[HUDI-4861] Relax MERGE INTO restrictions to permit casting of the matching condition

• Type: Bug
• Status: Closed
• Priority: Major
• Resolution: Fixed
• Affects Version/s: 0.12.0
• Fix Version/s: 0.12.1
• Component/s: spark-sql
• Labels: pull-request-available
• Story Points: 2
• Epic Link: Hudi Spark Datasource
• Assignee: Alexey Kudinkin
• Reporter: Alexey Kudinkin
• Created: 16/Sep/22 19:47
• Updated: 29/Sep/22 15:38
• Resolved: 29/Sep/22 15:38

Description

Reported by user:

https://github.com/apache/hudi/issues/6626

 

Following code

 

     target_df = spark.read.format("hudi").load(basePath)
    print("###################################")
    print(target_df.printSchema())
    # # target_df.show()
    target_datatype_map = {}
    for name, dtype in target_df.dtypes:
        target_datatype_map[name] = dtype
    print(str(target_datatype_map))
    print("###################################")

    for col in columns:
        if has_column(deflateDf, col):
            deflateDf = deflateDf.withColumn(col, F.col(col))
        else:
            deflateDf = deflateDf.withColumn(col, F.lit(None))
    deflateDf.createOrReplaceTempView("deflate_table")
    create_sql = "create table RESULTDATA using hudi location '/tmp/RESULTDATA_mor'"
    spark.sql(create_sql)
    
    merge_sql = """
    merge into RESULTDATA as target
        using (
            select * from deflate_table as deflate
        )
        on target._context_id_ = deflate._context_id_ and target.id = deflate.id
        when matched
        then update set
        target.CREATED = cast(if(array_contains(deflate.changed_cols, 'CREATED'), deflate.CREATED, target.CREATED) as timestamp),target.CREATEDBY = cast(if(array_contains(deflate.changed_cols, 'CREATEDBY'), deflate.CREATEDBY, target.CREATEDBY) as string),target.DELETED = cast(if(array_contains(deflate.changed_cols, 'DELETED'), deflate.DELETED, target.DELETED) as timestamp),target.DELETEDBY = cast(if(array_contains(deflate.changed_cols, 'DELETEDBY'), deflate.DELETEDBY, target.DELETEDBY) as string),target.EXPIRATIONDATE = cast(if(array_contains(deflate.changed_cols, 'EXPIRATIONDATE'), deflate.EXPIRATIONDATE, target.EXPIRATIONDATE) as timestamp),target.ID = cast(if(array_contains(deflate.changed_cols, 'ID'), deflate.ID, target.ID) as decimal(12,0)),target.KEY = cast(if(array_contains(deflate.changed_cols, 'KEY'), deflate.KEY, target.KEY) as string),target.LASTMODIFIED = cast(if(array_contains(deflate.changed_cols, 'LASTMODIFIED'), deflate.LASTMODIFIED, target.LASTMODIFIED) as timestamp),target.LASTMODIFIEDBY = cast(if(array_contains(deflate.changed_cols, 'LASTMODIFIEDBY'), deflate.LASTMODIFIEDBY, target.LASTMODIFIEDBY) as string),target.ORDERING = cast(if(array_contains(deflate.changed_cols, 'ORDERING'), deflate.ORDERING, target.ORDERING) as decimal(12,0)),target.RESULTID = cast(if(array_contains(deflate.changed_cols, 'RESULTID'), deflate.RESULTID, target.RESULTID) as decimal(12,0)),target.REPORTINGPERIODTYPE = cast(if(array_contains(deflate.changed_cols, 'REPORTINGPERIODTYPE'), deflate.REPORTINGPERIODTYPE, target.REPORTINGPERIODTYPE) as string),target.RESULTDATE = cast(if(array_contains(deflate.changed_cols, 'RESULTDATE'), deflate.RESULTDATE, target.RESULTDATE) as timestamp),target.SATISFYINGNUMERATOR = cast(if(array_contains(deflate.changed_cols, 'SATISFYINGNUMERATOR'), deflate.SATISFYINGNUMERATOR, target.SATISFYINGNUMERATOR) as decimal(12,0)),target.VALUE = cast(if(array_contains(deflate.changed_cols, 'VALUE'), deflate.VALUE, target.VALUE) as string),target._ETL_RUN_ID_ = cast(if(array_contains(deflate.changed_cols, '_ETL_RUN_ID_'), deflate._ETL_RUN_ID_, target._ETL_RUN_ID_) as decimal(38,0)),target._ETL_MODIFIED_ = cast(if(array_contains(deflate.changed_cols, '_ETL_MODIFIED_'), deflate._ETL_MODIFIED_, target._ETL_MODIFIED_) as timestamp),target._EXTRACTED_ = cast(if(array_contains(deflate.changed_cols, '_EXTRACTED_'), deflate._EXTRACTED_, target._EXTRACTED_) as timestamp),target._SOURCE_EXTRACTED_ = cast(if(array_contains(deflate.changed_cols, '_SOURCE_EXTRACTED_'), deflate._SOURCE_EXTRACTED_, target._SOURCE_EXTRACTED_) as timestamp),target._LAST_MODIFIED_SEQ_ = cast(if(array_contains(deflate.changed_cols, '_LAST_MODIFIED_SEQ_'), deflate._LAST_MODIFIED_SEQ_, target._LAST_MODIFIED_SEQ_) as decimal(38,0)),target._SCHEMA_CLASS_ = cast(if(array_contains(deflate.changed_cols, '_SCHEMA_CLASS_'), deflate._SCHEMA_CLASS_, target._SCHEMA_CLASS_) as string),target._CONTEXT_ID_ = cast(if(array_contains(deflate.changed_cols, '_CONTEXT_ID_'), deflate._CONTEXT_ID_, target._CONTEXT_ID_) as decimal(12,0)),target._IS_DELETED_ = cast(if(array_contains(deflate.changed_cols, '_IS_DELETED_'), deflate._IS_DELETED_, target._IS_DELETED_) as boolean)
        when not matched
        then insert
        (CREATED,CREATEDBY,DELETED,DELETEDBY,EXPIRATIONDATE,ID,KEY,LASTMODIFIED,LASTMODIFIEDBY,ORDERING,RESULTID,REPORTINGPERIODTYPE,RESULTDATE,SATISFYINGNUMERATOR,VALUE,_ETL_RUN_ID_,_ETL_MODIFIED_,_EXTRACTED_,_SOURCE_EXTRACTED_,_LAST_MODIFIED_SEQ_,_SCHEMA_CLASS_,_CONTEXT_ID_,_IS_DELETED_) values (cast(deflate.CREATED as timestamp),cast(deflate.CREATEDBY as string),cast(deflate.DELETED as timestamp),cast(deflate.DELETEDBY as string),cast(deflate.EXPIRATIONDATE as timestamp),cast(deflate.ID as decimal(12,0)),cast(deflate.KEY as string),cast(deflate.LASTMODIFIED as timestamp),cast(deflate.LASTMODIFIEDBY as string),cast(deflate.ORDERING as decimal(12,0)),cast(deflate.RESULTID as decimal(12,0)),cast(deflate.REPORTINGPERIODTYPE as string),cast(deflate.RESULTDATE as timestamp),cast(deflate.SATISFYINGNUMERATOR as decimal(12,0)),cast(deflate.VALUE as string),cast(deflate._ETL_RUN_ID_ as decimal(38,0)),cast(deflate._ETL_MODIFIED_ as timestamp),cast(deflate._EXTRACTED_ as timestamp),cast(deflate._SOURCE_EXTRACTED_ as timestamp),cast(deflate._LAST_MODIFIED_SEQ_ as decimal(38,0)),cast(deflate._SCHEMA_CLASS_ as string),cast(deflate._CONTEXT_ID_ as decimal(12,0)),cast(deflate._IS_DELETED_ as boolean))
        """
    spark.sql(merge_sql) 

