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Date: Wed, 01 Aug 2012 15:51:41 +0200
From: Thomas Spengler <thomas.spengler@toptarif.de>
Organization: Toptarif Internet GmbH
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To: user@cassandra.apache.org
Subject: Re: virtual memory of all cassandra-nodes is growing extremly since
 Cassandra 1.1.0
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Just for information

we are running on 1.1.2
JNA or not, had no difference
Manually call full gc, had no difference

but
in my case

the reduction of
commitlog_total_space_in_mb to 2048 (from default 4096)
makes the difference.


On 07/26/2012 04:27 PM, Mina Naguib wrote:
> 
> Hi Thomas
> 
> On a modern 64bit server, I recommend you pay little attention to the virtual size.  It's made up of almost everything within the process's address space, including on-disk files mmap()ed in for zero-copy access.  It's not unreasonable for a machine with N amount RAM to have a process whose virtual size is several times the value of N.  That in and of itself is not problematic
> 
> In a default cassandra 1.1.x setup, the bulk of that will be your sstables' data and index files.  On linux you can invoke the "pmap" tool on the cassandra process's PID to see what's in there.  Much of it will be anonymous memory allocations (the JVM heap itself, off-heap data structures, etc), but lots of it will be references to files on disk (binaries, libraries, mmap()ed files, etc).
> 
> What's more important to keep an eye on is the JVM heap - typically statically allocated to a fixed size at cassandra startup.  You can get info about its used/capacity values via "nodetool -h localhost info".  You can also hook up jconsole and trend it over time.
> 
> The other critical piece is the process's RESident memory size, which includes the JVM heap but also other off-heap data structures and miscellanea.  Cassandra has recently been making more use of off-heap structures (for example, row caching via SerializingCacheProvider).  This is done as a matter of efficiency - a serialized off-heap row is much smaller than a classical object sitting in the JVM heap - so you can do more with less.
> 
> Unfortunately, in my experience, it's not perfect.  They still have a cost, in terms of on-heap usage, as well as off-heap growth over time.
> 
> Specifically, my experience with cassandra 1.1.0 showed that off-heap row caches incurred a very high on-heap cost (ironic) - see my post at http://mail-archives.apache.org/mod_mbox/cassandra-user/201206.mbox/%3C6FEB097F-287B-471D-BEA2-48862B30F382@bloomdigital.com%3E - as documented in that email, I managed that with regularly scheduled full GC runs via System.gc()
> 
> I have, since then, moved away from scheduled System.gc() to scheduled row cache invalidations.  While this had the same effect as System.gc() I described in my email, it eliminated the 20-30 second pause associated with it.  It did however introduce (or may be I never noticed earlier), slow creep in memory usage outside of the heap.
> 
> It's typical in my case for example for a process configured with 6G of JVM heap to start up, stabilize at 6.5 - 7GB RESident usage, then creep up slowly throughout a week to 10-11GB range.  Depending on what else the box is doing, I've experienced the linux OOM killer killing cassandra as you've described, or heavy swap usage bringing everything down (we're latency-sensitive), etc..
> 
> And now for the good news.  Since I've upgraded to 1.1.2:
> 	1. There's no more need for regularly scheduled System.gc()
> 	2. There's no more need for regularly scheduled row cache invalidation
> 	3. The HEAP usage within the JVM is stable over time
> 	4. The RESident size of the process appears also stable over time
> 
> Point #4 above is still pending as I only have 3 day graphs since the upgrade, but they show promising results compared to the slope of the same graph before the upgrade to 1.1.2
> 
> So my advice is give 1.1.2 a shot - just be mindful of https://issues.apache.org/jira/browse/CASSANDRA-4411
> 
> 
> On 2012-07-26, at 2:18 AM, Thomas Spengler wrote:
> 
>> I saw this.
>>
>> All works fine upto version 1.1.0
>> the 0.8.x takes 5GB of memory of an 8GB machine
>> the 1.0.x takes between 6 and 7 GB on a 8GB machine
>> and
>> the 1.1.0 takes all
>>
>> and it is a problem
>> for me it is no solution to wait of the OOM-Killer from the linux kernel
>> and restart the cassandraprocess
>>
>> when my machine has less then 100MB ram available then I have a problem.
>>
>>
>>
>> On 07/25/2012 07:06 PM, Tyler Hobbs wrote:
>>> Are you actually seeing any problems from this? High virtual memory usage
>>> on its own really doesn't mean anything. See
>>> http://wiki.apache.org/cassandra/FAQ#mmap
>>>
>>> On Wed, Jul 25, 2012 at 1:21 AM, Thomas Spengler <
>>> thomas.spengler@toptarif.de> wrote:
>>>
>>>> No one has any idea?
>>>>
>>>> we tryed
>>>>
>>>> update to 1.1.2
>>>> DiskAccessMode standard, indexAccessMode standard
>>>> row_cache_size_in_mb: 0
>>>> key_cache_size_in_mb: 0
>>>>
>>>>
>>>> Our next try will to change
>>>>
>>>> SerializingCacheProvider to ConcurrentLinkedHashCacheProvider
>>>>
>>>> any other proposals are welcom
>>>>
>>>> On 07/04/2012 02:13 PM, Thomas Spengler wrote:
>>>>> Hi @all,
>>>>>
>>>>> since our upgrade form cassandra 1.0.3 to 1.1.0 the virtual memory usage
>>>>> of the cassandra-nodes explodes
>>>>>
>>>>> our setup is:
>>>>> * 5 - centos 5.8 nodes
>>>>> * each 4 CPU's and 8 GB RAM
>>>>> * each node holds about 100 GB on data
>>>>> * each jvm's uses 2GB Ram
>>>>> * DiskAccessMode is standard, indexAccessMode is standard
>>>>>
>>>>> The memory usage grows upto the whole memory is used.
>>>>>
>>>>> Just for information, as we had cassandra 1.0.3, we used
>>>>> * DiskAccessMode is standard, indexAccessMode is mmap
>>>>> * and the ram-usage was ~4GB
>>>>>
>>>>>
>>>>> can anyone help?
>>>>>
>>>>>
>>>>> With Regards
> 


-- 
Thomas Spengler
Chief Technology Officer
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