Hello,
We have another update on performance on 2.1.11. compression_chunk_size didn’t
really help much but We changed concurrent_compactors from default to 64 in
2.1.11 and read latencies improved significantly. However, 2.1.11 read
latencies are still 1.5 slower than 2.0.9. One thing we noticed in JMX metric
that could affect read latencies is that 2.1.11 is running
ReadRepairedBackground and ReadRepairedBlocking too frequently compared to
2.0.9 even though our read_repair_chance is same on both. Could anyone shed
some light on why 2.1.11 could be running read repair 10 to 50 times more in
spite of same configuration on both clusters?
dclocal_read_repair_chance=0.100000 AND
read_repair_chance=0.000000 AND
Here is the table for read repair metrics for both clusters.
2.0.9 2.1.11
ReadRepairedBackground 5MinAvg 0.006 0.1
15MinAvg 0.009 0.153
ReadRepairedBlocking 5MinAvg 0.002 0.55
15MinAvg 0.007 0.91
Thanks
Praveen
From: Jeff Jirsa <jeff.ji...@crowdstrike.com<mailto:jeff.ji...@crowdstrike.com>>
Reply-To: <user@cassandra.apache.org<mailto:user@cassandra.apache.org>>
Date: Thursday, January 14, 2016 at 2:58 PM
To: "user@cassandra.apache.org<mailto:user@cassandra.apache.org>"
<user@cassandra.apache.org<mailto:user@cassandra.apache.org>>
Subject: Re: Slow performance after upgrading from 2.0.9 to 2.1.11
Sorry I wasn’t as explicit as I should have been
The same buffer size is used by compressed reads as well, but tuned with
compression_chunk_size table property. It’s likely true that if you lower
compression_chunk_size, you’ll see improved read performance.
This was covered in the AWS re:Invent youtube link I sent in my original reply.
From: "Peddi, Praveen"
Reply-To: "user@cassandra.apache.org<mailto:user@cassandra.apache.org>"
Date: Thursday, January 14, 2016 at 11:36 AM
To: "user@cassandra.apache.org<mailto:user@cassandra.apache.org>", Zhiyan Shao
Cc: "Agrawal, Pratik"
Subject: Re: Slow performance after upgrading from 2.0.9 to 2.1.11
Hi,
We will try with reduced “rar_buffer_size” to 4KB. However
CASSANDRA-10249<https://issues.apache.org/jira/browse/CASSANDRA-10249> says
"this only affects users who have 1. disabled compression, 2. switched to
buffered i/o from mmap’d”. None of this is true for us I believe. We use
default disk_access_mode which should be mmap. We also used LZ4Compressor when
created table.
We will let you know if this property had any effect. We were testing with
2.1.11 and this was only fixed in 2.1.12 so we need to play with latest version.
Praveen
From: Jeff Jirsa <jeff.ji...@crowdstrike.com<mailto:jeff.ji...@crowdstrike.com>>
Reply-To: <user@cassandra.apache.org<mailto:user@cassandra.apache.org>>
Date: Thursday, January 14, 2016 at 1:29 PM
To: Zhiyan Shao <zhiyan.s...@gmail.com<mailto:zhiyan.s...@gmail.com>>,
"user@cassandra.apache.org<mailto:user@cassandra.apache.org>"
<user@cassandra.apache.org<mailto:user@cassandra.apache.org>>
Cc: "Agrawal, Pratik" <paagr...@amazon.com<mailto:paagr...@amazon.com>>
Subject: Re: Slow performance after upgrading from 2.0.9 to 2.1.11
This may be due to https://issues.apache.org/jira/browse/CASSANDRA-10249 /
https://issues.apache.org/jira/browse/CASSANDRA-8894 - whether or not this is
really the case depends on how much of your data is in page cache, and whether
or not you’re using mmap. Since the original question was asked by someone
using small RAM instances, it’s possible.
We mitigate this by dropping compression_chunk_size in order to force a smaller
buffer on reads, so we don’t over read very small blocks. This has other side
effects (lower compression ratio, more garbage during streaming), but
significantly speeds up read workloads for us.
