您基本上需要执行以下操作：
从列表中创建Dataframe
使用 explode 通过从对中提取键值（&V） select 可以这样做（源数据位于名为 a ):

from pyspark.sql.functions import explode, col
df = spark.createDataFrame(a, ['key1', 'val'])
df2 = df.select(col('key1'), explode(col('val')).alias('val'))
df3 = df2.select('key1', col('val')._1.alias('key2'), col('val')._2.alias('value'))

我们可以检查架构和数据是否匹配：

>>> df3.printSchema()
root
 |-- key1: string (nullable = true)
 |-- key2: string (nullable = true)
 |-- value: double (nullable = true)

>>> df3.show(2)
+----------+----------+------------------+
|      key1|      key2|             value|
+----------+----------+------------------+
|1052762305|1007819788|0.9206884810054885|
|1052762305|1005886801| 0.913818268123084|
+----------+----------+------------------+
only showing top 2 rows

我们还可以检查中间结果的模式：

>>> df.printSchema()
root
 |-- key1: string (nullable = true)
 |-- val: array (nullable = true)
 |    |-- element: struct (containsNull = true)
 |    |    |-- _1: string (nullable = true)
 |    |    |-- _2: double (nullable = true)

>>> df2.printSchema()
root
 |-- key1: string (nullable = true)
 |-- val: struct (nullable = true)
 |    |-- _1: string (nullable = true)
 |    |-- _2: double (nullable = true)

您可以使用输入预先创建一个模式。使用explode并访问value结构中的元素。

from pyspark.sql import SparkSession
    from pyspark.sql import functions as F
    from pyspark.sql.types import  StructType, StructField,StringType,ArrayType, DoubleType

    spark = SparkSession.builder \
        .appName('SO')\
        .getOrCreate()

        schema = StructType([StructField("key1",StringType()), StructField("value",ArrayType(
            StructType([ StructField("key2", StringType()),
               StructField("score", DoubleType())])
        )) ])

    df = spark.createDataFrame(
        [('1052762305',
          [('1007819788', 0.9206884810054885),
           ('1005886801', 0.913818268123084),
           ('1003863766', 0.9131746152849486),
           ('1007811435', 0.9128666156173751),
           ('1005879599', 0.9126368405937075),
           ('1003705572', 0.9122051062936369),
           ('1007804896', 0.9083424459788203),
           ('1005890270', 0.8982097535650703),
           ('1007806781', 0.8708761186829758),
           ('1003670458', 0.8452789033694487)]),

         ('1064808607',
          [('1007804896', 0.9984397647563017),
           ('1003705572', 0.9970498347406341),
           ('1005879599', 0.9951581013190172),
           ('1007811435', 0.9934813787902085),
           ('1005886801', 0.9930572794622374),
           ('1003863766', 0.9928815742735568),
           ('1007819788', 0.9869723713790797),
           ('1005890270', 0.9642640856016443),
           ('1007806781', 0.9211558765137313),
           ('1003670458', 0.8519872445941068)])
         ],schema
    )

    df.show()

    +----------+--------------------+
    |      key1|          value    |
    +----------+--------------------+
    |1052762305|[[1007819788, 0.9...|
    |1064808607|[[1007804896, 0.9...|
    +----------+--------------------+

    df.printSchema()

    root
     |-- key1: string (nullable = true)
     |-- value: array (nullable = true)
     |    |-- element: struct (containsNull = true)
     |    |    |-- key2: string (nullable = true)
     |    |    |-- score: double (nullable = true)

    df1=df.select('key1',F.explode('value').alias('value'))
    df1.show()
    +----------+--------------------+
    |      key1|          value     |
    +----------+--------------------+
    |1052762305|[1007819788, 0.92...|
    |1052762305|[1005886801, 0.91...|
    |1052762305|[1003863766, 0.91...|
    |1052762305|[1007811435, 0.91...|
    |1052762305|[1005879599, 0.91...|
    |1052762305|[1003705572, 0.91...|
    |1052762305|[1007804896, 0.90...|
    |1052762305|[1005890270, 0.89...|
    |1052762305|[1007806781, 0.87...|
    |1052762305|[1003670458, 0.84...|
    |1064808607|[1007804896, 0.99...|
    |1064808607|[1003705572, 0.99...|
    |1064808607|[1005879599, 0.99...|
    |1064808607|[1007811435, 0.99...|
    |1064808607|[1005886801, 0.99...|
    |1064808607|[1003863766, 0.99...|
    |1064808607|[1007819788, 0.98...|
    |1064808607|[1005890270, 0.96...|
    |1064808607|[1007806781, 0.92...|
    |1064808607|[1003670458, 0.85...|
    +----------+--------------------+

    df1.printSchema()

    root
     |-- key1: string (nullable = true)
     |-- value: struct (nullable = true)
     |    |-- key2: string (nullable = true)
     |    |-- score: double (nullable = true)

    df1.select("key1", "value.key2","value.score").show()

    +----------+----------+------------------+
    |      key1|      key2|             score|
    +----------+----------+------------------+
    |1052762305|1007819788|0.9206884810054885|
    |1052762305|1005886801| 0.913818268123084|
    |1052762305|1003863766|0.9131746152849486|
    |1052762305|1007811435|0.9128666156173751|
    |1052762305|1005879599|0.9126368405937075|
    |1052762305|1003705572|0.9122051062936369|
    |1052762305|1007804896|0.9083424459788203|
    |1052762305|1005890270|0.8982097535650703|
    |1052762305|1007806781|0.8708761186829758|
    |1052762305|1003670458|0.8452789033694487|
    |1064808607|1007804896|0.9984397647563017|
    |1064808607|1003705572|0.9970498347406341|
    |1064808607|1005879599|0.9951581013190172|
    |1064808607|1007811435|0.9934813787902085|
    |1064808607|1005886801|0.9930572794622374|
    |1064808607|1003863766|0.9928815742735568|
    |1064808607|1007819788|0.9869723713790797|
    |1064808607|1005890270|0.9642640856016443|
    |1064808607|1007806781|0.9211558765137313|
    |1064808607|1003670458|0.8519872445941068|