The released docker image is available here.

Major features

• Support for SQL-on-FHIR-v2 views in relational DBs; issues #821 #822 #916
• Several improvements in memory management/requirements; issues #777 #823 #824 #948
• Support for OAuth based authentication in the pipelines/controller; issue #587
• Sample Spark SQL flat views added for 10+ resources; issues #820

Bug fixes/minor features

• Fix resource ID's mismatch between original FHIR resource and the corresponding resource in the parquet file in HAPI JDBC mode. by @vbothe23 in https://github.com/google/fhir-data-pipes/pull/754
• Handling large resource parsing exception using DataFormatException by @suriyan3 in https://github.com/google/fhir-data-pipes/pull/756
• Fixes missing QuestionnaireResponse answer fields by @bashir2 in https://github.com/google/fhir-data-pipes/pull/759
• Fixed bugs in recursion depth and added a path example by @bashir2 in https://github.com/google/fhir-data-pipes/pull/761
• Add user name and password to controller config by @LJNIC in https://github.com/google/fhir-data-pipes/pull/781
• Added sample flat views for 12 resources by @bashir2 in https://github.com/google/fhir-data-pipes/pull/844
• Added the option for automatic registration of views. by @bashir2 in https://github.com/google/fhir-data-pipes/pull/850
• Register micrometer gauges as strong references by @chandrashekar-s in https://github.com/google/fhir-data-pipes/pull/852
• Addressed "critical" docker image vulnerabilities by @bashir2 in https://github.com/google/fhir-data-pipes/pull/860
• Prevent creation of resource tables for erroneous DWH dirs by @bashir2 in https://github.com/google/fhir-data-pipes/pull/866
• Changes to support the Windows OS platform by @chandrashekar-s in https://github.com/google/fhir-data-pipes/pull/868
• Do not display the View Raw Logs button when the error file is not available by @chandrashekar-s in https://github.com/google/fhir-data-pipes/pull/870
• adds uuid to the list of primitive types by @bashir2 in https://github.com/google/fhir-data-pipes/pull/937
• Fixes the changes in handling of text vs zipped resources in recent HAPI versions by @muhammad-levi in https://github.com/google/fhir-data-pipes/pull/926
• Deprecation of maxWorkers param by @chandrashekar-s in https://github.com/google/fhir-data-pipes/pull/951
• replaces the spinner GIF with CSS by @bashir2 in https://github.com/google/fhir-data-pipes/pull/953
• Update Hibernate.dialect for latest HAPI version by @chandrashekar-s in https://github.com/google/fhir-data-pipes/pull/970
• Some minor pom clean-ups by @bashir2 in https://github.com/google/fhir-data-pipes/pull/962
• Minor change/fix in default memory by @bashir2 in https://github.com/google/fhir-data-pipes/pull/972

New Contributors

• @suriyan3 made their first contribution in https://github.com/google/fhir-data-pipes/pull/756
• @vbothe23 made their first contribution in https://github.com/google/fhir-data-pipes/pull/754
• @LJNIC made their first contribution in https://github.com/google/fhir-data-pipes/pull/781
• @muhammad-levi made their first contribution in https://github.com/google/fhir-data-pipes/pull/926

Full Changelog: https://github.com/google/fhir-data-pipes/compare/0.1.0...0.3.0

This is the first beta release. The released docker image is available here.

Main features

• Pipelines to fetch resources from a FHIR server and transform them into Analytics friendly formats:
  • Input modes include: FHIR-search API, direct JDBC connection (for HAPI FHIR or OpenMRS), and JSON files.
  • Output modes include: Parquet files, another FHIR server, or PostgreSQL JSONB based tables.
  • Pipelines implemented using Apache Beam making it possible to run on different local or cluster environments such as Apache Flink, Apache Spark or Dataflow.
  • Support bulk fetch of all resources and incremental updates.
• A controller to manage and monitor continuous updates of the data warehouse:
  • Simplifies monitoring of pipelines, shows progress, vital pipeline execution metrics, error logs, etc.
  • Automatically updates table definitions if a Spark Thrift-server is configured.
• Updated version of the Bunsen library to convert FHIR resources to SQL-on-FHIR based records.
  • Added FHIR R4 support.
  • High fidelity with SQL-on-FHIR on BigQuery.
• A set of docker based configurations to demonstrate sample deployment options.
• Cloud Build based end-to-end tests continuously run on each PR.
• A corpus of Wiki pages on how to use the components, connect them to external tools, and query the data-warehouse.