Re: Parallelize stream replication process - Mailing list pgsql-hackers
| From | Jakub Wartak |
|---|---|
| Subject | Re: Parallelize stream replication process |
| Date | |
| Msg-id | VI1PR0701MB6960AD39940E8D4CDCD1C2BCF63E0@VI1PR0701MB6960.eurprd07.prod.outlook.com Whole thread Raw |
| In response to | Re: Parallelize stream replication process (Li Japin <japinli@hotmail.com>) |
| Responses |
Re: Parallelize stream replication process
(Li Japin <japinli@hotmail.com>)
|
| List | pgsql-hackers |
Li Japin wrote: > If we can improve the efficiency of replay, then we can shorten the database recovery time (streaming replication or databasecrash recovery). (..) > For streaming replication, we may need to improve the transmission of WAL logs to improve the entire recovery process. > I’m not sure if this is correct. Hi, If you are interested in increased efficiency of WAL replay internals/startup performance then you might be interested infollowing threads: Cache relation sizes in recovery - https://www.postgresql.org/message-id/flat/CA%2BhUKG%2BNPZeEdLXAcNr%2Bw0YOZVb0Un0_MwTBpgmmVDh7No2jbg%40mail.gmail.com#feace7ccbb8e3df8b086d0a2217df91f Faster compactify_tuples() - https://www.postgresql.org/message-id/flat/CA+hUKGKMQFVpjr106gRhwk6R-nXv0qOcTreZuQzxgpHESAL6dw@mail.gmail.com Handing off SLRU fsyncs to the checkpointer - https://www.postgresql.org/message-id/flat/CA%2BhUKGLJ%3D84YT%2BNvhkEEDAuUtVHMfQ9i-N7k_o50JmQ6Rpj_OQ%40mail.gmail.com Optimizing compactify_tuples() - https://www.postgresql.org/message-id/flat/CA%2BhUKGKMQFVpjr106gRhwk6R-nXv0qOcTreZuQzxgpHESAL6dw%40mail.gmail.com Background bgwriter during crash recovery - https://www.postgresql.org/message-id/flat/CA+hUKGJ8NRsqgkZEnsnRc2MFROBV-jCnacbYvtpptK2A9YYp9Q@mail.gmail.com WIP: WAL prefetch (another approach) - https://www.postgresql.org/message-id/flat/CA%2BhUKGJ4VJN8ttxScUFM8dOKX0BrBiboo5uz1cq%3DAovOddfHpA%40mail.gmail.com Division in dynahash.c due to HASH_FFACTOR - https://www.postgresql.org/message-id/flat/VI1PR0701MB696044FC35013A96FECC7AC8F62D0%40VI1PR0701MB6960.eurprd07.prod.outlook.com [PATCH] guc-ify the formerly hard-coded MAX_SEND_SIZE to max_wal_send - https://www.postgresql.org/message-id/flat/CACJqAM2uAUnEAy0j2RRJOSM1UHPdGxCr%3DU-HbqEf0aAcdhUoEQ%40mail.gmail.com Unnecessary delay in streaming replication due to replay lag - https://www.postgresql.org/message-id/flat/CANXE4Tc3FNvZ_xAimempJWv_RH9pCvsZH7Yq93o1VuNLjUT-mQ%40mail.gmail.com WAL prefetching in future combined with AIO (IO_URING) - longer term future, https://anarazel.de/talks/2020-05-28-pgcon-aio/2020-05-28-pgcon-aio.pdf Good way to start is to profile the system what is taking time during Your failover situation OR Your normal hot-standbybehavior and then proceed to identifying and characterizing the main bottleneck - there can be many depending on the situation (inefficientsingle processes PostgreSQL code, CPU-bound startup/recovering, IOPS/VFS/ syscall/s / API limitations, single TCP stream limitations single TCP stream latencyimpact in WAN, contention on locks in hot-standby case...) . Some of the above are already commited in for 14/master, some are not and require further discussions and testing. Without real identification of the bottleneck and WAL stream statistics you are facing , it's hard to say how would parallelWAL recovery improve the situation. -J.
pgsql-hackers by date: