从 Cloudant IBM Bluemix NoSQL 数据库中提取价值
Extract value from cloudant IBM Bluemix NoSQL Database
如何从以 JSON 格式存储的 Cloudant IBM Bluemix NoSQL 数据库中提取值?
我试过这个代码
def readDataFrameFromCloudant(host,user,pw,database):
cloudantdata=spark.read.format("com.cloudant.spark"). \
option("cloudant.host",host). \
option("cloudant.username", user). \
option("cloudant.password", pw). \
load(database)
cloudantdata.createOrReplaceTempView("washing")
spark.sql("SELECT * from washing").show()
return cloudantdata
hostname = ""
user = ""
pw = ""
database = "database"
cloudantdata=readDataFrameFromCloudant(hostname, user, pw, database)
以这种格式存储
{
"_id": "31c24a382f3e4d333421fc89ada5361e",
"_rev": "1-8ba1be454fed5b48fa493e9fe97bedae",
"d": {
"count": 9,
"hardness": 72,
"temperature": 85,
"flowrate": 11,
"fluidlevel": "acceptable",
"ts": 1502677759234
}
}
我想要这个结果
预计
实际结果
创建用于重现问题的虚拟数据集:
cloudantdata = spark.read.json(sc.parallelize(["""
{
"_id": "31c24a382f3e4d333421fc89ada5361e",
"_rev": "1-8ba1be454fed5b48fa493e9fe97bedae",
"d": {
"count": 9,
"hardness": 72,
"temperature": 85,
"flowrate": 11,
"fluidlevel": "acceptable",
"ts": 1502677759234
}
}
"""]))
cloudantdata.take(1)
Returns:
[Row(_id='31c24a382f3e4d333421fc89ada5361e', _rev='1-8ba1be454fed5b48fa493e9fe97bedae', d=Row(count=9, flowrate=11, fluidlevel='acceptable', hardness=72, temperature=85, ts=1502677759234))]
现在展平:
flat_df = cloudantdata.select("_id", "_rev", "d.*")
flat_df.take(1)
Returns:
[Row(_id='31c24a382f3e4d333421fc89ada5361e', _rev='1-8ba1be454fed5b48fa493e9fe97bedae', count=9, flowrate=11, fluidlevel='acceptable', hardness=72, temperature=85, ts=1502677759234)]
我使用 IBM Data Science Experience notebook 使用 Python 3.5(实验)和 Spark 2.0
测试了这段代码
此答案基于:
如何从以 JSON 格式存储的 Cloudant IBM Bluemix NoSQL 数据库中提取值?
我试过这个代码
def readDataFrameFromCloudant(host,user,pw,database):
cloudantdata=spark.read.format("com.cloudant.spark"). \
option("cloudant.host",host). \
option("cloudant.username", user). \
option("cloudant.password", pw). \
load(database)
cloudantdata.createOrReplaceTempView("washing")
spark.sql("SELECT * from washing").show()
return cloudantdata
hostname = ""
user = ""
pw = ""
database = "database"
cloudantdata=readDataFrameFromCloudant(hostname, user, pw, database)
以这种格式存储
{
"_id": "31c24a382f3e4d333421fc89ada5361e",
"_rev": "1-8ba1be454fed5b48fa493e9fe97bedae",
"d": {
"count": 9,
"hardness": 72,
"temperature": 85,
"flowrate": 11,
"fluidlevel": "acceptable",
"ts": 1502677759234
}
}
我想要这个结果
预计
实际结果
创建用于重现问题的虚拟数据集:
cloudantdata = spark.read.json(sc.parallelize(["""
{
"_id": "31c24a382f3e4d333421fc89ada5361e",
"_rev": "1-8ba1be454fed5b48fa493e9fe97bedae",
"d": {
"count": 9,
"hardness": 72,
"temperature": 85,
"flowrate": 11,
"fluidlevel": "acceptable",
"ts": 1502677759234
}
}
"""]))
cloudantdata.take(1)
Returns:
[Row(_id='31c24a382f3e4d333421fc89ada5361e', _rev='1-8ba1be454fed5b48fa493e9fe97bedae', d=Row(count=9, flowrate=11, fluidlevel='acceptable', hardness=72, temperature=85, ts=1502677759234))]
现在展平:
flat_df = cloudantdata.select("_id", "_rev", "d.*")
flat_df.take(1)
Returns:
[Row(_id='31c24a382f3e4d333421fc89ada5361e', _rev='1-8ba1be454fed5b48fa493e9fe97bedae', count=9, flowrate=11, fluidlevel='acceptable', hardness=72, temperature=85, ts=1502677759234)]
我使用 IBM Data Science Experience notebook 使用 Python 3.5(实验)和 Spark 2.0
测试了这段代码此答案基于: