|PostgreSQL Reference Manual - Volume 1 - SQL Language Reference|
by The PostgreSQL Global Development Group
Paperback (6"x9"), 716 pages
RRP £32.00 ($49.95)
Sales of this book support the PostgreSQL project! Get a printed copy>>>
9.7 Partial Indexes
A partial index is an index built over a subset of a table; the subset is defined by a conditional expression (called the predicate of the partial index). The index contains entries for only those table rows that satisfy the predicate. Partial indexes are a specialized feature, but there are several situations in which they are useful.
One major reason for using a partial index is to avoid indexing common values. Since a query searching for a common value (one that accounts for more than a few percent of all the table rows) will not use the index anyway, there is no point in keeping those rows in the index at all. This reduces the size of the index, which will speed up queries that do use the index. It will also speed up many table update operations because the index does not need to be updated in all cases. section 9.7 Partial Indexes shows a possible application of this idea.
Setting up a Partial Index to Exclude Common Values:
Suppose you are storing web server access logs in a database. Most accesses originate from the IP address range of your organization but some are from elsewhere (say, employees on dial-up connections). If your searches by IP are primarily for outside accesses, you probably do not need to index the IP range that corresponds to your organization's subnet.
Assume a table like this:
CREATE TABLE access_log ( url varchar, client_ip inet, ... );
To create a partial index that suits our example, use a command such as this:
CREATE INDEX access_log_client_ip_ix ON access_log (client_ip) WHERE NOT (client_ip > inet '192.168.100.0' AND client_ip < inet '192.168.100.255');
A typical query that can use this index would be:
SELECT * FROM access_log WHERE url = '/index.html' AND client_ip = inet '184.108.40.206';
A query that cannot use this index is:
SELECT * FROM access_log WHERE client_ip = inet '192.168.100.23';
Observe that this kind of partial index requires that the common values be predetermined. If the distribution of values is inherent (due to the nature of the application) and static (not changing over time), this is not difficult, but if the common values are merely due to the coincidental data load this can require a lot of maintenance work to change the index definition from time to time.
Another possible use for a partial index is to exclude values from the index that the typical query workload is not interested in; this is shown in section 9.7 Partial Indexes. This results in the same advantages as listed above, but it prevents the “uninteresting” values from being accessed via that index at all, even if an index scan might be profitable in that case. Obviously, setting up partial indexes for this kind of scenario will require a lot of care and experimentation.
Setting up a Partial Index to Exclude Uninteresting Values:
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 those are the most-accessed rows, you can improve performance by creating an index on just the unbilled rows. The command to create the index would look like this:
CREATE INDEX orders_unbilled_index ON orders (order_nr) WHERE billed is not true;
A possible query to use this index would be
SELECT * FROM orders WHERE billed is not true AND order_nr < 10000;
However, the index can also be used in queries that do not involve
order_nr at all, e.g.,
SELECT * FROM orders WHERE billed is not true AND amount > 5000.00;
This is not as efficient as a partial index on the
amount column would be, since the system has to
scan the entire index. Yet, if there are relatively few unbilled
orders, using this partial index just to find the unbilled orders
could be a win.
Note that this query cannot use this index:
SELECT * FROM orders WHERE order_nr = 3501;
The order 3501 may be among the billed or among the unbilled orders.
section 9.7 Partial Indexes also illustrates that the
indexed column and the column used in the predicate do not need to
match. PostgreSQL supports partial
indexes with arbitrary predicates, so long as only columns of the
table being indexed are involved. However, keep in mind that the
predicate must match the conditions used in the queries that
are supposed to benefit from the index. To be precise, a partial
index can be used in a query only if the system can recognize that
WHERE condition of the query mathematically implies
the predicate of the index.
PostgreSQL does not have a sophisticated
theorem prover that can recognize mathematically equivalent
expressions that are written in different forms. (Not
only is such a general theorem prover extremely difficult to
create, it would probably be too slow to be of any real use.)
The system can recognize simple inequality implications, for example
“x < 1” implies “x < 2”; otherwise
the predicate condition must exactly match part of the query's
or the index will not be recognized to be usable. Matching takes
place at query planning time, not at run time. As a result,
parameterized query clauses will not work with a partial index. For
example a prepared query with a parameter might specify
“x < ?” which will never imply
“x < 2” for all possible values of the parameter.
A third possible use for partial indexes does not require the index to be used in queries at all. The idea here is to create a unique index over a subset of a table, as in section 9.7 Partial Indexes. This enforces uniqueness among the rows that satisfy the index predicate, without constraining those that do not.
Setting up a Partial Unique Index:
Suppose that we have a table describing test outcomes. We wish to ensure that there is only one “successful” entry for a given subject and target combination, but there might be any number of “unsuccessful” entries. Here is one way to do it:
CREATE TABLE tests ( subject text, target text, success boolean, ... ); CREATE UNIQUE INDEX tests_success_constraint ON tests (subject, target) WHERE success;
This is a particularly efficient way of doing it when there are few successful tests and many unsuccessful ones.
Finally, a partial index can also be used to override the system's query plan choices. It may occur that data sets with peculiar distributions will cause the system to use an index when it really should not. In that case the index can be set up so that it is not available for the offending query. Normally, PostgreSQL makes reasonable choices about index usage (e.g., it avoids them when retrieving common values, so the earlier example really only saves index size, it is not required to avoid index usage), and grossly incorrect plan choices are cause for a bug report.
Keep in mind that setting up a partial index indicates that you know at least as much as the query planner knows, in particular you know when an index might be profitable. Forming this knowledge requires experience and understanding of how indexes in PostgreSQL work. In most cases, the advantage of a partial index over a regular index will not be much.
More information about partial indexes can be found in [Stonebraker, M, 1989b], section 14.16 Proceedings and Articles, and [Seshardri, 1995].
|ISBN 0954612027||PostgreSQL Reference Manual - Volume 1 - SQL Language Reference||See the print edition|