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.
Make all tests in org.apache.hudi.cli.commands extend org.apache.hudi.cli.functional.CLIFunctionalTestHarness and tag as "functional".
This also resolves a blocker where DFS init consistently failed when moving to ubuntu 18.04
- 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-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>
- use codecov flags for each module to report coverage
- parallelize CI jobs for shorter time
- add a testcase for MetricsReporterFactory (to trigger codecov comment)
- Add spotless format fixing to project
- One time reformatting for conformity
- Build fails for formatting changes and mvn spotless:apply autofixes them
- Documented principles applied for redesign at packaging/README.md
- No longer depends on incl commons-codec, commons-io, commons-pool, commons-dbcp, commons-lang, commons-logging, avro-mapred
- Introduce new FileIOUtils & added checkstyle rule for illegal import of above
- Parquet, Avro dependencies moved to provided scope to enable being picked up from Hive/Spark/Presto instead
- Pickup jackson jars for Hive sync tool from HIVE_HOME & unbundling jackson everywhere
- Remove hive-jdbc standalone jar from being bundled in Spark/Hive/Utilities bundles
- 6.5x reduced number of classes across bundles
- Redo all classes based on org.parquet only
- remove unuused dependencies like parquet-hadoop, common-configuration2
- timeline-service does not build a fat jar anymore
- Fix utilities and hadoop-mr bundles based on above
- [HUDI-172] Cleanup Maven POM/Classpath
- Fix ordering of dependencies in poms, to enable better resolution
- Idea is to place more specific ones at the top
- And place dependencies which use them below them
- [HUDI-68] : Automate demo steps on docker setup
- Move hive queries from hive cli to beeline
- Standardize on taking query input from text command files
- Deltastreamer ingest, also does hive sync in a single step
- Spark Incremental Query materialized as a derived Hive table using datasource
- Fix flakiness in HDFS spin up and output comparison
- Code cleanup around streamlining and loc reduction
- Also fixed pom to not shade some hive classs in spark, to enable hive sync
