Patrick Young created SPARK-23612:
-------------------------------------
Summary: Specify formats for individual DateType and TimestampType
columns in schemas
Key: SPARK-23612
URL: https://issues.apache.org/jira/browse/SPARK-23612
Project: Spark
Issue Type: Improvement
Components: PySpark, SQL
Affects Versions: 2.3.0
Reporter: Patrick Young
[https://github.com/apache/spark/blob/407f67249639709c40c46917700ed6dd736daa7d/python/pyspark/sql/types.py#L162-L200]
It would be very helpful if it were possible to specify the format for
individual columns in a schema when reading csv files, rather than one format:
{code:title=Bar.python|borderStyle=solid}
# Currently can only do something like:
spark.read.option("**dateFormat", "yyyyMMdd").csv(...)
# Would like to be able to do something like:
schema = StructType([
StructField("date1", DateType(format="MM/dd/yyyy"), True),
StructField("date2", DateType(format="yyyyMMdd"), True)
]
read.schema(schema).csv(...)
{{{code}}}
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