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Db partition analytics cmeyers2 Keep old primary key based analytics gathering for unpartitioned tables. Use created time on new partitioned tables. 80 million partitioned + 1.5 million unpartitioned Events Query awx-manage gather_analytics --dry-run Time Micro Benchmark Query Time* Query Only Time** sequential index scan, multiple ::json casts, 100,000 event batches 102m7.836s 6s 80 minutes sequential index scan, optimized json cast, 100,000 event batches 48m9.276s 2.2s 30.4 minutes sequential index scan, optimized json cast, 1,00,000 event batches 39m35.094s 10s 13.3 minutes sequential table scan, optimized json cast, per-partition batch 600,000 *** 36m42.081s 11.5s 25.5 minutes *micro benchmarking consists of simply copying a query, running it manually, and observing the runtime. **micro benchmark time x (80 million / batch size) **Note that this testing does NOT include the extra modified range query that is needed for correctness. We expect this to be quite fast and is only needed to catch edge case events. Reviewed-by: Ladislav Smola <lsmola@redhat.com> Reviewed-by: Elijah DeLee <kdelee@redhat.com>
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AWX provides a web-based user interface, REST API, and task engine built on top of Ansible. It is one of the upstream projects for Red Hat Ansible Automation Platform.
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