个人中心
文章发布
退出
作者热门文章
- html - 出于某种原因，IE8 对我的 Sass 文件中继承的 html5 CSS 不友好？
- JMeter 在响应断言中使用 span 标签的问题
- html - 在 :hover and :active? 上具有不同效果的 CSS 动画
- html - 相对于居中的 html 内容固定的 CSS 重复背景？
24
4
我创建了一个 Azure 流分析作业，它将从 EventHub 获取输入数据并写入 cosmosDB 和 Blob。
我有时会看到来自 eventHub 的数据是重复的，因此重复的数据将被写入 cosmosDB 和 Blob 存储。
下面显示了从 EventHub 到流分析的示例输入数据。
[
{
"idnum":"00011XXX01",
"basetime":0,
"time":189834,
"sig1":36.341587,
"sig2":
[
{
"sig3":"04XXX",
"id":1
},
{
"sig3":"000000",
"id":61
}
],
"signals":
[
{
"timestamp":190915,
"value":45,
},
{
"timestamp":190915,
"value":10.2,
},
{
"timestamp":190915,
}
],
"sig3TriggeredDateTime": {"dateTime":{"date":{"year":2019,"month":5,"day":16},"time":{"hour":4,"minute":56,"second":19,"nano":480389000}},"offset":{"totalSeconds":0}}
},
{
"idnum":"00086XXX02",
"basetime":0,
"time":189834,
"sig1":36.341587,
"sig2":
[
{
"sig3":"03XXX",
"id":1
},
{
"sig3":"04XXX",
"id":1
}
],
"signals":
[
{
"timestamp":190915,
"value":45,
},
{
"timestamp":190915,
"value":10.2,
},
{
"timestamp":190915,
},
{
"timestamp":190915,
"value":0,
}
],
"sig3TriggeredDateTime": {"dateTime":{"date":{"year":2019,"month":5,"day":16},"time":{"hour":4,"minute":56,"second":19,"nano":480389000}},"offset":{"totalSeconds":0}}
},
{
"idnum":"00086XXX02",
"basetime":0,
"time":189834,
"sig1":36.341587,
"sig2":
[
{
"sig3":"03XXX",
"id":1
},
{
"sig3":"04XXX",
"id":1
}
],
"signals":
[
{
"timestamp":190915,
"value":45,
},
{
"timestamp":190915,
"value":10.2,
},
{
"timestamp":190915,
},
{
"timestamp":190915,
"value":0,
}
],
"sig3TriggeredDateTime": {"dateTime":{"date":{"year":2019,"month":5,"day":16},"time":{"hour":4,"minute":56,"second":19,"nano":480389000}},"offset":{"totalSeconds":0}}
},{
"idnum":"00086XXX02",
"basetime":0,
"time":189834,
"sig1":36.341587,
"sig2":
[
{
"sig3":"03XXX",
"id":1
},
{
"sig3":"04XXX",
"id":1
}
],
"signals":
[
{
"timestamp":190915,
"value":45,
},
{
"timestamp":190915,
"value":10.2,
},
{
"timestamp":190915,
},
{
"timestamp":190915,
"value":0,
}
],
"sig3TriggeredDateTime": {"dateTime":{"date":{"year":2019,"month":5,"day":16},"time":{"hour":4,"minute":56,"second":19,"nano":480389000}},"offset":{"totalSeconds":0}}
},{
"idnum":"00086XXX02",
"basetime":0,
"time":189834,
"sig1":36.341587,
"sig2":
[
{
"sig3":"03XXX",
"id":1
},
{
"sig3":"04XXX",
"id":1
}
],
"signals":
[
{
"timestamp":190915,
"value":45,
},
{
"timestamp":190915,
"value":10.2,
},
{
"timestamp":190915,
},
{
"timestamp":190915,
"value":0,
}
],
"sig3TriggeredDateTime": {"dateTime":{"date":{"year":2019,"month":5,"day":16},"time":{"hour":4,"minute":56,"second":19,"nano":480389000}},"offset":{"totalSeconds":0}}
},
{
"idnum":"00026XXX03",
"basetime":0,
"time":189834,
"sig1":36.341587,
"sig2":
[
{
