Re:Beringei: A high-performance time series storage engine
by cocoflunchy on Saturday February 04, 2017 @12:30PM
(#13567875)
Yes, we only have one DB for everything and it is bottle-necking on writes. Queuing the writes is probably the easiest solution since we already have RabbitMQ setup... thanks for your answer.
Re:Beringei: A high-performance time series storage engine
by saosebastiao on Saturday February 04, 2017 @01:27PM
(#13568185)
There are a lot of good suggestions here, but if this is the route you're going down and you are still using the same database, do everything you can to batch your inserts. In your queue consumer, aggregate as much as you can tolerate in memory, and then insert them all and commit the inserts in a single transaction. This eliminates a huge amount of MVCC overhead.
With some basic assumptions on my part including that you can have a delay in writing data to the database (since it's archival and analysis), but you don't want the application to be delayed, putting a fast queue like Kafka or RabbitMQ in place could help. It'll buffer when the database is under load, isolating your application from that.
Offline analysis might also skip the database entirely: columnar data formats (parquet) or log structured merge / sorted string tables (rocksdb) could work very well for archival or offline analysis in MR type environments.