Hello,
We have a job where its main purpose is to track whether or not we've
previously seen a particular event - that's it. If it's new, we save it to
an external database. If we've seen it, we block the write. There's a 3-day
TTL to manage the state size. The downstream db can tolerate new data
Hey Trystan,
Based on my personal experience, good disk IO for RocksDB matters a lot.
Are you using the fastest SSD storage you can get for RocskDB folders?
For example, when running on GCP, we noticed *10x* throughput improvement
by switching RocksDB storage to
https://cloud.google.com/compute/d
Thanks for the info! We're running EBS gp2 volumes... awhile back we tested
local SSDs with a different job and didn't notice any gains, but that was
likely due to an under-optimized job where the bottleneck was elsewhere
On Wed, Apr 20, 2022, 11:08 AM Yaroslav Tkachenko
wrote:
> Hey Trystan,
>
Yep, I'd give it another try. EBS could be too slow in some use-cases.
On Wed, Apr 20, 2022 at 9:39 AM Trystan wrote:
> Thanks for the info! We're running EBS gp2 volumes... awhile back we
> tested local SSDs with a different job and didn't notice any gains, but
> that was likely due to an under
ttps://nightlies.apache.org/flink/flink-docs-release-1.14/docs/deployment/config/#state-backend-rocksdb-memory-partitioned-index-filters
Best
Yun Tang
From: Yaroslav Tkachenko
Sent: Thursday, April 21, 2022 0:44
To: Trystan
Cc: user
Subject: Re: RocksDB effici