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From "Durity, Sean R" <>
Subject RE: [EXTERNAL] Re: Good way of configuring Apache spark with Apache Cassandra
Date Wed, 09 Jan 2019 15:18:22 GMT
I think you could consider option C: Create a (new) analytics DC in Cassandra and run your
spark nodes there. Then you can address the scaling just on that DC. You can also use less
vnodes, only replicate certain keyspaces, etc. in order to perform the analytics more efficiently.

Sean Durity

From: Dor Laor <>
Sent: Friday, January 04, 2019 4:21 PM
Subject: [EXTERNAL] Re: Good way of configuring Apache spark with Apache Cassandra

I strongly recommend option B, separate clusters. Reasons:
 - Networking of node-node is negligible compared to networking within the node
 - Different scaling considerations
   Your workload may require 10 Spark nodes and 20 database nodes, so why bundle them?
   This ratio may also change over time as your application evolves and amount of data changes.
 - Isolation - If Spark has a spike in cpu/IO utilization, you wouldn't want it to affect
Cassandra and the opposite.
   If you isolate it with cgroups, you may have too much idle time when the above doesn't

On Fri, Jan 4, 2019 at 12:47 PM Goutham reddy <<>>
We have requirement of heavy data lifting and analytics requirement and decided to go with
Apache Spark. In the process we have come up with two patterns
a. Apache Spark and Apache Cassandra co-located and shared on same nodes.
b. Apache Spark on one independent cluster and Apache Cassandra as one independent cluster.

Need good pattern how to use the analytic engine for Cassandra. Thanks in advance.



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