- This adds a restore plan and serializes it to restore.requested meta file in timeline. This also means that we are introducing schedule and execution phases for restore which was not present before.
* [HUDI-1295] Metadata Index - Bloom filter and Column stats index to speed up index lookups
- Today, base files have bloom filter at their footers and index lookups
have to load the base file to perform any bloom lookups. Though we have
interval tree based file purging, we still end up in significant amount
of base file read for the bloom filter for the end index lookups for the
keys. This index lookup operation can be made more performant by having
all the bloom filters in a new metadata partition and doing pointed
lookups based on keys.
* [HUDI-1295] Metadata Index - Bloom filter and Column stats index to speed up index lookups
- Adding indexing support for clean, restore and rollback operations.
Each of these operations will now be converted to index records for
bloom filter and column stats additionally.
* [HUDI-1295] Metadata Index - Bloom filter and Column stats index to speed up index lookups
- Making hoodie key consistent for both column stats and bloom index by
including fileId instead of fileName, in both read and write paths.
- Performance optimization for looking up records in the metadata table.
- Avoiding multi column sorting needed for HoodieBloomMetaIndexBatchCheckFunction
* [HUDI-1295] Metadata Index - Bloom filter and Column stats index to speed up index lookups
- HoodieBloomMetaIndexBatchCheckFunction cleanup to remove unused classes
- Base file checking before reading the file footer for bloom or column stats
* [HUDI-1295] Metadata Index - Bloom filter and Column stats index to speed up index lookups
- Updating the bloom index and column stats index to have full file name
included in the key instead of just file id.
- Minor test fixes.
* [HUDI-1295] Metadata Index - Bloom filter and Column stats index to speed up index lookups
- Fixed flink commit method to handle metadata table all partition update records
- TestBloomIndex fixes
* [HUDI-1295] Metadata Index - Bloom filter and Column stats index to speed up index lookups
- SparkHoodieBloomIndexHelper code simplification for various config modes
- Signature change for getBloomFilters() and getColumnStats(). Callers can
just pass in interested partition and file names, the index key is then
constructed internally based on the passed in parameters.
- KeyLookupHandle and KeyLookupResults code refactoring
- Metadata schema changes - removed the reserved field
* [HUDI-1295] Metadata Index - Bloom filter and Column stats index to speed up index lookups
- Removing HoodieColumnStatsMetadata and using HoodieColumnRangeMetadata instead.
Fixed the users of the the removed class.
* [HUDI-1295] Metadata Index - Bloom filter and Column stats index to speed up index lookups
- Extending meta index test to cover deletes, compactions, clean
and restore table operations. Also, fixed the getBloomFilters()
and getColumnStats() to account for deleted entries.
* [HUDI-1295] Metadata Index - Bloom filter and Column stats index to speed up index lookups
- Addressing review comments - java doc for new classes, keys sorting for
lookup, index methods renaming.
* [HUDI-1295] Metadata Index - Bloom filter and Column stats index to speed up index lookups
- Consolidated the bloom filter checking for keys in to one
HoodieMetadataBloomIndexCheckFunction instead of a spearate batch
and lazy mode. Removed all the configs around it.
- Made the metadata table partition file group count configurable.
- Fixed the HoodieKeyLookupHandle to have auto closable file reader
when checking bloom filter and range keys.
- Config property renames. Test fixes.
* [HUDI-1295] Metadata Index - Bloom filter and Column stats index to speed up index lookups
- Enabling column stats indexing for all columns by default
- Handling column stat generation errors and test update
* [HUDI-1295] Metadata Index - Bloom filter and Column stats index to speed up index lookups
- Metadata table partition file group count taken from the slices when
the table is bootstrapped.
- Prep records for the commit refactored to the base class
- HoodieFileReader interface changes for filtering keys
- Multi column and data types support for colums stats index
* [HUDI-1295] Metadata Index - Bloom filter and Column stats index to speed up index lookups
- rebase to latest master and merge fixes for the build and test failures
* [HUDI-1295] Metadata Index - Bloom filter and Column stats index to speed up index lookups
- Extending the metadata column stats type payload schema to include
more statistics about the column ranges to help query integration.
* [HUDI-1295] Metadata Index - Bloom filter and Column stats index to speed up index lookups
- Addressing review comments
* [HUDI-2154] Add index key field to HoodieKey
* [HUDI-2157] Add the bucket index and its read/write implemention of Spark engine.
* revert HUDI-2154 add index key field to HoodieKey
* fix all comments and introduce a new tricky way to get index key at runtime
support double insert for bucket index
* revert spark read optimizer based on bucket index
* add the storage layout
* index tag, hash function and add ut
* fix ut
* address partial comments
* Code review feedback
* add layout config and docs
* fix ut
* rename hoodie.layout and rebase master
Co-authored-by: Vinoth Chandar <vinoth@apache.org>
* [HUDI-3029] Transaction manager: avoid deadlock when doing begin and end transactions
- Transaction manager has begin and end transactions as synchronized methods.
Based on the lock provider implementaion, this can lead to deadlock
situation when the underlying lock() calls are blocking or with a long timeout.
- Fixing transaction manager begin and end transactions to not get to deadlock
and to not assume anything on the lock provider implementation.
