在 pyspark 中创建一个包含单列元组的数据框 [英] Create a dataframe in pyspark that contains a single column of tuples

问题描述

我有一个 RDD，其中包含以下 [('column 1',value), ('column 2',value), ('column 3',value), ... , ('column 100',value)].我想创建一个包含带有元组的单列的数据框.

I have an RDD that contains the following [('column 1',value), ('column 2',value), ('column 3',value), ... , ('column 100',value)]. I want to create a dataframe that contains a single column with tuples.

我得到的最接近的是:

schema = StructType((StructField("char", StringType(), False), (StructField("count", IntegerType(), False))))
    my_udf = udf(lambda w, c: (w,c), schema)

然后

df.select(my_udf('char', 'int').alias('char_int'))

但这会生成一个包含一列列表的数据框，而不是元组.

but this produces a dataframe with a column of lists, not tuples.

推荐答案

struct 是在 Spark SQL 中表示产品类型的正确方法，例如 tuple，这是正是您使用代码获得的:

struct is a s correct way to represent product types, like tuple, in Spark SQL and this is exactly what you get using your code:

df = (sc.parallelize([("a", 1)]).toDF(["char", "int"])
    .select(my_udf("char", "int").alias("pair")))
df.printSchema()

## root
##  |-- pair: struct (nullable = true)
##  |    |-- char: string (nullable = false)
##  |    |-- count: integer (nullable = false)

没有其他方法可以表示元组，除非您想创建 UDT(2.0.0 不再支持)或将腌制对象存储为 BinaryType.

There is no other way to represent a tuple unless you want to create an UDT (no longer supported in 2.0.0) or store pickled objects as BinaryType.

此外，struct 字段在本地表示为 tuple:

Moreover struct fields are locally represented as tuple:

isinstance(df.first().pair, tuple)
## True

我猜你在调用 show 时可能会被方括号搞糊涂:

I guess you may be confused by square brackets when you call show:

df.show()

## +-----+
## | pair|
## +-----+
## |[a,1]|
## +-----+

它们只是 JVM 对应的选择渲染的表示，不指示 Python 类型.

which are simply a representation of choice render by JVM counterpart and don't indicate Python types.

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