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inpostgrespro/aqo (press backspace or delete to remove)Intro If we make 'JOB' benchmark results with specific preferences ( script ): fsync = off
max_parallel_workers_per_gather = 0
statement_timeout = 600000
from_collapse_limit = 20
join_collapse_limit ...
- Last updated on Apr 18, 2022
Join Order Benchmark (AQO v. 1.1) Join Order Benchmark (AQO v. 1.2)
- Last updated on Feb 6, 2020
Common differences c-cpp.yml - names of branches, patch filename. stable13 - > stable14 QueryID machinery. From stable14 we can use the jumbling technique to generate queryid or another lightweight ...
- Last updated on Dec 22, 2022
Structure of main branches: master - development, may be non-stable stable9_6 - branch for PostgreSQL 9.6 (no longer supported). stable11 - for PostgreSQL 10 and 11 stable12, stable13, stable14 ... - for ...
- Last updated on Oct 6, 2022
How AQO accelerates queries execution over constant dataset postgresql.conf custom options: shared_preload_libraries = 'aqo' aqo.mode = 'intelligent' min_parallel_table_scan_size = 0 min_parallel_index_scan_size ...
- Last updated on Feb 6, 2020
How AQO v.1.2 accelerates queries execution over constant dataset postgresql.conf custom options: shared_preload_libraries = 'aqo' min_parallel_table_scan_size = 0 min_parallel_index_scan_size ...
- Last updated on Feb 6, 2020
To realize how stable AQO code is, before a release it should be tested according to the steps: make check , make check-world , of course. Stress test. See the bash script: ./configure --enable-tap-tests ...
- Last updated on Jul 12, 2022
Why are we not get the optimal query plan? Planner get incorrect cost estimations for plan nodes. GEQO algorithm can't achieve global optimum. If we use AQO we have correct estimations for each node ...
- Last updated on Feb 21, 2020
GUCs aqo.mode - defines how AQO works with incoming queries. Possible modes: DISABLED , CONTROLLED , LEARN , INTELLIGENT and FROZEN . aqo.show_hash - hash value computed by a query tree which have a sense ...
- Last updated on Feb 6, 2023
GUCs aqo.min_neighbors_for_predicting - minimum number of neighbors is used for cardinality prediction: if there are fewer of them, AQO won't make prediction. aqo.predict_with_few_neighbors - enable ...
- Last updated on Feb 7, 2023