Currently, Data Skipping is not handling correctly the case when column-stats are not aligned and, for ex, some of the (column, file) combinations are missing from the CSI.
This could occur in different scenarios (schema evolution, CSI config changes), and has to be handled properly when we're composing CSI projection for Data Skipping. This PR addresses that.
- Added appropriate aligning for the transposed CSI projection
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>
