Quick questions: why are you cache both rdd and table?
Which stage of job is slow?
On 23 Apr 2015 17:12, "Nikolay Tikhonov" <[email protected]> wrote:
> Hi,
> I have Spark SQL performance issue. My code contains a simple JavaBean:
>
> public class Person implements Externalizable {
> private int id;
> private String name;
> private double salary;
> ....................
> }
>
>
> Apply a schema to an RDD and register table.
>
> JavaRDD<Person> rdds = ...
> rdds.cache();
>
> DataFrame dataFrame = sqlContext.createDataFrame(rdds, Person.class);
> dataFrame.registerTempTable("person");
>
> sqlContext.cacheTable("person");
>
>
> Run sql query.
>
> sqlContext.sql("SELECT id, name, salary FROM person WHERE salary >= YYY
> AND salary <= XXX").collectAsList()
>
>
> I launch standalone cluster which contains 4 workers. Each node runs on
> machine with 8 CPU and 15 Gb memory. When I run the query on the
> environment
> over RDD which contains 1 million persons it takes 1 minute. Somebody can
> tell me how to tuning the performance?
>
>
>
> --
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