- Brings more order and cohesion to the classes in hudi-common
- Utils classes related to a particular concept (avro, timeline,...) are placed near to the package
- common.fs package now contains all the filesystem level classes including wrapper filesystem
- bloom.filter package renamed to just bloom
- config package contains classes that help store properties
- common.fs.inline package contains all the inline filesystem classes/impl
- common.table.timeline now consolidates all timeline related classes
- common.table.view consolidates all the classes related to filesystem view metadata
- common.table.timeline.versioning contains all classes related to versioning of timeline
- Fix few unit tests as a result
- Moved the test packages around to match the source file move
- Rename AvroUtils to TimelineMetadataUtils & minor fixes/typos
- Just package, class moves and renames with the following intent
- `client` now has all the various client classes, that do the transaction management
- `func` renamed to `execution` and some helpers moved to `client/utils`
- All compaction code under `io` now under `table/compact`
- Rollback code under `table/rollback` and in general all code for individual operations under `table`
- `exception` `config`, `metrics` left untouched
- Moved the tests also accordingly
- Fixed some flaky tests
- Storage Type replaced with Table Type (remaining instances)
- View types replaced with query types;
- ReadOptimized view referred as Snapshot Query
- TableFileSystemView sub interfaces renamed to BaseFileOnly and Slice Views
- HoodieDataFile renamed to HoodieBaseFile
- Hive Sync tool will register RO tables for MOR with a `_ro` suffix
- Datasource/Deltastreamer options renamed accordingly
- Support fallback to old config values as well, so migration is painless
- Config for controlling _ro suffix addition
- Renaming DataFile to BaseFile across DTOs, HoodieFileSlice and AbstractTableFileSystemView
- Docs were talking about storage types before, cWiki moved to "Table"
- Most of code already has HoodieTable, HoodieTableMetaClient - correct naming
- Replacing renaming use of dataset across code/comments
- Few usages in comments and use of Spark SQL DataSet remain unscathed
- Introduced configs for bloom filter type
- Implemented dynamic bloom filter with configurable max number of keys
- BloomFilterFactory abstractions; Defaults to current simple bloom filter
Before this change, Cleaner performs cleaning of old file versions and then stores the deleted files in .clean files.
With this setup, we will not be able to track file deletions if a cleaner fails after deleting files but before writing .clean metadata.
This is fine for regular file-system view generation but Incremental timeline syncing relies on clean/commit/compaction metadata to keep a consistent file-system view.
Cleaner state transitions is now similar to that of compaction.
1. Requested : HoodieWriteClient.scheduleClean() selects the list of files that needs to be deleted and stores them in metadata
2. Inflight : HoodieWriteClient marks the state to be inflight before it starts deleting
3. Completed : HoodieWriteClient marks the state after completing the deletion according to the cleaner plan
