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https://issues.apache.org/jira/browse/CASSANDRA-7949?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14174702#comment-14174702
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Nikolai Grigoriev edited comment on CASSANDRA-7949 at 10/17/14 3:57 AM:
------------------------------------------------------------------------
Update:
Using the property from CASSANDRA-6621 does help to get out of this state. My
cluster is slowly digesting the large sstables and creating bunch of nice small
sstables from them. It is slower than using sstablesplit, I believe, because it
actually does real compactions and, thus, processes and reprocesses different
sets of sstables. My understanding is that every time I get new bunch of L0
sstables there is a phase for updating other levels and it repeats and repeats.
With that property set I see that my total number of sstables grows, my number
of "huge" sstables decreases and the average size of the sstable decreases as
result.
My conclusions so far:
1. STCS fallback in LCS is a double-edged sword. It is needed to prevent the
flooding the node with tons of small sstables resulting from ongoing writes.
These small ones are often much smaller than the configured target size and hey
need to be merged. But also the use of STCS results in generation of the
super-sized sstables. These become a large headache when the fallback stops and
LCS is supposed to resume normal operations. It appears to me (my humble
opinion) that fallback should be done to some kind of specialized "rescue" STCS
flavor that merges the small sstables to approximately the LCS target sstable
size BUT DOES NOT create sstables that are much larger than the target size.
With this approach the LCS will resume normal operations much faster than the
cause for the fallback (abnormally high write load) is gone.
2. LCS has major (performance?) issue when you have super-large sstables in the
system. It often gets stuck with single long (many hours) compaction stream
that, by itself, will increase the probability of another STCS fallback even
with reasonable write load. As a possible workaround I was recommended to
consider running multiple C* instances on our relatively powerful machines - to
significantly reduce the amount of data per node and increase compaction
throughput.
3. In the existing systems, depending on the severity of the STCS fallback
"work", the fix from CASSANDRA-6621 may help to recover while keeping the nodes
up. It will take a very long time to recover but the nodes will be online.
4. Recovery (see above) is very long. It is much much longer than the duration
of the "stress period" that causes the condition. In my case I was writing like
crazy for about 4 days and it's been over a week of compactions after that. I
am still very far from 0 pending compactions. Considering this it makes sense
to artificially throttle the write speed when generating the data (like in the
use case I described in previous comments). Extra time spent on writing the
data will be still significantly shorter than the amount of time required to
recover from the consequences of abusing the available write bandwidth.
was (Author: ngrigor...@gmail.com):
Update:
Using the property from CASSANDRA-6621 does help to get out of this state. My
cluster is slowly digesting the large sstables and creating bunch of nice small
sstables from them. It is slower than using sstablesplit, I believe, because it
actually does real compactions and, thus, processes and reprocesses different
sets of sstables. My understanding is that every time I get new bunch of L0
sstables there is a phase for updating other levels and it repeats and repeats.
With that property set I see that my total number of sstables grows, my number
of "huge" sstables decreases and the average size of the sstable decreases as
result.
My conclusions so far:
1. STCS fallback in LCS is a double-edged sword. It is needed to prevent the
flooding the node with tons of small sstables resulting from ongoing writes.
These small ones are often much smaller than the configured target size and hey
need to be merged. But also the use of STCS results in generation of the
super-sized sstables. These become a large headache when the fallback stops and
LCS is supposed to resume normal operations. It appears to me (my humble
opinion) that fallback should be done to some kind of specialized "rescue" STCS
flavor that merges the small sstables to approximately the LCS target sstable
size BUT DOES NOT create sstables that are much larger than the target size.
With this approach the LCS will resume normal operations much faster than the
cause for the fallback (abnormally high write load) is gone.
2. LCS has major (performance?) issue when you have super-large sstables in the
system. It often gets stuck with single long (many hours) compaction stream
that, by itself, will increase the probability of another STCS fallback even
with reasonable write load. As a possible workaround I was recommended to
consider running multiple C* instances on our relatively powerful machines - to
significantly reduce the amount of data per node and increase compaction
throughput.
3. In the existing systems, depending on the severity of the STCS fallback
"work" the fix from CASSANDRA-6621 may help to recover while keeping the nodes
up. It will take a very long time to recover but the nodes will be online.
