Hello,
As I understand you should not have any issues with reading 200K records in postgres. Unless your tables are being heavily written to at the same time or over indexed (or not indexed at all), you could also check how much your tables have ‘bloated’ to see whether or not you need to run a vacuum on it.
SELECT schemaname, relname, n_live_tup, n_dead_tup, trunc(100*n_dead_tup/(n_live_tup+1))::float "ratio%",
to_char(last_autovacuum, 'YYYY-MM-DD HH24:MI:SS') as autovacuum_date,
to_char(last_autoanalyze, 'YYYY-MM-DD HH24:MI:SS') as autoanalyze_date
FROM pg_stat_all_tables
ORDER BY last_autovacuum;
This can help by showing you how many dead tuples you have laying around on your tables. Also shows you the last time your tables were analyzed and autovacuumed by the vacuum daemon.
Hope that helps a bit,
Eshara
From: Renjith Gk <renjithgk@gmail.com>
Sent: Tuesday, April 23, 2019 9:07 AM
To: pgsql-admin@lists.postgresql.org
Subject: Performance Optimisation - Identifying the correct DB
Hello Friends,
I am seeking a better suggestion for Identifying the correct DB as part of READ operation (fetching queries).
What is the optimal execution time for Reading 200k records in Postgres. We had issues for reading records in cassandra which faced time out for ~200K records.
any ideal solution or recommendation towards Postgres.
