Query - Execute
Executes Time Series Query in pages of results - Get Events, Get Series or Aggregate Series.
POST https://{environmentFqdn}/timeseries/query?api-version=2020-07-31POST https://{environmentFqdn}/timeseries/query?api-version=2020-07-31&storeType={storeType}URI Parameters
| Name | In | Required | Type | Description |
|---|---|---|---|---|
|
environment
|
path | True |
string |
Per environment FQDN, for example 10000000-0000-0000-0000-100000000109.env.timeseries.azure.com. You can obtain this domain name from the response of the Get Environments API, Azure portal, or Azure Resource Manager. |
|
api-version
|
query | True |
string |
Version of the API to be used with the client request. Currently supported version is "2020-07-31". |
|
store
|
query |
string |
For the environments with warm store enabled, the query can be executed either on the 'WarmStore' or 'ColdStore'. This parameter in the query defines which store the query should be executed on. If not defined, the query will be executed on the cold store. |
Request Header
| Name | Required | Type | Description |
|---|---|---|---|
| x-ms-continuation |
string |
Continuation token from previous page of results to retrieve the next page of the results in calls that support pagination. To get the first page results, specify null continuation token as parameter value. Returned continuation token is null if all results have been returned, and there is no next page of results. |
|
| x-ms-client-request-id |
string |
Optional client request ID. Service records this value. Allows the service to trace operation across services, and allows the customer to contact support regarding a particular request. |
|
| x-ms-client-session-id |
string |
Optional client session ID. Service records this value. Allows the service to trace a group of related operations across services, and allows the customer to contact support regarding a particular group of requests. |
Request Body
| Name | Type | Description |
|---|---|---|
| aggregateSeries |
Aggregate Series query. Allows to calculate an aggregated time series from events for a given Time Series ID and search span. |
|
| getEvents |
Get Events query. Allows to retrieve raw events for a given Time Series ID and search span. |
|
| getSeries |
Get Series query. Allows to retrieve time series of calculated variable values from events for a given Time Series ID and search span. |
Responses
| Name | Type | Description |
|---|---|---|
| 200 OK |
Successful query. Headers x-ms-request-id: string |
|
| Other Status Codes |
Unexpected error. Headers x-ms-request-id: string |
Security
azure_auth
Azure Active Directory OAuth2 Flow
Type:
oauth2
Flow:
implicit
Authorization URL:
https://login.microsoftonline.com/common/oauth2/authorize
Scopes
| Name | Description |
|---|---|
| user_impersonation | impersonate your user account |
Examples
ColdStoreQueryAggregateSeriesPage1
Sample Request
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"
]
}
}
Sample Response
{
"progress": 50,
"continuationToken": "aXsic2tpcCI6MTAwMCwidGFrZSI6MTAwMH0="
}ColdStoreQueryAggregateSeriesPage2
Sample Request
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"
]
}
}
Sample Response
{
"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
Sample Request
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"
}
]
}
}
Sample Response
{
"progress": 50,
"continuationToken": "aXsic2tpcCI6MTAwMCwidGFrZSI6MTAwMH0="
}ColdStoreQueryGetEventsPage2
Sample Request
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"
}
]
}
}
Sample Response
{
"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
Sample Request
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"
}
]
}
}
Sample Response
{
"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
Sample Request
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"
}
]
}
}
Sample Response
{
"timestamps": [],
"properties": [],
"progress": 100
}ColdStoreQueryGetSeriesPage1
Sample Request
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"
]
}
}
Sample Response
{
"progress": 50,
"continuationToken": "aXsic2tpcCI6MTAwMCwidGFrZSI6MTAwMH0="
}ColdStoreQueryGetSeriesPage2
Sample Request
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"
]
}
}
Sample Response
{
"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
Sample Request
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"
]
}
}
Sample Response
{
"timestamps": [
"2016-08-01T00:00:21Z"
],
"properties": [
{
"name": "temperatures",
"type": "Double",
"values": [
67.825
]
}
],
"progress": 100
}QueryAggregateSeriesPage1
Sample Request
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"
]
}
}
Sample Response
{
"progress": 50,
"continuationToken": "aXsic2tpcCI6MTAwMCwidGFrZSI6MTAwMH0="
}QueryAggregateSeriesPage2
Sample Request
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"
]
}
}
Sample Response
{
"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
Sample Request
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"
]
}
}
Sample Response
{
"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
Sample Request
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"
]
}
}
Sample Response
{
"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
Sample Request
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"
]
}
}
Sample Response
{
"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
Sample Request
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"
}
]
}
}
Sample Response
{
"progress": 50,
"continuationToken": "aXsic2tpcCI6MTAwMCwidGFrZSI6MTAwMH0="
}QueryGetEventsPage2
Sample Request
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"
}
]
}
}
Sample Response
{
"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
Sample Request
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"
}
]
}
}
Sample Response
{
"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
Sample Request
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"
}
]
}
}
Sample Response
{
"timestamps": [],
