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Query - Execute

服务:: Time Series Insights

API 版本:: 2020-07-31

在结果页中执行时序查询 - 获取事件、获取序列或聚合序列。

POST https://{environmentFqdn}/timeseries/query?api-version=2020-07-31

具有可选参数:

POST https://{environmentFqdn}/timeseries/query?api-version=2020-07-31&storeType={storeType}

URI 参数

名称	在	必需	类型	说明
environmentFqdn	path	True	string	每个环境 FQDN，例如 10000000-0000-0000-0000-100000000109.env.timeseries.azure.com。可以从 Get Environments API、Azure 门户或 Azure 资源管理器的响应中获取此域名。
api-version	query	True	string	要用于客户端请求的 API 的版本。当前支持的版本为“2020-07-31”。
storeType	query		string	对于启用了暖存储的环境，可以在“WarmStore”或“ColdStore”上执行查询。查询中的此参数定义应在哪个商店执行查询。如果未定义，查询将在冷存储上执行。

请求头

名称	类型	说明
x-ms-continuation	string	在支持分页的调用中检索结果的下一页的结果的延续标记。若要获取第一页结果，请将 null 继续标记指定为参数值。如果返回了所有结果，则返回的继续标记为 null，并且没有下一页的结果。
x-ms-client-request-id	string	可选的客户端请求 ID。服务记录此值。允许服务跨服务跟踪作，并允许客户联系有关特定请求的支持人员。
x-ms-client-session-id	string	可选的客户端会话 ID。服务记录此值。允许服务跨服务跟踪一组相关作，并允许客户联系有关特定请求组的支持人员。

请求正文

名称	类型	说明
aggregateSeries	AggregateSeries	聚合序列查询。允许根据给定时序 ID 和搜索范围从事件计算聚合时序。
getEvents	GetEvents	获取事件查询。允许检索给定时序 ID 和搜索范围的原始事件。
getSeries	GetSeries	获取序列查询。允许从给定时序 ID 和搜索范围的事件中检索计算变量值的时序。

响应

名称	类型	说明
200 OK	QueryResultPage	成功查询。标头 x-ms-request-id: string
Other Status Codes	TsiError	意外错误。标头 x-ms-request-id: string

名称

类型

说明

200 OK

QueryResultPage

成功查询。

标头

x-ms-request-id: string

Other Status Codes

TsiError

意外错误。

标头

x-ms-request-id: string

安全性

azure_auth

Azure Active Directory OAuth2 流

类型: oauth2
流向: implicit
授权 URL: https://login.microsoftonline.com/common/oauth2/authorize

作用域

名称	说明
user_impersonation	模拟用户帐户

示例

ColdStoreQueryAggregateSeriesPage1

ColdStoreQueryAggregateSeriesPage2

ColdStoreQueryGetEventsPage1

ColdStoreQueryGetEventsPage2

ColdStoreQueryGetEventsPage3

ColdStoreQueryGetEventsPage4

ColdStoreQueryGetSeriesPage1

ColdStoreQueryGetSeriesPage2

ColdStoreQueryGetSeriesPage3

QueryAggregateSeriesPage1

QueryAggregateSeriesPage2

QueryAggregateSeriesWithCategoricalInterpolatedVariable

QueryAggregateSeriesWithCategoricalVariable

QueryAggregateSeriesWithSampleInterpolation

QueryGetEventsPage1

QueryGetEventsPage2

QueryGetEventsPage3

QueryGetEventsPage4

QueryGetEventsWithTakePage1

QueryGetEventsWithTakePage2

QueryGetSeriesPage1

QueryGetSeriesPage2

QueryGetSeriesPage3

QueryGetSeriesWithTakePage1

QueryGetSeriesWithTakePage2

WarmStoreQueryAggregateSeriesPage

WarmStoreQueryGetEventsPage1

WarmStoreQueryGetEventsPage2

WarmStoreQueryGetEventsPage3

WarmStoreQueryGetEventsPage4

WarmStoreQueryGetSeriesPage1

WarmStoreQueryGetSeriesPage2

WarmStoreQueryGetSeriesPage3

ColdStoreQueryAggregateSeriesPage1

示例请求

HTTP

POST https://10000000-0000-0000-0000-100000000109.env.timeseries.azure.com/timeseries/query?api-version=2020-07-31&storeType=coldstore

{
  "aggregateSeries": {
    "timeSeriesId": [
      "006dfc2d-0324-4937-998c-d16f3b4f1952",
      "T1"
    ],
    "searchSpan": {
      "from": "2016-08-01T00:00:00Z",
      "to": "2016-08-01T00:16:50Z"
    },
    "interval": "PT1M",
    "inlineVariables": {
      "Count": {
        "kind": "aggregate",
        "filter": null,
        "aggregation": {
          "tsx": "count()"
        }
      },
      "MinTemperature": {
        "kind": "numeric",
        "value": {
          "tsx": "$event.Temperature"
        },
        "filter": null,
        "aggregation": {
          "tsx": "min($value)"
        }
      },
      "MaxTemperature": {
        "kind": "numeric",
        "value": {
          "tsx": "$event.Temperature"
        },
        "filter": null,
        "aggregation": {
          "tsx": "max($value)"
        }
      }
    },
    "projectedVariables": [
      "Count",
      "MinTemperature",
      "MaxTemperature"
    ]
  }
}

示例响应

状态代码:: 200

{
  "progress": 50,
  "continuationToken": "aXsic2tpcCI6MTAwMCwidGFrZSI6MTAwMH0="
}

ColdStoreQueryAggregateSeriesPage2

示例请求

HTTP

POST https://10000000-0000-0000-0000-100000000109.env.timeseries.azure.com/timeseries/query?api-version=2020-07-31&storeType=coldstore

{
  "aggregateSeries": {
    "timeSeriesId": [
      "006dfc2d-0324-4937-998c-d16f3b4f1952",
      "T1"
    ],
    "searchSpan": {
      "from": "2016-08-01T00:00:00Z",
      "to": "2016-08-01T00:16:50Z"
    },
    "interval": "PT1M",
    "inlineVariables": {
      "Count": {
        "kind": "aggregate",
        "filter": null,
        "aggregation": {
          "tsx": "count()"
        }
      },
      "MinTemperature": {
        "kind": "numeric",
        "value": {
          "tsx": "$event.Temperature"
        },
        "filter": null,
        "aggregation": {
          "tsx": "min($value)"
        }
      },
      "MaxTemperature": {
        "kind": "numeric",
        "value": {
          "tsx": "$event.Temperature"
        },
        "filter": null,
        "aggregation": {
          "tsx": "max($value)"
        }
      }
    },
    "projectedVariables": [
      "Count",
      "MinTemperature",
      "MaxTemperature"
    ]
  }
}

示例响应

状态代码:: 200

{
  "timestamps": [
    "2016-08-01T00:00:00Z",
    "2016-08-01T00:01:00Z",
    "2016-08-01T00:02:00Z",
    "2016-08-01T00:03:00Z",
    "2016-08-01T00:04:00Z",
    "2016-08-01T00:05:00Z",
    "2016-08-01T00:06:00Z",
    "2016-08-01T00:07:00Z",
    "2016-08-01T00:08:00Z",
    "2016-08-01T00:09:00Z",
    "2016-08-01T00:10:00Z"
  ],
  "properties": [
    {
      "name": "Count",
      "type": "Long",
      "values": [
        50,
        60,
        60,
        60,
        60,
        60,
        60,
        60,
        60,
        60,
        null
      ]
    },
    {
      "name": "AverageTemperature",
      "type": "Double",
      "values": [
        71.25,
        85,
        82.5,
        80,
        89.16666666666667,
        75,
        90,
        75.83333333333333,
        85,
        82.5,
        null
      ]
    },
    {
      "name": "MinTemperature",
      "type": "Double",
      "values": [
        65.125,
        77.625,
        65.125,
        72.625,
        65.125,
        67.625,
        82.625,
        65.125,
        77.625,
        65.125,
        null
      ]
    },
    {
      "name": "MaxTemperature",
      "type": "Double",
      "values": [
        77.375,
        92.375,
        99.875,
        87.375,
        99.875,
        82.375,
        97.375,
        99.875,
        92.375,
        99.875,
        null
      ]
    }
  ],
  "progress": 100
}

ColdStoreQueryGetEventsPage1

示例请求

HTTP

POST https://10000000-0000-0000-0000-100000000109.env.timeseries.azure.com/timeseries/query?api-version=2020-07-31&storeType=coldstore

{
  "getEvents": {
    "timeSeriesId": [
      "006dfc2d-0324-4937-998c-d16f3b4f1952",
      "T1"
    ],
    "searchSpan": {
      "from": "2016-08-01T00:00:00Z",
      "to": "2016-08-01T00:16:50Z"
    },
    "filter": {
      "tsx": "($event.Value.Double != null) OR ($event.Status.String = 'Good')"
    },
    "projectedProperties": [
      {
        "name": "Building",
        "type": "String"
      },
      {
        "name": "Temperature",
        "type": "Double"
      }
    ]
  }
}

示例响应

状态代码:: 200

{
  "progress": 50,
  "continuationToken": "aXsic2tpcCI6MTAwMCwidGFrZSI6MTAwMH0="
}

