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Joby Joje updated SPARK-30149: ------------------------------ Attachment: Schema.py Output.txt > Schema Definition Spark Read > ---------------------------- > > Key: SPARK-30149 > URL: https://issues.apache.org/jira/browse/SPARK-30149 > Project: Spark > Issue Type: Bug > Components: PySpark, Spark Core > Affects Versions: 2.4.0 > Reporter: Joby Joje > Priority: Blocker > Attachments: Output.txt, Schema.py, Test.SDL, Test1.SDL > > > Reading a CSV file with defined schema I am able to load the files and do the > processing, which works fine using the below code. The schema is defined as > to strictly follow the datatype to record precision's with accuracy. > {code:java} > source_schema = StructType([source_schema = StructType([ StructField("NAME", > StringType(), True), StructField("AGE", StringType(), True), > StructField("GENDER", StringType(), True), StructField("PROFESSION", > StringType(), True), StructField("SALARY", DecimalType(38, 14), True), > StructField("BAD_RECORD", StringType(), True)]){code} > {code:java} > df_raw_file = sparksession.read \ > .format("csv") \ > .option("delimiter", '\t') \ > .option("header", "false") \ > .option("inferSchema", "true") \ > .option("columnNameOfCorruptRecord", "BAD_RECORD") \ > .schema(source_schema) \ .load(in_file_list) \ > .withColumn("LINE_NUMBER", monotonically_increasing_id()) \ > .withColumn("SOURCE_FILE_NAME", input_file_name()){code} > As per the Spark Documentation the mode is {{PERMISSIVE}} by default is its > not set and A record with less/more tokens than schema is not a corrupted > record to CSV. When it meets a record having fewer tokens than the length of > the schema, sets {{null}} to extra fields. When the record has more tokens > than the length of the schema, it drops extra tokens. > {code:java} > FILE SCHEMA TEST.CSVFILE SCHEMA TEST.CSV > root > |-- NAME: string (nullable = true) > |-- AGE: string (nullable = true) > |-- GENDER: string (nullable = true) > |-- PROFESSION: string (nullable = true) > |-- SALARY: decimal(38,14) (nullable = true) > |-- BAD_RECORD: string (nullable = true) > |-- LINE_NUMBER: long (nullable = false) > |-- SOURCE_FILE_NAME: string (nullable = false) > OUTPUT THE FILE TEST.CSV > +------+----+------+----------+------------------+---------------------------------+-----------+-----------------+ > |NAME |AGE |GENDER|PROFESSION|SALARY |BAD_RECORD > |LINE_NUMBER|SOURCE_FILE_NAME | > +------+----+------+----------+------------------+---------------------------------+-----------+-----------------+ > |null |null|null |null |null |NAME AGE GENDER > PROFESSION SALARY|0 |Test.CSV| > |JOHN |27 |MALE |CEO |300.12314234500000|null > |1 |Test.CSV| > |JUSTIN|67 |MALE |CTO |123.23453543450000|null > |2 |Test.CSV| > |SARAH |45 |FEMALE|CS |null |null > |3 |Test.CSV| > |SEAN |66 |MALE |CA |null |SEAN 66 MALE > CA |4 |Test.CSV| > |PHIL |34 |MALE |null |234.98698600000000|null > |5 |Test.CSV| > |null |null|null |null |null |JILL 25 > BOARD |6 |Test.CSV| > |JACK |30 |MALE |BOARD |null |JACK 30 MALE > BOARD |7 |Test.CSV| > +------+----+------+----------+------------------+---------------------------------+-----------+-----------------+{code} > > The TEST1.CSV doesnt have the SALARY column so it should have NULLED the > column and the BAD_RECORD column should be NULL for the rows, that doesnt > seem to have and the values are considered as CORRUPT. > Also when it meets a corrupted record, puts the malformed string into a field > configured by {{columnNameOfCorruptRecord}}, and sets other fields to > {{null}} this is also not happening and I see this happening only for the > JILL row. > > > {code:java} > FILE SCHEMA TEST1.CSV > root > |-- NAME: string (nullable = true) > |-- AGE: string (nullable = true) > |-- GENDER: string (nullable = true) > |-- PROFESSION: string (nullable = true) > |-- SALARY: decimal(38,14) (nullable = true) > |-- BAD_RECORD: string (nullable = true) > |-- LINE_NUMBER: long (nullable = false) > |-- SOURCE_FILE_NAME: string (nullable = false) > OUTPUT THE FILE TEST1.CSV > +------+----+------+----------+------+--------------------------+-----------+-----------------+ > |NAME |AGE |GENDER|PROFESSION|SALARY|BAD_RECORD > |LINE_NUMBER|SOURCE_FILE_NAME | > +------+----+------+----------+------+--------------------------+-----------+-----------------+ > > |NAME |AGE |GENDER|PROFESSION|null |NAME AGE GENDER PROFESSION|0 |Test1.CSV| > |JOHN |27 |MALE |CEO |null |JOHN 27 MALE CEO |1 |Test1.CSV| > |JUSTIN|67 |MALE |CTO |null |JUSTIN 67 MALE CTO |2 |Test1.CSV| > |SARAH |45 |FEMALE|CS |null |SARAH 45 FEMALE CS |3 |Test1.CSV| > |SEAN |66 |MALE |CA |null |SEAN 66 MALE CA |4 |Test1.CSV| > |PHIL |34 |MALE |null |null |PHIL 34 MALE |5 |Test1.CSV| > |null |null|null |null |null |JILL 25 BOARD |6 |Test1.CSV| > |JACK |30 |MALE |BOARD |null |JACK 30 MALE BOARD |7 |Test1.CSV| > +------+----+------+----------+------+--------------------------+-----------+-----------------+{code} > -- This message was sent by Atlassian Jira (v8.3.4#803005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org