"sig3":"03XXX",
"id":1
},
{
"sig3":"000000",
"id":61
}
],
"signals":
[
{
"timestamp":190915,
"value":45,
},
{
"timestamp":190915,
"value":10.2,
}
],
"sig3TriggeredDateTime": {"dateTime":{"date":{"year":2019,"month":5,"day":16},"time":{"hour":4,"minute":56,"second":19,"nano":480389000}},"offset":{"totalSeconds":0}}
}
]
在上面的示例中，idnum: 00086XXX02 的事件重复了 3 次。
我正在进行以下分析并获得重复的输出。
temp AS (
SELECT
input.idnum AS IDNUM,
input.basetime AS BASETIME,
input.time AS TIME,
ROUND(input.sig1,5) AS SIG1,
flatArrayElement as SIG2,
udf.sgnlArrayMap(input.signals, input.basetime) AS SGNL //UDF to process the signals in input
FROM [input01] as input
CROSS APPLY GetArrayElements(input.sig2) AS flatArrayElement
WHERE GetArrayLength(input.sig2) >=1
),
SIGNALS AS (
SELECT * FROM temp T JOIN master M ON T.SIG2.ArrayValue.sig3 = M.sig3
)
--Insert SIG2 to COSMOS Container
SELECT
t.IDNUM,
t.BASETIME,
t.TIME,
t.SIG1,
t.SIG2.ArrayValue.id AS ID,
t.SIG2.ArrayValue.sig3 AS SIG3,
t.SGNL
INTO [CosmosTbl]
FROM SIGNALS PARTITION BY PartitionId
输出如下，其中 "idnum":"00086XXX02"存在重复事件
[
{
"idnum":"00011XXX01",
"basetime":0,
"time":189834,
"sig1":36.341587,
"sig2":
"sig3":"04XXX",
"id":1
"signals":
[
{
"timestamp":190915,
"value":45,
},
{
"timestamp":190915,
"value":10.2,
},
{
"timestamp":190915,
}
],
"sig3TriggeredDateTime": {"dateTime":{"date":{"year":2019,"month":5,"day":16},"time":{"hour":4,"minute":56,"second":19,"nano":480389000}},"offset":{"totalSeconds":0}}
},
{
"idnum":"00011XXX01",
"basetime":0,
"time":189834,
"sig1":36.341587,
"sig2":
"sig3":"000000",
"id":61
"signals":
[
{
"timestamp":190915,
"value":45,
},
{
"timestamp":190915,
"value":10.2,
},
{
"timestamp":190915,
}
],
"sig3TriggeredDateTime": {"dateTime":{"date":{"year":2019,"month":5,"day":16},"time":{"hour":4,"minute":56,"second":19,"nano":480389000}},"offset":{"totalSeconds":0}}
},
{
"idnum":"00086XXX02",
"basetime":0,
"time":189834,
"sig1":36.341587,
"sig2":
"sig3":"03XXX",
"id":1
"signals":
[
{
"timestamp":190915,
"value":45,
},
{
"timestamp":190915,
"value":10.2,
},
{
"timestamp":190915,
},
{
"timestamp":190915,
"value":0,
}
],
"sig3TriggeredDateTime": {"dateTime":{"date":{"year":2019,"month":5,"day":16},"time":{"hour":4,"minute":56,"second":19,"nano":480389000}},"offset":{"totalSeconds":0}}
},
{
"idnum":"00086XXX02",
"basetime":0,
"time":189834,
"sig1":36.341587,
"sig2":
"sig3":"04XXX",
"id":1
"signals":
[
{
"timestamp":190915,
"value":45,
},
{
"timestamp":190915,
"value":10.2,
},
{
"timestamp":190915,
},
{
"timestamp":190915,
"value":0,
}
],
"sig3TriggeredDateTime": {"dateTime":{"date":{"year":2019,"month":5,"day":16},"time":{"hour":4,"minute":56,"second":19,"nano":480389000}},"offset":{"totalSeconds":0}}
},
{
"idnum":"00086XXX02",