"properties": [],
"progress": 100
}QueryGetEventsWithTakePage1
Sample Request
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
}
}
Sample Response
{
"progress": 50,
"continuationToken": "aXsic2tpcCI6MTAwMCwidGFrZSI6MTAwMH0="
}QueryGetEventsWithTakePage2
Sample Request
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
}
}
Sample Response
{
"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
Sample Request
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"
]
}
}
Sample Response
{
"progress": 50,
"continuationToken": "aXsic2tpcCI6MTAwMCwidGFrZSI6MTAwMH0="
}QueryGetSeriesPage2
Sample Request
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"
]
}
}
Sample Response
{
"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
Sample Request
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"
]
}
}
Sample Response
{
"timestamps": [
"2016-08-01T00:00:21Z"
],
"properties": [
{
"name": "temperatures",
"type": "Double",
"values": [
67.825
]
}
],
"progress": 100
}QueryGetSeriesWithTakePage1
Sample Request
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
}
}
Sample Response
{
"progress": 50,
"continuationToken": "aXsic2tpcCI6MTAwMCwidGFrZSI6MTAwMH0="
}QueryGetSeriesWithTakePage2
Sample Request
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
}
}
Sample Response
{
"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
Sample Request
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"
]
}
}
Sample Response
{
"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
Sample Request
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"
}
]
}
}
Sample Response
{
"progress": 50,
"continuationToken": "aXsic2tpcCI6MTAwMCwidGFrZSI6MTAwMH0="
}WarmStoreQueryGetEventsPage2
Sample Request
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"
}
]
}
}
Sample Response
{
"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
Sample Request
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"
}
]
}
}
Sample Response
{
"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
Sample Request
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"
}
]
}
}
Sample Response
{
"timestamps": [],
"properties": [],
"progress": 100
}WarmStoreQueryGetSeriesPage1
Sample Request
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"
]
}
}
Sample Response
{
"progress": 50,
"continuationToken": "aXsic2tpcCI6MTAwMCwidGFrZSI6MTAwMH0="
}WarmStoreQueryGetSeriesPage2
Sample Request
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"
]
}
}
Sample Response
{
"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
Sample Request
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"
]
}
}
Sample Response
{
"timestamps": [
"2016-08-01T00:00:21Z"
],
"properties": [
{
"name": "temperatures",
"type": "Double",
"values": [
67.825
]
}
],
"progress": 100
}Definitions
| Name | Description |
|---|---|
|
Aggregate |
Aggregate Series query. Allows to calculate an aggregated time series from events for a given Time Series ID and search span. |
|
Aggregate |
Aggregate variable represents any aggregation calculation. Aggregate Variables does not support interpolation. |
| Boundary |
The time range to the left and right of the search span to be used for Interpolation. This is helpful in scenarios where the data points are missing close to the start or end of the input search span. Can be null. |
|
Categorical |
Categorical variable represents signal that needs to be analyzed based on the count or duration of occurrence of limited set of defined values. |
|
Date |
The range of time. Cannot be null or negative. |
|
Event |
Property of an event that is either stored or computed. Properties are identified by both name and type. Different events can have properties with same name, but different type. |
|
Get |
Get Events query. Allows to retrieve raw events for a given Time Series ID and search span. |
|
Get |
Get Series query. Allows to retrieve time series of calculated variable values from events for a given Time Series ID and search span. |
| Interpolation |
The interpolation operation to be performed on the raw data points. Currently, only sampling of interpolated time series is allowed. Allowed aggregate function - eg: left($value). Can be null if no interpolation needs to be applied. |
|
Interpolation |
The type of interpolation technique : "Linear" or "Step". |
|
Numeric |
Numeric variable represents a single continuous numeric signal that can be reconstructed using interpolation. |
|
Property |
The type of the property. |
|
Property |
Values of a single property corresponding to the timestamps. May contain nulls. Type of values matches the type of property. |
|
Query |
Request to execute a time series query over events. Exactly one of "getEvents", "getSeries" or "aggregateSeries" must be set. |
|
Query |
A single page of query results. If query has not finished yet, a page will have continuation token set. In this case, to get the next page of results, send the same request again with continuation token parameter. If query has completed, the continuation token is null. It is also possible to get an empty page with only continuation token set when no query results have been computed yet. If paging has completed (continuation token is null), then timestamps and properties may be empty if there is no data to return. |
|
Time |
Category used in categorical variables. A category is defined by 'label' and the 'values' that are assigned this label. |
|
Time |
Represents the default category. |
|
Tsi |
Information about an API error. |
|
Tsi |
A particular API error with an error code and a message. |
|
Tsi |
Additional error information. |
| Tsx |
Time series expression (TSX) written as a single string. Examples: "$event.Status.String='Good'", "avg($event.Temperature)". Refer to the documentation on how to write time series expressions. |
AggregateSeries
Aggregate Series query. Allows to calculate an aggregated time series from events for a given Time Series ID and search span.
