First off, I'm curious what hardware (system specs) you're running this on?

Secondly, here are some observations:
* You're not running the newest JDK7, I can tell by your stack-size.  Consider getting the newest.

* Cassandra 2.0.2 has a lot of improvements, consider upgrading.  We noticed improved heap usage compared to 2.0.2

* Have you simply tried decreasing the size of your row cache?  Tried 256MB?

* Do you have JNA installed?  Otherwise, you're not getting off-heap usage for these caches which seems likely.  Check your cassandra.log to verify JNA operation.

* Your NewGen is too small.  See your heap peaks?  This is because short-lived memory is being put into OldGen, which only gets cleaned up during fullGC.  You should set your NewGen to about 25-30% of your total heapsize.  Many objects are short-lived, and CMS GC is significantly more efficient if the shorter-lived objects never get promoted to OldGen; you'll get more concurrent, non-blocking GC.  If you're not using JNA (per above) row-cache and key-cache is still on-heap, so you want your NewGen to be >= twice as large as the size of these combined caches.  You should never so those crazy heap spikes, your caches are essentially overflowing into OldGen (with JNA).

On Tue, Nov 5, 2013 at 3:04 AM, Jiri Horky <> wrote:
Hi there,

we are seeing extensive memory allocation leading to quite long and
frequent GC pauses when using row cache. This is on cassandra 2.0.0
cluster with JNA 4.0 library with following settings:

key_cache_size_in_mb: 300
key_cache_save_period: 14400
row_cache_size_in_mb: 1024
row_cache_save_period: 14400
commitlog_sync: periodic
commitlog_sync_period_in_ms: 10000
commitlog_segment_size_in_mb: 32

-XX:+UseThreadPriorities -XX:ThreadPriorityPolicy=42 -Xms10G -Xmx10G
-Xmn1024M -XX:+HeapDumpOnOutOfMemoryError
-Xss180k -XX:+UseParNewGC -XX:+UseConcMarkSweepGC
-XX:+CMSParallelRemarkEnabled -XX:SurvivorRatio=8
-XX:MaxTenuringThreshold=1 -XX:CMSInitiatingOccupancyFraction=75
-XX:+UseCMSInitiatingOccupancyOnly -XX:+UseTLAB -XX:+UseCondCardMark

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. I have also taken 10x "jmap -histo" after 5s on a affected
server and plotted the result, attached as well.

I have taken a dump of the application when the heap size was 10GB, most
of the memory was unreachable, which was expected. The majority was used
by 55-59M objects of HeapByteBuffer, byte[] and
org.apache.cassandra.db.Column classes. I also include a list of inbound
references to the HeapByteBuffer objects from which it should be visible
where they are being allocated. This was acquired using Eclipse MAT.

Here is the comparison of GC times when row cache enabled and disabled:

prg01 - row cache enabled
      - uptime 20h45m
      - ConcurrentMarkSweep - 11494686ms
      - ParNew - 14690885 ms
      - time spent in GC: 35%
prg02 - row cache disabled
      - uptime 23h45m
      - ConcurrentMarkSweep - 251ms
      - ParNew - 230791 ms
      - time spent in GC: 0.27%

I would be grateful for any hints. Please let me know if you need any
further information. For now, we are going to disable the row cache.

Jiri Horky