Hello,
We are evaluating Cassandra performance and would like to know if the
numbers we've gotten can be improved upon. Right now we're just testing a
simple key/value store using the cassandra-stress tool. A quick summary of
our setup:
* Using the datastax 2.2 distribution, Oracle HotSpot Java
Hi,
Thanks for the information..
I upgraded my cassandra version to 1.2.0 and tried running the
experiment again to find the statistics.
My application took nearly 529 seconds for querying 76896 keys.
Please find the statistic information below for 32 threads ( where
each thread query 76896 key
You can also see what it looks like from the server side.
nodetool proxyhistograms will show you full request latency recorded by the
coordinator.
nodetool cfhistograms will show you the local read latency, this is just the
time it takes to read data on a replica and does not include network o
The fact that it's still exactly 521 seconds is very suspicious. I can't
debug your script over the mailing list, but do some sanity checks to make
sure there's not a bottleneck somewhere you don't expect.
On Fri, Jan 18, 2013 at 12:44 PM, Pradeep Kumar Mantha wrote:
> Hi,
>
> Thanks Tyler.
>
Hi,
Thanks Tyler.
Below is the *global* connection pool I am trying to use, where the
server_list contains all the ips of 12 DataNodes I am using and
pool_size is the number of threads and I just set to timeout to 60 to
avoid connection retry errors.
pool = pycassa.ConnectionPool('Blast',
serve
You just need to increase the ConnectionPool size to handle the number of
threads you have using it concurrently. Set the pool_size kwarg to at
least the number of threads you're using.
On Thu, Jan 17, 2013 at 6:46 PM, Pradeep Kumar Mantha
wrote:
> Thanks Tyler.
>
> I just moved the pool and cf
Thanks Tyler.
I just moved the pool and cf which store the connection pool and CF
information to have global scope.
Increased the server_list values from 1 to 4. ( i think i can increase
them max to 12 since I have 12 data nodes )
when I created 8 threads using python threading package , I see
ConnectionPools and ColumnFamilies are thread-safe in pycassa, and it's
best to share them across multiple threads. Of course, when you do that,
make sure to make the ConnectionPool large enough to support all of the
threads making queries concurrently. I'm also not sure if you're just
omitting t
Hi,
Thanks. I would like to benchmark cassandra with our application so
that we understand the details of how the actual benchmarking is done.
Not sure, how easy it would be to integrate YCSB with our application.
So, i am trying different client interfaces to cassandra.
I found
for 12 Data Nod
Wow you managed to do a load test through the cassandra-cli. There should
be a merit badge for that.
You should use the built in stress tool or YCSB.
The CLI has to do much more string conversion then a normal client would
and it is not built for performance. You will definitely get better number
Hi,
I am trying to maximize execution of the number of read queries/second.
Here is my cluster configuration.
Replication - Default
12 Data Nodes.
16 Client Nodes - used for querying.
Each client node executes 32 threads - each thread executes 76896 read
queries using cassandra-cli tool.
> 1. Changing consistency level configurations from Write.ALL + Read.ONE
> to Write.ALL + Read.ALL increases write latency (expected) and
> decrease read latency (unexpected).
When you tested at CL.ONE, was read repair turned on?
The two ways I can think of right now, by which read latency might
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