| Name | Type | Description |
|---|---|---|
| filter |
Top-level filter over the events that restricts the number of events being considered for computation. This filter is AND'ed with filter in each variable. Example: "$event.Status.String='Good'". Optional. |
|
| inlineVariables |
object |
This allows the user the optionally define inline-variables apart from the ones already defined in the model. When the inline variable names have the same name as the model, the inline variable definition takes precedence. Can be null. |
| interval |
string |
Interval size is specified in ISO-8601 duration format. All intervals are the same size. One month is always converted to 30 days, and one year is always 365 days. Examples: 1 minute is "PT1M", 1 millisecond is "PT0.001S". For more information, see https://www.w3.org/TR/xmlschema-2/#duration |
| projectedVariables |
string[] |
This allows the user to optionally select the variables that needs to be projected. When it is null or not set, all the variables from inlineVariables and model are returned. Can be null. |
| searchSpan |
The range of time on which the query is executed. Cannot be null. |
|
| timeSeriesId |
Time |
A single Time Series ID value that uniquely identifies a single time series instance (e.g. a device). Note that a single Time Series ID can be composite if multiple properties are specified as Time Series ID at environment creation time. The position and type of values must match Time Series ID properties specified on the environment and returned by Get Model Setting API. Cannot be null. |
AggregateVariable
Aggregate variable represents any aggregation calculation. Aggregate Variables does not support interpolation.
| Name | Type | Description |
|---|---|---|
| aggregation |
Aggregation time series expression when kind is "aggregate" is used to represent the aggregation that needs to be performed directly using event properties like "$event.Temperature". For example, aggregation for calculating range of temperature changes can be written as: "max($event.Temperature)-min($event.Temperature)". |
|
| filter |
Filter over the events that restricts the number of events being considered for computation. Example: "$event.Status.String='Good'". Optional. |
|
| kind |
string:
aggregate |
Allowed "kind" values are - "numeric" or "aggregate". While "numeric" allows you to specify value of the reconstructed signal and the expression to aggregate them, the "aggregate" kind lets you directly aggregate on the event properties without specifying value. |
Boundary
The time range to the left and right of the search span to be used for Interpolation. This is helpful in scenarios where the data points are missing close to the start or end of the input search span. Can be null.
| Name | Type | Description |
|---|---|---|
| span |
string |
CategoricalVariable
Categorical variable represents signal that needs to be analyzed based on the count or duration of occurrence of limited set of defined values.
| Name | Type | Description |
|---|---|---|
| categories |
Category used in categorical variables. A category is defined by 'label' and the 'values' that are assigned this label. |
|
| defaultCategory |
Represents the default category. |
|
| filter |
Filter over the events that restricts the number of events being considered for computation. Example: "$event.Status.String='Good'". Optional. |
|
| interpolation |
Categorical variable supports only 'step' interpolation. |
|
| kind |
string:
categorical |
Allowed "kind" values are - "numeric" or "aggregate". While "numeric" allows you to specify value of the reconstructed signal and the expression to aggregate them, the "aggregate" kind lets you directly aggregate on the event properties without specifying value. |
| value |
Value time series expression is used to represent the value of the signal that is going to be categorized. It can evaluate to only 'String' or 'Long' type for categorical variables. |
DateTimeRange
The range of time. Cannot be null or negative.
| Name | Type | Description |
|---|---|---|
| from |
string |
Start timestamp of the time range. Start timestamp is inclusive when used in time series query requests. Events that have this timestamp are included. |
| to |
string |
End timestamp of the time range. End timestamp is exclusive when used in time series query requests. Events that match this timestamp are excluded. Note that end timestamp is inclusive when returned by Get Availability (meaning that there is an event with this exact "to" timestamp). |
EventProperty
Property of an event that is either stored or computed. Properties are identified by both name and type. Different events can have properties with same name, but different type.
| Name | Type | Description |
|---|---|---|
| name |
string |
The name of the property. |
| type |
The type of the property. |
GetEvents
Get Events query. Allows to retrieve raw events for a given Time Series ID and search span.
