These configuration parameters provide a crude method of
influencing the query plans chosen by the query optimizer. If
the default plan chosen by the optimizer for a particular query
is not optimal, a temporary solution is to use one
of these configuration parameters to force the optimizer to
choose a different plan.
Better ways to improve the quality of the
plans chosen by the optimizer include adjusting the planer cost
constants (see Section 18.7.2),
running ANALYZE manually, increasing
the value of the default_statistics_target configuration parameter,
and increasing the amount of statistics collected for
specific columns using ALTER TABLE SET
STATISTICS.
enable_bitmapscan (boolean)
Enables or disables the query planner's use of bitmap-scan plan
types. The default is on.
enable_hashagg (boolean)
Enables or disables the query planner's use of hashed
aggregation plan types. The default is on.
enable_hashjoin (boolean)
Enables or disables the query planner's use of hash-join plan
types. The default is on.
enable_indexscan (boolean)
Enables or disables the query planner's use of index-scan plan
types. The default is on.
enable_material (boolean)
Enables or disables the query planner's use of materialization.
It is impossible to suppress materialization entirely,
but turning this variable off prevents the planner from inserting
materialize nodes except in cases where it is required for correctness.
The default is on.
enable_mergejoin (boolean)
Enables or disables the query planner's use of merge-join plan
types. The default is on.
enable_nestloop (boolean)
Enables or disables the query planner's use of nested-loop join
plans. It is impossible to suppress nested-loop joins entirely,
but turning this variable off discourages the planner from using
one if there are other methods available. The default is
on.
enable_seqscan (boolean)
Enables or disables the query planner's use of sequential scan
plan types. It is impossible to suppress sequential scans
entirely, but turning this variable off discourages the planner
from using one if there are other methods available. The
default is on.
enable_sort (boolean)
Enables or disables the query planner's use of explicit sort
steps. It is impossible to suppress explicit sorts entirely,
but turning this variable off discourages the planner from
using one if there are other methods available. The default
is on.
enable_tidscan (boolean)
Enables or disables the query planner's use of TID
scan plan types. The default is on.
The cost variables described in this section are measured
on an arbitrary scale. Only their relative values matter, hence
scaling them all up or down by the same factor will result in no change
in the planner's choices. By default, these cost variables are based on
the cost of sequential page fetches; that is,
seq_page_cost is conventionally set to 1.0
and the other cost variables are set with reference to that. But
you can use a different scale if you prefer, such as actual execution
times in milliseconds on a particular machine.
Note: Unfortunately, there is no well-defined method for determining ideal
values for the cost variables. They are best treated as averages over
the entire mix of queries that a particular installation will receive. This
means that changing them on the basis of just a few experiments is very
risky.
seq_page_cost (floating point)
Sets the planner's estimate of the cost of a disk page fetch
that is part of a series of sequential fetches. The default is 1.0.
This value can be overridden for a particular tablespace by setting
the tablespace parameter of the same name
(see ALTER TABLESPACE).
random_page_cost (floating point)
Sets the planner's estimate of the cost of a
non-sequentially-fetched disk page. The default is 4.0.
This value can be overridden for a particular tablespace by setting
the tablespace parameter of the same name
(see ALTER TABLESPACE).
Reducing this value relative to seq_page_cost
will cause the system to prefer index scans; raising it will
make index scans look relatively more expensive. You can raise
or lower both values together to change the importance of disk I/O
costs relative to CPU costs, which are described by the following
parameters.
Tip: Although the system will let you set random_page_cost to
less than seq_page_cost, it is not physically sensible
to do so. However, setting them equal makes sense if the database
is entirely cached in RAM, since in that case there is no penalty
for touching pages out of sequence. Also, in a heavily-cached
database you should lower both values relative to the CPU parameters,
since the cost of fetching a page already in RAM is much smaller
than it would normally be.
cpu_tuple_cost (floating point)
Sets the planner's estimate of the cost of processing
each row during a query.
The default is 0.01.
cpu_index_tuple_cost (floating point)
Sets the planner's estimate of the cost of processing
each index entry during an index scan.
The default is 0.005.
cpu_operator_cost (floating point)
Sets the planner's estimate of the cost of processing each
operator or function executed during a query.
The default is 0.0025.
effective_cache_size (integer)
Sets the planner's assumption about the effective size of the
disk cache that is available to a single query. This is
factored into estimates of the cost of using an index; a
higher value makes it more likely index scans will be used, a
lower value makes it more likely sequential scans will be
used. When setting this parameter you should consider both
PostgreSQL's shared buffers and the
portion of the kernel's disk cache that will be used for
PostgreSQL data files. Also, take
into account the expected number of concurrent queries on different
tables, since they will have to share the available
space. This parameter has no effect on the size of shared
memory allocated by PostgreSQL, nor
does it reserve kernel disk cache; it is used only for estimation
purposes. The system also does not assume data remains in
the disk cache between queries. The default is 128 megabytes
(128MB).
The genetic query optimizer (GEQO) is an algorithm that does query
planning using heuristic searching. This reduces planning time for
complex queries (those joining many relations), at the cost of producing
plans that are sometimes inferior to those found by the normal
exhaustive-search algorithm.
