- infer repeated sync configs from original configs
- `META_SYNC_BASE_FILE_FORMAT`
- infer from `org.apache.hudi.common.table.HoodieTableConfig.BASE_FILE_FORMAT`
- `META_SYNC_ASSUME_DATE_PARTITION`
- infer from `org.apache.hudi.common.config.HoodieMetadataConfig.ASSUME_DATE_PARTITIONING`
- `META_SYNC_DECODE_PARTITION`
- infer from `org.apache.hudi.common.table.HoodieTableConfig.URL_ENCODE_PARTITIONING`
- `META_SYNC_USE_FILE_LISTING_FROM_METADATA`
- infer from `org.apache.hudi.common.config.HoodieMetadataConfig.ENABLE`
As proposed in https://github.com/apache/hudi/blob/master/rfc/rfc-55/rfc-55.md#compatible-changes
We provide an alternative way of fetching Column Stats Index within the reading process to avoid the penalty of a more heavy-weight execution scheduled through a Spark engine.
For MOR, when no merging is performed there is no point in reading either primary-key or pre-combine-key values (unless query is referencing these). Avoiding reading these allows to potentially save substantial resources wasted for reading it out.
This set of changes makes sure that all builtin KeyGenerators properly implement Spark-specific APIs in a performant way (minimizing key-generators overhead)
Fixes the missing bloom filters in metadata table in the non-partitioned table due to incorrect record key generation, because of wrong file names when generating the metadata payload for the bloom filter.
Currently when doing Hudi queries w/ Spark, it won't
load the external configurations. Say if customers enabled
metadata listing in their global config file, then this would
let them actually query w/o metadata feature enabled.
This PR fixes this issue and allows loading global
configs during the Hudi reading phase.
Co-authored-by: Wenning Ding <wenningd@amazon.com>
Currently, all Hudi Relations bear performance gap relative to Spark's HadoopFsRelation
and the reason to that is SchemaPruning optimization rule (pruning nested schemas)
that is unfortunately predicated on usage of HadoopFsRelation, meaning that it's
not applied in cases when any other relation is used.
This change is porting this rule to Hudi relations (MOR, Incremental, etc)
by the virtue of leveraging HoodieSparkSessionExtensions mechanism
injecting modified version of the original SchemaPruning rule
that is adopted to work w/ Hudi's custom relations.
- Added customOptimizerRules to HoodieAnalysis
- Added NestedSchemaPrunning Spark's Optimizer rule
- Handle Spark's Optimizer pruned data schema (to effectively prune nested schemas)
- Enable HoodieClientTestHarness to inject HoodieSparkSessionExtensions
- Injecting Spark Session extensions for TestMORDataSource, TestCOWDataSource
- Disabled fallback to HadoopFsRelation
