Re: Postgresql RDS DB Latency Chossing Hash join Plan

How many total rows in these tables? I am assuming these are partitions and those 100 million rows got distributed. If the data difference is significant, then you aren't guaranteed similar performance. You may want to follow more of the suggested steps on.

https://wiki.postgresql.org/wiki/SlowQueryQuestions

Michael Lewis  |  Software Engineer

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c: 619.370.8697

On Thu, Feb 14, 2019 at 8:48 AM github kran <githubkran@gmail.com> wrote:

On Wed, Feb 13, 2019 at 11:38 AM Michael Lewis <mlewis@entrata.com> wrote:

I didn't see your email yesterday, sorry about that. Index scans instead of sequential scans and nested loop instead of hash join means that you have bad row count estimates on "Non prod Aurora RDS instance" as far as I can figure. Have you run commands like-

analyze asset_info_2019_2_part4;

analyze asset_info_2019_2_part2;

etc? If data are very similar, indexes all exist, and default_statistics_target are the same, then you should be getting the same plans.

Michael Lewis  |  Software Engineer

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c: 619.370.8697

1)  Yes did the VACUUM for all the tables like asset_info_2019_2_part1, part2 , part4 and also for location_info_xxx  to remove any dead tuples and also rebuilt the indexes..

2)   REINDEX table  location_data_2018_12_part4;( Like wise ran for all the tables and also VACUUM for all the tables).

3)  The data in Non prod instance is more.  One thing to mention here when we built the Non prod instance we copied SNAPSHOT from Prod instance and on top of that inserted data about 100 million rows and then did VACUUM and re-indexed the tables.

I cant think of anything we can do here but let us know if you need any more details on this problem. Iam happy to share more details.

 

On Wed, Feb 13, 2019 at 8:49 AM github kran <githubkran@gmail.com> wrote:

On Tue, Feb 12, 2019 at 12:55 PM github kran <githubkran@gmail.com> wrote:

On Tue, Feb 12, 2019 at 12:33 PM Michael Lewis <mlewis@entrata.com> wrote:

Did you update the stats by running ANALYZE on the tables involved, or perhaps the entire database on the 'Non prod Aurora RDS instance'? Can you share the two execution plans?

Michael Lewis  |  Software Engineer

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c: 619.370.8697

Here is the plan for both of the DB instances. 

Michael - Did you get any chance to look at this issue. Also we see there is a sequential scan being done instead of index scan. 

On Tue, Feb 12, 2019 at 11:27 AM github kran <githubkran@gmail.com> wrote:

On Tue, Feb 12, 2019 at 7:07 AM github kran <githubkran@gmail.com> wrote:

On Mon, Feb 11, 2019 at 6:00 PM github kran <githubkran@gmail.com> wrote:

On Mon, Feb 11, 2019 at 3:29 PM Michael Lewis <mlewis@entrata.com> 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 Engineer

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Thanks 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 little 

more 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@gmail.com> 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 the 

DB 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 and 

recreated 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 observed

this 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. 

Thanks 

githubKran