ColdStoreQueryGetEventsPage2

示例请求

HTTP

POST https://10000000-0000-0000-0000-100000000109.env.timeseries.azure.com/timeseries/query?api-version=2020-07-31&storeType=coldstore

{
  "getEvents": {
    "timeSeriesId": [
      "006dfc2d-0324-4937-998c-d16f3b4f1952",
      "T1"
    ],
    "searchSpan": {
      "from": "2016-08-01T00:00:00Z",
      "to": "2016-08-01T00:16:50Z"
    },
    "filter": {
      "tsx": "($event.Value.Double != null) OR ($event.Status.String = 'Good')"
    },
    "projectedProperties": [
      {
        "name": "Building",
        "type": "String"
      },
      {
        "name": "Temperature",
        "type": "Double"
      }
    ]
  }
}

示例响应

状态代码:: 200

{
  "timestamps": [
    "2016-08-01T00:00:10Z",
    "2016-08-01T00:00:11Z",
    "2016-08-01T00:00:12Z",
    "2016-08-01T00:00:13Z",
    "2016-08-01T00:00:14Z",
    "2016-08-01T00:00:15Z",
    "2016-08-01T00:00:16Z",
    "2016-08-01T00:00:17Z",
    "2016-08-01T00:00:18Z",
    "2016-08-01T00:00:19Z"
  ],
  "properties": [
    {
      "name": "Building",
      "type": "String",
      "values": [
        "Millenium",
        "Millenium",
        "Millenium",
        "Millenium",
        "Millenium",
        "Millenium",
        "Millenium",
        "Millenium",
        "Millenium",
        "Millenium"
      ]
    },
    {
      "name": "Temperature",
      "type": "Double",
      "values": [
        65.125,
        65.375,
        65.625,
        65.875,
        66.125,
        66.375,
        66.625,
        66.875,
        67.125,
        67.375
      ]
    }
  ],
  "progress": 50,
  "continuationToken": "aXsic2tpcCI6MTAxYZwidGFrZSI6MTAwMH0="
}

ColdStoreQueryGetEventsPage3

示例请求

HTTP

POST https://10000000-0000-0000-0000-100000000109.env.timeseries.azure.com/timeseries/query?api-version=2020-07-31&storeType=coldstore

{
  "getEvents": {
    "timeSeriesId": [
      "006dfc2d-0324-4937-998c-d16f3b4f1952",
      "T1"
    ],
    "searchSpan": {
      "from": "2016-08-01T00:00:00Z",
      "to": "2016-08-01T00:16:50Z"
    },
    "filter": {
      "tsx": "($event.Value.Double != null) OR ($event.Status.String = 'Good')"
    },
    "projectedProperties": [
      {
        "name": "Building",
        "type": "String"
      },
      {
        "name": "Temperature",
        "type": "Double"
      }
    ]
  }
}

示例响应

状态代码:: 200

{
  "timestamps": [
    "2016-08-01T00:00:20Z"
  ],
  "properties": [
    {
      "name": "Building",
      "type": "String",
      "values": [
        "Millenium"
      ]
    },
    {
      "name": "Temperature",
      "type": "Double",
      "values": [
        67.575
      ]
    }
  ],
  "progress": 50,
  "continuationToken": "aXsic2tpcCI6MTAbCDewidGFrZSI6MTAwMH0="
}

ColdStoreQueryGetEventsPage4

示例请求

HTTP

POST https://10000000-0000-0000-0000-100000000109.env.timeseries.azure.com/timeseries/query?api-version=2020-07-31&storeType=coldstore

{
  "getEvents": {
    "timeSeriesId": [
      "006dfc2d-0324-4937-998c-d16f3b4f1952",
      "T1"
    ],
    "searchSpan": {
      "from": "2016-08-01T00:00:00Z",
      "to": "2016-08-01T00:16:50Z"
    },
    "filter": {
      "tsx": "($event.Value.Double != null) OR ($event.Status.String = 'Good')"
    },
    "projectedProperties": [
      {
        "name": "Building",
        "type": "String"
      },
      {
        "name": "Temperature",
        "type": "Double"
      }
    ]
  }
}

示例响应

状态代码:: 200

{
  "timestamps": [],
  "properties": [],
  "progress": 100
}

ColdStoreQueryGetSeriesPage1

示例请求

HTTP

POST https://10000000-0000-0000-0000-100000000109.env.timeseries.azure.com/timeseries/query?api-version=2020-07-31&storeType=coldstore

{
  "getSeries": {
    "timeSeriesId": [
      "006dfc2d-0324-4937-998c-d16f3b4f1952",
      "T1"
    ],
    "searchSpan": {
      "from": "2016-08-01T00:00:00Z",
      "to": "2016-08-01T00:16:50Z"
    },
    "filter": null,
    "inlineVariables": {
      "temperatures": {
        "kind": "numeric",
        "value": {
          "tsx": "$event.Temperature"
        },
        "filter": null,
        "aggregation": {
          "tsx": "avg($value)"
        }
      }
    },
    "projectedVariables": [
      "temperatures"
    ]
  }
}

示例响应

状态代码:: 200

{
  "progress": 50,
  "continuationToken": "aXsic2tpcCI6MTAwMCwidGFrZSI6MTAwMH0="
}

ColdStoreQueryGetSeriesPage2

示例请求

HTTP

POST https://10000000-0000-0000-0000-100000000109.env.timeseries.azure.com/timeseries/query?api-version=2020-07-31&storeType=coldstore

{
  "getSeries": {
    "timeSeriesId": [
      "006dfc2d-0324-4937-998c-d16f3b4f1952",
      "T1"
    ],
    "searchSpan": {
      "from": "2016-08-01T00:00:00Z",
      "to": "2016-08-01T00:16:50Z"
    },
    "filter": null,
    "inlineVariables": {
      "temperatures": {
        "kind": "numeric",
        "value": {
          "tsx": "$event.Temperature"
        },
        "filter": null,
        "aggregation": {
          "tsx": "avg($value)"
        }
      }
    },
    "projectedVariables": [
      "temperatures"
    ]
  }
}

示例响应

状态代码:: 200

{
  "timestamps": [
    "2016-08-01T00:00:10Z",
    "2016-08-01T00:00:11Z",
    "2016-08-01T00:00:12Z",
    "2016-08-01T00:00:13Z",
    "2016-08-01T00:00:14Z",
    "2016-08-01T00:00:15Z",
    "2016-08-01T00:00:16Z",
    "2016-08-01T00:00:17Z",
    "2016-08-01T00:00:18Z",
    "2016-08-01T00:00:19Z",
    "2016-08-01T00:00:20Z"
  ],
  "properties": [
    {
      "name": "temperatures",
      "type": "Double",
      "values": [
        65.125,
        65.375,
        65.625,
        65.875,
        66.125,
        66.375,
        66.625,
        66.875,
        67.125,
        67.375,
        67.625
      ]
    }
  ],
  "progress": 50,
  "continuationToken": "aXsic2tpcCI6MTAxYZwidGFrZSI6MTAwMH0="
}

ColdStoreQueryGetSeriesPage3

示例请求

HTTP

POST https://10000000-0000-0000-0000-100000000109.env.timeseries.azure.com/timeseries/query?api-version=2020-07-31&storeType=coldstore

{
  "getSeries": {
    "timeSeriesId": [
      "006dfc2d-0324-4937-998c-d16f3b4f1952",
      "T1"
    ],
    "searchSpan": {
      "from": "2016-08-01T00:00:00Z",
      "to": "2016-08-01T00:16:50Z"
    },
    "filter": null,
    "inlineVariables": {
      "temperatures": {
        "kind": "numeric",
        "value": {
          "tsx": "$event.Temperature"
        },
        "filter": null,
        "aggregation": {
          "tsx": "avg($value)"
        }
      }
    },
    "projectedVariables": [
      "temperatures"
    ]
  }
}

示例响应

状态代码:: 200

{
  "timestamps": [
    "2016-08-01T00:00:21Z"
  ],
  "properties": [
    {
      "name": "temperatures",
      "type": "Double",
      "values": [
        67.825
      ]
    }
  ],
  "progress": 100
}

QueryAggregateSeriesPage1

示例请求

HTTP

POST https://10000000-0000-0000-0000-100000000109.env.timeseries.azure.com/timeseries/query?api-version=2020-07-31

{
  "aggregateSeries": {
    "timeSeriesId": [
      "006dfc2d-0324-4937-998c-d16f3b4f1952",
      "T1"
    ],
    "searchSpan": {
      "from": "2016-08-01T00:00:00Z",
      "to": "2016-08-01T00:16:50Z"
    },
    "interval": "PT1M",
    "inlineVariables": {
      "Count": {
        "kind": "aggregate",
        "filter": null,
        "aggregation": {
          "tsx": "count()"
        }
      },
      "MinTemperature": {
        "kind": "numeric",
        "value": {
          "tsx": "$event.Temperature"
        },
        "filter": null,
        "aggregation": {
          "tsx": "min($value)"
        }
      },
      "MaxTemperature": {
        "kind": "numeric",
        "value": {
          "tsx": "$event.Temperature"
        },
        "filter": null,
        "aggregation": {
          "tsx": "max($value)"
        }
      }
    },
    "projectedVariables": [
      "Count",
      "MinTemperature",
      "MaxTemperature"
    ]
  }
}

