On 10/20/20 11:37 AM, Mats Julian Olsen wrote:
Dear Postgres community,
I'm looking for some help to manage queries against two large tables.
Context:
We run a relatively large postgresql instance (5TB, 32 vCPU, 120GB
RAM) with a hybrid transactional/analytical workload. Data is written
in batches every 15 seconds or so, and the all queryable tables are
append-only (we never update or delete). Our users can run analytical
queries on top of these tables.
We recently came across a series of troublesome queries one of which
I'll dive into here.
Please see the following gist for both the query we run and the \d+
output:
https://gist.github.com/mewwts/9f11ae5e6a5951593b8999559f5418cf
<https://gist.github.com/mewwts/9f11ae5e6a5951593b8999559f5418cf>.
The tables in question are:
- `ethereum.transactions`: 833M rows, partitioned, 171M rows after WHERE
- `uniswap_v2."Pair_evt_Swap": 12M rows, not partitioned, 12M rows
after WHERE
The query plans I submitted was querying the table
`uniswap_v2."Pair_evt_Mint"`which has 560k rows before and after WHERE.
Also not partitioned. Apologies for the inconsistency, but as I
mentioned the same performance problem holds when using
`uniswap_v2."Pair_evt_Swap" (even worse due to it's size).
The crux of our issue is that the query planner chooses a nested loop
join for this query. Essentially making this query (and other queries)
take a very long time to complete. In contrast, by toggling
`enable_nestloop` and `enable_seqscan` off we can take the total
runtime down from 16 minutes to 2 minutes.
1) Vanilla plan (16 min) : https://explain.depesz.com/s/NvDR
<https://explain.depesz.com/s/NvDR>
2) enable_nestloop=off (4 min): https://explain.depesz.com/s/buKK
<https://explain.depesz.com/s/buKK>
3) enable_nestloop=off; enable_seqscan=off (2 min):
https://explain.depesz.com/s/0WXx <https://explain.depesz.com/s/0WXx>
How can I get Postgres not to loop over 12M rows?
Let me know if there is anything I left out here that would be useful
for further debugging.
--
Mats
CTO @ Dune Analytics
We're hiring: https://careers.duneanalytics.com
<https://careers.duneanalytics.com>
