Articles & Content

Archives

F09 - Spark Analytics for Database Professionals

Topic: Cross Platform DB2 for z/OS & LUW

Subtopic: 2016



Apache Spark is an open source parallel processing framework for large-scale data analytics that runs across large compute clusters. Spark became a top-level project of the Apache Software Foundation in 2014, with the release of version 1.0 of Apache Spark in May 2014. Spark provides insight of data with faster time-to-value because the querying of large volumes of real-time or archived data is done in-memory. In this session we will outline the most common use cases of Spark and compare them to another popular platform – the Hadoop space as an Open Data Platform. We will also compare the different ways Spark applications can be written in either Python or Scala and provide a comparative analysis amongst the two programming languages for several Spark extensions such as: SQL, machine learning and streaming analysis.



Click Here to Download

NOTE: These are only open to members of IDUG. If you are not a member, please CLICK HERE for more information.