"basetime":0,
"time":189834,
"sig1":36.341587,
"sig2":
"sig3":"03XXX",
"id":1
"signals":
[
{
"timestamp":190915,
"value":45,
},
{
"timestamp":190915,
"value":10.2,
},
{
"timestamp":190915,
},
{
"timestamp":190915,
"value":0,
}
],
"sig3TriggeredDateTime": {"dateTime":{"date":{"year":2019,"month":5,"day":16},"time":{"hour":4,"minute":56,"second":19,"nano":480389000}},"offset":{"totalSeconds":0}}
},
{
"idnum":"00086XXX02",
"basetime":0,
"time":189834,
"sig1":36.341587,
"sig2":
"sig3":"04XXX",
"id":1
"signals":
[
{
"timestamp":190915,
"value":45,
},
{
"timestamp":190915,
"value":10.2,
},
{
"timestamp":190915,
},
{
"timestamp":190915,
"value":0,
}
],
"sig3TriggeredDateTime": {"dateTime":{"date":{"year":2019,"month":5,"day":16},"time":{"hour":4,"minute":56,"second":19,"nano":480389000}},"offset":{"totalSeconds":0}}
},
{
"idnum":"00086XXX02",
"basetime":0,
"time":189834,
"sig1":36.341587,
"sig2":
"sig3":"03XXX",
"id":1
"signals":
[
{
"timestamp":190915,
"value":45,
},
{
"timestamp":190915,
"value":10.2,
},
{
"timestamp":190915,
},
{
"timestamp":190915,
"value":0,
}
],
"sig3TriggeredDateTime": {"dateTime":{"date":{"year":2019,"month":5,"day":16},"time":{"hour":4,"minute":56,"second":19,"nano":480389000}},"offset":{"totalSeconds":0}}
},
{
"idnum":"00086XXX02",
"basetime":0,
"time":189834,
"sig1":36.341587,
"sig2":
"sig3":"04XXX",
"id":1
"signals":
[
{
"timestamp":190915,
"value":45,
},
{
"timestamp":190915,
"value":10.2,
},
{
"timestamp":190915,
},
{
"timestamp":190915,
"value":0,
}
],
"sig3TriggeredDateTime": {"dateTime":{"date":{"year":2019,"month":5,"day":16},"time":{"hour":4,"minute":56,"second":19,"nano":480389000}},"offset":{"totalSeconds":0}}
},
{
"idnum":"00086XXX02",
"basetime":0,
"time":189834,
"sig1":36.341587,
"sig2":
"sig3":"03XXX",
"id":1
"signals":
[
{
"timestamp":190915,
"value":45,
},
{
"timestamp":190915,
"value":10.2,
},
{
"timestamp":190915,
},
{
"timestamp":190915,
"value":0,
}
],
"sig3TriggeredDateTime": {"dateTime":{"date":{"year":2019,"month":5,"day":16},"time":{"hour":4,"minute":56,"second":19,"nano":480389000}},"offset":{"totalSeconds":0}}
},
{
"idnum":"00086XXX02",
"basetime":0,
"time":189834,
"sig1":36.341587,
"sig2":
"sig3":"04XXX",
"id":1
"signals":
[
{
"timestamp":190915,
"value":45,
},
{
"timestamp":190915,
"value":10.2,
},
{
"timestamp":190915,
},
{
"timestamp":190915,
"value":0,
}
],
"sig3TriggeredDateTime": {"dateTime":{"date":{"year":2019,"month":5,"day":16},"time":{"hour":4,"minute":56,"second":19,"nano":480389000}},"offset":{"totalSeconds":0}}
}
]
预期输出将是没有重复的事件(对于提供的示例，“idnum”不应该有重复的事件:“00086XXX02”)
在将数据写入存储之前，我想删除重复的事件。可以通过流分析来实现吗？
使用唯一ID创建cosmos DB集合是Cosmos端的一个解决方案，但是这里的表已经存在，我们可以从流分析端做任何事情吗？
最佳答案
我将你的测试sql简化如下:
