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
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.
- 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