Suppose we have a table similar to this:
CREATE TABLE test1 ( id integer, content varchar );
and the application issues many queries of the form:
SELECT content FROM test1 WHERE id =
With no advance preparation, the system would have to scan the entire
table, row by row, to find all
matching entries. If there are many rows in
and only a few rows (perhaps zero
or one) that would be returned by such a query, this is clearly an
inefficient method. But if the system has been instructed to maintain an
index on the
column, it can use a more
efficient method for locating matching rows. For instance, it
might only have to walk a few levels deep into a search tree.
A similar approach is used in most non-fiction books: terms and concepts that are frequently looked up by readers are collected in an alphabetic index at the end of the book. The interested reader can scan the index relatively quickly and flip to the appropriate page(s), rather than having to read the entire book to find the material of interest. Just as it is the task of the author to anticipate the items that readers are likely to look up, it is the task of the database programmer to foresee which indexes will be useful.
The following command can be used to create an index on the
column, as discussed:
CREATE INDEX test1_id_index ON test1 (id);
can be chosen
freely, but you should pick something that enables you to remember
later what the index was for.
To remove an index, use the
Indexes can be added to and removed from tables at any time.
Once an index is created, no further intervention is required: the
system will update the index when the table is modified, and it will
use the index in queries when it thinks doing so would be more efficient
than a sequential table scan. But you might have to run the
command regularly to update
statistics to allow the query planner to make educated decisions.
for information about
how to find out whether an index is used and when and why the
planner might choose
to use an index.
Indexes can also benefit
commands with search conditions.
Indexes can moreover be used in join searches. Thus,
an index defined on a column that is part of a join condition can
also significantly speed up queries with joins.
Creating an index on a large table can take a long time. By default,
allows reads (
statements) to occur
on the table in parallel with index creation, but writes (
) are blocked until the index build is finished.
In production environments this is often unacceptable.
It is possible to allow writes to occur in parallel with index
creation, but there are several caveats to be aware of -
for more information see
Building Indexes Concurrently
After an index is created, the system has to keep it synchronized with the table. This adds overhead to data manipulation operations. Indexes can also prevent the creation of heap-only tuples . Therefore indexes that are seldom or never used in queries should be removed.