with t AS (
SELECT
flatArrayElement as SIG2
FROM fromblob as input
CROSS APPLY GetArrayElements(input.sig2) AS flatArrayElement
WHERE GetArrayLength(input.sig2) >=1
)
SELECT
t.SIG2.ArrayValue.id AS ID,
t.SIG2.ArrayValue.sig3 AS SIG3
FROM t PARTITION BY PartitionId
由于 GetArrayElements() 方法，它会产生重复的数据，我认为这是正常的。数组被拆分，结果肯定应该重复。
根据我的经验和我的 findings (加上这个feedback)，ASA中没有明确的方法。我认为原因是ASA处理的是实时流数据，而不是像SQL表这样的静态数据。它无法判断每个时间单位内的数据是否重复。
结合最后一个cosmos db案例(How to find Duplicate documents in Cosmos DB)，我认为解决方案的关键点是找到根本原因:为什么事件中心处理重复的源数据。当然，你可以设置一个cosmos db触发器来防止重复的数据流入db。但我认为这不是一个有效的方法。
关于azure - 从 Azure 流分析中的 EventHub 删除重复项，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/59408124/
24
4
0
这个问题在这里已经有了答案: Why filter() after flatMap() is "not completely" lazy in Java streams? (8 个答案) 关闭 6
我正在创建一个应用程序来从 Instagram 收集数据。我正在寻找像 Twitter 流 API 这样的流 API，这样我就可以自动实时收集数据而无需发送请求。 Instagram 有类似的 API
我正在使用 Apache Commons 在 Google App Engine 中上传一个 .docx 文件，如此链接中所述 File upload servlet .上传时，我还想使用 Apach
我尝试使用 DynamoDB 流和 AWS 提供的 Java DynamoDB 流 Kinesis 适配器捕获 DynamoDB 表更改。我正在 Scala 应用程序中使用 AWS Java 开发工具
我目前有一个采用 H.264 编码的 IP 摄像机流式视频 (RTSP)。 我想使用 FFmpeg 将此 H.264 编码流转换为另一个 RTSP 流，但 MPEG-2 编码。我该怎么做？我应该使用哪
Redis 流是否受益于集群模式？假设您有 10 个流，它们是分布在整个集群中还是都分布在同一节点上？我计划使用 Redis 流来实现真正的高吞吐量(200 万条消息/秒)，所以我担心这种规模的 Re
这件事困扰了我一段时间。 所以我有一个 Product 类，它有一个 Image 列表(该列表可能为空)。 我想做 product.getImages().stream().filter(...) 但
是否可以使用 具有持久存储的 Redis 流 还是流仅限于内存数据？ 我知道可以将 Redis 与核心数据结构的持久存储一起使用，但我已经能够理解是否也可以使用 Redis 中的流的持久存储。 最佳答
我开始学习 Elixir 并遇到了一个我无法轻松解决的挑战。 我正在尝试创建一个函数，该函数接受一个 Enumerable.t 并返回另一个 Enumerable.t ，其中包含下 n 个项目。它与
我试图从 readLine 调用创建一个无限的字符串流: import java.io.{BufferedReader, InputStreamReader} val in = new Buffere
你能帮我使用 Java 8 流 API 编写以下代码吗？ SuperUser superUser = db.getSuperUser; for (final Client client : super
我正在尝试服用补品routeguide tutorial，并将客户端变成rocket服务器。我只是接受响应并将gRPC转换为字符串。 service RouteGuide { rpc GetF
流程代码可以是run here. 使用 flow，我有一个函数，它接受一个键值对对象并获取它的值 - 它获取的值应该是字符串、数字或 bool 值。 type ValueType = string
如果我有一个函数返回一个包含数据库信息的对象或一个空对象，如下所示: getThingFromDB: async function(id:string):Promise{ const from
我正在尝试使用javascript api和FB.ui将ogg音频文件发布到流中， 但是我不知道该怎么做。 这是我给FB.ui的电话: FB.ui( { method: '
我正在尝试删除工作区(或克隆它以使其看起来像父工作区，但我似乎两者都做不到)。但是，当我尝试时，我收到此消息:无法删除工作区 test_workspace，因为它有一个非空的默认组。 据我所知，这意味
可以使用 Stream|Map 来完成此操作，这样我就不需要将结果放入外部 HashMap 中，而是使用 .collect(Collectors.toMap(...)); 收集结果？ Map rep
当我们从集合列表中获取 Stream 时，幕后到底发生了什么？我发现很多博客都说Stream不存储任何数据。如果这是真的，请考虑代码片段: List list = new ArrayList(); l
我对流及其工作方式不熟悉，我正在尝试获取列表中添加的特定对象的出现次数。 我找到了一种使用Collections来做到这一点的方法。其过程如下: for (int i = 0; i p.conten
我希望将一个 map 列表转换为另一个分组的 map 列表。 所以我有以下 map 列表 - List [{ "accId":"1", "accName":"TestAcc1", "accNumber
我是一名优秀的程序员,十分优秀！