Addressing the problem of Data Skipping not respecting Metadata Table configs which might differ b/w write/read paths. More details could be found in HUDI-3812.
- Fixing Data Skipping configuration to respect MT configs (on the Read path)
- Tightening up DS handling of cases when no top-level columns are in the target query
- Enhancing tests to cover all possible case
Fixing performance hits in reading Column Stats Index:
[HUDI-3834] There's substantial performance degradation in Avro 1.10 default generated Builder classes: they by default rely on SpecificData.getForSchema that load corresponding model's class using reflection, which takes a hit when executed on the hot-path (this was bringing overall runtime to read full Column Stats Index of 800k records to 60s, whereas now it's taking mere 3s)
Addressing memory churn by over-used Hadoop's Path creation: Path ctor is not a lightweight sequence and produces quite a bit of memory churn adding pressure on GC. Cleaning such avoidable allocations up to make sure there's no unnecessarily added pressure on GC.
* Filter out empty string (for non-partitioned table) being added to "__all_partitions__" record
* Instead of filtering, transform empty partition-id to `NON_PARTITIONED_NAME`
* Cleaned up `HoodieBackedTableMetadataWriter`
* Make sure REPLACE_COMMITS are handled as well
* Depend on FSUtils#getRelativePartitionPath(basePath, logFilePath.getParent)
to get the partition.
* If the list of log file paths in the split is empty, then fallback to usual behaviour.
- Adding capability to fetch Metadata Records by key prefix so that Data Skipping could fetch only Column Stats
- Index records pertaining to the columns being queried by, instead of reading out whole Index.
- Fixed usages of HFileScanner in HFileReader. few code paths uses cached scanner if available. Other code paths uses its own HFileScanner w/ positional read.
Brief change log
- Rebasing ColumnStatsIndexSupport to rely on HoodieBackedTableMetadata in lieu of reading t/h Spark DS
- Adding methods enabling key-prefix lookups to HoodiFileReader, HoodieHFileReader
- Wiring key-prefix lookup t/h LogRecordScanner impls
- Cleaning up HoodieHFileReader impl
Co-authored-by: sivabalan <n.siva.b@gmail.com>
Co-authored-by: Sagar Sumit <sagarsumit09@gmail.com>
* [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 checks for metadata table init to avoid possible out-of-sync
* Revise the logic to reuse existing table config
* Revise docs and naming
Co-authored-by: yuezhang <yuezhang@freewheel.tv>
Co-authored-by: Y Ethan Guo <ethan.guoyihua@gmail.com>
