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Thanks for the clarification.

1. Do you use Postgresql 9.6 query parallelization (https://www.postgresql.org/docs/9.6/static/parallel-plans.ht...) or your own method for processing chunks parallelly? When we have >1B rows with >20 columns, the IO usually becomes a huge the bottleneck in our experience. If you use multiple disks and parallelize the work among different CPU cores, it would help I guess.



Currently support 9.6 query parallelization. Also considering extending with some of our own methods on chunks as well.

(Timescale supports multiple disks either through RAID or tablespaces. Unlike PG, you can add multiple tablespaces to a single hypertable.)

Happy to also go into more details on Slack (https://slack-login.timescale.com) or email.




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