Spark is an in-memory architecture, so you're not going to see it go faster
than CQL for a simple select from 1 table on a few keys. Where you'll see a
benefit is loading lots of data into memory and doing some "report like"
query where you join data from multiple tables.
On Thu, Dec 11, 2014 at 8:09 AM, Ajay <ajay.ga...@gmail.com> wrote:
> Hi,
>
> To test Spark SQL Vs CQL performance on Cassandra, I did the following:
>
> 1) Cassandra standalone server (1 server in a cluster)
> 2) Spark Master and 1 Worker
> Both running in a Thinkpad laptop with 4 cores and 8GB RAM.
> 3) Written Spark SQL code using Cassandra-Spark Driver from Cassandra
> (JavaApiDemo.java. Run with spark://127.0.0.1:7077 127.0.0.1)
> 4) Writen CQL code using Java driver from Cassandra
> (CassandraJavaApiDemo.java)
> In both the case, I create 1 millions rows and query for 1
>
> Observation:
> 1) It takes less than 10 milliseconds using CQL (SELECT * FROM users WHERE
> name='Anna')
> 2) It takes around .6 second using Spark (either SELECT * FROM users WHERE
> name='Anna' or javaFunctions(sc).cassandraTable("test", "people",
> mapRowTo(Person.class)).where("name=?", "Anna");
>
> Please let me know if I am missing something in Spark configuration or
> Cassandra-Spark Driver.
>
> Thanks
> Ajay Garga
>
>
>
>
>
