- This change breaks `hudi-client` into `hudi-client-common` and `hudi-spark-client` modules
- Simple usages of Spark using jsc.parallelize() has been redone using EngineContext#map, EngineContext#flatMap etc
- Code changes in the PR, break classes into `BaseXYZ` parent classes with no spark dependencies living in `hudi-client-common`
- Classes on `hudi-spark-client` are named `SparkXYZ` extending the parent classes with all the Spark dependencies
- To simplify/cleanup, HoodieIndex#fetchRecordLocation has been removed and its usages in tests replaced with alternatives
Co-authored-by: Vinoth Chandar <vinoth@apache.org>
* [HUDI-1181] Fix decimal type display issue for record key field
* Remove getNestedFieldVal method from DataSourceUtils
* resolve comments
Co-authored-by: Wenning Ding <wenningd@amazon.com>
For Delete API, "hoodie.delete.shuffle.parallelism" isn't used as opposed to "hoodie.upsert.shuffle.parallelism" is used for upsert, this creates the performance difference between delete by upsert API with "EmptyHoodieRecordPayload" and delete API for certain cases.
This patch makes the following fixes in this regard.
- Let deduplicateKeys method use "hoodie.delete.shuffle.parallelism"
- Repartition inputRDD as "hoodie.delete.shuffle.parallelism" in case "hoodie.combine.before.delete=false"
- Adding ability to use native spark row writing for bulk_insert
- Controlled by `ENABLE_ROW_WRITER_OPT_KEY` datasource write option
- Introduced KeyGeneratorInterface in hudi-client, moved KeyGenerator back to hudi-spark
- Simplified the new API additions to just two new methods : getRecordKey(row), getPartitionPath(row)
- Fixed all built-in key generators with new APIs
- Made the field position map lazily created upon the first call to row based apis
- Implemented native row based key generators for CustomKeyGenerator
- Fixed all the tests, with these new APIs
Co-authored-by: Balaji Varadarajan <varadarb@uber.com>
Co-authored-by: Vinoth Chandar <vinoth@apache.org>
- This PR implements Spark Datasource for MOR table in the RDD approach.
- Implemented SnapshotRelation
- Implemented HudiMergeOnReadRDD
- Implemented separate Iterator to handle merge and unmerge record reader.
- Added TestMORDataSource to verify this feature.
- Clean up test file name, add tests for mixed query type tests
- We can now revert the change made in DefaultSource
Co-authored-by: Vinoth Chandar <vchandar@confluent.io>
- Generalize the hive-sync module for syncing to multiple metastores
- Added new options for datasource
- Added new command line for delta streamer
Co-authored-by: Vinoth Chandar <vinoth@apache.org>
- [HUDI-418] Bootstrap Index Implementation using HFile with unit-test
- [HUDI-421] FileSystem View Changes to support Bootstrap with unit-tests
- [HUDI-424] Implement Query Side Integration for querying tables containing bootstrap file slices
- [HUDI-423] Implement upsert functionality for handling updates to these bootstrap file slices
- [HUDI-421] Bootstrap Write Client with tests
- [HUDI-425] Added HoodieDeltaStreamer support
- [HUDI-899] Add a knob to change partition-path style while performing metadata bootstrap
- [HUDI-900] Metadata Bootstrap Key Generator needs to handle complex keys correctly
- [HUDI-424] Simplify Record reader implementation
- [HUDI-423] Implement upsert functionality for handling updates to these bootstrap file slices
- [HUDI-420] Hoodie Demo working with hive and sparkSQL. Also, Hoodie CLI working with bootstrap tables
Co-authored-by: Mehrotra <uditme@amazon.com>
Co-authored-by: Vinoth Chandar <vinoth@apache.org>
Co-authored-by: Balaji Varadarajan <varadarb@uber.com>
- Consolidate transform functions for tests in Transformations.java
- Consolidate assertion functions for tests in Assertions.java
- Make use of SchemaTestUtil for loading schema from resource
* [HUDI-472] Introduce the configuration and new modes of record sorting for bulk_insert(#1149). Three sorting modes are implemented: global sort ("global_sort"), local sort inside each RDD partition ("partition_sort") and no sort ("none")
- use codecov flags for each module to report coverage
- parallelize CI jobs for shorter time
- add a testcase for MetricsReporterFactory (to trigger codecov comment)
Notable changes:
1. HoodieFileWriter and HoodieFileReader abstractions for writer/reader side of a base file format
2. HoodieDataBlock abstraction for creation specific data blocks for base file formats. (e.g. Parquet has HoodieAvroDataBlock)
3. All hardocded references to Parquet / Parquet based classes have been abstracted to call methods which accept a base file format
4. HiveSyncTool accepts the base file format as a CLI parameter
5. HoodieDeltaStreamer accepts the base file format as a CLI parameter
6. HoodieSparkSqlWriter accepts the base file format as a parameter
