Is there any specific reason for using Cassandra for search instead of using
something like elastic search & Kibana?
________________________________
From: Jan<mailto:cne...@yahoo.com>
Sent: 1/31/2015 1:08 PM
To: user@cassandra.apache.org<mailto:user@cassandra.apache.org>
Subject: Re: Cassandra 2.0.11 with stargate-core read writes are slow
HI Asit;
Question 1) Am I using the right hardware as of now I am testing say 100000
record reads.
Answer: Recommend looking at either the 'sar' output logs & watching nodetool
cfstats & watching your system.log files to track hardware usage & JVM
presssure. As a rule of thumb, its recommeneded to have 8 GB for the C* JVM
itself on production systems.
Question 3) Is unclear, pl. rephrase the question.
hope this helpsJan
C* Architect
On Saturday, January 31, 2015 5:33 AM, Carlos Rolo <r...@pythian.com>
wrote:
HI Asit,
The only help I'm going to give is on point 3), as I have little experience
with 2) and 1) depends on a lot of factors.
For testing the workload use this:
http://www.datastax.com/documentation/cassandra/2.1/cassandra/tools/toolsCStress_t.html
It probably covers all your testing needs.
Regards,
Carlos Juzarte RoloCassandra Consultant Pythian - Love your data
rolo@pythian | Twitter: cjrolo | Linkedin:
linkedin.com/in/carlosjuzarteroloTel: 1649www.pythian.com
On Sat, Jan 31, 2015 at 2:49 AM, Asit KAUSHIK <asitkaushikno...@gmail.com>
wrote:
Hi all,
We are testing our logging application on 3 node cluster each system is virtual
machine with 4 cores and 8GB RAM with RedHat enterprise. Now my question is in
3 parts
1) Am I using the right hardware as of now I am testing say 100000 record reads.
2) I am using Stargate-core for full text search is there any slowness observed
because of that as ???
2) How can I simulate the write load I created an application which creates say
20 threads and each tread I insert 1000 records and on each thread I open
cluster connection session connection execute 1000 records and close the
connection. This takes a lot of time please suggest if I missing something
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