如何将字典列表转换为Pyspark DataFrame [英] How to convert list of dictionaries into Pyspark DataFrame
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问题描述
我想将我的词典列表转换为DataFrame.这是列表:
I want to convert my list of dictionaries into DataFrame. This is the list:
mylist =
[
{"type_activity_id":1,"type_activity_name":"xxx"},
{"type_activity_id":2,"type_activity_name":"yyy"},
{"type_activity_id":3,"type_activity_name":"zzz"}
]
这是我的代码:
from pyspark.sql.types import StringType
df = spark.createDataFrame(mylist, StringType())
df.show(2,False)
+-----------------------------------------+
| value|
+-----------------------------------------+
|{type_activity_id=1,type_activity_id=xxx}|
|{type_activity_id=2,type_activity_id=yyy}|
|{type_activity_id=3,type_activity_id=zzz}|
+-----------------------------------------+
我假设我应该为每列提供一些映射和类型,但是我不知道该怎么做.
I assume that I should provide some mapping and types for each column, but I don't know how to do it.
更新:
我也尝试过:
schema = ArrayType(
StructType([StructField("type_activity_id", IntegerType()),
StructField("type_activity_name", StringType())
]))
df = spark.createDataFrame(mylist, StringType())
df = df.withColumn("value", from_json(df.value, schema))
但是随后我得到了null
值:
+-----+
|value|
+-----+
| null|
| null|
+-----+
推荐答案
您可以这样做.您将获得一个包含2列的数据框.
You can do it like this. You will get a dataframe with 2 columns.
mylist = [
{"type_activity_id":1,"type_activity_name":"xxx"},
{"type_activity_id":2,"type_activity_name":"yyy"},
{"type_activity_id":3,"type_activity_name":"zzz"}
]
myJson = sc.parallelize(mylist)
myDf = sqlContext.read.json(myJson)
输出:
+----------------+------------------+
|type_activity_id|type_activity_name|
+----------------+------------------+
| 1| xxx|
| 2| yyy|
| 3| zzz|
+----------------+------------------+
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