From: Zhiyan Shao
Date: Thursday, January 14, 2016 at 9:49 AM
To: "user@cassandra.apache.org<mailto:user@cassandra.apache.org>"
Cc: Jeff Jirsa, "Agrawal, Pratik"
Subject: Re: Slow performance after upgrading from 2.0.9 to 2.1.11
Praveen, if you search "Read is slower in 2.1.6 than 2.0.14" in this forum, you
can find another thread I sent a while ago. The perf test I did indicated that
read is slower for 2.1.6 than 2.0.14 so we stayed with 2.0.14.
On Tue, Jan 12, 2016 at 9:35 AM, Peddi, Praveen
<pe...@amazon.com<mailto:pe...@amazon.com>> wrote:
Thanks Jeff for your reply. Sorry for delayed response. We were running some
more tests and wanted to wait for the results.
So basically we saw higher CPU with 2.1.11 was higher compared to 2.0.9 (see
below) for the same exact load test. Memory spikes were also aggressive on
2.1.11.
So we wanted to rule out any of our custom setting so we ended up doing some
testing with Cassandra stress test and default Cassandra installation. Here are
the results we saw between 2.0.9 and 2.1.11. Both are default installations and
both use Cassandra stress test with same params. This is the closest
apple-apple comparison we can get. As you can see both read and write latencies
are 30 to 50% worse in 2.1.11 than 2.0.9. Since we are using default
installation.
Highlights of the test:
Load: 2x reads and 1x writes
CPU: 2.0.9 (goes upto 25%) compared to 2.1.11 (goes upto 60%)
Local read latency: 0.039 ms for 2.0.9 and 0.066 ms for 2.1.11
Local write Latency: 0.033 ms for 2.0.9 Vs 0.030 ms for 2.1.11
One observation is, As the number of threads are increased, 2.1.11 read
latencies are getting worse compared to 2.0.9 (see below table for 24 threads
vs 54 threads)
Not sure if anyone has done this kind of comparison before and what their
thoughts are. I am thinking for this same reason
2.0.9 Plain type total ops op/s pk/s
row/s mean med 0.95 0.99 0.999 max
time
16 threadCount READ 66854 7205 7205 7205 1.6 1.3 2.8
3.5 9.6 85.3 9.3
16 threadCount WRITE 33146 3572 3572 3572 1.3 1 2.6
3.3 7 206.5 9.3
16 threadCount total 100000 10777 10777 10777 1.5 1.3 2.7
3.4 7.9 206.5 9.3
2.1.11 Plain
16 threadCount READ 67096 6818 6818 6818 1.6 1.5 2.6
3.5 7.9 61.7 9.8
16 threadCount WRITE 32904 3344 3344 3344 1.4 1.3 2.3
3 6.5 56.7 9.8
16 threadCount total 100000 10162 10162 10162 1.6 1.4 2.5
3.2 6 61.7 9.8
2.0.9 Plain
24 threadCount READ 66414 8167 8167 8167 2 1.6 3.7
7.5 16.7 208 8.1
24 threadCount WRITE 33586 4130 4130 4130 1.7 1.3 3.4
5.4 25.6 45.4 8.1
24 threadCount total 100000 12297 12297 12297 1.9 1.5 3.5
6.2 15.2 208 8.1
2.1.11 Plain
24 threadCount READ 66628 7433 7433 7433 2.2 2.1 3.4
4.3 8.4 38.3 9
24 threadCount WRITE 33372 3723 3723 3723 2 1.9 3.1
3.8 21.9 37.2 9
24 threadCount total 100000 11155 11155 11155 2.1 2 3.3
4.1 8.8 38.3 9
2.0.9 Plain
54 threadCount READ 67115 13419 13419 13419 2.8 2.6 4.2
6.4 36.9 82.4 5
54 threadCount WRITE 32885 6575 6575 6575 2.5 2.3 3.9
5.6 15.9 81.5 5
54 threadCount total 100000 19993 19993 19993 2.7 2.5 4.1
5.7 13.9 82.4 5
2.1.11 Plain
54 threadCount READ 66780 8951 8951 8951 4.3 3.9 6.8
9.7 49.4 69.9 7.5
54 threadCount WRITE 33220 4453 4453 4453 3.5 3.2 5.7
8.2 36.8 68 7.5
54 threadCount total 100000 13404 13404 13404 4 3.7 6.6
9.2 48 69.9 7.5
From: Jeff Jirsa <jeff.ji...@crowdstrike.com<mailto:jeff.ji...@crowdstrike.com>>
Date: Thursday, January 7, 2016 at 1:01 AM
To: "user@cassandra.apache.org<mailto:user@cassandra.apache.org>"
<user@cassandra.apache.org<mailto:user@cassandra.apache.org>>, Peddi Praveen
<pe...@amazon.com<mailto:pe...@amazon.com>>
Subject: Re: Slow performance after upgrading from 2.0.9 to 2.1.11
Anecdotal evidence typically agrees that 2.1 is faster than 2.0 (our experience
was anywhere from 20-60%, depending on workload).