示例响应

状态代码:: 200

{
  "progress": 50,
  "continuationToken": "aXsic2tpcCI6MTAwMCwidGFrZSI6MTAwMH0="
}

QueryAggregateSeriesPage2

示例请求

HTTP

POST https://10000000-0000-0000-0000-100000000109.env.timeseries.azure.com/timeseries/query?api-version=2020-07-31

{
  "aggregateSeries": {
    "timeSeriesId": [
      "006dfc2d-0324-4937-998c-d16f3b4f1952",
      "T1"
    ],
    "searchSpan": {
      "from": "2016-08-01T00:00:00Z",
      "to": "2016-08-01T00:16:50Z"
    },
    "interval": "PT1M",
    "inlineVariables": {
      "Count": {
        "kind": "aggregate",
        "filter": null,
        "aggregation": {
          "tsx": "count()"
        }
      },
      "MinTemperature": {
        "kind": "numeric",
        "value": {
          "tsx": "$event.Temperature"
        },
        "filter": null,
        "aggregation": {
          "tsx": "min($value)"
        }
      },
      "MaxTemperature": {
        "kind": "numeric",
        "value": {
          "tsx": "$event.Temperature"
        },
        "filter": null,
        "aggregation": {
          "tsx": "max($value)"
        }
      }
    },
    "projectedVariables": [
      "Count",
      "MinTemperature",
      "MaxTemperature"
    ]
  }
}

示例响应

状态代码:: 200

{
  "timestamps": [
    "2016-08-01T00:00:00Z",
    "2016-08-01T00:01:00Z",
    "2016-08-01T00:02:00Z",
    "2016-08-01T00:03:00Z",
    "2016-08-01T00:04:00Z",
    "2016-08-01T00:05:00Z",
    "2016-08-01T00:06:00Z",
    "2016-08-01T00:07:00Z",
    "2016-08-01T00:08:00Z",
    "2016-08-01T00:09:00Z",
    "2016-08-01T00:10:00Z"
  ],
  "properties": [
    {
      "name": "Count",
      "type": "Long",
      "values": [
        50,
        60,
        60,
        60,
        60,
        60,
        60,
        60,
        60,
        60,
        null
      ]
    },
    {
      "name": "AverageTemperature",
      "type": "Double",
      "values": [
        71.25,
        85,
        82.5,
        80,
        89.16666666666667,
        75,
        90,
        75.83333333333333,
        85,
        82.5,
        null
      ]
    },
    {
      "name": "MinTemperature",
      "type": "Double",
      "values": [
        65.125,
        77.625,
        65.125,
        72.625,
        65.125,
        67.625,
        82.625,
        65.125,
        77.625,
        65.125,
        null
      ]
    },
    {
      "name": "MaxTemperature",
      "type": "Double",
      "values": [
        77.375,
        92.375,
        99.875,
        87.375,
        99.875,
        82.375,
        97.375,
        99.875,
        92.375,
        99.875,
        null
      ]
    }
  ],
  "progress": 100
}

QueryAggregateSeriesWithCategoricalInterpolatedVariable

示例请求

HTTP

POST https://10000000-0000-0000-0000-100000000109.env.timeseries.azure.com/timeseries/query?api-version=2020-07-31

{
  "aggregateSeries": {
    "searchSpan": {
      "from": "2019-10-10T23:41:04.021Z",
      "to": "2019-10-10T23:42:22.846Z"
    },
    "timeSeriesId": [
      "Sensor_58"
    ],
    "interval": "PT2S",
    "inlineVariables": {
      "Status_String": {
        "kind": "categorical",
        "value": {
          "tsx": "$event.[Status].String"
        },
        "interpolation": {
          "kind": "Step",
          "boundary": {
            "span": "PT5S"
          }
        },
        "categories": [
          {
            "label": "Good",
            "values": [
              "Good",
              "Very Good",
              "Excellent"
            ]
          },
          {
            "label": "Bad",
            "values": [
              "Bad",
              "OK"
            ]
          },
          {
            "label": "Other",
            "values": [
              "Other"
            ]
          }
        ],
        "defaultCategory": {
          "label": "Unknown"
        }
      },
      "Status_Long": {
        "kind": "categorical",
        "value": {
          "tsx": "tolong($event.[Status].Double)"
        },
        "interpolation": {
          "kind": "Step",
          "boundary": {
            "span": "PT5S"
          }
        },
        "categories": [
          {
            "label": "Good",
            "values": [
              0,
              1,
              2
            ]
          },
          {
            "label": "Bad",
            "values": [
              3,
              4
            ]
          },
          {
            "label": "Other",
            "values": [
              5
            ]
          }
        ],
        "defaultCategory": {
          "label": "Unknown"
        }
      }
    },
    "projectedVariables": [
      "Status_String",
      "Status_Long"
    ]
  }
}

示例响应

状态代码:: 200

{
  "timestamps": [
    "2019-10-10T23:41:04Z",
    "2019-10-10T23:41:06Z",
    "2019-10-10T23:41:08Z",
    "2019-10-10T23:41:10Z",
    "2019-10-10T23:41:12Z",
    "2019-10-10T23:41:14Z",
    "2019-10-10T23:41:16Z",
    "2019-10-10T23:41:18Z",
    "2019-10-10T23:41:20Z",
    "2019-10-10T23:41:22Z"
  ],
  "properties": [
    {
      "values": [
        0.203,
        0.141,
        0.268,
        0.398,
        0.402,
        0.047,
        0.1245,
        0.75,
        0.206,
        0.2635
      ],
      "name": "Status_String[Good]",
      "type": "Double"
    },
    {
      "values": [
        0.266,
        0.1955,
        0.242,
        0.148,
        0.25,
        0.055,
        0.6295,
        0.109,
        0.41,
        0.2125
      ],
      "name": "Status_String[Bad]",
      "type": "Double"
    },
    {
      "values": [
        0.5205,
        0.6635,
        0.49,
        0.454,
        0.348,
        0.898,
        0.246,
        0.141,
        0.384,
        0.524
      ],
      "name": "Status_String[Other]",
      "type": "Double"
    },
    {
      "values": [
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0
      ],
      "name": "Status_String[Unknown]",
      "type": "Double"
    },
    {
      "values": [
        0.203,
        0.141,
        0.268,
        0.398,
        0.402,
        0.047,
        0.1245,
        0.75,
        0.206,
        0.2635
      ],
      "name": "Status_Long[Good]",
      "type": "Double"
    },
    {
      "values": [
        0.266,
        0.1955,
        0.242,
        0.148,
        0.25,
        0.055,
        0.6295,
        0.109,
        0.41,
        0.2125
      ],
      "name": "Status_Long[Bad]",
      "type": "Double"
    },
    {
      "values": [
        0.5205,
        0.6635,
        0.49,
        0.454,
        0.348,
        0.898,
        0.246,
        0.141,
        0.384,
        0.524
      ],
      "name": "Status_Long[Other]",
      "type": "Double"
    },
    {
      "values": [
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0
      ],
      "name": "Status_Long[Unknown]",
      "type": "Double"
    }
  ],
  "progress": 100
}

QueryAggregateSeriesWithCategoricalVariable

示例请求

HTTP

POST https://10000000-0000-0000-0000-100000000109.env.timeseries.azure.com/timeseries/query?api-version=2020-07-31

{
  "aggregateSeries": {
    "searchSpan": {
      "from": "2019-10-10T23:42:00.000Z",
      "to": "2019-10-10T23:42:20.000Z"
    },
    "timeSeriesId": [
      "Sensor_58"
    ],
    "interval": "PT2S",
    "inlineVariables": {
      "Status_String": {
        "kind": "categorical",
        "value": {
          "tsx": "$event.[Status].String"
        },
        "categories": [
          {
            "label": "Good",
            "values": [
              "Good",
              "Very Good",
              "Excellent"
            ]
          },
          {
            "label": "Bad",
            "values": [
              "Bad",
              "OK"
            ]
          },
          {
            "label": "Other",
            "values": [
              "Other"
            ]
          }
        ],
        "defaultCategory": {
          "label": "Unknown"
        }
      },
      "Status_Long": {
        "kind": "categorical",
        "value": {
          "tsx": "tolong($event.[Status].Double)"
        },
        "categories": [
          {
            "label": "Good",
            "values": [
              0,
              1,
              2
            ]
          },
          {
            "label": "Bad",
            "values": [
              3,
              4
            ]
          },
          {
            "label": "Other",
            "values": [
              5
            ]
          }
        ],
        "defaultCategory": {
          "label": "Unknown"
        }
      }
    },
    "projectedVariables": [
      "Status_String",
      "Status_Long"
    ]
  }
}

