Bagikan melalui


Meledak

Mengembalikan baris baru untuk setiap elemen dalam array atau peta yang diberikan. Menggunakan nama col kolom default untuk elemen dalam array dan key dan value untuk elemen dalam peta kecuali ditentukan sebaliknya.

Nota

Hanya satu ledakan yang diizinkan per SELECT klausul.

Syntax

from pyspark.sql import functions as sf

sf.explode(col)

Parameter-parameternya

Pengaturan Tipe Description
col pyspark.sql.Column atau nama kolom Kolom target untuk dikerjakan.

Pengembalian Barang

pyspark.sql.Column: Satu baris per item array atau nilai kunci peta.

Examples

Contoh 1: Meledakkan kolom array

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|
+---+---------------+----+

Contoh 2: Meledakkan kolom peta

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 |
+---+---------------------------+---+-----+

Contoh 3: Meledakkan beberapa kolom array

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|
+------+---------+---+---+

Contoh 4: Meledakkan array kolom struct

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|
+---+---+