However, it’s not necessarily true that everything behaves exactly the same –
in particular, memtables are different, commitlog segment handling is
different, and GC params may need to be tuned differently for 2.1 than 2.0.
When the system is busy, what’s it actually DOING? Cassandra exposes a TON of
metrics – have you plugged any into a reporting system to see what’s going on?
Is your latency due to pegged cpu, iowait/disk queues or gc pauses?
My colleagues spent a lot of time validating different AWS EBS configs (video
from reinvent at https://www.youtube.com/watch?v=1R-mgOcOSd4), 2.1 was faster
in almost every case, but you’re using an instance size I don’t believe we
tried (too little RAM to be viable in production). c3.2xl only gives you 15G
of ram – most “performance” based systems want 2-4x that (people running G1
heaps usually start at 16G heaps and leave another 16-30G for page cache),
you’re running fairly small hardware – it’s possible that 2.1 isn’t “as good”
on smaller hardware.
(I do see your domain, presumably you know all of this, but just to be sure):
You’re using c3, so presumably you’re using EBS – are you using GP2? Which
volume sizes? Are they the same between versions? Are you hitting your iops
limits? Running out of burst tokens? Do you have enhanced networking enabled?
At load, what part of your system is stressed? Are you cpu bound? Are you
seeing GC pauses hurt latency? Have you tried changing memtable_allocation_type
-> offheap objects (available in 2.1, not in 2.0)?
Tuning gc_grace is weird – do you understand what it does? Are you overwriting
or deleting a lot of data in your test (that’d be unusual)? Are you doing a lot
of compaction?
From: "Peddi, Praveen"
Reply-To: "user@cassandra.apache.org<mailto:user@cassandra.apache.org>"
Date: Wednesday, January 6, 2016 at 11:41 AM
To: "user@cassandra.apache.org<mailto:user@cassandra.apache.org>"
Subject: Slow performance after upgrading from 2.0.9 to 2.1.11
Hi,
We have upgraded Cassandra from 2.0.9 to 2.1.11 in our loadtest environment
with pretty much same yaml settings in both (removed unused yaml settings and
renamed few others) and we have noticed performance on 2.1.11 is worse compared
to 2.0.9. After more investigation we found that the performance gets worse as
we increase replication factor on 2.1.11 where as on 2.0.9 performance is more
or less same. Has anything architecturally changed as far as replication is
concerned in 2.1.11?
All googling only suggested 2.1.11 should be FASTER than 2.0.9 so we are
obviously doing something different. However the client code, load test is all
identical in both cases.
Details:
Nodes: 3 ec2 c3.2x large
R/W Consistency: QUORUM
Renamed memtable_total_space_in_mb to memtable_heap_space_in_mb and removed
unused properties from yaml file.
We run compaction aggressive compaction with low gc_grace (15 mins) but this is
true for both 2.0.9 and 2.1.11.
As you can see, all p50, p90 and p99 latencies stayed with in 10% difference on
2.0.9 when we increased RF from 1 to 3, where as on 2.1.11 latencies almost
doubled (especially reads are much slower than writes).
# Nodes RF # of rows 2.0.9 2.1.11
READ
P50 P90 P99 P50 P90 P99
3 1 450 306 594 747 425 849 1085
3 3 450 358 634 877 708 1274 2642
WRITE
3 1 10 26 80 179 37 131 196
3 3 10 31 96 184 46 166 468
Any pointers on how to debug performance issues will be appreciated.
Praveen
