将 PySpark 数据框列从列表转换为字符串 [英] Convert PySpark dataframe column from list to string

问题描述

我有这个 PySpark 数据框

I have this PySpark dataframe

+-----------+--------------------+
|uuid       |   test_123         |    
+-----------+--------------------+
|      1    |[test, test2, test3]|
|      2    |[test4, test, test6]|
|      3    |[test6, test9, t55o]|

我想将 test_123 列转换成这样:

and I want to convert the column test_123 to be like this:

+-----------+--------------------+
|uuid       |   test_123         |    
+-----------+--------------------+
|      1    |"test,test2,test3"  |
|      2    |"test4,test,test6"  |
|      3    |"test6,test9,t55o"  |

所以从列表变成字符串.

so from list to be string.

我怎样才能用 PySpark 做到这一点?

how can I do it with PySpark?

推荐答案

您可以创建一个 udf 加入 array/list 然后将其应用到 测试栏:

You can create a udf that joins array/list and then apply it to the test column:

from pyspark.sql.functions import udf, col

join_udf = udf(lambda x: ",".join(x))
df.withColumn("test_123", join_udf(col("test_123"))).show()

+----+----------------+
|uuid|        test_123|
+----+----------------+
|   1|test,test2,test3|
|   2|test4,test,test6|
|   3|test6,test9,t55o|
+----+----------------+

初始数据框创建自:

from pyspark.sql.types import StructType, StructField
schema = StructType([StructField("uuid",IntegerType(),True),StructField("test_123",ArrayType(StringType(),True),True)])
rdd = sc.parallelize([[1, ["test","test2","test3"]], [2, ["test4","test","test6"]],[3,["test6","test9","t55o"]]])
df = spark.createDataFrame(rdd, schema)

df.show()
+----+--------------------+
|uuid|            test_123|
+----+--------------------+
|   1|[test, test2, test3]|
|   2|[test4, test, test6]|
|   3|[test6, test9, t55o]|
+----+--------------------+

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