将 DataFrame 中的字符串数组拆分为自己的列

Question

我有一个这样的数据框：

df.show()

+-----+ 
|col1 | 
+-----+ 
|[a,b]| 
|[c,d]|   
+-----+

如何将其转换成如下数据框

+----+----+ 
|col1|col2| 
+----+----+ 
|   a|   b| 
|   c|   d|  
+----+----+

Answer 1

这取决于你的类型 "list":

如果是ArrayType()类型：

df = spark.createDataFrame(spark.sparkContext.parallelize([['a', ["a","b","c"]], ['b', ["d","e","f"]]]), ["key", "col"])
df.printSchema()
df.show()
root
 |-- key: string (nullable = true)
 |-- col: array (nullable = true)
 |    |-- element: string (containsNull = true)
+---+---------+
|key|      col|
+---+---------+
|  a|[a, b, c]|
|  b|[d, e, f]|
+---+---------+

您可以像使用 python 一样使用 []:

df.select("key", df.col[0], df.col[1], df.col[2]).show()
+---+------+------+------+
|key|col[0]|col[1]|col[2]|
+---+------+------+------+
|  a|     a|     b|     c|
|  b|     d|     e|     f|
+---+------+------+------+

如果它是 StructType() 类型：（也许您通过阅读 JSON 构建了数据框）

df2 = df.select("key", F.struct(
        df.col[0].alias("col1"), 
        df.col[1].alias("col2"), 
        df.col[2].alias("col3")
    ).alias("col"))
df2.printSchema()
df2.show()

root
 |-- key: string (nullable = true)
 |-- col: struct (nullable = false)
 |    |-- col1: string (nullable = true)
 |    |-- col2: string (nullable = true)
 |    |-- col3: string (nullable = true)
+---+---------+
|key|      col|
+---+---------+
|  a|[a, b, c]|
|  b|[d, e, f]|
+---+---------+

你可以直接'split'列使用*:

df2.select('key', 'col.*').show()

+---+----+----+----+
|key|col1|col2|col3|
+---+----+----+----+
|  a|   a|   b|   c|
|  b|   d|   e|   f|
+---+----+----+----+

将 DataFrame 中的字符串数组拆分为自己的列

Split Array of Strings in a DataFrame into their own columns

json

dataframe

apache-spark

pyspark

explode