On Mon, Feb 11, 2019 at 6:00 PM github kran <githubkran@xxxxxxxxx> wrote:
On Mon, Feb 11, 2019 at 3:29 PM Michael Lewis <mlewis@xxxxxxxxxxx> wrote:Are default statistics target the same on both prod and AWS? Have you analyzed all tables being used in this query to ensure stats are up proper? If the optimizer is choosing a different plan, then the stats must be different IMO.Michael Lewis | Software EngineerEntrataThanks for your reply I have verified few of the tables and their default statistics target and they seem to be same but is there anything in particular you want me to look at it to differentiate Prod and Non prod databases ?. ( Also the DB instance size is same but there is littlemore data in the Non prod Aurora RDS instance compared to Prod instance).Query used.select * from pg_stats where tablename = 'tableName'On Mon, Feb 11, 2019 at 2:15 PM github kran <githubkran@xxxxxxxxx> wrote:Hi Postgres Team,We are using AWS Aurora RDS Postgres DB 9.6.8 Engine. We recently deleted few million rows from the database and ran into a issue in one of our dev account where theDB was not normal after this deletion. We did re index, vacuuming entire database but we couldnt bring it to the same state as earlier. So next steps we deleted the database andrecreated the database by copying the snapshot from a production instance. Further did vacumming, re-index on the database.After this now the dev database seems to be in a better state than earlier but we are seeing few of our DB calls are taking more than 1 minute when we are fetching data and we observedthis is because the query plan was executing a hash join as part of the query whereas a similar query on prod instance is not doing any hash join and is returning faster.Also we did not want to experiment by modifing the DB settings by doing enable_hash_join to off or random_page_count to 1 as we dont have these settings in Prod instance.Note:The partition table sizes we have here is between 40 GB to 75 GB and this is our normal size range, we have a new partition table for every 7 days.Appreciate your ideas on what we could be missing and what we can correct here to reduce the query latency.ThanksgithubKran