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
- Move clean related configuration to HoodieCleanConfig
- Move Archival related configuration to HoodieArchivalConfig
- hoodie.compaction.payload.class move this to HoodiePayloadConfig
* [HUDI-4276] Reconcile schema-inject null values for missing fields and add new fields.
* fix comments
Co-authored-by: public (bdcee5037027) <mengtao0326@qq.com>
* [HUDI-3730] Improve meta sync class design and hierarchies (#5754)
* Implements class design proposed in RFC-55
Co-authored-by: jian.feng <fengjian428@gmial.com>
Co-authored-by: jian.feng <jian.feng@shopee.com>
Fixed sequence determining whether Parquet's legacy-format writing property should be overridden to only kick in when it has not been explicitly specified by the caller
- Upgrade junit to 5.7.2
- Downgrade surefire and failsafe to 2.22.2
- Fix test failures that were previously not reported
- Improve azure pipeline configs
Co-authored-by: liujinhui1994 <965147871@qq.com>
Co-authored-by: Y Ethan Guo <ethan.guoyihua@gmail.com>
There are multiple issues with our current DataSource V2 integrations: b/c we advertise Hudi tables as V2, Spark expects it to implement certain APIs which are not implemented at the moment, instead we're using custom Resolution rule (in HoodieSpark3Analysis) to instead manually fallback to V1 APIs. This commit fixes the issue by reverting DSv2 APIs and making Spark use V1, except for schema evaluation logic.
Bulk insert row writer code path had a gap wrt hive style partitioning and default partition when virtual keys are enabled with SimpleKeyGen. This patch fixes the issue.
As has been outlined in HUDI-4176, we've hit a roadblock while testing Hudi on a large dataset (~1Tb) having pretty fat commits where Hudi's commit metadata could reach into 100s of Mbs.
Given the size some of ours commit metadata instances Spark's parsing and resolving phase (when spark.sql(...) is involved, but before returned Dataset is dereferenced) starts to dominate some of our queries' execution time.
- Rebased onto new APIs to avoid excessive Hadoop's Path allocations
- Eliminated hasOperationField completely to avoid repeatitive computations
- Cleaning up duplication in HoodieActiveTimeline
- Added caching for common instances of HoodieCommitMetadata
- Made tableStructSchema lazy;
- Added pure immutable test yamls to integ test framework. Added SparkBulkInsertNode as part of it.
- Added delete_partition support to integ test framework using spark-datasource.
- Added a single yaml to test all non core write operations (insert overwrite, insert overwrite table and delete partitions)
- Added tests for 4 concurrent spark datasource writers (multi-writer tests).
- Fixed readme w/ sample commands for multi-writer.
- Avoid using udf for key generator for SimpleKeyGen and NonPartitionedKeyGen.
- Fixed NonPartitioned Key generator to directly fetch record key from row rather than involving GenericRecord.
- Other minor fixes around using static values instead of looking up hashmap.
This PR fixes the projection logic around a nested field which is used as the pre-combined key field. The fix is to only check and append the root level field for projection, i.e., "a", for a nested field "a.b.c" in the mandatory columns.
- Changes the logic to check and append the root level field for a required nested field in the mandatory columns in HoodieBaseRelation.appendMandatoryColumns
