我正在按照示例演练Export to SQL from Application Insights using Stream Analytics进行操作。我试图导出自定义事件维度(下面的JSON示例中的context.custom.dimensions),它将作为嵌套的JSON数组添加到数据文件中。如何在context.custom.dimensions中展平维度数组以导出到SQL?
... JSON
{
"event": [
{
"name": "50_DistanceSelect",
"count": 1
}
],
"internal": {
"data": {
"id": "aad2627b-60c5-48e8-aa35-197cae30a0cf",
"documentVersion": "1.5"
}
},
"context": {
"device": {
"os": "Windows",
"osVersion": "Windows 8.1",
"type": "PC",
"browser": "Chrome",
"browserVersion": "Chrome 43.0",
"screenResolution": {
"value": "1920X1080"
},
"locale": "unknown",
"id": "browser",
"userAgent": "Mozilla/5.0 (Windows NT 6.3; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/43.0.2357.134 Safari/537.36"
},
"application": {},
"location": {
"continent": "North America",
"country": "United States",
"point": {
"lat": 38.0,
"lon": -97.0
},
"clientip": "0.115.6.185",
"province": "",
"city": ""
},
"data": {
"isSynthetic": false,
"eventTime": "2015-07-15T23:43:27.595Z",
"samplingRate": 0.0
},
"operation": {
"id": "2474EE6F-5F6F-48C3-BA43-51636928075A"
},
"user": {
"anonId": "BA05C4BE-1C42-482F-9836-D79008E78A9D",
"anonAcquisitionDate": "0001-01-01T00:00:00Z",
"authAcquisitionDate": "0001-01-01T00:00:00Z",
"accountAcquisitionDate": "0001-01-01T00:00:00Z"
},
"custom": {
"dimensions": [
{
"CategoryAction": "click"
},
{
"SessionId": "73ef454d-fa39-4125-b4d0-44486933533b"
},
{
"WebsiteVersion": "3.0"
},
{
"PageSection": "FilterFind"
},
{
"Category": "EventCategory1"
},
{
"Page": "/page-in-question"
}
],
"metrics": []
},
"session": {
"id": "062703E5-5E15-491A-AC75-2FE54EF03623",
"isFirst": false
}
}
}
答案 0 :(得分:6)
稍微更动态的解决方案是设置临时表:
WITH ATable AS (
SELECT
temp.internal.data.id as ID
,dimensions.ArrayValue.CategoryAction as CategoryAction
,dimensions.ArrayValue.SessionId as SessionId
,dimensions.ArrayValue.WebsiteVersion as WebsiteVersion
,dimensions.ArrayValue.PageSection as PageSection
,dimensions.ArrayValue.Category as Category
,dimensions.ArrayValue.Page as Page
FROM [analyticseventinputs] temp
CROSS APPLY GetElements(temp.[context].[custom].[dimensions]) as dimensions)
然后根据唯一键
进行连接FROM [analyticseventinputs] Input
Left JOIN ATable CategoryAction on
Input.internal.data.id = CategoryAction.ID AND
CategoryAction.CategoryAction <> "" AND
DATEDIFF(day, Input, CategoryAction) BETWEEN 0 AND 5
相当恼人的一点是对datediff的要求,因为连接旨在组合2个数据流,但在这种情况下,您只加入唯一键。所以我把它设置为5天的大值。与其他解决方案相比,这实际上只能防止自定义参数不符合要求。
答案 1 :(得分:5)
大多数教程在线使用CROSS APPLY或OUTER APPLY,但这不是您要查找的内容,因为它会将每个属性放在不同的行上。为了解决这个问题,请使用以下函数:GetRecordPropertyValue和GetArrayElement。这会将属性展平为一行。
SELECT
GetRecordPropertyValue(GetArrayElement(MySource.context.custom.dimensions, 0), 'CategoryAction') AS CategoryAction,
GetRecordPropertyValue(GetArrayElement(MySource.context.custom.dimensions, 1), 'SessionId') AS SessionId,
GetRecordPropertyValue(GetArrayElement(MySource.context.custom.dimensions, 2), 'WebsiteVersion') AS WebsiteVersion,
GetRecordPropertyValue(GetArrayElement(MySource.context.custom.dimensions, 3), 'PageSection') AS PageSection,
GetRecordPropertyValue(GetArrayElement(MySource.context.custom.dimensions, 4), 'Category') AS Category,
GetRecordPropertyValue(GetArrayElement(MySource.context.custom.dimensions, 5), 'Page') AS Page
INTO
[outputstream]
FROM
[inputstream] MySource
答案 2 :(得分:2)
SQL中有哪些架构?你想要SQL中的所有单行吗? 尺寸为列?
