Optimising HANA Query push-down from Apache Spark

As you start using it with larger Tables or Views in HANA, you may notice that the query that is pushed down into HANA is not optimised efficiently. SUM & GROUP BY Clauses are NOT pushed down into HANA,  this may cause a large granular result set to be move across the network, to only be Aggregated in Spark.  That is certainly a waste of HANA's powerful query engine.
In this blog I will demonstrate the problem and show several ways to help get around it, using Apache Spark.

Using the same dataset from the earlier blog  we can see how more complex Spark SQL ( executing against a test table in HANA - "RDATA") is actually pushed down into HANA.

[SAP HANA Academy] Configure the SAP HANA Spark Controller to Read SAP HANA Vora Tables

In another part of the SAP HANA Academy's SAP HANA Vora series Tahir Hussain Babar (Bob) walks through how to configure the SAP HANA Spark Controller in nine tutorial videos. With the SAP HANA Spark Controller you will be able to read your SAP HANA Vora tables from SAP HANA.

Each and every script that Bob uses through out this nine part series can be found here on GitHub.

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