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postgresqlparallel-processing
olokki
olokki

Reputation: 1027

PostgreSQL 9.6 parallel aggregates

PostgreSQL in version 9.6 adds support for parallel aggregates.

With 9.6, PostgreSQL introduces initial support for parallel execution of large queries. Only strictly read-only queries where the driving table is accessed via a sequential scan can be parallelized. Hash joins and nested loops can be performed in parallel, as can aggregation (for supported aggregates). Much remains to be done, but this is already a useful set of features.

Upvotes: 4

Views: 1662

Answers (1)

olokki
olokki

Reputation: 1027

PostgreSQL 9.6 User-defined Aggregates documentation now mentions parallel aggregates:

35.10.4. Partial Aggregation

Optionally, an aggregate function can support partial aggregation. The idea of partial aggregation is to run the aggregate's state transition function over different subsets of the input data independently, and then to combine the state values resulting from those subsets to produce the same state value that would have resulted from scanning all the input in a single operation. This mode can be used for parallel aggregation by having different worker processes scan different portions of a table. Each worker produces a partial state value, and at the end those state values are combined to produce a final state value. (In the future this mode might also be used for purposes such as combining aggregations over local and remote tables; but that is not implemented yet.)

To support partial aggregation, the aggregate definition must provide a combine function, which takes two values of the aggregate's state type (representing the results of aggregating over two subsets of the input rows) and produces a new value of the state type, representing what the state would have been after aggregating over the combination of those sets of rows. It is unspecified what the relative order of the input rows from the two sets would have been. This means that it's usually impossible to define a useful combine function for aggregates that are sensitive to input row order.

Upvotes: 1

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