示例响应

状态代码:: 200

{
  "timestamps": [
    "2019-10-10T23:42:00Z",
    "2019-10-10T23:42:02Z",
    "2019-10-10T23:42:04Z",
    "2019-10-10T23:42:06Z",
    "2019-10-10T23:42:08Z",
    "2019-10-10T23:42:10Z",
    "2019-10-10T23:42:12Z",
    "2019-10-10T23:42:14Z",
    "2019-10-10T23:42:16Z",
    "2019-10-10T23:42:18Z"
  ],
  "properties": [
    {
      "values": [
        5,
        8,
        4,
        6,
        9,
        8,
        3,
        6,
        5,
        8
      ],
      "name": "Status_String[Good]",
      "type": "Long"
    },
    {
      "values": [
        4,
        3,
        3,
        5,
        5,
        3,
        9,
        7,
        7,
        7
      ],
      "name": "Status_String[Bad]",
      "type": "Long"
    },
    {
      "values": [
        11,
        9,
        13,
        9,
        6,
        9,
        8,
        7,
        8,
        5
      ],
      "name": "Status_String[Other]",
      "type": "Long"
    },
    {
      "values": [
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0
      ],
      "name": "Status_String[Unknown]",
      "type": "Long"
    },
    {
      "values": [
        5,
        8,
        4,
        6,
        9,
        8,
        3,
        6,
        5,
        8
      ],
      "name": "Status_Long[Good]",
      "type": "Long"
    },
    {
      "values": [
        4,
        3,
        3,
        5,
        5,
        3,
        9,
        7,
        7,
        7
      ],
      "name": "Status_Long[Bad]",
      "type": "Long"
    },
    {
      "values": [
        11,
        9,
        13,
        9,
        6,
        9,
        8,
        7,
        8,
        5
      ],
      "name": "Status_Long[Other]",
      "type": "Long"
    },
    {
      "values": [
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0,
        0
      ],
      "name": "Status_Long[Unknown]",
      "type": "Long"
    }
  ],
  "progress": 100
}

QueryAggregateSeriesWithSampleInterpolation

示例请求

HTTP

POST https://10000000-0000-0000-0000-100000000109.env.timeseries.azure.com/timeseries/query?api-version=2020-07-31

{
  "aggregateSeries": {
    "timeSeriesId": [
      "006dfc2d-0324-4937-998c-d16f3b4f1952",
      "T1"
    ],
    "searchSpan": {
      "from": "2016-08-01T00:00:00Z",
      "to": "2016-08-01T00:16:50Z"
    },
    "interval": "PT1M",
    "inlineVariables": {
      "LinearSampleInterpolation": {
        "kind": "numeric",
        "value": {
          "tsx": "$event.Temperature"
        },
        "filter": null,
        "interpolation": {
          "kind": "Linear",
          "boundary": {
            "span": "P1D"
          }
        },
        "aggregation": {
          "tsx": "left($value)"
        }
      },
      "StepSampleInterpolation": {
        "kind": "numeric",
        "value": {
          "tsx": "$event.Temperature"
        },
        "filter": null,
        "interpolation": {
          "kind": "Step",
          "boundary": {
            "span": "P1D"
          }
        },
        "aggregation": {
          "tsx": "left($value)"
        }
      }
    },
    "projectedVariables": [
      "LinearSampleInterpolation",
      "StepSampleInterpolation"
    ]
  }
}

示例响应

状态代码:: 200

{
  "timestamps": [
    "2016-08-01T00:00:00Z",
    "2016-08-01T00:01:00Z",
    "2016-08-01T00:02:00Z",
    "2016-08-01T00:03:00Z",
    "2016-08-01T00:04:00Z",
    "2016-08-01T00:05:00Z",
    "2016-08-01T00:06:00Z",
    "2016-08-01T00:07:00Z",
    "2016-08-01T00:08:00Z",
    "2016-08-01T00:09:00Z",
    "2016-08-01T00:10:00Z"
  ],
  "properties": [
    {
      "name": "LinearSampleInterpolation",
      "type": "Double",
      "values": [
        50,
        60,
        60,
        60,
        60,
        60,
        60,
        60,
        60,
        60,
        62
      ]
    },
    {
      "name": "StepSampleInterpolation",
      "type": "Double",
      "values": [
        71.25,
        85,
        82.5,
        80,
        89.16666666666667,
        75,
        90,
        75.83333333333333,
        85,
        82.5,
        84
      ]
    }
  ],
  "progress": 100
}

QueryGetEventsPage1

示例请求

HTTP

POST https://10000000-0000-0000-0000-100000000109.env.timeseries.azure.com/timeseries/query?api-version=2020-07-31

{
  "getEvents": {
    "timeSeriesId": [
      "006dfc2d-0324-4937-998c-d16f3b4f1952",
      "T1"
    ],
    "searchSpan": {
      "from": "2016-08-01T00:00:00Z",
      "to": "2016-08-01T00:16:50Z"
    },
    "filter": {
      "tsx": "($event.Value.Double != null) OR ($event.Status.String = 'Good')"
    },
    "projectedProperties": [
      {
        "name": "Building",
        "type": "String"
      },
      {
        "name": "Temperature",
        "type": "Double"
      }
    ]
  }
}

示例响应

状态代码:: 200

{
  "progress": 50,
  "continuationToken": "aXsic2tpcCI6MTAwMCwidGFrZSI6MTAwMH0="
}

QueryGetEventsPage2

示例请求

HTTP

POST https://10000000-0000-0000-0000-100000000109.env.timeseries.azure.com/timeseries/query?api-version=2020-07-31

{
  "getEvents": {
    "timeSeriesId": [
      "006dfc2d-0324-4937-998c-d16f3b4f1952",
      "T1"
    ],
    "searchSpan": {
      "from": "2016-08-01T00:00:00Z",
      "to": "2016-08-01T00:16:50Z"
    },
    "filter": {
      "tsx": "($event.Value.Double != null) OR ($event.Status.String = 'Good')"
    },
    "projectedProperties": [
      {
        "name": "Building",
        "type": "String"
      },
      {
        "name": "Temperature",
        "type": "Double"
      }
    ]
  }
}

示例响应

状态代码:: 200

{
  "timestamps": [
    "2016-08-01T00:00:10Z",
    "2016-08-01T00:00:11Z",
    "2016-08-01T00:00:12Z",
    "2016-08-01T00:00:13Z",
    "2016-08-01T00:00:14Z",
    "2016-08-01T00:00:15Z",
    "2016-08-01T00:00:16Z",
    "2016-08-01T00:00:17Z",
    "2016-08-01T00:00:18Z",
    "2016-08-01T00:00:19Z"
  ],
  "properties": [
    {
      "name": "Building",
      "type": "String",
      "values": [
        "Millenium",
        "Millenium",
        "Millenium",
        "Millenium",
        "Millenium",
        "Millenium",
        "Millenium",
        "Millenium",
        "Millenium",
        "Millenium"
      ]
    },
    {
      "name": "Temperature",
      "type": "Double",
      "values": [
        65.125,
        65.375,
        65.625,
        65.875,
        66.125,
        66.375,
        66.625,
        66.875,
        67.125,
        67.375
      ]
    }
  ],
  "progress": 50,
  "continuationToken": "aXsic2tpcCI6MTAxYZwidGFrZSI6MTAwMH0="
}

QueryGetEventsPage3

示例请求

HTTP

POST https://10000000-0000-0000-0000-100000000109.env.timeseries.azure.com/timeseries/query?api-version=2020-07-31

{
  "getEvents": {
    "timeSeriesId": [
      "006dfc2d-0324-4937-998c-d16f3b4f1952",
      "T1"
    ],
    "searchSpan": {
      "from": "2016-08-01T00:00:00Z",
      "to": "2016-08-01T00:16:50Z"
    },
    "filter": {
      "tsx": "($event.Value.Double != null) OR ($event.Status.String = 'Good')"
    },
    "projectedProperties": [
      {
        "name": "Building",
        "type": "String"
      },
      {
        "name": "Temperature",
        "type": "Double"
      }
    ]
  }
}

示例响应

状态代码:: 200

{
  "timestamps": [
    "2016-08-01T00:00:20Z"
  ],
  "properties": [
    {
      "name": "Building",
      "type": "String",
      "values": [
        "Millenium"
      ]
    },
    {
      "name": "Temperature",
      "type": "Double",
      "values": [
        67.575
      ]
    }
  ],
  "progress": 50,
  "continuationToken": "aXsic2tpcCI6MTAbCDewidGFrZSI6MTAwMH0="
}

QueryGetEventsPage4

示例请求

HTTP

POST https://10000000-0000-0000-0000-100000000109.env.timeseries.azure.com/timeseries/query?api-version=2020-07-31

{
  "getEvents": {
    "timeSeriesId": [
      "006dfc2d-0324-4937-998c-d16f3b4f1952",
      "T1"
    ],
    "searchSpan": {
      "from": "2016-08-01T00:00:00Z",
      "to": "2016-08-01T00:16:50Z"
    },
    "filter": {
      "tsx": "($event.Value.Double != null) OR ($event.Status.String = 'Good')"
    },
    "projectedProperties": [
      {
        "name": "Building",
        "type": "String"
      },
      {
        "name": "Temperature",
        "type": "Double"
      }
    ]
  }
}

示例响应

状态代码:: 200

{
  "timestamps": [],
  "properties": [],
  "progress": 100
}

QueryGetEventsWithTakePage1

示例请求

HTTP

POST https://10000000-0000-0000-0000-100000000109.env.timeseries.azure.com/timeseries/query?api-version=2020-07-31

