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| PostgreSQL 8.2.6 Documentation | ||||
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CREATE [ UNIQUE ] INDEX [ CONCURRENTLY ] name ON table [ USING method ]
( { column | ( expression ) } [ opclass ] [, ...] )
[ WITH ( storage_parameter = value [, ... ] ) ]
[ TABLESPACE tablespace ]
[ WHERE predicate ]CREATE INDEX constructs an index index_name on the specified 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.
PostgreSQL provides the index methods B-tree, hash, GiST, and 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 11.7 for more discussion.
The expression used in the WHERE clause may 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.
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.
When this option is used, PostgreSQL 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.
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.
The name (possibly schema-qualified) of the table to be indexed.
The name of the index method to be used. Choices are btree, hash, gist, and gin. The default method is btree.
The name of a column of the table.
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 may be omitted if the expression has the form of a function call.
The name of an operator class. See below for details.
The name of an index-method-specific storage parameter. See below for details.
The tablespace in which to create the index. If not specified, default_tablespace is used, or the database's default tablespace if default_tablespace is an empty string.
The constraint expression for a partial index.
The WITH clause can specify storage parameters for indexes. Each index method can have its own set of allowed storage parameters. The built-in index methods all accept a single parameter:
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 (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 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.
Creating an index can interfere with regular operation of a database. Normally PostgreSQL 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. 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.
PostgreSQL supports building indexes without locking out writes. This method is invoked by specifying the CONCURRENTLY option of CREATE INDEX. When this option is used, PostgreSQL must perform two scans of the table, and in addition it must wait for all existing transactions 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 may slow other operations.
If a problem arises during the second scan of the table, such as 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 may be incomplete; however it will still consume update overhead. 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. However, since REINDEX does not support concurrent builds, this option is unlikely to seem attractive.)
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 in parallel, but only one concurrent index build can occur on a table at a time. In both cases, no other types of schema modification on the table are allowed meanwhile. Another difference is that a regular CREATE INDEX command can be performed within a transaction block, but CREATE INDEX CONCURRENTLY cannot.
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 and GiST index methods support multicolumn indexes. Up to 32 fields may be specified by default. (This limit can be altered when building PostgreSQL.) Only B-tree currently supports unique indexes.
An operator class 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 making an index. More information about operator classes is in Section 11.8 and in Section 33.14.
Use DROP INDEX to remove an index.
Indexes are not used for IS NULL clauses by default. The best way to use indexes in such cases is to create a partial index using an IS NULL predicate.
Prior releases of PostgreSQL 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 B-tree index on the column title in the table films:
CREATE UNIQUE INDEX title_idx ON films (title);
To create an index on the expression lower(title), allowing efficient case-insensitive searches:
CREATE INDEX lower_title_idx ON films ((lower(title)));
To create an index with non-default fill factor:
CREATE UNIQUE INDEX title_idx ON films (title) WITH (fillfactor = 70);
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);