- Changes the default config of marker type (HoodieWriteConfig.MARKERS_TYPE or hoodie.write.markers.type) from DIRECT to TIMELINE_SERVER_BASED for Spark Engine.
- Adds engine-specific marker type configs: Spark -> TIMELINE_SERVER_BASED, Flink -> DIRECT, Java -> DIRECT.
- Uses DIRECT markers as well for Spark structured streaming due to timeline server only available for the first mini-batch.
- Fixes the marker creation method for non-partitioned table in TimelineServerBasedWriteMarkers.
- Adds the fallback to direct markers even when TIMELINE_SERVER_BASED is configured, in WriteMarkersFactory: when HDFS is used, or embedded timeline server is disabled, the fallback to direct markers happens.
- Fixes the closing of timeline service.
- Fixes tests that depend on markers, mainly by starting the timeline service for each test.
* Rebased `DFSPropertiesConfiguration` to access Hadoop config in liue of FS to avoid confusion
* Fixed `readConfig` to take Hadoop's `Configuration` instead of FS;
Fixing usages
* Added test for local FS access
* Rebase to use `FSUtils.getFs`
* Combine properties provided as a file along w/ overrides provided from the CLI
* Added helper utilities to `HoodieClusteringConfig`;
Make sure corresponding config methods fallback to defaults;
* Fixed DeltaStreamer usage to respect properly combined configuration;
Abstracted `HoodieClusteringConfig.from` convenience utility to init Clustering config from `Properties`
* Tidying up
* `lint`
* Reverting changes to `HoodieWriteConfig`
* Tdiying up
* Fixed incorrect merge of the props
* Converted `HoodieConfig` to wrap around `Properties` into `TypedProperties`
* Fixed compilation
* Fixed compilation
- Adds support for generating commit timestamps with millisecs granularity.
- Older commit timestamps (in secs granularity) will be suffixed with 999 and parsed with millisecs format.
* [HUDI-2795] Add mechanism to safely update,delete and recover table properties
- Fail safe mechanism, that lets queries succeed off a backup file
- Readers who are not upgraded to this version of code will just fail until recovery is done.
- Added unit tests that exercises all these scenarios.
- Adding CLI for recovery, updation to table command.
- [Pending] Add some hash based verfication to ensure any rare partial writes for HDFS
* Fixing upgrade/downgrade infrastructure to use new updation method
* Enabling timeline server based markers
* Enabling timeline server based markers and marker based rollback
* Removing constraint that timeline server can be enabled only for hdfs
* Fixing tests
* [HUDI-2285] Adding Synchronous updates to metadata before completion of commits in data timelime.
- This patch adds synchronous updates to metadata table. In other words, every write is first committed to metadata table followed by data table. While reading metadata table, we ignore any delta commits that are present only in metadata table and not in data table timeline.
- Compaction of metadata table is fenced by the condition that we trigger compaction only when there are no inflight requests in datatable. This ensures that all base files in metadata table is always in sync with data table(w/o any holes) and only there could be some extra invalid commits among delta log files in metadata table.
- Due to this, archival of data table also fences itself up until compacted instant in metadata table.
All writes to metadata table happens within the datatable lock. So, metadata table works in one writer mode only. This might be tough to loosen since all writers write to same FILES partition and so, will result in a conflict anyways.
- As part of this, have added acquiring locks in data table for those operations which were not before while committing (rollback, clean, compaction, cluster). To note, we were not doing any conflict resolution. All we are doing here is to commit by taking a lock. So that all writes to metadata table is always a single writer.
- Also added building block to add buckets for partitions, which will be leveraged by other indexes like record level index, etc. For now, FILES partition has only one bucket. In general, any number of buckets per partition is allowed and each partition has a fixed fileId prefix with incremental suffix for each bucket within each partition.
Have fixed [HUDI-2476]. This fix is about retrying a failed compaction if it succeeded in metadata for first time, but failed w/ data table.
- Enabling metadata table by default.
- Adding more tests for metadata table
Co-authored-by: Prashant Wason <pwason@uber.com>
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
- Added upgrade and downgrade step to and from 0.9.0. Upgrade adds few table properties. Downgrade recreates timeline server based marker files if any.
- fix problem of archiving replace commits
- Fix problem when getting empty replacecommit.requested
- Improved the logic of handling empty and non-empty requested/inflight commit files. Added unit tests to cover both empty and non-empty inflight files cases and cleaned up some unused test util methods
Co-authored-by: yorkzero831 <yorkzero8312@gmail.com>
Co-authored-by: zheren.yu <zheren.yu@paypay-corp.co.jp>
* [HUDI-845] Added locking capability to allow multiple writers
1. Added LockProvider API for pluggable lock methodologies
2. Added Resolution Strategy API to allow for pluggable conflict resolution
3. Added TableService client API to schedule table services
4. Added Transaction Manager for wrapping actions within transactions
* [HUDI-1552] Improve performance of key lookups from base file in Metadata Table.
1. Cache the KeyScanner across lookups so that the HFile index does not have to be read for each lookup.
2. Enable block caching in KeyScanner.
3. Move the lock to a limited scope of the code to reduce lock contention.
4. Removed reuse configuration
* Properly close the readers, when metadata table is accessed from executors
- Passing a reuse boolean into HoodieBackedTableMetadata
- Preserve the fast return behavior when reusing and opening from multiple threads (no contention)
- Handle concurrent close() and open readers, for reuse=false, by always synchronizing
Co-authored-by: Vinoth Chandar <vinoth@apache.org>
