Piezīmes
Lai piekļūtu šai lapai, ir nepieciešama autorizācija. Varat mēģināt pierakstīties vai mainīt direktorijus.
Lai piekļūtu šai lapai, ir nepieciešama autorizācija. Varat mēģināt mainīt direktorijus.
Returns a string column by concatenating the elements of the input array column using the delimiter. Null values within the array can be replaced with a specified string through the null_replacement argument. If null_replacement is not set, null values are ignored.
Syntax
from pyspark.sql import functions as sf
sf.array_join(col, delimiter, null_replacement=None)
Parameters
| Parameter | Type | Description |
|---|---|---|
col |
pyspark.sql.Column or str |
The input column containing the arrays to be joined. |
delimiter |
str | The string to be used as the delimiter when joining the array elements. |
null_replacement |
str, optional | The string to replace null values within the array. If not set, null values are ignored. |
Returns
pyspark.sql.Column: A new column of string type, where each value is the result of joining the corresponding array from the input column.
Examples
Example 1: Basic usage of array_join function.
from pyspark.sql import functions as sf
df = spark.createDataFrame([(["a", "b", "c"],), (["a", "b"],)], ['data'])
df.select(sf.array_join(df.data, ",")).show()
+-------------------+
|array_join(data, ,)|
+-------------------+
| a,b,c|
| a,b|
+-------------------+
Example 2: Usage of array_join function with null_replacement argument.
from pyspark.sql import functions as sf
df = spark.createDataFrame([(["a", None, "c"],)], ['data'])
df.select(sf.array_join(df.data, ",", "NULL")).show()
+-------------------------+
|array_join(data, ,, NULL)|
+-------------------------+
| a,NULL,c|
+-------------------------+
Example 3: Usage of array_join function without null_replacement argument.
from pyspark.sql import functions as sf
df = spark.createDataFrame([(["a", None, "c"],)], ['data'])
df.select(sf.array_join(df.data, ",")).show()
+-------------------+
|array_join(data, ,)|
+-------------------+
| a,c|
+-------------------+
Example 4: Usage of array_join function with an array that is null.
from pyspark.sql import functions as sf
from pyspark.sql.types import StructType, StructField, ArrayType, StringType
schema = StructType([StructField("data", ArrayType(StringType()), True)])
df = spark.createDataFrame([(None,)], schema)
df.select(sf.array_join(df.data, ",")).show()
+-------------------+
|array_join(data, ,)|
+-------------------+
| NULL|
+-------------------+
Example 5: Usage of array_join function with an array containing only null values.
from pyspark.sql import functions as sf
from pyspark.sql.types import StructType, StructField, ArrayType, StringType
schema = StructType([StructField("data", ArrayType(StringType()), True)])
df = spark.createDataFrame([([None, None],)], schema)
df.select(sf.array_join(df.data, ",", "NULL")).show()
+-------------------------+
|array_join(data, ,, NULL)|
+-------------------------+
| NULL,NULL|
+-------------------------+