[
https://issues.apache.org/jira/browse/SPARK-36277?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
anju updated SPARK-36277:
-------------------------
Description:
I am trying to read the two dataframes from one file using with/without
predefined schema. Issue is when i read a DF with a predefined schema and with
mode as "dropmalformed", the record count in df is not dropping the records.
The record count is same as actual file where i am expecting less record
count,as there are few malformed records . But when i try to select and display
the records in df ,it is not showing malformed records. So display is correct.
output is attached in the aattchement
code
{{s3_obj =boto3.client('s3')
s3_clientobj = s3_obj.get_object(Bucket='xyz',
Key='data/test_files/schema_xyz.json')
s3_clientobj
s3_clientdata =
s3_clientobj['Body'].read().decode('utf-8')#print(s3_clientdata)schemaSource=json.loads(s3_clientdata)
schemaFromJson =StructType.fromJson(json.loads(s3_clientdata))
extract_with_schema_df =
spark.read.csv("s3:few_columns.csv",header=True,sep=",",schema=schemaFromJson,mode="DROPMALFORMED")
extract_without_schema_df =
spark.read.csv("s3:few_columns.csv",header=True,sep=",",mode="permissive")
extract_with_schema_df.select("col1","col2").show()
cnt1=extract_with_schema_df.select("col1","col2").count()print("count of the
records with schema "+ str(cnt1))
cnt2=extract_without_schema_df.select("col1","col2").count()print("count of the
records without schema "+str(cnt2))
cnt2=extract_without_schema_df.select("col1","col2").show()}}
was:
I am trying to read the two dataframes from one file using with/without
predefined schema. Issue is when i read a DF with a predefined schema and with
mode as "dropmalformed", the record count in df is not dropping the records.
The record count is same as actual file where i am expecting less record
count,as there are few malformed records . But when i try to select and display
the records in df ,it is not showing malformed records. So display is correct.
output is attached in the atatchement
!image-2021-07-23-16-31-46-172.png!
> Issue with record count of data frame while reading in DropMalformed mode
> -------------------------------------------------------------------------
>
> Key: SPARK-36277
> URL: https://issues.apache.org/jira/browse/SPARK-36277
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 2.4.3
> Reporter: anju
> Priority: Major
> Attachments: 111.PNG
>
>
> I am trying to read the two dataframes from one file using with/without
> predefined schema. Issue is when i read a DF with a predefined schema and
> with mode as "dropmalformed", the record count in df is not dropping the
> records. The record count is same as actual file where i am expecting less
> record count,as there are few malformed records . But when i try to select
> and display the records in df ,it is not showing malformed records. So
> display is correct. output is attached in the aattchement
> code
>
> {{s3_obj =boto3.client('s3')
> s3_clientobj = s3_obj.get_object(Bucket='xyz',
> Key='data/test_files/schema_xyz.json')
> s3_clientobj
> s3_clientdata =
> s3_clientobj['Body'].read().decode('utf-8')#print(s3_clientdata)schemaSource=json.loads(s3_clientdata)
> schemaFromJson =StructType.fromJson(json.loads(s3_clientdata))
> extract_with_schema_df =
> spark.read.csv("s3:few_columns.csv",header=True,sep=",",schema=schemaFromJson,mode="DROPMALFORMED")
>
> extract_without_schema_df =
> spark.read.csv("s3:few_columns.csv",header=True,sep=",",mode="permissive")
> extract_with_schema_df.select("col1","col2").show()
> cnt1=extract_with_schema_df.select("col1","col2").count()print("count of the
> records with schema "+ str(cnt1))
> cnt2=extract_without_schema_df.select("col1","col2").count()print("count of
> the records without schema "+str(cnt2))
> cnt2=extract_without_schema_df.select("col1","col2").show()}}
>
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