{
  "getEvents": {
    "timeSeriesId": [
      "006dfc2d-0324-4937-998c-d16f3b4f1952",
      "T1"
    ],
    "searchSpan": {
      "from": "2016-08-01T00:00:00Z",
      "to": "2016-08-01T00:16:50Z"
    },
    "filter": {
      "tsx": "($event.Value.Double != null) OR ($event.Status.String = 'Good')"
    },
    "projectedProperties": [
      {
        "name": "Building",
        "type": "String"
      },
      {
        "name": "Temperature",
        "type": "Double"
      }
    ],
    "take": 10
  }
}

示例响应

状态代码:: 200

{
  "progress": 50,
  "continuationToken": "aXsic2tpcCI6MTAwMCwidGFrZSI6MTAwMH0="
}

QueryGetEventsWithTakePage2

示例请求

HTTP

POST https://10000000-0000-0000-0000-100000000109.env.timeseries.azure.com/timeseries/query?api-version=2020-07-31

{
  "getEvents": {
    "timeSeriesId": [
      "006dfc2d-0324-4937-998c-d16f3b4f1952",
      "T1"
    ],
    "searchSpan": {
      "from": "2016-08-01T00:00:00Z",
      "to": "2016-08-01T00:16:50Z"
    },
    "filter": {
      "tsx": "($event.Value.Double != null) OR ($event.Status.String = 'Good')"
    },
    "projectedProperties": [
      {
        "name": "Building",
        "type": "String"
      },
      {
        "name": "Temperature",
        "type": "Double"
      }
    ],
    "take": 10
  }
}

示例响应

状态代码:: 200

{
  "timestamps": [
    "2016-08-01T00:00:10Z",
    "2016-08-01T00:00:11Z",
    "2016-08-01T00:00:12Z",
    "2016-08-01T00:00:13Z",
    "2016-08-01T00:00:14Z",
    "2016-08-01T00:00:15Z",
    "2016-08-01T00:00:16Z",
    "2016-08-01T00:00:17Z",
    "2016-08-01T00:00:18Z",
    "2016-08-01T00:00:19Z"
  ],
  "properties": [
    {
      "name": "Building",
      "type": "String",
      "values": [
        "Millenium",
        "Millenium",
        "Millenium",
        "Millenium",
        "Millenium",
        "Millenium",
        "Millenium",
        "Millenium",
        "Millenium",
        "Millenium"
      ]
    },
    {
      "name": "Temperature",
      "type": "Double",
      "values": [
        65.125,
        65.375,
        65.625,
        65.875,
        66.125,
        66.375,
        66.625,
        66.875,
        67.125,
        67.375
      ]
    }
  ],
  "progress": 100
}

QueryGetSeriesPage1

示例请求

HTTP

POST https://10000000-0000-0000-0000-100000000109.env.timeseries.azure.com/timeseries/query?api-version=2020-07-31

{
  "getSeries": {
    "timeSeriesId": [
      "006dfc2d-0324-4937-998c-d16f3b4f1952",
      "T1"
    ],
    "searchSpan": {
      "from": "2016-08-01T00:00:00Z",
      "to": "2016-08-01T00:16:50Z"
    },
    "filter": null,
    "inlineVariables": {
      "temperatures": {
        "kind": "numeric",
        "value": {
          "tsx": "$event.Temperature"
        },
        "filter": null,
        "aggregation": {
          "tsx": "avg($value)"
        }
      }
    },
    "projectedVariables": [
      "temperatures"
    ]
  }
}

示例响应

状态代码:: 200

{
  "progress": 50,
  "continuationToken": "aXsic2tpcCI6MTAwMCwidGFrZSI6MTAwMH0="
}

QueryGetSeriesPage2

示例请求

HTTP

POST https://10000000-0000-0000-0000-100000000109.env.timeseries.azure.com/timeseries/query?api-version=2020-07-31

{
  "getSeries": {
    "timeSeriesId": [
      "006dfc2d-0324-4937-998c-d16f3b4f1952",
      "T1"
    ],
    "searchSpan": {
      "from": "2016-08-01T00:00:00Z",
      "to": "2016-08-01T00:16:50Z"
    },
    "filter": null,
    "inlineVariables": {
      "temperatures": {
        "kind": "numeric",
        "value": {
          "tsx": "$event.Temperature"
        },
        "filter": null,
        "aggregation": {
          "tsx": "avg($value)"
        }
      }
    },
    "projectedVariables": [
      "temperatures"
    ]
  }
}

示例响应

状态代码:: 200

{
  "timestamps": [
    "2016-08-01T00:00:10Z",
    "2016-08-01T00:00:11Z",
    "2016-08-01T00:00:12Z",
    "2016-08-01T00:00:13Z",
    "2016-08-01T00:00:14Z",
    "2016-08-01T00:00:15Z",
    "2016-08-01T00:00:16Z",
    "2016-08-01T00:00:17Z",
    "2016-08-01T00:00:18Z",
    "2016-08-01T00:00:19Z",
    "2016-08-01T00:00:20Z"
  ],
  "properties": [
    {
      "name": "temperatures",
      "type": "Double",
      "values": [
        65.125,
        65.375,
        65.625,
        65.875,
        66.125,
        66.375,
        66.625,
        66.875,
        67.125,
        67.375,
        67.625
      ]
    }
  ],
  "progress": 50,
  "continuationToken": "aXsic2tpcCI6MTAxYZwidGFrZSI6MTAwMH0="
}

QueryGetSeriesPage3

示例请求

HTTP

POST https://10000000-0000-0000-0000-100000000109.env.timeseries.azure.com/timeseries/query?api-version=2020-07-31

{
  "getSeries": {
    "timeSeriesId": [
      "006dfc2d-0324-4937-998c-d16f3b4f1952",
      "T1"
    ],
    "searchSpan": {
      "from": "2016-08-01T00:00:00Z",
      "to": "2016-08-01T00:16:50Z"
    },
    "filter": null,
    "inlineVariables": {
      "temperatures": {
        "kind": "numeric",
        "value": {
          "tsx": "$event.Temperature"
        },
        "filter": null,
        "aggregation": {
          "tsx": "avg($value)"
        }
      }
    },
    "projectedVariables": [
      "temperatures"
    ]
  }
}

示例响应

状态代码:: 200

{
  "timestamps": [
    "2016-08-01T00:00:21Z"
  ],
  "properties": [
    {
      "name": "temperatures",
      "type": "Double",
      "values": [
        67.825
      ]
    }
  ],
  "progress": 100
}

QueryGetSeriesWithTakePage1

示例请求

HTTP

POST https://10000000-0000-0000-0000-100000000109.env.timeseries.azure.com/timeseries/query?api-version=2020-07-31

{
  "getSeries": {
    "timeSeriesId": [
      "006dfc2d-0324-4937-998c-d16f3b4f1952",
      "T1"
    ],
    "searchSpan": {
      "from": "2016-08-01T00:00:00Z",
      "to": "2016-08-01T00:16:50Z"
    },
    "filter": null,
    "inlineVariables": {
      "temperatures": {
        "kind": "numeric",
        "value": {
          "tsx": "$event.Temperature"
        },
        "filter": null,
        "aggregation": {
          "tsx": "avg($value)"
        }
      }
    },
    "projectedVariables": [
      "temperatures"
    ],
    "take": 10
  }
}

示例响应

状态代码:: 200

{
  "progress": 50,
  "continuationToken": "aXsic2tpcCI6MTAwMCwidGFrZSI6MTAwMH0="
}

QueryGetSeriesWithTakePage2

示例请求

HTTP

POST https://10000000-0000-0000-0000-100000000109.env.timeseries.azure.com/timeseries/query?api-version=2020-07-31

{
  "getSeries": {
    "timeSeriesId": [
      "006dfc2d-0324-4937-998c-d16f3b4f1952",
      "T1"
    ],
    "searchSpan": {
      "from": "2016-08-01T00:00:00Z",
      "to": "2016-08-01T00:16:50Z"
    },
    "filter": null,
    "inlineVariables": {
      "temperatures": {
        "kind": "numeric",
        "value": {
          "tsx": "$event.Temperature"
        },
        "filter": null,
        "aggregation": {
          "tsx": "avg($value)"
        }
      }
    },
    "projectedVariables": [
      "temperatures"
    ],
    "take": 10
  }
}

示例响应

状态代码:: 200

{
  "timestamps": [
    "2016-08-01T00:00:10Z",
    "2016-08-01T00:00:11Z",
    "2016-08-01T00:00:12Z",
    "2016-08-01T00:00:13Z",
    "2016-08-01T00:00:14Z",
    "2016-08-01T00:00:15Z",
    "2016-08-01T00:00:16Z",
    "2016-08-01T00:00:17Z",
    "2016-08-01T00:00:18Z",
    "2016-08-01T00:00:19Z",
    "2016-08-01T00:00:20Z"
  ],
  "properties": [
    {
      "name": "temperatures",
      "type": "Double",
      "values": [
        65.125,
        65.375,
        65.625,
        65.875,
        66.125,
        66.375,
        66.625,
        66.875,
        67.125,
        67.375,
        67.625
      ]
    }
  ],
  "progress": 100
}

WarmStoreQueryAggregateSeriesPage

示例请求

HTTP

POST https://10000000-0000-0000-0000-100000000109.env.timeseries.azure.com/timeseries/query?api-version=2020-07-31&storeType=warmstore

