返回给定数组或映射中每个元素的新行。 对数组中的元素和keyvalue映射中的元素使用默认列名col，除非另有指定。
注释
每个子句只允许发生一次 SELECT 爆炸。
Syntax
from pyspark.sql import functions as sf
sf.explode(col)
参数
| 参数 | 类型 | Description |
|---|---|---|
col |
pyspark.sql.Column 或列名 |
要处理的目标列。 |
退货
pyspark.sql.Column：每个数组项或映射键值一行。
例子
示例 1：分解数组列
from pyspark.sql import functions as sf
df = spark.sql('SELECT * FROM VALUES (1,ARRAY(1,2,3,NULL)), (2,ARRAY()), (3,NULL) AS t(i,a)')
df.show()
+---+---------------+
| i| a|
+---+---------------+
| 1|[1, 2, 3, NULL]|
| 2| []|
| 3| NULL|
+---+---------------+
df.select('*', sf.explode('a')).show()
+---+---------------+----+
| i| a| col|
+---+---------------+----+
| 1|[1, 2, 3, NULL]| 1|
| 1|[1, 2, 3, NULL]| 2|
| 1|[1, 2, 3, NULL]| 3|
| 1|[1, 2, 3, NULL]|NULL|
+---+---------------+----+
示例 2：分解地图列
from pyspark.sql import functions as sf
df = spark.sql('SELECT * FROM VALUES (1,MAP(1,2,3,4,5,NULL)), (2,MAP()), (3,NULL) AS t(i,m)')
df.show(truncate=False)
+---+---------------------------+
|i |m |
+---+---------------------------+
|1 |{1 -> 2, 3 -> 4, 5 -> NULL}|
|2 |{} |
|3 |NULL |
+---+---------------------------+
df.select('*', sf.explode('m')).show(truncate=False)
+---+---------------------------+---+-----+
|i |m |key|value|
+---+---------------------------+---+-----+
|1 |{1 -> 2, 3 -> 4, 5 -> NULL}|1 |2 |
|1 |{1 -> 2, 3 -> 4, 5 -> NULL}|3 |4 |
|1 |{1 -> 2, 3 -> 4, 5 -> NULL}|5 |NULL |
+---+---------------------------+---+-----+
示例 3：分解多个数组列
import pyspark.sql.functions as sf
df = spark.sql('SELECT ARRAY(1,2) AS a1, ARRAY(3,4,5) AS a2')
df.select(
'*', sf.explode('a1').alias('v1')
).select('*', sf.explode('a2').alias('v2')).show()
+------+---------+---+---+
| a1| a2| v1| v2|
+------+---------+---+---+
|[1, 2]|[3, 4, 5]| 1| 3|
|[1, 2]|[3, 4, 5]| 1| 4|
|[1, 2]|[3, 4, 5]| 1| 5|
|[1, 2]|[3, 4, 5]| 2| 3|
|[1, 2]|[3, 4, 5]| 2| 4|
|[1, 2]|[3, 4, 5]| 2| 5|
+------+---------+---+---+
示例 4：分解结构列数组
import pyspark.sql.functions as sf
df = spark.sql('SELECT ARRAY(NAMED_STRUCT("a",1,"b",2), NAMED_STRUCT("a",3,"b",4)) AS a')
df.select(sf.explode('a').alias("s")).select("s.*").show()
+---+---+
| a| b|
+---+---+
| 1| 2|
| 3| 4|
+---+---+