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List:       cassandra-user
Subject:    Re: virtual memory of all cassandra-nodes is growing extremly since Cassandra 1.1.0
From:       Mina Naguib <mina.naguib () bloomdigital ! com>
Date:       2012-07-26 14:27:30
Message-ID: 0F6330E2-C047-44AE-A2FE-DE2D31743F7B () bloomdigital ! com
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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


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