{
  "aggregateSeries": {
    "timeSeriesId": [
      "006dfc2d-0324-4937-998c-d16f3b4f1952",
      "T1"
    ],
    "searchSpan": {
      "from": "2016-08-01T00:00:00Z",
      "to": "2016-08-01T00:16:50Z"
    },
    "interval": "PT1M",
    "inlineVariables": {
      "Count": {
        "kind": "aggregate",
        "filter": null,
        "aggregation": {
          "tsx": "count()"
        }
      },
      "MinTemperature": {
        "kind": "numeric",
        "value": {
          "tsx": "$event.Temperature"
        },
        "filter": null,
        "aggregation": {
          "tsx": "min($value)"
        }
      },
      "MaxTemperature": {
        "kind": "numeric",
        "value": {
          "tsx": "$event.Temperature"
        },
        "filter": null,
        "aggregation": {
          "tsx": "max($value)"
        }
      }
    },
    "projectedVariables": [
      "Count",
      "MinTemperature",
      "MaxTemperature"
    ]
  }
}

示例响应

状态代码:: 200

{
  "timestamps": [
    "2016-08-01T00:00:00Z",
    "2016-08-01T00:01:00Z",
    "2016-08-01T00:02:00Z",
    "2016-08-01T00:03:00Z",
    "2016-08-01T00:04:00Z",
    "2016-08-01T00:05:00Z",
    "2016-08-01T00:06:00Z",
    "2016-08-01T00:07:00Z",
    "2016-08-01T00:08:00Z",
    "2016-08-01T00:09:00Z",
    "2016-08-01T00:10:00Z"
  ],
  "properties": [
    {
      "name": "Count",
      "type": "Long",
      "values": [
        50,
        60,
        60,
        60,
        60,
        60,
        60,
        60,
        60,
        60,
        null
      ]
    },
    {
      "name": "AverageTemperature",
      "type": "Double",
      "values": [
        71.25,
        85,
        82.5,
        80,
        89.16666666666667,
        75,
        90,
        75.83333333333333,
        85,
        82.5,
        null
      ]
    },
    {
      "name": "MinTemperature",
      "type": "Double",
      "values": [
        65.125,
        77.625,
        65.125,
        72.625,
        65.125,
        67.625,
        82.625,
        65.125,
        77.625,
        65.125,
        null
      ]
    },
    {
      "name": "MaxTemperature",
      "type": "Double",
      "values": [
        77.375,
        92.375,
        99.875,
        87.375,
        99.875,
        82.375,
        97.375,
        99.875,
        92.375,
        99.875,
        null
      ]
    }
  ],
  "progress": 100
}

WarmStoreQueryGetEventsPage1

示例请求

HTTP

POST https://10000000-0000-0000-0000-100000000109.env.timeseries.azure.com/timeseries/query?api-version=2020-07-31&storeType=warmstore

{
  "getEvents": {
    "timeSeriesId": [
      "006dfc2d-0324-4937-998c-d16f3b4f1952",
      "T1"
    ],
    "searchSpan": {
      "from": "2016-08-01T00:00:00Z",
      "to": "2016-08-01T00:16:50Z"
    },
    "filter": {
      "tsx": "($event.Value.Double != null) OR ($event.Status.String = 'Good')"
    },
    "projectedProperties": [
      {
        "name": "Building",
        "type": "String"
      },
      {
        "name": "Temperature",
        "type": "Double"
      }
    ]
  }
}

示例响应

状态代码:: 200

{
  "progress": 50,
  "continuationToken": "aXsic2tpcCI6MTAwMCwidGFrZSI6MTAwMH0="
}

WarmStoreQueryGetEventsPage2

示例请求

HTTP

POST https://10000000-0000-0000-0000-100000000109.env.timeseries.azure.com/timeseries/query?api-version=2020-07-31&storeType=warmstore

{
  "getEvents": {
    "timeSeriesId": [
      "006dfc2d-0324-4937-998c-d16f3b4f1952",
      "T1"
    ],
    "searchSpan": {
      "from": "2016-08-01T00:00:00Z",
      "to": "2016-08-01T00:16:50Z"
    },
    "filter": {
      "tsx": "($event.Value.Double != null) OR ($event.Status.String = 'Good')"
    },
    "projectedProperties": [
      {
        "name": "Building",
        "type": "String"
      },
      {
        "name": "Temperature",
        "type": "Double"
      }
    ]
  }
}

示例响应

状态代码:: 200

{
  "timestamps": [
    "2016-08-01T00:00:10Z",
    "2016-08-01T00:00:11Z",
    "2016-08-01T00:00:12Z",
    "2016-08-01T00:00:13Z",
    "2016-08-01T00:00:14Z",
    "2016-08-01T00:00:15Z",
    "2016-08-01T00:00:16Z",
    "2016-08-01T00:00:17Z",
    "2016-08-01T00:00:18Z",
    "2016-08-01T00:00:19Z"
  ],
  "properties": [
    {
      "name": "Building",
      "type": "String",
      "values": [
        "Millenium",
        "Millenium",
        "Millenium",
        "Millenium",
        "Millenium",
        "Millenium",
        "Millenium",
        "Millenium",
        "Millenium",
        "Millenium"
      ]
    },
    {
      "name": "Temperature",
      "type": "Double",
      "values": [
        65.125,
        65.375,
        65.625,
        65.875,
        66.125,
        66.375,
        66.625,
        66.875,
        67.125,
        67.375
      ]
    }
  ],
  "progress": 50,
  "continuationToken": "aXsic2tpcCI6MTAxYZwidGFrZSI6MTAwMH0="
}

WarmStoreQueryGetEventsPage3

示例请求

HTTP

POST https://10000000-0000-0000-0000-100000000109.env.timeseries.azure.com/timeseries/query?api-version=2020-07-31&storeType=warmstore

{
  "getEvents": {
    "timeSeriesId": [
      "006dfc2d-0324-4937-998c-d16f3b4f1952",
      "T1"
    ],
    "searchSpan": {
      "from": "2016-08-01T00:00:00Z",
      "to": "2016-08-01T00:16:50Z"
    },
    "filter": {
      "tsx": "($event.Value.Double != null) OR ($event.Status.String = 'Good')"
    },
    "projectedProperties": [
      {
        "name": "Building",
        "type": "String"
      },
      {
        "name": "Temperature",
        "type": "Double"
      }
    ]
  }
}

示例响应

状态代码:: 200

{
  "timestamps": [
    "2016-08-01T00:00:20Z"
  ],
  "properties": [
    {
      "name": "Building",
      "type": "String",
      "values": [
        "Millenium"
      ]
    },
    {
      "name": "Temperature",
      "type": "Double",
      "values": [
        67.575
      ]
    }
  ],
  "progress": 50,
  "continuationToken": "aXsic2tpcCI6MTAbCDewidGFrZSI6MTAwMH0="
}

WarmStoreQueryGetEventsPage4

示例请求

HTTP

POST https://10000000-0000-0000-0000-100000000109.env.timeseries.azure.com/timeseries/query?api-version=2020-07-31&storeType=warmstore

{
  "getEvents": {
    "timeSeriesId": [
      "006dfc2d-0324-4937-998c-d16f3b4f1952",
      "T1"
    ],
    "searchSpan": {
      "from": "2016-08-01T00:00:00Z",
      "to": "2016-08-01T00:16:50Z"
    },
    "filter": {
      "tsx": "($event.Value.Double != null) OR ($event.Status.String = 'Good')"
    },
    "projectedProperties": [
      {
        "name": "Building",
        "type": "String"
      },
      {
        "name": "Temperature",
        "type": "Double"
      }
    ]
  }
}

示例响应

状态代码:: 200

{
  "timestamps": [],
  "properties": [],
  "progress": 100
}

WarmStoreQueryGetSeriesPage1

示例请求

HTTP

POST https://10000000-0000-0000-0000-100000000109.env.timeseries.azure.com/timeseries/query?api-version=2020-07-31&storeType=warmstore

{
  "getSeries": {
    "timeSeriesId": [
      "006dfc2d-0324-4937-998c-d16f3b4f1952",
      "T1"
    ],
    "searchSpan": {
      "from": "2016-08-01T00:00:00Z",
      "to": "2016-08-01T00:16:50Z"
    },
    "filter": null,
    "inlineVariables": {
      "temperatures": {
        "kind": "numeric",
        "value": {
          "tsx": "$event.Temperature"
        },
        "filter": null,
        "aggregation": {
          "tsx": "avg($value)"
        }
      }
    },
    "projectedVariables": [
      "temperatures"
    ]
  }
}

示例响应

状态代码:: 200

{
  "progress": 50,
  "continuationToken": "aXsic2tpcCI6MTAwMCwidGFrZSI6MTAwMH0="
}

WarmStoreQueryGetSeriesPage2

示例请求

HTTP

POST https://10000000-0000-0000-0000-100000000109.env.timeseries.azure.com/timeseries/query?api-version=2020-07-31&storeType=warmstore

{
  "getSeries": {
    "timeSeriesId": [
      "006dfc2d-0324-4937-998c-d16f3b4f1952",
      "T1"
    ],
    "searchSpan": {
      "from": "2016-08-01T00:00:00Z",
      "to": "2016-08-01T00:16:50Z"
    },
    "filter": null,
    "inlineVariables": {
      "temperatures": {
        "kind": "numeric",
        "value": {
          "tsx": "$event.Temperature"
        },
        "filter": null,
        "aggregation": {
          "tsx": "avg($value)"
        }
      }
    },
    "projectedVariables": [
      "temperatures"
    ]
  }
}

