DataHub v0.3.1

Added

• 3765c1d Enable parallel Gradle build @keremsahin1
• #1575 Enable Failed Metadata Change Event for MCE Processor @arunvasudevan
• #1570 Use pictureLink property to show person picture @afranzi
• #1569 Show Dataset description in Dataset view @afranzi
• #1597 Ingestion tool to load JSON data to DataHub (in /contrib) @clojurians-org
• #1585 Nix sandbox (in /contrib) @clojurians-org
• 71f2d14 Added EventUtilsTest @keremsahin1

Changed

• 36a5d23 Migrate to getSnapshot API & remove dataset snapshot @keremsahin1
• b17b91f Bump gradle to 5.6.4 and pegasus to 27.7.18 @keremsahin1
• Documentation

Removed

• #1581 Drop LinkedIn internal fabrics @mars-lan
• 1fff6c9 Cleanup unused snapshot resources for corp users & groups @keremsahin1

Fixed

• #1590 Gradle Build Fails When Run in Parallel @RyanHolstien
• #1574 Fix typo and watchman error @clojurians-org
• #1564 Allow dashes in user urn @ben5448
• 3d64c45 Fix browse result pagination @keremsahin1
• fba5cd8 Handle optional aspects/fields for CorpUser gracefully @keremsahin1

DataHub v0.3.0

• Onboarded people as a top level entity
• Enabled people search
• Created Docker image for running ingestion pipeline
• Misc bug fixes
• Documentation updates
• Code cleanup

DataHub v0.2.0-alpha

• Added Neo4j graph indexing/querying pipeline
• Dataset downstream lineage is now powered by graph
• Added MySQL ETL example
• Updated docker-compose settings for low resource environments
• Misc bug fixes

DataHub v0.1.1-alpha

• Added Kafka crawler sample
• Added support for surfacing downstream dataset lineage using search. This is a stop-gap solution until neo4j support is added

Data Hub v0.1.0-alpha

First official release of Data Hub:

• Leveraging GMA architecture
• Backend: GMS implementation - support for dataset & user entities
• Frontend: Data Hub Web Application
• Pub-sub: Kafka
• Stream processing: MXE consumer jobs using Kafka Streams
• Generic modeling layer with CRUD on MySQL
• Search support using Elasticsearch
• Supported metadata sources: LDAP and Hive