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From "Benjamin Roth (JIRA)" <j...@apache.org>
Subject [jira] [Comment Edited] (CASSANDRA-13241) Lower default chunk_length_in_kb from 64kb to 4kb
Date Tue, 28 Feb 2017 08:58:45 GMT

    [ https://issues.apache.org/jira/browse/CASSANDRA-13241?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15887602#comment-15887602
] 

Benjamin Roth edited comment on CASSANDRA-13241 at 2/28/17 8:58 AM:
--------------------------------------------------------------------

Just thinking about Jeffs + Bens comments:

Even if you have 4 TB of data and 32GB RAM 4KB might help. In that (extreme) case, you'd steal
~8GB from page cache for "chunk tables". These 8GB probably would have helped a fraction of
nothing when used as page cache if you look at the RAM/Load ratio. Most probably the PC would
be totally ineffective, if you don't have a very, very low percentage of hot data. So the
probability that nearly every read results in a physical IO is very high.
So in that case lowering the chunk size to 4KB would at least save you from immense overread
and help the SSDs to survive that situation.

That said, I see only one REAL problem:
If you have more chunk-offset data than fits in your memory. But in that case my answer would
simply be: Get more RAM. There are certain mininum requirements you MUST fulfill. The imagination
of running a node with many TBs of data with less than say 16-32GB is simply insane from any
perspective.

Nevertheless optimizing the memory usage of chunk-offset lookup would be a big deal either.


was (Author: brstgt):
Just thinking about Jeffs + Bens comments:

Even if you have 4 TB of data and 32GB RAM 4KB might help. In that (extreme) case, you'd steal
~8GB from page cache for "chunk tables". These 8GB probably would have helped a fraction of
nothing when used as page cache if you look at the RAM/Load ratio. Most probably the PC would
be totally ineffective, if you don't have a very, very low percentage of hot data. So the
probability that nearly every read results in a physical IO is very high.
So in that case lowering the chunk size to 4KB would at least save you from immense overread
and help the SSDs to survive that situation.

That said, I see only one REAL problem:
If you have more chunk-offset data than fits in your memory. But in that case my answer would
simply be: Get more RAM. There are certain mininum requirements you MUST fulfill. The imagination
of running a node with many TBs of data with less than say 16-32GB is simply insane from all
kinds of perspective.

Nevertheless optimizing the memory usage of chunk-offset lookup would be a big deal either.

> Lower default chunk_length_in_kb from 64kb to 4kb
> -------------------------------------------------
>
>                 Key: CASSANDRA-13241
>                 URL: https://issues.apache.org/jira/browse/CASSANDRA-13241
>             Project: Cassandra
>          Issue Type: Wish
>          Components: Core
>            Reporter: Benjamin Roth
>
> Having a too low chunk size may result in some wasted disk space. A too high chunk size
may lead to massive overreads and may have a critical impact on overall system performance.
> In my case, the default chunk size lead to peak read IOs of up to 1GB/s and avg reads
of 200MB/s. After lowering chunksize (of course aligned with read ahead), the avg read IO
went below 20 MB/s, rather 10-15MB/s.
> The risk of (physical) overreads is increasing with lower (page cache size) / (total
data size) ratio.
> High chunk sizes are mostly appropriate for bigger payloads pre request but if the model
consists rather of small rows or small resultsets, the read overhead with 64kb chunk size
is insanely high. This applies for example for (small) skinny rows.
> Please also see here:
> https://groups.google.com/forum/#!topic/scylladb-dev/j_qXSP-6-gY
> To give you some insights what a difference it can make (460GB data, 128GB RAM):
> - Latency of a quite large CF: https://cl.ly/1r3e0W0S393L
> - Disk throughput: https://cl.ly/2a0Z250S1M3c
> - This shows, that the request distribution remained the same, so no "dynamic snitch
magic": https://cl.ly/3E0t1T1z2c0J



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