Apache: Big Data North America 2017

Spark's capabilities as a better and faster Hadoop, as a distributed Scala platform, and as an interactive, batch and streaming environment are quite well known. But its prowess to be all that as a multilingual platform have not received sufficient spotlight. Traditionally RDBMS environments needed to glue together set oriented SQL with row-level specialized procedural languages (e.g. Pl/SQL), or use APIs in non-SQL languages e.g. JDBC. In spark however, the confluence of Scala and SQL is that of two equals as both are set or collection oriented, but have their own unique strengths.  This presentation will illustrate with background and examples on how to exploit this fusion of Scala and SQL in a way that takes advantage of both their strengths as well as boosts productivity.