array_repeat
Creates an array containing a column repeated count times.
Syntax
Python
from pyspark.sql import functions as sf
sf.array_repeat(col, count)
Parameters
Parameter | Type | Description |
|---|---|---|
|
| The name of the column or an expression that represents the element to be repeated. |
|
| The name of the column, an expression, or an integer that represents the number of times to repeat the element. |
Returns
pyspark.sql.Column: A new column that contains an array of repeated elements.
Examples
Example 1: Usage with string
Python
from pyspark.sql import functions as sf
df = spark.createDataFrame([('ab',)], ['data'])
df.select(sf.array_repeat(df.data, 3)).show()
Output
+---------------------+
|array_repeat(data, 3)|
+---------------------+
| [ab, ab, ab]|
+---------------------+
Example 2: Usage with integer
Python
from pyspark.sql import functions as sf
df = spark.createDataFrame([(3,)], ['data'])
df.select(sf.array_repeat(df.data, 2)).show()
Output
+---------------------+
|array_repeat(data, 2)|
+---------------------+
| [3, 3]|
+---------------------+
Example 3: Usage with array
Python
from pyspark.sql import functions as sf
df = spark.createDataFrame([(['apple', 'banana'],)], ['data'])
df.select(sf.array_repeat(df.data, 2)).show(truncate=False)
Output
+----------------------------------+
|array_repeat(data, 2) |
+----------------------------------+
|[[apple, banana], [apple, banana]]|
+----------------------------------+
Example 4: Usage with null
Python
from pyspark.sql import functions as sf
from pyspark.sql.types import IntegerType, StructType, StructField
schema = StructType([
StructField("data", IntegerType(), True)
])
df = spark.createDataFrame([(None, )], schema=schema)
df.select(sf.array_repeat(df.data, 3)).show()
Output
+---------------------+
|array_repeat(data, 3)|
+---------------------+
| [NULL, NULL, NULL]|
+---------------------+