Caching DataFrame in Spark Thrift Server

Question

I have a Spark Thrift Server. I connect to the Thrift Server and get data of Hive table. If I query the same table again, it will again load the file in memory and execute the query.

Is there any way I can cache the table data using Spark Thrift Server? If yes, please let me know how to do it

Answer 1

Pay attention that memory could be consumed by the Driver, not the executor (depend on your settings, local/cluster ...), so don't forget to allocate more memory to your driver.

To put in data:

CACHE TABLE today AS
SELECT * FROM datahub WHERE year=2017 AND fullname IN ("api.search.search") LIMIT 40000

Start by limiting the data, then look how memory is consumed to avoid OOM exception.

Answer 2

Two things:

• use CACHE LAZY TABLE as in this answer: Spark SQL: how to cache sql query result without using rdd.cache() and cache tables in apache spark sql
• use spark.sql.hive.thriftServer.singleSession=true so that other clients can use this cached table.

Remember that caching is lazy, so it will be cached during first computation