get all the dates between two dates in Spark DataFrame

Question

I have a DF in which I have bookingDt and arrivalDt columns. I need to find all the dates between these two dates.

Sample code:

Answer 1

Well, you can do following.

Create a dataframe with dates only:

dates_df # with all days between first bookingDt and last arrivalDt

and then join those df with between condition:

df.join(dates_df, 
  on=col('dates_df.dates').between(col('df.bookindDt'), col('dt.arrivalDt'))
.select('df.*', 'dates_df.dates')

It might work even faster then solution with explode, however you need to figure out what is start and end date for this df. 10 years df will have just 3650 records not that many to worry about.

Answer 2

As @vvg suggested:

# I assume, bookindDt has dates range including arrivalDt, 
# otherwise you have to find intersection of unique dates of bookindDt and arrivalDt

dates_df = df.select('bookindDt').distinct()
dates_df = dates_df.withColumnRenamed('bookindDt', 'day_of_listing')

listing_days_df = df.join(dates_df, on=dates_df.day_of_listing.between(df.bookindDt, df.arrivalDt))

Output:

+----------+----------+-------+-------------------+
| arrivalDt| bookingDt|vyge_id|day_of_listing     |
+----------+----------+-------+-------------------+
|2018-01-05|2018-01-01|   1000|2018-01-01         |
+----------+----------+-------+-------------------+
|2018-01-05|2018-01-01|   1000|2018-01-02         |
+----------+----------+-------+-------------------+
|2018-01-05|2018-01-01|   1000|2018-01-03         |
+----------+----------+-------+-------------------+
|2018-01-05|2018-01-01|   1000|2018-01-04         |
+----------+----------+-------+-------------------+
|2018-01-05|2018-01-01|   1000|2018-01-05         |
+----------+----------+-------+-------------------+

Answer 3

As long as you're using Spark version 2.1 or higher, you can exploit the fact that we can use column values as arguments when using pyspark.sql.functions.expr():

• Create a dummy string of repeating commas with a length equal to diffDays
• Split this string on ',' to turn it into an array of size diffDays
• Use pyspark.sql.functions.posexplode() to explode this array along with its indices
• Finally use pyspark.sql.functions.date_add() to add the index value number of days to the bookingDt

Code:

import pyspark.sql.functions as f

diffDaysDF.withColumn("repeat", f.expr("split(repeat(',', diffDays), ',')"))\
    .select("*", f.posexplode("repeat").alias("txnDt", "val"))\
    .drop("repeat", "val", "diffDays")\
    .withColumn("txnDt", f.expr("date_add(bookingDt, txnDt)"))\
    .show()
#+----------+----------+-------+----------+
#| arrivalDt| bookingDt|vyge_id|     txnDt|
#+----------+----------+-------+----------+
#|2018-01-05|2018-01-01|   1000|2018-01-01|
#|2018-01-05|2018-01-01|   1000|2018-01-02|
#|2018-01-05|2018-01-01|   1000|2018-01-03|
#|2018-01-05|2018-01-01|   1000|2018-01-04|
#|2018-01-05|2018-01-01|   1000|2018-01-05|
#+----------+----------+-------+----------+

Answer 4

For Spark 2.4+ sequence can be used to create an array containg all dates between bookingDt and arrivalDt. This array can then be exploded.

from pyspark.sql import functions as F

df = df \
  .withColumn('bookingDt', F.col('bookingDt').cast('date')) \
  .withColumn('arrivalDt', F.col('arrivalDt').cast('date'))

df.withColumn('txnDt', F.explode(F.expr('sequence(bookingDt, arrivalDt, interval 1 day)')))\
  .show()

Output:

+-------+----------+----------+----------+
|vyge_id| bookingDt| arrivalDt|     txnDt|
+-------+----------+----------+----------+
|   1000|2018-01-01|2018-01-05|2018-01-01|
|   1000|2018-01-01|2018-01-05|2018-01-02|
|   1000|2018-01-01|2018-01-05|2018-01-03|
|   1000|2018-01-01|2018-01-05|2018-01-04|
|   1000|2018-01-01|2018-01-05|2018-01-05|
+-------+----------+----------+----------+