Description
CREATE INDEX constructs an index
index_name
on the specified table.
Tip: Indexes are primarily used to enhance database performance.
But inappropriate use will result in slower performance.
In the first syntax shown above, the key field(s) for the
index are specified as column names.
Multiple fields can be specified if the index access method supports
multicolumn indexes.
In the second syntax shown above, an index is defined on the result
of a user-specified function func_name applied to one or more
columns of a single table. These functional
indexes can be used to obtain fast access to data based
on operators that would normally require some transformation to apply
them to the base data. For example, a functional index on
upper(col) would allow the clause
WHERE upper(col) = 'JIM' to use an index.
PostgreSQL provides B-tree, R-tree, hash,
and GiST access methods for indexes. The B-tree access method is an
implementation of Lehman-Yao high-concurrency B-trees. The R-tree
access method implements standard R-trees using Guttman's quadratic
split algorithm. The hash access method is an implementation of
Litwin's linear hashing. We mention the algorithms used solely to
indicate that all of these access methods are fully dynamic and do
not have to be optimized periodically (as is the case with, for
example, static hash access methods).
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 somehow more interesting 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.
The expression used in the WHERE clause may refer
only to columns of the underlying table (but it can use all columns,
not only the one(s) being indexed). Presently, subqueries and
aggregate expressions are also forbidden in WHERE.
All functions and operators used in an index definition must be
immutable, that is, their results must depend only on
their input 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, remember to mark the function immutable
when you create it.
Use DROP INDEX
to remove an index.
Notes
The PostgreSQL
query optimizer will consider using a B-tree index whenever
an indexed attribute is involved in a comparison using one of:
<, <=, =, >=, >
The PostgreSQL
query optimizer will consider using an R-tree index whenever
an indexed attribute is involved in a comparison using one of:
<<, &<, &>, >>, @, ~=, &&
The PostgreSQL
query optimizer will consider using a hash index whenever
an indexed attribute is involved in a comparison using
the = operator.
Testing has shown PostgreSQL's hash indexes to be similar or slower
than B-tree indexes, and the index size and build time for hash
indexes is much worse. Hash indexes also suffer poor performance
under high concurrency. For these reasons, hash index use is
discouraged.
Currently, only the B-tree and gist access methods support multicolumn
indexes. Up to 32 keys 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 field'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. There are also some operator
classes with special purposes:
The operator classes box_ops and
bigbox_ops both support R-tree indexes on the
box data type.
The difference between them is that bigbox_ops
scales box coordinates down, to avoid floating-point exceptions from
doing multiplication, addition, and subtraction on very large
floating-point coordinates. (Note: this was true some time ago,
but currently the two operator classes both use floating point
and are effectively identical.)
The following query shows all defined operator classes:
SELECT am.amname AS acc_method,
opc.opcname AS ops_name
FROM pg_am am, pg_opclass opc
WHERE opc.opcamid = am.oid
ORDER BY acc_method, ops_name;