* [HUDI-2923] Fixing metadata table reader when metadata compaction is inflight
* Fixing retry of pending compaction in metadata table and enhancing tests
* `ZCurveOptimizeHelper` > `ZOrderingIndexHelper`;
Moved Z-index helper under `hudi.index.zorder` package
* Tidying up `ZOrderingIndexHelper`
* Fixing compilation
* Fixed index new/original table merging sequence to always prefer values from new index;
Cleaned up `HoodieSparkUtils`
* Added test for `mergeIndexSql`
* Abstracted Z-index name composition w/in `ZOrderingIndexHelper`;
* Fixed `DataSkippingUtils` to interrupt prunning in case data filter contains non-indexed column reference
* Properly handle exceptions origination during pruning in `HoodieFileIndex`
* Make sure no errors are logged upon encountering `AnalysisException`
* Cleaned up Z-index updating sequence;
Tidying up comments, java-docs;
* Fixed Z-index to properly handle changes of the list of clustered columns
* Tidying up
* `lint`
* Suppressing `JavaDocStyle` first sentence check
* Fixed compilation
* Fixing incorrect `DecimalType` conversion
* Refactored test `TestTableLayoutOptimization`
- Added Z-index table composition test (against fixtures)
- Separated out GC test;
Tidying up
* Fixed tests re-shuffling column order for Z-Index table `DataFrame` to align w/ the one by one loaded from JSON
* Scaffolded `DataTypeUtils` to do basic checks of Spark types;
Added proper compatibility checking b/w old/new index-tables
* Added test for Z-index tables merging
* Fixed import being shaded by creating internal `hudi.util` package
* Fixed packaging for `TestOptimizeTable`
* Revised `updateMetadataIndex` seq to provide Z-index updating process w/ source table schema
* Make sure existing Z-index table schema is sync'd to source table's one
* Fixed shaded refs
* Fixed tests
* Fixed type conversion of Parquet provided metadata values into Spark expected schemas
* Fixed `composeIndexSchema` utility to propose proper schema
* Added more tests for Z-index:
- Checking that Z-index table is built correctly
- Checking that Z-index tables are merged correctly (during update)
* Fixing source table
* Fixing tests to read from Parquet w/ proper schema
* Refactored `ParquetUtils` utility reading stats from Parquet footers
* Fixed incorrect handling of Decimals extracted from Parquet footers
* Worked around issues in javac failign to compile stream's collection
* Fixed handling of `Date` type
* Fixed handling of `DateType` to be parsed as `LocalDate`
* Updated fixture;
Make sure test loads Z-index fixture using proper schema
* Removed superfluous scheme adjusting when reading from Parquet, since Spark is actually able to perfectly restore schema (given Parquet was previously written by Spark as well)
* Fixing race-condition in Parquet's `DateStringifier` trying to share `SimpleDataFormat` object which is inherently not thread-safe
* Tidying up
* Make sure schema is used upon reading to validate input files are in the appropriate format;
Tidying up;
* Worked around javac (1.8) inability to infer expression type properly
* Updated fixtures;
Tidying up
* Fixing compilation after rebase
* Assert clustering have in Z-order layout optimization testing
* Tidying up exception messages
* XXX
* Added test validating Z-index lookup filter correctness
* Added more test-cases;
Tidying up
* Added tests for string expressions
* Fixed incorrect Z-index filter lookup translations
* Added more test-cases
* Added proper handling on complex negations of AND/OR expressions by pushing NOT operator down into inner expressions for appropriate handling
* Added `-target:jvm-1.8` for `hudi-spark` module
* Adding more tests
* Added tests for non-indexed columns
* Properly handle non-indexed columns by falling back to a re-write of containing expression as `TrueLiteral` instead
* Fixed tests
* Removing the parquet test files and disabling corresponding tests
Co-authored-by: Vinoth Chandar <vinoth@apache.org>
- 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-2634] Improved the metadata table bootstrap for very large tables.
Following improvements are implemented:
1. Memory overhead reduction:
- Existing code caches FileStatus for each file in memory.
- Created a new class DirectoryInfo which is used to cache a director's file list with parts of the FileStatus (only filename and file len). This reduces the memory requirements.
2. Improved parallelism:
- Existing code collects all the listing to the Driver and then creates HoodieRecord on the Driver.
- This takes a long time for large tables (11million HoodieRecords to be created)
- Created a new function in SparkRDDWriteClient specifically for bootstrap commit. In it, the HoodieRecord creation is parallelized across executors so it completes fast.
3. Fixed setting to limit the number of parallel listings:
- Existing code had a bug wherein 1500 executors were hardcoded to perform listing. This leads to exception due to limit in the spark's result memory.
- Corrected the use of the config.
Result:
Dataset has 1299 partitions and 12Million files.
file listing time=1.5mins
HoodieRecord creation time=13seconds
deltacommit duration=2.6mins
Co-authored-by: Sivabalan Narayanan <n.siva.b@gmail.com>
* [HUDI-2101]support z-order for hudi
* Renaming some configs for consistency/simplicity.
* Minor code cleanups
Co-authored-by: Vinoth Chandar <vinoth@apache.org>
- There are two code paths, where we are taking double locking. this was added as part of adding data table locks to update metadata table. Fixing those flows to avoid taking locks if a parent transaction already acquired a lock.
- Fix is to make Metadata table writer creation aware of the currently inflight action so that it can
make some informed decision about whether bootstrapping is needed for the table and whether
any pending action on the data timeline can be ignored.
* [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>
- This patch introduces rollback plan and rollback.requested instant. Rollback will be done in two phases, namely rollback plan and rollback action. In planning, we prepare the rollback plan and serialize it to rollback.requested. In the rollback action phase, we fetch details from the plan and just delete the files as per the plan. This will ensure final rollback commit metadata will contain all files that got rolled back even if rollback failed midway and retried again.
