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Performance degrade 6.3.1 vs 6.2.2

Open academe-01 opened this issue 1 year ago • 10 comments

Hi, I tested on different systems, but every time the results are the same, 6.3.x works worse than 6.2.x.

redis-benchmark -q -n 1000000 --threads 64
image

academe-01 avatar Jul 15 '22 02:07 academe-01

Second that 👍 also latency grew for us 4-5x times and thats ALOT. Waiting for next release for it to be better and faster than older version 6.2x or at least same performance with new functionality and bugfixes.

keydbupgrade

smarakdas314 avatar Aug 22 '22 06:08 smarakdas314

Same thing for us. On a single server it works ok, we had a master / master cluster with a small dataset. 6 or 7 streams, a couple with 500,000 key streams, most of them are smaller. Usual assortment of zset, hset, keys etc.

We saw the same issues. Latency was so bad that the UI or underlying processes would receive a disconnect from the server.

Summary:

  • AOF file loads are huge and time consuming
  • AOF partial reloads fail almost every time
  • Lots of errors regarding rreplay
  • Memory usage is doubled or tripled
  • Keydb itself stalls. We tried to adjust haproxy timeouts etc. We kept getting check errors where keydb would not respond to the haproxy check. Behavior was noticeable on the cli. Typing a simple command to check memory would hang for 1-3 seconds or more.
  • We upsized and tried two different VM types and the problems continued. We tried both ARM and X86 and we saw the behavior on both versions of 6.3.1.

It really seems to be something with the replication that is eating up resources over time. Unfortunately we had to roll back to 6.2.2 for stability reasons and an approaching deadline.

jgerry2002 avatar Aug 26 '22 07:08 jgerry2002

Same here. We run a bunch of opertions for each event on a frequency of ~ 100 events/s. The operations are (in this order): get, set, expire, hget, hset expiremember On 6.2 it took ~40-50 ms (95% percentile). With 6.3.1, the required time increased to >200ms and the throuhput dropped to 50 events/s (so the impact is even higher that factor 4x).

CPU load of keydb increased significantly (~50%), memory usage by ~ 30-40%

micw avatar Sep 01 '22 09:09 micw