pyspark.sql.functions.sequence#

pyspark.sql.functions.sequence(start, stop, step=None)[source]#

Array function: Generate a sequence of integers from start to stop, incrementing by step. If step is not set, the function increments by 1 if start is less than or equal to stop, otherwise it decrements by 1.

New in version 2.4.0.

Changed in version 3.4.0: Supports Spark Connect.

Parameters

startColumn or str: The starting value (inclusive) of the sequence.
stopColumn or str: The last value (inclusive) of the sequence.
stepColumn or str, optional: The value to add to the current element to get the next element in the sequence. The default is 1 if start is less than or equal to stop, otherwise -1.

Returns

Column: A new column that contains an array of sequence values.

Examples

Example 1: Generating a sequence with default step

>>> import pyspark.sql.functions as sf
>>> df = spark.createDataFrame([(-2, 2)], ['start', 'stop'])
>>> df.select(sf.sequence(df.start, df.stop)).show()
+---------------------+
|sequence(start, stop)|
+---------------------+
|    [-2, -1, 0, 1, 2]|
+---------------------+

Example 2: Generating a sequence with a custom step

>>> import pyspark.sql.functions as sf
>>> df = spark.createDataFrame([(4, -4, -2)], ['start', 'stop', 'step'])
>>> df.select(sf.sequence(df.start, df.stop, df.step)).show()
+---------------------------+
|sequence(start, stop, step)|
+---------------------------+
|          [4, 2, 0, -2, -4]|
+---------------------------+

Example 3: Generating a sequence with a negative step

>>> import pyspark.sql.functions as sf
>>> df = spark.createDataFrame([(5, 1, -1)], ['start', 'stop', 'step'])
>>> df.select(sf.sequence(df.start, df.stop, df.step)).show()
+---------------------------+
|sequence(start, stop, step)|
+---------------------------+
|            [5, 4, 3, 2, 1]|
+---------------------------+