问题
I have a large data frame df containing a column for date in the format yyyymmdd
, how can I convert it into MM-dd-yyyy
in pySpark.
回答1:
from datetime import datetime
from pyspark.sql.functions import col,udf
from pyspark.sql.types import DateType
rdd = sc.parallelize(['20161231', '20140102', '20151201', '20161124'])
df1 = sqlContext.createDataFrame(rdd, ['old_col'])
//UDF to convert string to date
func = udf (lambda x: datetime.strptime(x, '%Y%M%d'), DateType())
df = df1.withColumn('new_col', date_format(func(col('old_col')), 'MM-dd-yyy'))
df.show()
回答2:
This is also working:
from datetime import datetime
from pyspark.sql.functions import col,udf,unix_timestamp
from pyspark.sql.types import DateType
func = udf(lambda x: datetime.strptime(str(x), '%m%d%y'), DateType())
df2 = df.withColumn('date', func(col('InvcDate')))
来源:https://stackoverflow.com/questions/41392303/converting-yyyymmdd-to-mm-dd-yyyy-format-in-pyspark