CREATE INDEX — define a new index
CREATE [ UNIQUE ] INDEX [ CONCURRENTLY ] [ [ IF NOT EXISTS ]name
] ON [ ONLY ]table_name
[ USINGmethod
] ( {column_name
| (expression
) } [ COLLATEcollation
] [opclass
[ (opclass_parameter
=value
[, ... ] ) ] ] [ ASC | DESC ] [ NULLS { FIRST | LAST } ] [ LOCAL | GLOBAL ] [, ...] ) [ INCLUDE (column_name
[, ...] ) ] [ WITH (storage_parameter
[=value
] [, ... ] ) ] [ TABLESPACEtablespace_name
] [ WHEREpredicate
]
CREATE INDEX
constructs an index on the specified column(s)
of the specified relation, which can be a table or a materialized view.
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, GiST, SP-GiST, GIN, and BRIN. 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 11.8 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.
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.
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 and the GiST index access methods support this
feature. In B-tree and the GiST 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
,
gist
, spgist
, gin
, and
brin
.
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.
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, GiST and SP-GiST 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 60.4.2. Set to
ON
or OFF
to enable or
disable the optimization. (Alternative spellings of
ON
and OFF
are allowed as
described in Section 17.1.) The default is
ON
.
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.
GiST indexes additionally accept this parameter:
buffering
(enum
)
Determines whether the buffering build technique described in
Section 61.4.1 is used to build the index. With
OFF
it is disabled, with ON
it is enabled, and
with AUTO
it is initially disabled, but turned on
on-the-fly once the index size reaches effective_cache_size. The default is AUTO
.
GIN indexes accept different parameters:
fastupdate
(boolean
)
This setting controls usage of the fast update technique described in
Section 63.4.1. It is a Boolean parameter:
ON
enables fast update, OFF
disables it.
The default is ON
.
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.
BRIN indexes accept different parameters:
pages_per_range
(integer
)
Defines the number of table blocks that make up one block range for
each entry of a BRIN index (see Section 64.1
for more details). The default is 128
.
autosummarize
(boolean
)
Defines whether a summarization run is queued for the previous page
range whenever an insertion is detected on the next one.
See Section 64.1.1 for more details.
The default is off
.
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 13) 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.
See Chapter 11 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, GiST, GIN, and BRIN 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 11.10 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.
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 because
it had no significant advantages over the GiST method.
If USING rtree
is specified, CREATE INDEX
will interpret it as USING gist
, to simplify conversion
of old databases to GiST.
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 a GiST index on a point attribute so that we can efficiently use box operators on the result of the conversion function:
CREATE INDEX pointloc ON points USING gist (box(location,location)); SELECT * FROM points WHERE box(location,location) && '(0,0),(1,1)'::box;
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;
CREATE INDEX
is a
LightDB language extension. There
are no provisions for indexes in the SQL standard.