- 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
- Data types extending CharSequence implement a #toString method which provides an easy way to convert them to String.
- For example, org.apache.avro.util.Utf8 is easily convertible into String if we use the toString() method. It's better to make the support more generic to support a wider range of data types as partitionKey.
- 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
- Upgrade Spark to 2.4.4, Parquet to 1.10.1, Avro to 1.8.2
- Remove spark-avro from hudi-spark-bundle. Users need to provide --packages org.apache.spark:spark-avro:2.4.4 when running spark-shell or spark-submit
- Replace com.databricks:spark-avro with org.apache.spark:spark-avro
- Shade avro in hudi-hadoop-mr-bundle to make sure it does not conflict with hive's avro version.
- 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
- Provides ability to perform hard deletes by writing delete marker records into the source data
- if the record contains a special field _hoodie_delete_marker set to true, deletes are performed
- Add a transformer class, that adds `Op` fiels if not found in input frame
- Add a payload implementation, that issues deletes when Op=D
- Remove Parquet as a top level source type, consolidate with RowSource
- Made delta streamer work without a property file, simply using overridden cli options
- Unit tests for transformer/payload classes
