Acelerando a Manada. Parallel Queries no PostgreSQL
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1 Acelerando a Manada Parallel Queries no PostgreSQL
2 Paralelismo Intra-Consulta em PostgreSQL pré 9.6
3 Paralelismo Intra-Consulta - Requisitos Apresenta maiores ganhos em grandes volumes (Pode não encaixar em índices muito seletivos) Execução sequencial pode ser mais rápida Limitações de implementação - Consultas que contém operações de modificações de dados - Consultas que possam ser suspensas (Cursores) - Subconsulta de uma consulta já paralelizada - Nível de Isolamento de Transação = Serializable
4 Configuração max_worker_processes (8) max_parallel_workers_per_gather (2) max_parallel_workers (8) * dynamic_shared_memory_type (posix)
5 PostgreSQL 9.6 Paralelismo inicia com Busca Sequencial Parallel Join - Nested Loop - Hash Join Não disponível para índices
6 cliente=> EXPLAIN ANALYZE SELECT COUNT(*) FROM documento; Aggregate (cost= rows=1 width=8) (actual time= rows=1 loops=1) -> Seq Scan on documento (cost= rows= width=0) (actual time= rows= loops=1) Planning time: ms Execution time: ms (4 registros) Aggregate (cost= rows=1 width=8) (actual time= rows=1 loops=1) -> Seq Scan on documento (cost= rows= width=0) (actual time= rows= loops=1) Planning time: ms Execution time: ms (4 registros) Aggregate (cost= rows=1 width=8) (actual time= rows=1 loops=1) -> Seq Scan on documento (cost= rows= width=0) (actual time= rows= loops=1) Planning time: ms Execution time: ms (4 registros)
7 cliente=> EXPLAIN ANALYZE SELECT COUNT(*) FROM documento; Finalize Aggregate (cost= rows=1 width=8) (actual time= rows=1 loops=1) -> Gather (cost= rows=5 width=8) (actual time= rows=6 loops=1) Workers Planned: 5 Workers Launched: 5 -> Partial Aggregate (cost= rows=1 width=8) (actual time= rows=1 loops=6) -> Parallel Seq Scan on documento (cost= rows= width=0) (actual time= rows= loops=6) Planning time: ms Execution time: ms (8 registros) Finalize Aggregate (cost= rows=1 width=8) (actual time= rows=1 loops=1) -> Gather (cost= rows=5 width=8) (actual time= rows=6 loops=1) Workers Planned: 5 Workers Launched: 5 -> Partial Aggregate (cost= rows=1 width=8) (actual time= rows=1 loops=6) -> Parallel Seq Scan on documento (cost= rows= width=0) (actual time= rows= loops=6) Planning time: ms Execution time: ms (8 registros)
8 cliente=> EXPLAIN ANALYZE SELECT COUNT(*) FROM documento WHERE agenciaid = 36; QUERY PLAN Aggregate (cost= rows=1 width=8) (actual time= rows=1 loops=1) -> Seq Scan on documento (cost= rows= width=0) (actual time= rows= loops=1) Filter: (agenciaid = 36) Rows Removed by Filter: Planning time: ms Execution time: ms (6 registros) Aggregate (cost= rows=1 width=8) (actual time= rows=1 loops=1) -> Seq Scan on documento (cost= rows= width=0) (actual time= rows= loops=1) Filter: (agenciaid = 36) Rows Removed by Filter: Planning time: ms Execution time: ms Aggregate (cost= rows=1 width=8) (actual time= rows=1 loops=1) -> Seq Scan on documento (cost= rows= width=0) (actual time= rows= loops=1) Filter: (agenciaid = 36) Rows Removed by Filter: Planning time: ms Execution time: ms
9 cliente=> EXPLAIN ANALYZE SELECT COUNT(*) FROM documento WHERE agenciaid = 36; Finalize Aggregate (cost= rows=1 width=8) (actual time= rows=1 loops=1) -> Gather (cost= rows=5 width=8) (actual time= rows=6 loops=1) Workers Planned: 5 Workers Launched: 5 -> Partial Aggregate (cost= rows=1 width=8) (actual time= rows=1 loops=6) -> Parallel Seq Scan on documento (cost= rows=30108 width=0) (actual time= rows=25582 loops=6) Filter: (agenciaid = 36) Rows Removed by Filter: Planning time: ms Execution time: ms Finalize Aggregate (cost= rows=1 width=8) (actual time= rows=1 loops=1) -> Gather (cost= rows=5 width=8) (actual time= rows=6 loops=1) Workers Planned: 5 Workers Launched: 5 -> Partial Aggregate (cost= rows=1 width=8) (actual time= rows=1 loops=6) -> Parallel Seq Scan on documento (cost= rows=30108 width=0) (actual time= rows=25582 loops=6) Filter: (agenciaid = 36) Rows Removed by Filter: Planning time: ms Execution time: ms Finalize Aggregate (cost= rows=1 width=8) (actual time= rows=1 loops=1) -> Gather (cost= rows=5 width=8) (actual time= rows=6 loops=1) Workers Planned: 5 Workers Launched: 5 -> Partial Aggregate (cost= rows=1 width=8) (actual time= rows=1 loops=6) -> Parallel Seq Scan on documento (cost= rows=30108 width=0) (actual time= rows=25582 loops=6) Filter: (agenciaid = 36) Rows Removed by Filter: Planning time: ms Execution time: ms
