I had an opportunity to perform insertion of 700MM rows into Aurora Postgresql, for which performance insights are available. Turns out, that there are two stages of insert slowdown - first happens when max WAL buffers limit reached, second happens around 1 hour after.
The first stage cuts insert performance twice, and WALWrite lock is main bottleneck. I think WAL just can't sync changes log that fast, so it waits while older log entries are flushed. This creates both read and write IO.
The second stage is unique to Aurora/RDS and is characterized by excessive read data locks and total read IO. I couldn't figure out why does it read so much in a write only process, and AWS support didn't answer yet.
So, for you, try to throttle inserts so WAL is never overfilled and you don't experience WALWrite locks, and then increase wal buffers to max.
The first stage cuts insert performance twice, and WALWrite lock is main bottleneck. I think WAL just can't sync changes log that fast, so it waits while older log entries are flushed. This creates both read and write IO.
The second stage is unique to Aurora/RDS and is characterized by excessive read data locks and total read IO. I couldn't figure out why does it read so much in a write only process, and AWS support didn't answer yet.
So, for you, try to throttle inserts so WAL is never overfilled and you don't experience WALWrite locks, and then increase wal buffers to max.
24 груд. 2017 р. 21:51 "Jean Baro" <jfbaro@xxxxxxxxx> пише:
Hi there,We are testing a new application to try to find performance issues.AWS RDS m4.large 500GB storage (SSD)One table only, called Messages:UuidCountry (ISO)Role (Text)User id (Text)GroupId (integer)Channel (text)Title (Text)Payload (JSON, up to 20kb)Starts_in (UTC)Expires_in (UTC)Seen (boolean)Deleted (boolean)LastUpdate (UTC)Created_by (UTC)Created_in (UTC)Indexes:UUID (PK)UserID + Country (main index)LastUpdateGroupIDWe inserted 160MM rows, around 2KB each. No partitioning.Insert started at around 3.000 inserts per second, but (as expected) started to slow down as the number of rows increased. In the end we got around 500 inserts per second.Queries by Userd_ID + Country took less than 2 seconds, but while the batch insert was running the queries took over 20 seconds!!!We had 20 Lambda getting messages from SQS and bulk inserting them into Postgresql.The insert performance is important, but we would slow it down if needed in order to ensure a more flat query performance. (Below 2 seconds). Each query (userId + country) returns around 100 diferent messages, which are filtered and order by the synchronous Lambda function. So we don't do any special filtering, sorting, ordering or full text search in Postgres. In some ways we use it more like a glorified file system. :)We are going to limit the number of lambda workers to 1 or 2, and then run some queries concurrently to see if the query performance is not affect too much. We aim to get at least 50 queries per second (returning 100 messages each) under 2 seconds, even when there is millions of messages on SQS being inserted into PG.We haven't done any performance tuning in the DB.With all that said, the question is:What can be done to ensure good query performance (UserID+ country) even when the bulk insert is running (low priority).We are limited to use AWS RDS at the moment.Cheers
