4 ms·
We already partition our data correctly, as the AWS solution architects recommend, but there are limitations on the: - total throughput (100 Gbit/sec); - the nu
by zX41ZdbW 4y ago
We already partition our data correctly, as the AWS solution architects recommend,
but there are limitations on the:
- total throughput (100 Gbit/sec);
- the number of requests.
For example, at this moment, I'm doing an experiment: creating 10, 100, and 500 Clickhouse servers, and reading the data from s3, either from a MergeTree table or from a set of files.
Ten instances saturate 100 Gbit/sec bandwidth, and there is no subsequent improvement.
JFYI, 100 Gbit/sec is less than one PCI-e with a few M.2 SSDs can give.
- zX41ZdbW 4y agohttps://repost.aws/knowledge-center/s3-maximum-transfer-speed-ec2 https://repost.aws/knowledge-center/s3-maximum-transfer-spee...
- orf 4y agoAhh yes, sorry, you are running it on a single instance. That’s capped, but the aggregate throughput across instances can be a lot higher. There are request limits but these are per partition. There is also an undocumented hard cap on list requests per second which is much lower than get object.
- zX41ZdbW 4y agoNo, I'm creating 10, 100, and 500 different EC2 instances and measuring the aggregate throughput.
- zX41ZdbW 4y ago100 instances of m5.8xlarge, 500 instances of m5.2xlarge
- orf 4y agoSomething must be wrong, at my previous work we were able to achieve a much higher aggregate throughput - are you spreading them across AZ, and are you using a VPC endpoint? We did use multiple VPCs, that might make a difference
- zX41ZdbW 4y agoWorth to note that ClickHouse is a distributed MPP DBMS, it can scale up to 1000s of bare-metal servers and process terabytes (not terabits) of data per second. It also works on a laptop, or even without installation.