurrently in order to reduce the time where writes to the partitioned table will be locked out. In this case, building the partitioned index is a metadata only operation.

Notes

See Chapter 12 for information about when indexes can be used, when they are not used, and in which particular situations they can be useful.

Currently, only the B-tree, GIN index methods support multicolumn indexes. Up to 32 fields can be specified by default. (This limit can be altered when building LightDB.) Only B-tree currently supports unique indexes.

An operator class with optional parameters can be specified for each column of an index. The operator class identifies the operators to be used by the index for that column. For example, a B-tree index on four-byte integers would use the int4_ops class; this operator class includes comparison functions for four-byte integers. In practice the default operator class for the column's data type is usually sufficient. The main point of having operator classes is that for some data types, there could be more than one meaningful ordering. For example, we might want to sort a complex-number data type either by absolute value or by real part. We could do this by defining two operator classes for the data type and then selecting the proper class when creating an index. More information about operator classes is in Section 12.10 and in Section 36.16.

When CREATE INDEX is invoked on a partitioned table, the default behavior is to recurse to all partitions to ensure they all have matching indexes. Each partition is first checked to determine whether an equivalent index already exists, and if so, that index will become attached as a partition index to the index being created, which will become its parent index. If no matching index exists, a new index will be created and automatically attached; the name of the new index in each partition will be determined as if no index name had been specified in the command. If the ONLY option is specified, no recursion is done, and the index is marked invalid. (ALTER INDEX ... ATTACH PARTITION marks the index valid, once all partitions acquire matching indexes.) Note, however, that any partition that is created in the future using CREATE TABLE ... PARTITION OF will automatically have a matching index, regardless of whether ONLY is specified.

For index methods that support ordered scans (currently, only B-tree), the optional clauses ASC, DESC, NULLS FIRST, and/or NULLS LAST can be specified to modify the sort ordering of the index. Since an ordered index can be scanned either forward or backward, it is not normally useful to create a single-column DESC index — that sort ordering is already available with a regular index. The value of these options is that multicolumn indexes can be created that match the sort ordering requested by a mixed-ordering query, such as SELECT ... ORDER BY x ASC, y DESC. The NULLS options are useful if you need to support nulls sort low behavior, rather than the default nulls sort high, in queries that depend on indexes to avoid sorting steps.

The system regularly collects statistics on all of a table's columns. Newly-created non-expression indexes can immediately use these statistics to determine an index's usefulness. For new expression indexes, it is necessary to run ANALYZE or wait for the autovacuum daemon to analyze the table to generate statistics for these indexes.

For most index methods, the speed of creating an index is dependent on the setting of maintenance_work_mem. Larger values will reduce the time needed for index creation, so long as you don't make it larger than the amount of memory really available, which would drive the machine into swapping.

LightDB can build indexes while leveraging multiple CPUs in order to process the table rows faster. This feature is known as parallel index build. For index methods that support building indexes in parallel (currently, only B-tree), maintenance_work_mem specifies the maximum amount of memory that can be used by each index build operation as a whole, regardless of how many worker processes were started. Generally, a cost model automatically determines how many worker processes should be requested, if any.

Parallel index builds may benefit from increasing maintenance_work_mem where an equivalent serial index build will see little or no benefit. Note that maintenance_work_mem may influence the number of worker processes requested, since parallel workers must have at least a 32MB share of the total maintenance_work_mem budget. There must also be a remaining 32MB share for the leader process. Increasing max_parallel_maintenance_workers may allow more workers to be used, which will reduce the time needed for index creation, so long as the index build is not already I/O bound. Of course, there should also be sufficient CPU capacity that would otherwise lie idle.

Setting a value for parallel_workers via ALTER TABLE directly controls how many parallel worker processes will be requested by a CREATE INDEX against the table. This bypasses the cost model completely, and prevents maintenance_work_mem from affecting how many parallel workers are requested. Setting parallel_workers to 0 via ALTER TABLE will disable parallel index builds on the table in all cases.

Tip

You might want to reset parallel_workers after setting it as part of tuning an index build. This avoids inadvertent changes to query plans, since parallel_workers affects all parallel table scans.

While CREATE INDEX with the CONCURRENTLY option supports parallel builds without special restrictions, only the first table scan is actually performed in parallel.

Use DROP INDEX to remove an index.

Like any long-running transaction, CREATE INDEX on a table can affect which tuples can be removed by concurrent VACUUM on any other table.

Prior releases of LightDB also had an R-tree index method. This method has been removed.

Examples

To create a unique B-tree index on the column title in the table films:

CREATE UNIQUE INDEX title_idx ON films (title);

To create a unique B-tree index on the column title with included columns director and rating in the table films:

CREATE UNIQUE INDEX title_idx ON films (title) INCLUDE (director, rating);

To create a B-Tree index with deduplication disabled:

CREATE INDEX title_idx ON films (title) WITH (deduplicate_items = off);

To create an index on the expression lower(title), allowing efficient case-insensitive searches:

CREATE INDEX ON films ((lower(title)));

(In this example we have chosen to omit the index name, so the system will choose a name, typically films_lower_idx.)

To create an index with non-default collation:

CREATE INDEX title_idx_german ON films (title COLLATE "de_DE");

To create an index with non-default sort ordering of nulls:

CREATE INDEX title_idx_nulls_low ON films (title NULLS FIRST);

To create an index with non-default fill factor:

CREATE UNIQUE INDEX title_idx ON films (title) WITH (fillfactor = 70);

To create a GIN index with fast updates disabled:

CREATE INDEX gin_idx ON documents_table USING GIN (locations) WITH (fastupdate = off);

To create an index on the column code in the table films and have the index reside in the tablespace indexspace:

CREATE INDEX code_idx ON films (code) TABLESPACE indexspace;

To create an index without locking out writes to the table:

CREATE INDEX CONCURRENTLY sales_quantity_index ON sales_table (quantity);

To create an index with local or global:

CREATE INDEX index_local ON sales_table (quantity) LOCAL;
CREATE INDEX index_global ON sales_table (quantity) GLOBAL;

To create an index with global hash partition:

CREATE TABLE ora_ph_t(a int,b int,c int) PARTITION BY HASH(a) partitions 4;
CREATE INDEX t_global_ph_idx ON ora_ph_t(a) GLOBAL PARTITION BY hash(a) partitions 2;

\! mkdir /tmp/tbs_test_path
create tablespace tbs_test location '/tmp/tbs_test_path';
CREATE INDEX t_global_ph_idx_with_tbs ON ora_ph_t(a ASC ,b DESC) TABLESPACE tbs_test GLOBAL PARTITION BY hash(a) partitions 2;
DROP INDEX t_global_ph_idx_with_tbs;
drop tablespace tbs_test;
\! rm -rf /tmp/tbs_test_path

Create a index with COMPRESS/NOCOMPRESS/LOGGING/NOLOGGING options.

create table comp_log_test(id int);
create index idx_id on comp_log_test(id) nologging compress tablespace pg_default;

Create a index with schema name.

create table t1(id int);
create index hahaha.index_t1_id on t1(id);

Compatibility

CREATE INDEX is a LightDB language extension. There are no provisions for indexes in the SQL standard.

See Also

ALTER INDEX, DROP INDEX, REINDEX