4. Recovery (see above) is very long. It is much much longer than the duration
of the "stress period" that causes the condition. In my case I was writing like
crazy for about 4 days and it's been over a week of compactions after that. I
am still very far from 0 pending compactions. Considering this it makes sense
to artificially throttle the write speed when generating the data (like in the
use case I described in previous comments). Extra time spent on writing the
data will be still significantly shorter than the amount of time required to
recover from the consequences of abusing the available write bandwidth.
> LCS compaction low performance, many pending compactions, nodes are almost
> idle
> -------------------------------------------------------------------------------
>
> Key: CASSANDRA-7949
> URL: https://issues.apache.org/jira/browse/CASSANDRA-7949
> Project: Cassandra
> Issue Type: Bug
> Components: Core
> Environment: DSE 4.5.1-1, Cassandra 2.0.8
> Reporter: Nikolai Grigoriev
> Attachments: iostats.txt, nodetool_compactionstats.txt,
> nodetool_tpstats.txt, pending compactions 2day.png, system.log.gz, vmstat.txt
>
>
> I've been evaluating new cluster of 15 nodes (32 core, 6x800Gb SSD disks +
> 2x600Gb SAS, 128Gb RAM, OEL 6.5) and I've built a simulator that creates the
> load similar to the load in our future product. Before running the simulator
> I had to pre-generate enough data. This was done using Java code and DataStax
> Java driver. To avoid going deep into details, two tables have been
> generated. Each table currently has about 55M rows and between few dozens and
> few thousands of columns in each row.
> This data generation process was generating massive amount of non-overlapping
> data. Thus, the activity was write-only and highly parallel. This is not the
> type of the traffic that the system will have ultimately to deal with, it
> will be mix of reads and updates to the existing data in the future. This is
> just to explain the choice of LCS, not mentioning the expensive SSD disk
> space.
> At some point while generating the data I have noticed that the compactions
> started to pile up. I knew that I was overloading the cluster but I still
> wanted the genration test to complete. I was expecting to give the cluster
> enough time to finish the pending compactions and get ready for real traffic.
> However, after the storm of write requests have been stopped I have noticed
> that the number of pending compactions remained constant (and even climbed up
> a little bit) on all nodes. After trying to tune some parameters (like
> setting the compaction bandwidth cap to 0) I have noticed a strange pattern:
> the nodes were compacting one of the CFs in a single stream using virtually
> no CPU and no disk I/O. This process was taking hours. After that it would be
> followed by a short burst of few dozens of compactions running in parallel
> (CPU at 2000%, some disk I/O - up to 10-20%) and then getting stuck again for
> many hours doing one compaction at time. So it looks like this:
> # nodetool compactionstats
> pending tasks: 3351
> compaction type keyspace table completed
> total unit progress
> Compaction myks table_list1 66499295588
> 1910515889913 bytes 3.48%
> Active compaction remaining time : n/a
> # df -h
> ...
> /dev/sdb 1.5T 637G 854G 43% /cassandra-data/disk1
> /dev/sdc 1.5T 425G 1.1T 29% /cassandra-data/disk2
> /dev/sdd 1.5T 429G 1.1T 29% /cassandra-data/disk3
> # find . -name **table_list1**Data** | grep -v snapshot | wc -l
> 1310
> Among these files I see:
> 1043 files of 161Mb (my sstable size is 160Mb)
> 9 large files - 3 between 1 and 2Gb, 3 of 5-8Gb, 55Gb, 70Gb and 370Gb
> 263 files of various sized - between few dozens of Kb and 160Mb
> I've been running the heavy load for about 1,5days and it's been close to 3
> days after that and the number of pending compactions does not go down.
> I have applied one of the not-so-obvious recommendations to disable
> multithreaded compactions and that seems to be helping a bit - I see some
> nodes started to have fewer pending compactions. About half of the cluster,
> in fact. But even there I see they are sitting idle most of the time lazily
> compacting in one stream with CPU at ~140% and occasionally doing the bursts
> of compaction work for few minutes.
> I am wondering if this is really a bug or something in the LCS logic that
> would manifest itself only in such an edge case scenario where I have loaded
> lots of unique data quickly.
> By the way, I see this pattern only for one of two tables - the one that has
> about 4 times more data than another (space-wise, number of rows is the
> same). Looks like all these pending compactions are really only for that
> larger table.
> I'll be attaching the relevant logs shortly.
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