* [HUDI-3290] Different file formats for the partition metadata file.
Partition metadata files are stored in each partition to help identify the base path of a table. These files are saved in the properties file format. Some query engines do not work when non Parquet/ORC files are found in a partition.
Added a new table config 'hoodie.partition.metafile.use.data.format' which when enabled (default false for backward compatibility) ensures that partition metafiles will be saved in the same format as the base files of a dataset.
For new datasets, the config can be set via hudi-cli. Deltastreamer has a new parameter --partition-metafile-use-data-format which will create a table with this setting.
* Code review comments
- Adding a new command to migrate from text to base file formats for meta file.
- Reimplementing readFromFS() to first read the text format, then base format
- Avoid extra exists() checks in readFromFS()
- Added unit tests, enabled parquet format across hoodie-hadoop-mr
- Code cleanup, restructuring, naming consistency.
* Wiring in all the other Spark code paths to respect this config
- Turned on parquet meta format for COW data source tests
- Removed the deltastreamer command line to keep it shorter
* populate HoodiePartitionMetadata#format after readFromFS()
Co-authored-by: Vinoth Chandar <vinoth@apache.org>
Co-authored-by: Raymond Xu <2701446+xushiyan@users.noreply.github.com>
- Add a new action called INDEX, whose state transition is described in the RFC.
- Changes in timeline to support the new action.
- Add an index planner in ScheduleIndexActionExecutor.
- Add index plan executor in RunIndexActionExecutor.
- Add 3 APIs in HoodieTableMetadataWriter; a) scheduleIndex: will generate an index plan based on latest completed instant, initialize file groups and add a requested INDEX instant, b) index: executes the index plan and also takes care of writes that happened after indexing was requested, c) dropIndex: will drop index by removing the given metadata partition.
- Add 2 new table configs to serve as the source of truth for inflight and completed indexes.
- Support upgrade/downgrade taking care of the newly added configs.
- Add tool to trigger indexing in HoodieIndexer.
- Handle corner cases related to partial failures.
- Abort gracefully after deleting partition and instant.
- Handle other actions in timeline to consider before catching up
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.
* Remove glob pattern basePath from the deltastreamer tests.
* [HUDI-3689] Fix file scheme config
for CI failure in TestHoodieRealTimeRecordReader
Co-authored-by: Raymond Xu <2701446+xushiyan@users.noreply.github.com>
NOTE: This change is first part of the series to clean up Hudi's Spark DataSource related implementations, making sure there's minimal code duplication among them, implementations are consistent and performant
This PR is making sure that BaseFileOnlyViewRelation only reads projected columns as well as avoiding unnecessary serde from Row to InternalRow
Brief change log
- Introduced HoodieBaseRDD as a base for all custom RDD impls
- Extracted common fields/methods to HoodieBaseRelation
- Cleaned up and streamlined HoodieBaseFileViewOnlyRelation
- Fixed all of the Relations to avoid superfluous Row <> InternalRow conversions
Rework of #4761
This diff introduces following changes:
- Write stats are converted to metadata index records during the commit. Making them use the HoodieData type so that the record generation scales up with needs.
- Metadata index init support for bloom filter and column stats partitions.
- When building the BloomFilter from the index records, using the type param stored in the payload instead of hardcoded type.
- Delta writes can change column ranges and the column stats index need to be properly updated with new ranges to be consistent with the table dataset. This fix add column stats index update support for the delta writes.
Co-authored-by: Manoj Govindassamy <manoj.govindassamy@gmail.com>
