Hudi will be taking on promise for it bundles to stay compatible with Spark minor versions (for ex 2.4, 3.1, 3.2): meaning that single build of Hudi (for ex "hudi-spark3.2-bundle") will be compatible with ALL patch versions in that minor branch (in that case 3.2.1, 3.2.0, etc)
To achieve that we'll have to remove (and ban) "spark-avro" as a dependency, which on a few occasions was the root-cause of incompatibility b/w consecutive Spark patch versions (most recently 3.2.1 and 3.2.0, due to this PR).
Instead of bundling "spark-avro" as dependency, we will be copying over some of the classes Hudi depends on and maintain them along the Hudi code-base to make sure we're able to provide for the aforementioned guarantee. To workaround arising compatibility issues we will be applying local patches to guarantee compatibility of Hudi bundles w/in the Spark minor version branches.
Following Hudi modules to Spark minor branches is currently maintained:
"hudi-spark3" -> 3.2.x
"hudi-spark3.1.x" -> 3.1.x
"hudi-spark2" -> 2.4.x
Following classes hierarchies (borrowed from "spark-avro") are maintained w/in these Spark-specific modules to guarantee compatibility with respective minor version branches:
AvroSerializer
AvroDeserializer
AvroUtils
Each of these classes has been correspondingly copied from Spark 3.2.1 (for 3.2.x branch), 3.1.2 (for 3.1.x branch), 2.4.4 (for 2.4.x branch) into their respective modules.
SchemaConverters class in turn is shared across all those modules given its relative stability (there're only cosmetical changes from 2.4.4 to 3.2.1).
All of the aforementioned classes have their corresponding scope of visibility limited to corresponding packages (org.apache.spark.sql.avro, org.apache.spark.sql) to make sure broader code-base does not become dependent on them and instead relies on facades abstracting them.
Additionally, given that Hudi plans on supporting all the patch versions of Spark w/in aforementioned minor versions branches of Spark, additional build steps were added to validate that Hudi could be properly compiled against those versions. Testing, however, is performed against the most recent patch versions of Spark with the help of Azure CI.
Brief change log:
- Removing spark-avro bundling from Hudi by default
- Scaffolded Spark 3.2.x hierarchy
- Bootstrapped Spark 3.1.x Avro serializer/deserializer hierarchy
- Bootstrapped Spark 2.4.x Avro serializer/deserializer hierarchy
- Moved ExpressionCodeGen,ExpressionPayload into hudi-spark module
- Fixed AvroDeserializer to stay compatible w/ both Spark 3.2.1 and 3.2.0
- Modified bot.yml to build full matrix of support Spark versions
- Removed "spark-avro" dependency from all modules
- Fixed relocation of spark-avro classes in bundles to assist in running integ-tests.
* 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
