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从rest api到pyspark数据帧的嵌套json

[英]nested json from rest api to pyspark dataframe

我正在尝试创建一个数据管道,我在其中从 REST API 请求数据。 输出是一个很好的嵌套 json 文件。 我想将 json 文件读入 pyspark 数据帧。 当我在本地保存文件并使用以下代码时,这很好用:

from pyspark.sql import *
from pyspark.sql.functions import *

spark = SparkSession\
    .builder\
    .appName("jsontest")\
    .getOrCreate()

raw_df = spark.read.json(r"my_json_path", multiLine='true')

但是当我在发出 API 请求后想直接创建一个 pyspark 数据帧时,我收到以下错误:

尝试在此处创建 pyspark dataframeenter 图像描述时出错

我使用以下代码进行休息 api 调用并转换为 pyspark 数据帧:

apiCallHeaders = {'Authorization': 'Bearer ' + bearer_token}
apiCallResponse = requests.get(data_url, headers=apiCallHeaders, verify=True)
json_rdd = spark.sparkContext.parallelize(apiCallResponse.text)
raw_df = spark.read.json(json_rdd)

以下是部分响应输出

{"networks":[{"href":"/v2/networks/velobike-moscow","id":"velobike-moscow","name":"Velobike"},{"href":"/v2/networks/bycyklen","id":"bycyklen","name":"Bycyklen"},{"href":"/v2/networks/nu-connect","id":"nu-connect","name":"Nu-Connect"},{"href":"/v2/networks/baerum-bysykkel","id":"baerum-bysykkel","name":"Bysykkel"},{"href":"/v2/networks/bysykkelen","id":"bysykkelen","name":"Bysykkelen"},{"href":"/v2/networks/onroll-a-rua","id":"onroll-a-rua","name":"Onroll"},{"href":"/v2/networks/onroll-albacete","id":"onroll-albacete","name":"Onroll"},{"href":"/v2/networks/onroll-alhama-de-murcia","id":"onroll-alhama-de-murcia","name":"Onroll"},{"href":"/v2/networks/onroll-almunecar","id":"onroll-almunecar","name":"Onroll"},{"href":"/v2/networks/onroll-antequera","id":"onroll-antequera","name":"Onroll"},{"href":"/v2/networks/onroll-aranda-de-duero","id":"onroll-aranda-de-duero","name":"Onroll"}

我希望我的问题是有道理的,有人可以提供帮助。

提前致谢!

按照这个答案,您可以添加以下几行:

import os
import sys

os.environ['PYSPARK_PYTHON'] = sys.executable
os.environ['PYSPARK_DRIVER_PYTHON'] = sys.executable

要运行您的代码,必须在此处添加[ ]

rdd = spark.sparkContext.parallelize([apiCallResponse.text])

看一个例子:

import requests

response = requests.get('http://api.citybik.es/v2/networks?fields=id,name,href')
rdd = spark.sparkContext.parallelize([response.text])

df = spark.read.json(rdd)

df.printSchema()
# root
#  |-- networks: array (nullable = true)
#  |    |-- element: struct (containsNull = true)
#  |    |    |-- href: string (nullable = true)
#  |    |    |-- id: string (nullable = true)
#  |    |    |-- name: string (nullable = true)

(df
 .selectExpr('inline(networks)')
 .show(n=5, truncate=False))
# +----------------------------+---------------+----------+
# |href                        |id             |name      |
# +----------------------------+---------------+----------+
# |/v2/networks/velobike-moscow|velobike-moscow|Velobike  |
# |/v2/networks/bycyklen       |bycyklen       |Bycyklen  |
# |/v2/networks/nu-connect     |nu-connect     |Nu-Connect|
# |/v2/networks/baerum-bysykkel|baerum-bysykkel|Bysykkel  |
# |/v2/networks/bysykkelen     |bysykkelen     |Bysykkelen|
# +----------------------------+---------------+----------+

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