>> Are you doing large slices or do could you have a lot of tombstones on the
>> rows ?
> don't really know - how can I monitor that?
For tombstones, do you do a lot of deletes ?
Also in v2.0.2 cfstats has this
Average live cells per slice (last five minutes): 0.0
Average tombstones per slice (last five minutes): 0.0
For large slices you need to check your code. e.g. do you anything that reads
lots of columns or very large columns or lets the user select how many columns
to read?
The org.apache.cassandra.db.ArrayBackedSortedColumns in the trace back is used
during reads (.e.g. org.apache.cassandra.db.filter.SliceQueryFilter)
>> You probably want the heap to be 4G to 8G in size, 10G will encounter longer
>> pauses.
>> Also the size of the new heap may be too big depending on the number of
>> cores. I would recommend trying 800M
> I tried to decrease it first to 384M then to 128M with no change in the
> behaviour. I don't really care extra memory overhead of the cache - to be
> able to actual point to it with objects, but I don't really see the reason
> why it should create/delete those many objects so quickly.
Not sure what you changed to 384M.
>> Shows the heap growing very quickly. This could be due to wide reads or a
>> high write throughput.
> Well, both prg01 and prg02 receive the same load which is about ~150-250
> (during peak) read requests per seconds and 100-160 write requests per
> second. The only with heap growing rapidly and GC kicking in is on nodes with
> row cache enabled.
This sounds like on a row cache miss cassandra is reading the whole row, which
happens to be a wide row. I would also guess some writes are going to the rows
and they are getting invalidated out of the row cache.
The row cache is not great for rows the update frequently and/or wide rows.
How big are the rows ? use nodetool cfstats and nodetool cfhistograms.
Cheers
-----------------
Aaron Morton
New Zealand
@aaronmorton
Co-Founder & Principal Consultant
Apache Cassandra Consulting
http://www.thelastpickle.com
On 8/11/2013, at 11:47 pm, Jiri Horky <ho...@avast.com> wrote:
> Hi,
>
> On 11/07/2013 05:18 AM, Aaron Morton wrote:
>>> Class Name
>>> | Shallow Heap | Retained Heap
>>> -------------------------------------------------------------------------------------------------------------------------------------------
>>>
>>> | |
>>> java.nio.HeapByteBuffer @ 0x7806a0848
>>> | 48 | 80
>>> '- name org.apache.cassandra.db.Column @ 0x7806424e8
>>> | 32 | 112
>>> |- [338530] java.lang.Object[540217] @ 0x57d62f560 Unreachable
>>> | 2,160,888 | 2,160,888
>>> |- [338530] java.lang.Object[810325] @ 0x591546540
>>> | 3,241,320 | 7,820,328
>>> | '- elementData java.util.ArrayList @ 0x75e8424c0
>>> | 24 | 7,820,352
>>> | |- list
>>> org.apache.cassandra.db.ArrayBackedSortedColumns$SlicesIterator @
>>> 0x5940e0b18 | 48 | 128
>>> | | '- val$filteredIter
>>> org.apache.cassandra.db.filter.SliceQueryFilter$1 @ 0x5940e0b48
>>> | 32 | 7,820,568
>>> | | '- val$iter org.apache.cassandra.db.filter.QueryFilter$2 @
>>> 0x5940e0b68 Unreachable | 24 | 7,820,592
>>> | |- this$0, parent java.util.ArrayList$SubList @ 0x5940e0bb8
>>> | 40 | 40
>>> | | '- this$1 java.util.ArrayList$SubList$1 @ 0x5940e0be0
>>> | 40 | 80
>>> | | '- currentSlice
>>> org.apache.cassandra.db.ArrayBackedSortedColumns$SlicesIterator @
>>> 0x5940e0b18| 48 | 128
>>> | | '- val$filteredIter
>>> org.apache.cassandra.db.filter.SliceQueryFilter$1 @ 0x5940e0b48 |
>>> 32 | 7,820,568
>>> | | '- val$iter
>>> org.apache.cassandra.db.filter.QueryFilter$2 @ 0x5940e0b68 Unreachable
>>> | 24 | 7,820,592
>>> | |- columns org.apache.cassandra.db.ArrayBackedSortedColumns @
>>> 0x5b0a33488 | 32 | 56
>>> | | '- val$cf org.apache.cassandra.db.filter.SliceQueryFilter$1 @
>>> 0x5940e0b48 | 32 | 7,820,568
>>> | | '- val$iter org.apache.cassandra.db.filter.QueryFilter$2 @
>>> 0x5940e0b68 Unreachable | 24 | 7,820,592
>>> | '- Total: 3 entries
>>> | |
>>> |- [338530] java.lang.Object[360145] @ 0x7736ce2f0 Unreachable
>>> | 1,440,600 | 1,440,600
>>> '- Total: 3 entries
>>> | |
>>
>> Are you doing large slices or do could you have a lot of tombstones on the
>> rows ?
> don't really know - how can I monitor that?
>>
>>> We have disabled row cache on one node to see the difference. Please
>>> see attached plots from visual VM, I think that the effect is quite
>>> visible.
>> The default row cache is of the JVM heap, have you changed to the
>> ConcurrentLinkedHashCacheProvider ?
> Answered by Chris already :) No.
>>
>> One way the SerializingCacheProvider could impact GC is if the CF takes a
>> lot of writes. The SerializingCacheProvider invalidates the row when it is
>> written to and had to read the entire row and serialise it on a cache miss.
>>
>>>> -XX:+UseThreadPriorities -XX:ThreadPriorityPolicy=42 -Xms10G -Xmx10G
>>>> -Xmn1024M -XX:+HeapDumpOnOutOfMemoryError
>> You probably want the heap to be 4G to 8G in size, 10G will encounter longer
>> pauses.
>> Also the size of the new heap may be too big depending on the number of
>> cores. I would recommend trying 800M
> I tried to decrease it first to 384M then to 128M with no change in the
> behaviour. I don't really care extra memory overhead of the cache - to be
> able to actual point to it with objects, but I don't really see the reason
> why it should create/delete those many objects so quickly.
>>
>>
>>> prg01.visual.vm.png
>> Shows the heap growing very quickly. This could be due to wide reads or a
>> high write throughput.
> Well, both prg01 and prg02 receive the same load which is about ~150-250
> (during peak) read requests per seconds and 100-160 write requests per
> second. The only with heap growing rapidly and GC kicking in is on nodes with
> row cache enabled.
>
>>
>> Hope that helps.
> Thank you!
>
> Jiri Horky
>
