如何使用2个JSON文件创建pyspark数据框?
file1
{"RESIDENCY":"AUS","EFFDT":"01-01-1900","EFF_STATUS":"A","DESCR":"Australian Resident","DESCRSHORT":"Australian"}
file2
[{"fields":[{"metadata":{},"name":"RESIDENCY","nullable":true,"type":"string"},{"metadata":{},"name":"EFFDT","nullable":true,"type":"string"},{"metadata":{},"name":"EFF_STATUS","nullable":true,"type":"string"},{"metadata":{},"name":"DESCR","nullable":true,"type":"string"},{"metadata":{},"name":"DESCRSHORT","nullable":true,"type":"string"}],"type":"struct"}]
首先,您必须使用Python json.load
阅读架构文件,然后使用DataType
将其转换为StructType.fromJson
。
StructType.fromJson
现在只需将该架构传递给DataFrame Reader:
import json
from pyspark.sql.types import StructType
with open("/path/to/file2.json") as f:
json_schema = json.load(f)
schema = StructType.fromJson(json_schema[0])
编辑:
如果包含架构的文件位于GCS中,则可以使用Spark或Hadoop API来获取文件内容。这是一个使用Spark的示例:
df = spark.read.schema(schema).json("/path/to/file1.json")
df.show()
#+---------+----------+----------+-------------------+----------+
#|RESIDENCY| EFFDT|EFF_STATUS| DESCR|DESCRSHORT|
#+---------+----------+----------+-------------------+----------+
#| AUS|01-01-1900| A|Australian Resident|Australian|
#+---------+----------+----------+-------------------+----------+
我发现GCSFS软件包可以访问GCP存储桶中的文件:
file_content = spark.read.text("/path/to/file2.json").rdd.map(
lambda r: " ".join([str(elt) for elt in r])
).reduce(
lambda x, y: "\n".join([x, y])
)
json_schema = json.loads(file_content)