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From ka...@comcast.net
Subject Re: Write performance expectations...
Date Thu, 14 Feb 2013 13:07:26 GMT
Using multithreading, inserting 2000 per thread, resulted in no throughput increase. Each thread
is taking about 4 seconds per, indicating a bottleneck elsewhere. 




Ken.... 
----- Original Message -----
From: "Tyler Hobbs" <tyler@datastax.com> 
To: user@cassandra.apache.org 
Sent: Wednesday, February 13, 2013 11:06:30 AM 
Subject: Re: Write performance expectations... 


2500 inserts per second is about what a single python thread using pycassa can do against
a local node. Are you using multiple threads for the inserts? Multiple processes? 




On Wed, Feb 13, 2013 at 8:21 AM, Alain RODRIGUEZ < arodrime@gmail.com > wrote: 



Is there a particular reason for you to use EBS ? Instance Store are recommended because they
improve performances by reducing the I/O throttling. 


An other thing you should be aware of is that replicating the data to all node reduce your
performance, it is more or less like if you had only one node (at performance level I mean).



Also, writing to different datacenters probably induce some network latency. 


You should give the EC2 instance type (m1.xlarge / m1.large / ...) if you want some feedback
about the 2500 w/s, and also give the mean size of your rows. 


Alain 



2013/2/13 < kadey@comcast.net > 



<blockquote>


Hello, 
New member here, and I have (yet another) question on write performance. 

I'm using Apache Cassandra version 1.1, Python 2.7 and Pycassa 1.7. 

I have a cluster of 2 datacenters, each with 3 nodes, on AWS EC2 using EBS and the RandomPartioner.
I'm writing to a column family in a keyspace that's replicated to all nodes in both datacenters,
with a consistency level of LOCAL_QUORUM. 

I'm seeing write performance of around 2500 rows per second. 

Is this in the ballpark for this kind of configuration? 

Thanks in advance. 




Ken.... 




</blockquote>



-- 
Tyler Hobbs 
DataStax 

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