Release 0.4.3 (Nov. 18, 2016)¶
- 67 issues resolved
- Hive user impersonation. Ability to restrict Hive table access throughout Kylo based on permissions of logged-in user.
- Visual data lineage. Visualization of relationship between feeds, data sources, and sinks. Refer to Feed Lineage Configuration
- Auto-layout NiFi feeds. Beautified display of Kylo-generated feeds in NiFi.
- Sqoop export. Sqoop export and other Sqoop improvements from last release.
- Hive table formats. Final Hive table format extended to: RCFILE, CSV, AVRO (in addition to ORC, PARQUET).
- Hive change tracking. Batch timestamp (processing_dttm partition value) carried into final table for change tracking.
- Delete, disable, reorder templates. Ability to disable and/or remove templates as well as change their order in Kylo.
- Spark yarn-cluster support. ExecuteSparkJob processor now supports yarn-cluster mode (thanks Prav!).
- Kylo logo replaces Teradata Thinkbig logo (note: this is not our final approved logo).
Hive impersonation is not supported with CDH if using Sentry.
Wrangler does not yet support user impersonation.
- Existing wrangler feed tables will need to ALTER TABLE to add a processing_dttm field to table in order to work.
- Processing_dttm field is now java epoch time instead of formatted date to be timezone independent. Older feeds will now have partition keys in two different formats.
- All non-feed tables will now be created as managed tables.