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From Edward Capriolo <>
Subject Re: Practical node size limits
Date Mon, 30 Jul 2012 03:45:48 GMT
Yikes. You should read:

Essentially what it sounds like your are now running into is this:

The BloomFilters for each SSTable must exist in main memory. Repair
tends to create some extra data which normally gets compacted away

Your best bet is to temporarily raise the Xmx heap and adjust the
index sampling size. If you need to save the data (if it is just test
data you may want to give up and start fresh)

Generally the issue with the large disk configurations it is hard to
keep a good ram/disk ratio. Then most reads turn into disk seeks and
the throughput is low. I get the vibe people believe large stripes are
going to help Cassandra. The issue is that stripes generally only
increase sequential throughput, but Cassandra is a random read system.

How much ram/disk you need is case dependent but 1/5 ratio of RAM to
disk is where I think most people want to be, unless their system is
carrying SSD disks.

Again you have to keep your bloom filters in java heap memory so and
design that tries to create a quatrillion small rows is going to have
memory issues as well.

On Sun, Jul 29, 2012 at 10:40 PM, Dustin Wenz <> wrote:
> I'm trying to determine if there are any practical limits on the amount of data that
a single node can handle efficiently, and if so, whether I've hit that limit or not.
> We've just set up a new 7-node cluster with Cassandra 1.1.2 running under OpenJDK6. Each
node is 12-core Xeon with 24GB of RAM and is connected to a stripe of 10 3TB disk mirrors
(a total of 20 spindles each) and connected via dual SATA-3 interconnects. I can read and
write around 900MB/s sequentially on the arrays. I started out with Cassandra tuned with all-default
values, with the exception of the compaction throughput which was increased from 16MB/s to
100MB/s. These defaults will set the heap size to 6GB.
> Our schema is pretty simple; only 4 column families and each has one secondary index.
The replication factor was set to four, and compression disabled. Our access patterns are
intended to be about equal numbers of inserts and selects, with no updates, and the occasional
> The first thing we did was begin to load data into the cluster. We could perform about
3000 inserts per second, which stayed mostly flat. Things started to go wrong around the time
the nodes exceeded 800GB. Cassandra began to generate a lot of "mutations messages dropped"
warnings, and was complaining that the heap was over 75% capacity.
> At that point, we stopped all activity on the cluster and attempted a repair. We did
this so we could be sure that the data was fully consistent before continuing. Our mistake
was probably trying to repair all of the nodes simultaneously - within an hour, Java terminated
on one of the nodes with a heap out-of-memory message. I then increased all of the heap sizes
to 8GB, and reduced the heap_newsize to 800MB. All of the nodes were restarted, and there
was no no outside activity on the cluster. I then began a repair on a single node. Within
a few hours, it OOMed again and exited. I then increased the heap to 12GB, and attempted the
same thing. This time, the repair ran for about 7 hours before exiting from an OOM condition.
> By now, the repair had increased the amount of data on some of the nodes to over 1.2TB.
There is no going back to a 6GB heap size - Cassandra now exits with an OOM during startup
unless the heap is set higher. It's at 16GB now, and a single node has been repairing for
a couple of days. Though I have no personal experience with this, I've been told that Java's
garbage collector doesn't perform well with heaps above 8GB. I'm wary of setting it higher,
but I can add up to 192GB of RAM to each node if necessary.
> How much heap does cassandra need for this amount of data with only four CFs? Am I scaling
this cluster in completely the wrong direction? Is there a magic garbage collection setting
that I need to add in cassandra-env that isn't there by default?
> Thanks,
>   - .Dustin

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