示例响应

状态代码:: 200

{
  "timestamps": [
    "2016-08-01T00:00:10Z",
    "2016-08-01T00:00:11Z",
    "2016-08-01T00:00:12Z",
    "2016-08-01T00:00:13Z",
    "2016-08-01T00:00:14Z",
    "2016-08-01T00:00:15Z",
    "2016-08-01T00:00:16Z",
    "2016-08-01T00:00:17Z",
    "2016-08-01T00:00:18Z",
    "2016-08-01T00:00:19Z",
    "2016-08-01T00:00:20Z"
  ],
  "properties": [
    {
      "name": "temperatures",
      "type": "Double",
      "values": [
        65.125,
        65.375,
        65.625,
        65.875,
        66.125,
        66.375,
        66.625,
        66.875,
        67.125,
        67.375,
        67.625
      ]
    }
  ],
  "progress": 50,
  "continuationToken": "aXsic2tpcCI6MTAxYZwidGFrZSI6MTAwMH0="
}

WarmStoreQueryGetSeriesPage3

示例请求

HTTP

POST https://10000000-0000-0000-0000-100000000109.env.timeseries.azure.com/timeseries/query?api-version=2020-07-31&storeType=warmstore

{
  "getSeries": {
    "timeSeriesId": [
      "006dfc2d-0324-4937-998c-d16f3b4f1952",
      "T1"
    ],
    "searchSpan": {
      "from": "2016-08-01T00:00:00Z",
      "to": "2016-08-01T00:16:50Z"
    },
    "filter": null,
    "inlineVariables": {
      "temperatures": {
        "kind": "numeric",
        "value": {
          "tsx": "$event.Temperature"
        },
        "filter": null,
        "aggregation": {
          "tsx": "avg($value)"
        }
      }
    },
    "projectedVariables": [
      "temperatures"
    ]
  }
}

示例响应

状态代码:: 200

{
  "timestamps": [
    "2016-08-01T00:00:21Z"
  ],
  "properties": [
    {
      "name": "temperatures",
      "type": "Double",
      "values": [
        67.825
      ]
    }
  ],
  "progress": 100
}

定义

名称	说明
AggregateSeries	聚合序列查询。允许根据给定时序 ID 和搜索范围从事件计算聚合时序。
AggregateVariable	聚合变量表示任何聚合计算。聚合变量不支持内插。
Boundary	要用于内插的搜索范围的左侧和右侧的时间范围。这在数据点缺失到输入搜索范围的开始或结束的情况下非常有用。可以为 null。
CategoricalVariable	分类变量表示需要根据有限定义值集发生次数或持续时间进行分析的信号。
DateTimeRange	时间范围。不能为 null 或负值。
EventProperty	存储或计算的事件的属性。属性由名称和类型标识。不同的事件可以具有具有相同名称但类型不同的属性。
GetEvents	获取事件查询。允许检索给定时序 ID 和搜索范围的原始事件。
GetSeries	获取序列查询。允许从给定时序 ID 和搜索范围的事件中检索计算变量值的时序。
Interpolation	要对原始数据点执行的内插作。目前，仅允许对内插时序进行采样。允许的聚合函数 - 例如：left（$value）。如果不需要应用内插，可以为 null。
InterpolationKind	内插技术的类型：“Linear”或“Step”。
NumericVariable	数值变量表示可以使用内插重新构造的单个连续数值信号。
PropertyTypes	属性的类型。
PropertyValues	对应于时间戳的单个属性的值。可能包含 null。值类型与属性的类型匹配。
QueryRequest	请求对事件执行时序查询。必须设置“getEvents”、“getSeries”或“aggregateSeries”之一。
QueryResultPage	查询结果的单个页。如果查询尚未完成，则页面将设置继续标记。在这种情况下，若要获取下一页的结果，请使用继续标记参数再次发送相同的请求。如果查询已完成，则延续标记为 null。如果没有计算查询结果，还可以获取仅设置继续标记集的空页。如果分页已完成（延续标记为 null），则如果没有要返回的数据，时间戳和属性可能为空。
TimeSeriesAggregateCategory	分类变量中使用的类别。类别由“label”和分配此标签的“values”定义。
TimeSeriesDefaultCategory	表示默认类别。
TsiError	有关 API 错误的信息。
TsiErrorBody	具有错误代码和消息的特定 API 错误。
TsiErrorDetails	其他错误信息。
Tsx	以单个字符串形式编写的时序表达式（TSX）。示例：“$event。Status.String='Good'“， ”avg（$event.温度“。请参阅有关如何编写时序表达式的文档。

AggregateSeries

Object

聚合序列查询。允许根据给定时序 ID 和搜索范围从事件计算聚合时序。

名称	类型	说明
filter	Tsx	对限制要考虑计算的事件数的事件进行顶级筛选器。此筛选器是 AND'ed，其中包含每个变量中的筛选器。示例：“$event。Status.String='Good'”。可选。
inlineVariables	object	这允许用户选择定义内联变量，除了模型中已定义的变量。当内联变量名称与模型同名时，内联变量定义优先。可以为 null。
interval	string (duration)	间隔大小以 ISO-8601 持续时间格式指定。所有间隔都具有相同大小。一个月始终转换为 30 天，一年始终为 365 天。示例：1 分钟为“PT1M”，1 毫秒为“PT0.001S”。有关详细信息，请参阅 https://www.w3.org/TR/xmlschema-2/#duration
projectedVariables	string[]	这样，用户可以选择需要投影的变量。如果为 null 或未设置，则返回内联Variables 和模型中的所有变量。可以为 null。
searchSpan	DateTimeRange	执行查询的时间范围。不能为 null。
timeSeriesId	TimeSeriesId[]	唯一标识单个时序实例（例如设备）的单个时序 ID 值。请注意，如果在创建环境时将多个属性指定为时序 ID，则可以组合单个时序 ID。值的位置和类型必须与在环境中指定的时序 ID 属性匹配，并由“获取模型设置 API”返回。不能为 null。

AggregateVariable

Object

聚合变量表示任何聚合计算。聚合变量不支持内插。

名称	类型	说明
aggregation	Tsx	当类型为“aggregate”时，聚合时序表达式用于表示需要使用事件属性（如“$event”）直接执行的聚合。温度”。例如，计算温度变化范围的聚合可以写为：“max（$event）。温度）-min（$event.温度“。
filter	Tsx	筛选限制要考虑计算的事件数的事件。示例：“$event。Status.String='Good'”。可选。
kind	string: aggregate	允许的“kind”值为 -“numeric”或“aggregate”。虽然“numeric”允许指定重新构造信号的值和聚合它们的表达式，但“聚合”类型允许你直接聚合事件属性而不指定值。

Boundary

Object

要用于内插的搜索范围的左侧和右侧的时间范围。这在数据点缺失到输入搜索范围的开始或结束的情况下非常有用。可以为 null。

名称	类型	说明
span	string (duration)

CategoricalVariable

Object

分类变量表示需要根据有限定义值集发生次数或持续时间进行分析的信号。

名称	类型	说明
categories	TimeSeriesAggregateCategory[]	分类变量中使用的类别。类别由“label”和分配此标签的“values”定义。
defaultCategory	TimeSeriesDefaultCategory	表示默认类别。
filter	Tsx	筛选限制要考虑计算的事件数的事件。示例：“$event。Status.String='Good'”。可选。
interpolation	Interpolation	分类变量仅支持“步骤”内插。
kind	string: categorical	允许的“kind”值为 -“numeric”或“aggregate”。虽然“numeric”允许指定重新构造信号的值和聚合它们的表达式，但“聚合”类型允许你直接聚合事件属性而不指定值。
value	Tsx	值时序表达式用于表示要分类的信号的值。它只能计算为分类变量的“String”或“Long”类型。

DateTimeRange

Object

时间范围。不能为 null 或负值。

名称	类型	说明
from	string (date-time)	时间范围的开始时间戳。在时序查询请求中使用开始时间戳是非独占的。包含此时间戳的事件。
to	string (date-time)	时间范围的结束时间戳。在时序查询请求中使用结束时间戳是独占的。排除与此时间戳匹配的事件。请注意，Get Availability 返回时结束时间戳是非独占的（这意味着存在具有此确切“to”时间戳的事件）。

EventProperty

Object

存储或计算的事件的属性。属性由名称和类型标识。不同的事件可以具有具有相同名称但类型不同的属性。

名称	类型	说明
name	string	属性的名称。
type	PropertyTypes	属性的类型。

GetEvents

Object

获取事件查询。允许检索给定时序 ID 和搜索范围的原始事件。

名称	类型	说明
filter	Tsx	查询的可选顶级筛选器，该筛选器将应用于查询中的所有变量。示例：“$event。Status.String='Good'”。可以为 null。
projectedProperties	EventProperty[]	投影属性是要投影的属性数组。这些属性必须出现在事件中;否则，不会返回它们。
searchSpan	DateTimeRange	执行查询的时间范围。不能为 null。
take	integer (int32)	整个响应集中属性值的最大数目，而不是每个页面的最大属性值数。如果未设置，则默认值为 10,000。最大取值为 250,000。
timeSeriesId	TimeSeriesId[]	唯一标识单个时序实例（例如设备）的单个时序 ID 值。请注意，如果在创建环境时将多个属性指定为时序 ID，则可以组合单个时序 ID。值的位置和类型必须与在环境中指定的时序 ID 属性匹配，并由“获取模型设置 API”返回。不能为 null。

