* Bootstrapping initial support for Metadata Table in Spark Datasource
- Consolidated Avro/Row conversion utilities to center around Spark's AvroDeserializer ; removed duplication
- Bootstrapped HoodieBaseRelation
- Updated HoodieMergeOnReadRDD to be able to handle Metadata Table
- Modified MOR relations to be able to read different Base File formats (Parquet, HFile)
Fix dependency conflict
Fix repairs command
Implement putIfAbsent for DDB lock provider
Add upgrade step and validate while fetching configs
Validate checksum for latest table version only while fetching config
Move generateChecksum to BinaryUtil
Rebase and resolve conflict
Fix table version check
* Introduce hudi-spark3-common and hudi-spark2-common modules to place classes that would be reused in different spark versions, also introduce hudi-spark3.1.x to support spark 3.1.x.
* Introduce hudi format under hudi-spark2, hudi-spark3, hudi-spark3.1.x modules and change the hudi format in original hudi-spark module to hudi_v1 format.
* Manually tested on Spark 3.1.2 and Spark 3.2.0 SQL.
* Added a README.md file under hudi-spark-datasource module.
- Fixing packaging, naming of classes
- Use of log4j over slf4j for uniformity
- More follow-on fixes
- Added a version to control/coordinator events.
- Eliminated the config added to write config
- Fixed fetching of checkpoints based on table type
- Clean up of naming, code placement
Co-authored-by: Rajesh Mahindra <rmahindra@Rajeshs-MacBook-Pro.local>
Co-authored-by: Vinoth Chandar <vinoth@apache.org>
- Added two sources for two stage pipeline. a. S3EventsSource that fetches events from SQS and ingests to a meta hoodie table. b. S3EventsHoodieIncrSource reads S3 events from this meta hoodie table, fetches actual objects from S3 and ingests to sink hoodie table.
- Added selectors to assist in S3EventsSource.
Co-authored-by: Satish M <84978833+satishmittal1111@users.noreply.github.com>
Co-authored-by: Vinoth Chandar <vinoth@apache.org>
* fix azure pipeline configs
* add pentaho.org in maven repositories
* Make sure file paths with scheme in TestParquetUtils
* add azure build status to README
Main functions:
Support create table for hoodie.
Support CTAS.
Support Insert for hoodie. Including dynamic partition and static partition insert.
Support MergeInto for hoodie.
Support DELETE
Support UPDATE
Both support spark2 & spark3 based on DataSourceV1.
Main changes:
Add sql parser for spark2.
Add HoodieAnalysis for sql resolve and logical plan rewrite.
Add commands implementation for CREATE TABLE、INSERT、MERGE INTO & CTAS.
In order to push down the update&insert logical to the HoodieRecordPayload for MergeInto, I make same change to the
HoodieWriteHandler and other related classes.
1、Add the inputSchema for parser the incoming record. This is because the inputSchema for MergeInto is different from writeSchema as there are some transforms in the update& insert expression.
2、Add WRITE_SCHEMA to HoodieWriteConfig to pass the write schema for merge into.
3、Pass properties to HoodieRecordPayload#getInsertValue to pass the insert expression and table schema.
Verify this pull request
Add TestCreateTable for test create hoodie tables and CTAS.
Add TestInsertTable for test insert hoodie tables.
Add TestMergeIntoTable for test merge hoodie tables.
Add TestUpdateTable for test update hoodie tables.
Add TestDeleteTable for test delete hoodie tables.
Add TestSqlStatement for test supported ddl/dml currently.
