Release 0.5.0 (Dec. 14, 2016)


  • 65 issues resolved
  • Audit tracking.  All changes in Kylo are tracked for audit logging.
  • Spark 2.0 support!
  • PySparkExec support. New NiFi processor for executing Spark Python scripts
  • Plug-in API for adding raw formats.   Ability to plug-in support for new raw file formats and introspect schema
  • New raw formats: Parquet, ORC, Avro, JSON
  • Customize partition functions.  Ability to add custom UDF functions to dropdown for deriving partition keys
  • Feed import enhancements. Allow users to change target category on feed import
  • Sqoop improvements. Improved compatibility with Kylo UI and behavior
  • JPA conversion. Major conversion away from legacy Spring Batch persistence to JPA for Ops Mgr
  • Date/time standardization.  Storage of all dates and times will be epoch time to preserve the ability to apply timezones
  • New installation document showing an example on how to install Kylo on AWS in an HDP 2.5 cluster. Refer to HDP 2.5 Kerberos/Ranger Cluster Deployment Guide
  • Ranger enabled
  • Kerberos enabled
  • Minimal admin privileges
  • NiFi and Kylo on separate edge nodes

Known Issues

Modeshape versioning temporarily disabled for feeds due to rapid storage growth.   We will have a fix for this issue and re-introduce it in 0.5.1.

Potential Impacts

  • JPA conversion requires one-time script (see install instructions)
  • Spark Shell moved into Think Big services /opt directory
  • Date/time modification Timestamp fields converted to Java time for portability and timezone consistency.  Any custom reports will need to be modified