GetSeries

Object

获取序列查询。允许从给定时序 ID 和搜索范围的事件中检索计算变量值的时序。

名称	类型	说明
filter	Tsx	对限制要考虑计算的事件数的事件进行顶级筛选器。此筛选器是 AND'ed，其中包含每个变量中的筛选器。示例：“$event。Status.String='Good'”。可选。
inlineVariables	object	除了模型时序类型中已定义的变量之外，可选内联变量。当内联变量名称与模型中的名称相同时，内联变量定义优先。可以为 null。
projectedVariables	string[]	需要在查询结果中投影的选定变量。如果为 null 或未设置，则返回模型中内联Variables 和时序类型中的所有变量。可以为 null。
searchSpan	DateTimeRange	执行查询的时间范围。不能为 null。
take	integer (int32)	整个响应集中属性值的最大数目，而不是每个页面的最大属性值数。如果未设置，则默认值为 10,000。最大取值为 250,000。
timeSeriesId	TimeSeriesId[]	唯一标识单个时序实例（例如设备）的单个时序 ID 值。请注意，如果在创建环境时将多个属性指定为时序 ID，则可以组合单个时序 ID。值的位置和类型必须与在环境中指定的时序 ID 属性匹配，并由“获取模型设置 API”返回。不能为 null。

Interpolation

Object

要对原始数据点执行的内插作。目前，仅允许对内插时序进行采样。允许的聚合函数 - 例如：left（$value）。如果不需要应用内插，可以为 null。

名称	类型	说明
boundary	Boundary	要用于内插的搜索范围的左侧和右侧的时间范围。这在数据点缺失到输入搜索范围的开始或结束的情况下非常有用。可以为 null。
kind	InterpolationKind	内插技术的类型：“Linear”或“Step”。

InterpolationKind

枚举

内插技术的类型：“Linear”或“Step”。

值	说明
Linear
Step

NumericVariable

Object

数值变量表示可以使用内插重新构造的单个连续数值信号。

名称	类型	说明
aggregation	Tsx	当类型为“numeric”时，聚合时序表达式用于表示需要在$value表达式上执行的聚合。这需要指定$value，并且只能在聚合函数中使用$value。例如，计算最小$value的聚合写入为：“min（$value）”。
filter	Tsx	筛选限制要考虑计算的事件数的事件。示例：“$event。Status.String='Good'”。可选。
interpolation	Interpolation	要对原始数据点执行的内插作。目前，仅允许对内插时序进行采样。允许的聚合函数 - 例如：left（$value）。如果不需要应用内插，可以为 null。
kind	string: numeric	允许的“kind”值为 -“numeric”或“aggregate”。虽然“numeric”允许指定重新构造信号的值和聚合它们的表达式，但“聚合”类型允许你直接聚合事件属性而不指定值。
value	Tsx	值时序表达式用于表示要聚合或内插的信号的值。例如，事件中的温度值如下所示：“$event。Temperature.Double”。

PropertyTypes

枚举

属性的类型。

值	说明
Bool
DateTime
Double
String
TimeSpan
Long

PropertyValues

Object

对应于时间戳的单个属性的值。可能包含 null。值类型与属性的类型匹配。

名称	类型	说明
name	string	属性的名称。
type	PropertyTypes	属性的类型。
values	Values[]	对应于时间戳的单个属性的值。可能包含 null。值类型与属性的类型匹配。

QueryRequest

Object

请求对事件执行时序查询。必须设置“getEvents”、“getSeries”或“aggregateSeries”之一。

名称	类型	说明
aggregateSeries	AggregateSeries	聚合序列查询。允许根据给定时序 ID 和搜索范围从事件计算聚合时序。
getEvents	GetEvents	获取事件查询。允许检索给定时序 ID 和搜索范围的原始事件。
getSeries	GetSeries	获取序列查询。允许从给定时序 ID 和搜索范围的事件中检索计算变量值的时序。

QueryResultPage

Object

查询结果的单个页。如果查询尚未完成，则页面将设置继续标记。在这种情况下，若要获取下一页的结果，请使用继续标记参数再次发送相同的请求。如果查询已完成，则延续标记为 null。如果没有计算查询结果，还可以获取仅设置继续标记集的空页。如果分页已完成（延续标记为 null），则如果没有要返回的数据，时间戳和属性可能为空。

名称	类型	说明
continuationToken	string	如果返回，则表示当前结果表示部分结果。继续标记允许获取下一页的结果。若要获取下一页查询结果，请在“x-ms-continuation”HTTP 标头中使用延续标记参数发送相同的请求。
progress	number (double)	查询的大致进度（以百分比表示）。它可以介于 0 和 100 之间。当响应中的继续标记为 null 时，进度应为 100。
properties	PropertyValues[]	每个时间戳的时序属性和值的集合。如果服务器无法在此请求中填充页面，则为 null;如果继续标记为 null，则为空;如果继续标记为 null，则为空。
timestamps	string[] (date-time)	时序值的时间戳。如果使用了间隔的聚合，则时间戳表示相应间隔的开始。如果检索事件，时间戳是时间戳$ts事件属性的值。如果服务器无法在此请求中填充页面，则为 null;如果继续标记为 null，则为空;如果继续标记为 null，则为空。

TimeSeriesAggregateCategory

Object

分类变量中使用的类别。类别由“label”和分配此标签的“values”定义。

名称	类型	说明
label	string	将用于构造输出变量名称的类别的名称。
values	object[]	类别映射到的值列表。可以是字符串的唯一列表或长列表。

TimeSeriesDefaultCategory

Object

表示默认类别。

名称	类型	说明
label	string	将分配给与“类别”中定义的任何值不匹配的默认类别的名称。

TsiError

Object

有关 API 错误的信息。

名称	类型	说明
error	TsiErrorBody	具有错误代码和消息的特定 API 错误。

TsiErrorBody

Object

具有错误代码和消息的特定 API 错误。

名称	类型	说明
code	string	独立于语言且可读的字符串，用于定义特定于服务的错误代码。此代码用作响应中指定的 HTTP 错误代码的更具体的指示器。可用于以编程方式处理特定错误案例。
details	TsiErrorDetails[]	包含其他错误信息。可以为 null。
innerError	TsiErrorBody	包含更具体的错误，可缩小原因范围。可以为 null。
message	string	人为可读的、与语言无关的错误表示形式。它旨在帮助开发人员，不适合向最终用户公开。
target	string	特定错误的目标（例如，错误中属性的名称）。可以为 null。

TsiErrorDetails

Object

其他错误信息。

名称	类型	说明
code	string	独立于语言且可读的字符串，用于定义特定于服务的错误代码。此代码用作响应中指定的 HTTP 错误代码的更具体的指示器。可用于以编程方式处理特定错误案例。
message	string	人为可读的、与语言无关的错误表示形式。它旨在帮助开发人员，不适合向最终用户公开。

Tsx

Object

以单个字符串形式编写的时序表达式（TSX）。示例：“$event。Status.String='Good'“， ”avg（$event.温度“。请参阅有关如何编写时序表达式的文档。

名称	类型	说明
tsx	string	以单个字符串形式编写的时序表达式（TSX）。示例：“$event。Status.String='Good'“， ”avg（$event.温度“。请参阅有关如何编写时序表达式的文档。

通过

Query - Execute

URI 参数

请求头

请求正文

响应

安全性

azure_auth

作用域

示例

ColdStoreQueryAggregateSeriesPage1

示例请求

示例响应

ColdStoreQueryAggregateSeriesPage2

示例请求

示例响应

ColdStoreQueryGetEventsPage1

示例请求

示例响应

ColdStoreQueryGetEventsPage2

示例请求

示例响应

ColdStoreQueryGetEventsPage3

示例请求

示例响应

ColdStoreQueryGetEventsPage4

示例请求

示例响应

ColdStoreQueryGetSeriesPage1

示例请求

示例响应

ColdStoreQueryGetSeriesPage2

示例请求

示例响应

ColdStoreQueryGetSeriesPage3

示例请求

示例响应

QueryAggregateSeriesPage1

示例请求

示例响应

QueryAggregateSeriesPage2

示例请求

示例响应

QueryAggregateSeriesWithCategoricalInterpolatedVariable

示例请求

示例响应

QueryAggregateSeriesWithCategoricalVariable

示例请求

示例响应

QueryAggregateSeriesWithSampleInterpolation

示例请求

示例响应

QueryGetEventsPage1

示例请求

示例响应

QueryGetEventsPage2

示例请求

示例响应

QueryGetEventsPage3

示例请求

示例响应

QueryGetEventsPage4

示例请求

示例响应

QueryGetEventsWithTakePage1

示例请求

示例响应

QueryGetEventsWithTakePage2

示例请求

示例响应

QueryGetSeriesPage1

示例请求

示例响应

QueryGetSeriesPage2

示例请求

示例响应

QueryGetSeriesPage3

示例请求

示例响应

QueryGetSeriesWithTakePage1