通过


array_append

通过将值追加到现有数组来返回新的数组列。

Syntax

from pyspark.sql import functions as sf

sf.array_append(col, value)

参数

参数 类型 Description
col pyspark.sql.Column 或 str 包含数组的列的名称。
value 任意 要追加到数组中的文本值或 Column 表达式。

退货

pyspark.sql.Column:追加 value 到原始数组的新数组列。

例子

示例 1:将列值追加到数组列

from pyspark.sql import Row, functions as sf
df = spark.createDataFrame([Row(c1=["b", "a", "c"], c2="c")])
df.select(sf.array_append(df.c1, df.c2)).show()
+--------------------+
|array_append(c1, c2)|
+--------------------+
|        [b, a, c, c]|
+--------------------+

示例 2:将数值追加到数组列

from pyspark.sql import functions as sf
df = spark.createDataFrame([([1, 2, 3],)], ['data'])
df.select(sf.array_append(df.data, 4)).show()
+---------------------+
|array_append(data, 4)|
+---------------------+
|         [1, 2, 3, 4]|
+---------------------+

示例 3:将 null 值追加到数组列

from pyspark.sql import functions as sf
df = spark.createDataFrame([([1, 2, 3],)], ['data'])
df.select(sf.array_append(df.data, None)).show()
+------------------------+
|array_append(data, NULL)|
+------------------------+
|         [1, 2, 3, NULL]|
+------------------------+

示例 4:将值追加到 NULL 数组列

from pyspark.sql import functions as sf
from pyspark.sql.types import ArrayType, IntegerType, StructType, StructField
schema = StructType([
  StructField("data", ArrayType(IntegerType()), True)
])
df = spark.createDataFrame([(None,)], schema=schema)
df.select(sf.array_append(df.data, 4)).show()
+---------------------+
|array_append(data, 4)|
+---------------------+
|                 NULL|
+---------------------+

示例 5:将值追加到空数组

from pyspark.sql import functions as sf
from pyspark.sql.types import ArrayType, IntegerType, StructType, StructField
schema = StructType([
  StructField("data", ArrayType(IntegerType()), True)
])
df = spark.createDataFrame([([],)], schema=schema)
df.select(sf.array_append(df.data, 1)).show()
+---------------------+
|array_append(data, 1)|
+---------------------+
|                  [1]|
+---------------------+