CODEWITHSUNDEEP
pythonapache-sparkpyspark
Hugo Reyes
Hugo Reyes

Reputation: 1585

Why I get null results from date_format() PySpark function?

Suppose there is a dateframe with a column comprised of dates as strings. For that assumption, we create the following dataFrame as an example:

# Importing sql types
from pyspark.sql.types import StringType, IntegerType, StructType, StructField, DoubleType, FloatType, DateType
from pyspark.sql.functions  import date_format
import random
import time

def strTimeProp(start, end, format, prop):
    stime = time.mktime(time.strptime(start, format)) # Parse a string representing a time according to a format
    etime = time.mktime(time.strptime(end, format)) 
    ptime = stime + prop * (etime - stime) 
    return time.strftime(format, time.localtime(ptime))

def randomDate(start, end, prop):
    return strTimeProp(start, end, '%m-%d-%Y', prop)

# Creación de un dataframe de prueba:
schema = StructType(
        [
     StructField("dates1", StringType(), True),
         StructField("dates2",  StringType(), True)
    ]
)

size = 32
numCol1 = [str(randomDate("1-1-1991", "1-1-1992", random.random())) for number in range(size)]
numCol2 = [str(randomDate("1-1-1991", "1-1-1992", random.random())) for number in range(size)]
# Building dataFrame:
sqlContext = SQLContext(sc)
df = sqlContext.createDataFrame(list(zip(numCol1, numCol2)),schema=schema)
df.show(5)

In the code above, a random date column is generated, here is an example:

+----------+----------+
|    dates1|    dates2|
+----------+----------+
|12-21-1991|05-30-1991|
|05-28-1991|01-23-1991|
|03-01-1991|08-05-1991|
|07-15-1991|05-13-1991|
|07-21-1991|11-10-1991|
+----------+----------+

What I am trying to do is to change date format with the following code (from pySpark documentation):

# Changing date formats:
df.select(date_format('dates1', 'MM-dd-yyy').alias('newFormat')).show(5)

But I get this bad result:

+---------+
|newFormat|
+---------+
|     null|
|     null|
|     null|
|     null|
|     null|
+---------+

I suppose there is a problem relate with the string dataType but at same time, I don't understand why this code bellow works and the code above don't. 

fechas = ['1000-01-01', '1000-01-15']
df = sqlContext.createDataFrame(list(zip(fechas, fechas)), ['dates', 'd'])
df.show()

# Changing date formats:
df.select(date_format('dates', 'MM-dd-yyy').alias('newFormat')).show()

Output:

+----------+----------+
|     dates|         d|
+----------+----------+
|1000-01-01|1000-01-01|
|1000-01-15|1000-01-15|
+----------+----------+

+----------+
| newFormat|
+----------+
|01-01-1000|
|01-15-1000|
+----------+

This last results is what I want.

Upvotes: 4

Views: 20340

Answers (2)

Antonella Barbero
Antonella Barbero

Reputation: 101

You can solve it by first casting your date from string to timestamp with the to_timestamp function available on pyspark.sql (https://spark.apache.org/docs/latest/api/python/reference/pyspark.sql/api/pyspark.sql.functions.to_timestamp.html)

# Changing date formats:
from pyspark.sql.functions import to_timestamp, date_format
df.select(date_format(to_timestamp('dates1', "MM-dd-yyyy"), "MM-dd-yyy").alias('newFormat')).show(5)


+----------+
| newFormat|
+----------+
|08-11-1991|
|11-11-1991|
|12-04-1991|
|03-30-1991|
|04-22-1991|
+----------+

You can even get, for example, only the month and day:

df.select(date_format(to_timestamp('dates1', "MM-dd-yyyy"), "MM-dd").alias('newFormat')).show(5)

 +---------+
|newFormat|
+---------+
|    08-11|
|    11-11|
|    12-04|
|    03-30|
|    04-22|
+---------+

Upvotes: 0

zero323
zero323

Reputation: 330113

It doesn't work because your data is not a valid ISO 8601 representation and cast to date returns NULL:

sqlContext.sql("SELECT CAST('12-21-1991' AS DATE)").show()
## +----+
## | _c0|
## +----+
## |null|
## +----+

You'll have to parse data first using custom format:

output_format = ...  # Some SimpleDateFormat string
df.select(date_format(
    unix_timestamp("dates1", "MM-dd-yyyy").cast("timestamp"), 
    output_format
))

Upvotes: 12

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