今天可能无法做到这一点。但是,7月30日之后,Azure Stream Analytics中将有更多阵列/记录功能。
然后你就能做到这样的事情:
SELECT
CASE
WHEN GetArrayLength(A.context.custom.dimensions) > 0
THEN GetRecordPropertyValue(GetArrayElement(A.context.custom.dimensions, 0), 'CategoryAction')
ELSE ''
END AS CategoryAction
CASE
WHEN GetArrayLength(A.context.custom.dimensions) > 1
THEN GetRecordPropertyValue(GetArrayElement(A.context.custom.dimensions, 1), 'WebsiteVersion')
ELSE ''
END AS WebsiteVersion
CASE
WHEN GetArrayLength(A.context.custom.dimensions) > 2
THEN GetRecordPropertyValue(GetArrayElement(A.context.custom.dimensions, 2), 'PageSection')
ELSE ''
END AS PageSection
FROM input
如果您希望每个维度有单独的行,则可以使用CROSS APPLY运算符。
答案 3 :(得分:0)
Alex Raizman提出的一种非常方便的方法是对您要展平的字段进行一些汇总,并根据剩余的选择列表进行分组,假设
有些东西可以唯一地标识您的初始行(例如id)
SELECT
CategoryAction= MIN(CAST(GetRecordPropertyValue(d.arrayvalue, 'CategoryAction') AS
NVARCHAR(MAX))),
SessionId= min(CAST(GetRecordPropertyValue(d.arrayvalue, 'SessionId') AS
NVARCHAR(MAX))),
WebsiteVersion= MIN(CAST(GetRecordPropertyValue(d.arrayvalue, 'WebsiteVersion') AS
NVARCHAR(MAX))),
PageSection= MIN(CAST(GetRecordPropertyValue(d.arrayvalue, 'PageSection') AS
NVARCHAR(MAX))),
Category= MIN(CAST(GetRecordPropertyValue(d.arrayvalue, 'Category') AS
NVARCHAR(MAX))),
Page= MIN(CAST(GetRecordPropertyValue(d.arrayvalue, 'Page') AS NVARCHAR(MAX)))
INTO
[outputstream]
FROM [inputstream] MySource
CROSS APPLY GetArrayElements(MySource.[context].[custom].[dimensions]) d
GROUP BY System.Timestamp, MySource.id
我们还将System.Timestamp
分组,以创建Stream Analytics期望的一个时间窗口,以执行基于集合的操作,例如计数或聚合。
答案 4 :(得分:0)
尽管这个问题很古老。但这是实现自定义尺寸的单行的方式。随着自定义维度数量的增加,它可能会变得难看。
SELECT
A.internal.data.id,
eventFlat.ArrayValue.name as eventName,
A.context.operation.name as operation,
A.context.data.eventTime,
a1.company,
a2.userId,
a3.feature,
A.context.device,
A.context.location
FROM [YourInputAlias] A
OUTER APPLY GetArrayElements(A.event) eventFlat
LEFT JOIN (
SELECT
A1.internal.data.id as id,
customDimensionsFlat.ArrayValue.company
FROM [YourInputAlias] A1
OUTER APPLY GetArrayElements(A1.context.custom.dimensions) customDimensionsFlat
where customDimensionsFlat.ArrayValue.company IS NOT NULL
) a1 ON a.internal.data.id = a1.id AND datediff(day, a, a1) between 0 and 5
LEFT JOIN (
SELECT
A2.internal.data.id as id,
customDimensionsFlat.ArrayValue.userid
FROM [YourInputAlias] A2
OUTER APPLY GetArrayElements(A2.context.custom.dimensions) customDimensionsFlat
where customDimensionsFlat.ArrayValue.userid IS NOT NULL
) a2 ON a.internal.data.id = a2.id AND datediff(day, a, a2) between 0 and 5
LEFT JOIN (
SELECT
A3.internal.data.id as id,
customDimensionsFlat.ArrayValue.feature
FROM [YourInputAlias] A3
OUTER APPLY GetArrayElements(A3.context.custom.dimensions) customDimensionsFlat
where customDimensionsFlat.ArrayValue.feature IS NOT NULL
) a3 ON a.internal.data.id = a3.id AND datediff(day, a, a3) between 0 and 5