10 cliente=> EXPLAIN ANALYZE SELECT COUNT(*) FROM documento JOIN agencia USING (agenciaid); Finalize Aggregate (cost= rows=1 width=8) (actual time= rows=1 loops=1) -> Gather (cost= rows=5 width=8) (actual time= rows=6 loops=1) Workers Planned: 5 Workers Launched: 5 -> Partial Aggregate (cost= rows=1 width=8) (actual time= rows=1 loops=6) -> Hash Join (cost= rows= width=0) (actual time= rows= loops=6) Hash Cond: (documento.agenciaid = agencia.agenciaid) -> Parallel Seq Scan on documento (cost= rows= width=4) (actual time= rows= loops=6) -> Hash (cost= rows=160 width=4) (actual time= rows=160 loops=6) Buckets: 1024 Batches: 1 Memory Usage: 14kB -> Seq Scan on agencia (cost= rows=160 width=4) (actual time= rows=160 loops=6) Planning time: ms Execution time: ms (13 registros) Finalize Aggregate (cost= rows=1 width=8) (actual time= rows=1 loops=1) -> Gather (cost= rows=5 width=8) (actual time= rows=6 loops=1) Workers Planned: 5 Workers Launched: 5 -> Partial Aggregate (cost= rows=1 width=8) (actual time= rows=1 loops=6) -> Hash Join (cost= rows= width=0) (actual time= rows= loops=6) Hash Cond: (documento.agenciaid = agencia.agenciaid) -> Parallel Seq Scan on documento (cost= rows= width=4) (actual time= rows= loops=6) -> Hash (cost= rows=160 width=4) (actual time= rows=160 loops=6) Buckets: 1024 Batches: 1 Memory Usage: 14kB -> Seq Scan on agencia (cost= rows=160 width=4) (actual time= rows=160 loops=6) Planning time: ms Execution time: ms (13 registros)
11 cliente=> EXPLAIN ANALYZE SELECT COUNT(*) FROM documento JOIN agencia USING (agenciaid); Aggregate (cost= rows=1 width=8) (actual time= rows=1 loops=1) -> Hash Join (cost= rows= width=0) (actual time= rows= loops=1) Hash Cond: (documento.agenciaid = agencia.agenciaid) -> Seq Scan on documento (cost= rows= width=4) (actual time= rows= loops=1) -> Hash (cost= rows=160 width=4) (actual time= rows=160 loops=1) Buckets: 1024 Batches: 1 Memory Usage: 14kB -> Seq Scan on agencia (cost= rows=160 width=4) (actual time= rows=160 loops=1) Planning time: ms Execution time: ms Aggregate (cost= rows=1 width=8) (actual time= rows=1 loops=1) -> Hash Join (cost= rows= width=0) (actual time= rows= loops=1) Hash Cond: (documento.agenciaid = agencia.agenciaid) -> Seq Scan on documento (cost= rows= width=4) (actual time= rows= loops=1) -> Hash (cost= rows=160 width=4) (actual time= rows=160 loops=1) Buckets: 1024 Batches: 1 Memory Usage: 14kB -> Seq Scan on agencia (cost= rows=160 width=4) (actual time= rows=160 loops=1) Planning time: ms Execution time: ms Aggregate (cost= rows=1 width=8) (actual time= rows=1 loops=1) -> Hash Join (cost= rows= width=0) (actual time= rows= loops=1) Hash Cond: (documento.agenciaid = agencia.agenciaid) -> Seq Scan on documento (cost= rows= width=4) (actual time= rows= loops=1) -> Hash (cost= rows=160 width=4) (actual time= rows=160 loops=1) Buckets: 1024 Batches: 1 Memory Usage: 14kB -> Seq Scan on agencia (cost= rows=160 width=4) (actual time= rows=160 loops=1) Planning time: ms Execution time: ms
12 PostgreSQL 10 Parallel Bitmap Heap Scan Parallel Merge Join
13 PostgreSQL 11 Parallel Hash Join Parallel Append CREATE TABLE AS CREATE MATERIALIZED VIEW SELECT INTO CREATE INDEX - Também em tabelas particionadas
14 Referências EDB Query Parallelism In PostgreSQL Dilip Kumar PostgreSQL Documentation PostgreSQL 11 New Features Hewlett Packard Enterprise
15
16 Obrigado! /atuasistemas
Parallel Query In PostgreSQL
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