 

 

Results in the exception being thrown:

 

/09/07 18:47:12 INFO HoodieTableMetaClient: Finished Loading Table of type MERGE_ON_READ(version=1, baseFileFormat=PARQUET) from file:///tmp/RESULTDATA_mor
22/09/07 18:47:12 INFO HoodieActiveTimeline: Loaded instants upto : Option{val=[20220907150126010__deltacommit__COMPLETED]}
Traceback (most recent call last):
  File "/Users/parunkarthick/cdc-poc/main.py", line 971, in <module>
    process_table(deflate_df, tableName, table_cols[tableNames[0]], concurrent_write_enabled, delete_insert_enabled)
  File "/Users/parunkarthick/cdc-poc/main.py", line 767, in process_table
    merge_into_hudi(table_name, df, table_cols)
  File "/Users/parunkarthick/cdc-poc/main.py", line 599, in merge_into_hudi
    target_rows = spark.sql(sql)
  File "/opt/homebrew/Cellar/apache-spark/3.1.2/libexec/python/lib/pyspark.zip/pyspark/sql/session.py", line 723, in sql
  File "/opt/homebrew/Cellar/apache-spark/3.1.2/libexec/python/lib/py4j-0.10.9-src.zip/py4j/java_gateway.py", line 1304, in __call__
  File "/opt/homebrew/Cellar/apache-spark/3.1.2/libexec/python/lib/pyspark.zip/pyspark/sql/utils.py", line 117, in deco
pyspark.sql.utils.AnalysisException: Invalidate Merge-On condition: (CAST(target.`id` AS DECIMAL(20,0)) = CAST(CAST(deflate.`id` AS DECIMAL(20,0)) AS DECIMAL(20,0))).The validate condition should be 'targetColumn = sourceColumnExpression', e.g. t.id = s.id and t.dt = from_unixtime(s.ts) 

 

This occurs due to the fact that current impl of MergeIntoHoodieTableCommand restricts target table's primary key to be just an AttributeReference, which in this case is wrapped into a Cast

 

Issue Links

• links to: GitHub Pull Request #6820