For more information see Chapter 51.
geqo (boolean)
Enables or disables genetic query optimization.
This is on by default. It is usually best not to turn it off in
production; the geqo_threshold variable provides
more granular control of GEQO.
geqo_threshold (integer)
Use genetic query optimization to plan queries with at least
this many FROM items involved. (Note that a
FULL OUTER JOIN construct counts as only one FROM
item.) The default is 12. For simpler queries it is usually best
to use the regular, exhaustive-search planner, but for queries with
many tables the exhaustive search takes too long, often
longer than the penalty of executing a suboptimal plan. Thus,
a threshold on the size of the query is a convenient way to manage
use of GEQO.
geqo_effort
(integer)
Controls the trade-off between planning time and query plan
quality in GEQO. This variable must be an integer in the
range from 1 to 10. The default value is five. Larger values
increase the time spent doing query planning, but also
increase the likelihood that an efficient query plan will be
chosen.
geqo_effort doesn't actually do anything
directly; it is only used to compute the default values for
the other variables that influence GEQO behavior (described
below). If you prefer, you can set the other parameters by
hand instead.
geqo_pool_size (integer)
Controls the pool size used by GEQO, that is the
number of individuals in the genetic population. It must be
at least two, and useful values are typically 100 to 1000. If
it is set to zero (the default setting) then a suitable
value is chosen based on geqo_effort and
the number of tables in the query.
geqo_generations (integer)
Controls the number of generations used by GEQO, that is
the number of iterations of the algorithm. It must
be at least one, and useful values are in the same range as
the pool size. If it is set to zero (the default setting)
then a suitable value is chosen based on
geqo_pool_size.
geqo_selection_bias (floating point)
Controls the selection bias used by GEQO. The selection bias
is the selective pressure within the population. Values can be
from 1.50 to 2.00; the latter is the default.
geqo_seed (floating point)
Controls the initial value of the random number generator used
by GEQO to select random paths through the join order search space.
The value can range from zero (the default) to one. Varying the
value changes the set of join paths explored, and may result in a
better or worse best path being found.
Sets the default statistics target for table columns without
a column-specific target set via ALTER TABLE
SET STATISTICS. Larger values increase the time needed to
do ANALYZE, but might improve the quality of the
planner's estimates. The default is 100. For more information
on the use of statistics by the PostgreSQL
query planner, refer to Section 14.2.
constraint_exclusion (enum)
Controls the query planner's use of table constraints to
optimize queries.
The allowed values of constraint_exclusion are
on (examine constraints for all tables),
off (never examine constraints), and
partition (examine constraints only for inheritance child
tables and UNION ALL subqueries).
partition is the default setting.
It is often used with inheritance and partitioned tables to
improve performance.
When this parameter allows it for a particular table, the planner
compares query conditions with the table's CHECK
constraints, and omits scanning tables for which the conditions
contradict the constraints. For example:
CREATE TABLE parent(key integer, ...);
CREATE TABLE child1000(check (key between 1000 and 1999)) INHERITS(parent);
CREATE TABLE child2000(check (key between 2000 and 2999)) INHERITS(parent);
...
SELECT * FROM parent WHERE key = 2400;
With constraint exclusion enabled, this SELECT
will not scan child1000 at all, improving performance.
Currently, constraint exclusion is enabled by default
only for cases that are often used to implement table partitioning.
Turning it on for all tables imposes extra planning overhead that is
quite noticeable on simple queries, and most often will yield no
benefit for simple queries. If you have no partitioned tables
you might prefer to turn it off entirely.
Refer to Section 5.9.4 for
more information on using constraint exclusion and partitioning.
cursor_tuple_fraction (floating point)
Sets the planner's estimate of the fraction of a cursor's rows that
will be retrieved. The default is 0.1. Smaller values of this
setting bias the planner towards using "fast start" plans
for cursors, which will retrieve the first few rows quickly while
perhaps taking a long time to fetch all rows. Larger values
put more emphasis on the total estimated time. At the maximum
setting of 1.0, cursors are planned exactly like regular queries,
considering only the total estimated time and not how soon the
first rows might be delivered.
from_collapse_limit (integer)
The planner will merge sub-queries into upper queries if the
resulting FROM list would have no more than
this many items. Smaller values reduce planning time but might
yield inferior query plans. The default is eight.
For more information see Section 14.3.
Setting this value to geqo_threshold or more
may trigger use of the GEQO planner, resulting in non-optimal
plans. See Section 18.7.3.
join_collapse_limit (integer)
The planner will rewrite explicit JOIN
constructs (except FULL JOINs) into lists of
FROM items whenever a list of no more than this many items
would result. Smaller values reduce planning time but might
yield inferior query plans.
By default, this variable is set the same as
from_collapse_limit, which is appropriate
for most uses. Setting it to 1 prevents any reordering of
explicit JOINs. Thus, the explicit join order
specified in the query will be the actual order in which the
relations are joined. Because the query planner does not always choose
the optimal join order, advanced users can elect to
temporarily set this variable to 1, and then specify the join
order they desire explicitly.
For more information see Section 14.3.
Setting this value to geqo_threshold or more
may trigger use of the GEQO planner, resulting in non-optimal
plans. See Section 18.7.3.