Updated on 2024-05-07 GMT+08:00

Genetic Query Optimizer

This section describes parameters related to genetic query optimizer. The genetic query optimizer (GEQO) is an algorithm that plans queries by using heuristic searching. This algorithm reduces planning time for complex queries and the costs of producing plans are sometimes inferior to those found by the normal exhaustive-search algorithm.

geqo

Parameter description: Specifies whether to enable the genetic query optimization.

This parameter is a USERSET parameter. Set it based on instructions provided in Table 1.

It is best not to turn it off in execution. geqo_threshold provides more subtle control of GEQO.

If this parameter is modified by running the gs_guc reload command and the connection of a session on the current node is not from the client but from another node in the cluster to which the node belongs, this parameter does not take effect immediately on the session after the gs_guc reload command is executed. The setting takes effect only after the connection node is disconnected and then reconnected.

Value range: Boolean

  • on indicates that the genetic query optimization is enabled.
  • off indicates that the genetic query optimization is disabled.

Default value: on

geqo_threshold

Parameter description: Specifies the number of FROM items. Genetic query optimization is used to plan queries when the number of statements executed is greater than this value.

This parameter is a USERSET parameter. Set it based on instructions provided in Table 1.

  • For simpler queries it is best to use the regular, exhaustive-search planner, but for queries with many tables it is better to use GEQO to manage the queries.
  • A FULL OUTER JOIN construct counts as only one FROM item.

Value range: an integer ranging from 2 to 2147483647

Default value: 12

geqo_effort

Parameter description: Controls the trade-off between planning time and query plan quality in GEQO.

This parameter is a USERSET parameter. Set it based on instructions provided in Table 1.

geqo_effort does not do anything directly. This parameter is only used to compute the default values for the other variables that influence GEQO behavior. If you prefer, you can manually set the other parameters instead.

Value range: an integer ranging from 1 to 10

Larger values increase the time spent in query planning, but also increase the probability that an efficient query plan is chosen.

Default value: 5

geqo_pool_size

Parameter description: Controls the pool size used by GEQO, that is, the number of individuals in the genetic population.

This parameter is a USERSET parameter. Set it based on instructions provided in Table 1.

Value range: an integer ranging from 0 to 2147483647

The value of this parameter must be at least 2, and useful values are typically from 100 to 1000. If this parameter is set to 0, GaussDB selects a proper value based on geqo_effort and the number of tables.

Default value: 0

geqo_generations

Parameter description: Specifies the number of iterations of the GEQO.

This parameter is a USERSET parameter. Set it based on instructions provided in Table 1.

Value range: an integer ranging from 0 to 2147483647

The value of this parameter must be at least 1, and useful values are typically from 100 to 1000. If it is set to 0, a suitable value is chosen based on geqo_pool_size.

Default value: 0

geqo_selection_bias

Parameter description: Specifies the selection bias used by GEQO. The selection bias is the selective pressure within the population.

This parameter is a USERSET parameter. Set it based on instructions provided in Table 1.

Value range: a floating point number ranging from 1.5 to 2.0

Default value: 2

geqo_seed

Parameter description: Specifies the initial value of the random number generator used by GEQO to select random paths through the join order search space.

This parameter is a USERSET parameter. Set it based on instructions provided in Table 1.

Value range: a floating point number ranging from 0.0 to 1.0

Varying the value changes the set of join paths explored, and may result in a better or worse best path being found.

Default value: 0