| Name | Type | Description |
|---|---|---|
| filter |
Optional top-level filter for the query which will be applied to all the variables in the query. Example: "$event.Status.String='Good'". Can be null. |
|
| projectedProperties |
Projected properties is an array of properties which you want to project. These properties must appear in the events; otherwise, they are not returned. |
|
| searchSpan |
The range of time on which the query is executed. Cannot be null. |
|
| take |
integer |
Maximum number of property values in the whole response set, not the maximum number of property values per page. Defaults to 10,000 when not set. Maximum value of take can be 250,000. |
| timeSeriesId |
Time |
A single Time Series ID value that uniquely identifies a single time series instance (e.g. a device). Note that a single Time Series ID can be composite if multiple properties are specified as Time Series ID at environment creation time. The position and type of values must match Time Series ID properties specified on the environment and returned by Get Model Setting API. Cannot be null. |
GetSeries
Get Series query. Allows to retrieve time series of calculated variable values from events for a given Time Series ID and search span.
| Name | Type | Description |
|---|---|---|
| filter |
Top-level filter over the events that restricts the number of events being considered for computation. This filter is AND'ed with filter in each variable. Example: "$event.Status.String='Good'". Optional. |
|
| inlineVariables |
object |
Optional inline variables apart from the ones already defined in the time series type in the model. When the inline variable name is the same name as in the model, the inline variable definition takes precedence. Can be null. |
| projectedVariables |
string[] |
Selected variables that needs to be projected in the query result. When it is null or not set, all the variables from inlineVariables and time series type in the model are returned. Can be null. |
| searchSpan |
The range of time on which the query is executed. Cannot be null. |
|
| take |
integer |
Maximum number of property values in the whole response set, not the maximum number of property values per page. Defaults to 10,000 when not set. Maximum value of take can be 250,000. |
| timeSeriesId |
Time |
A single Time Series ID value that uniquely identifies a single time series instance (e.g. a device). Note that a single Time Series ID can be composite if multiple properties are specified as Time Series ID at environment creation time. The position and type of values must match Time Series ID properties specified on the environment and returned by Get Model Setting API. Cannot be null. |
Interpolation
The interpolation operation to be performed on the raw data points. Currently, only sampling of interpolated time series is allowed. Allowed aggregate function - eg: left($value). Can be null if no interpolation needs to be applied.
| Name | Type | Description |
|---|---|---|
| boundary |
The time range to the left and right of the search span to be used for Interpolation. This is helpful in scenarios where the data points are missing close to the start or end of the input search span. Can be null. |
|
| kind |
The type of interpolation technique : "Linear" or "Step". |
InterpolationKind
The type of interpolation technique : "Linear" or "Step".
| Name | Type | Description |
|---|---|---|
| Linear |
string |
|
| Step |
string |
NumericVariable
Numeric variable represents a single continuous numeric signal that can be reconstructed using interpolation.
| Name | Type | Description |
|---|---|---|
| aggregation |
Aggregation time series expression when kind is "numeric" is used to represent the aggregation that needs to be performed on the $value expression. This requires $value to be specified and can only use $value inside the aggregate functions. For example, aggregation for calculating minimum of the $value is written as: "min($value)". |
|
| filter |
Filter over the events that restricts the number of events being considered for computation. Example: "$event.Status.String='Good'". Optional. |
|
| interpolation |
The interpolation operation to be performed on the raw data points. Currently, only sampling of interpolated time series is allowed. Allowed aggregate function - eg: left($value). Can be null if no interpolation needs to be applied. |
|
| kind |
string:
numeric |
Allowed "kind" values are - "numeric" or "aggregate". While "numeric" allows you to specify value of the reconstructed signal and the expression to aggregate them, the "aggregate" kind lets you directly aggregate on the event properties without specifying value. |
| value |
Value time series expression is used to represent the value of the signal that is going to be aggregated or interpolated. For example, temperature values from the event is represented like this: "$event.Temperature.Double". |
PropertyTypes
The type of the property.
| Name | Type | Description |
|---|---|---|
| Bool |
string |
|
| DateTime |
string |
|
| Double |
string |
|
| Long |
string |
|
| String |
string |
|
| TimeSpan |
string |
PropertyValues
Values of a single property corresponding to the timestamps. May contain nulls. Type of values matches the type of property.
| Name | Type | Description |
|---|---|---|
| name |
string |
The name of the property. |
| type |
The type of the property. |
|
| values |
Values[] |
Values of a single property corresponding to the timestamps. May contain nulls. Type of values matches the type of property. |
QueryRequest
Request to execute a time series query over events. Exactly one of "getEvents", "getSeries" or "aggregateSeries" must be set.
| Name | Type | Description |
|---|---|---|
| aggregateSeries |
Aggregate Series query. Allows to calculate an aggregated time series from events for a given Time Series ID and search span. |
|
| getEvents |
Get Events query. Allows to retrieve raw events for a given Time Series ID and search span. |
|
| getSeries |
Get Series query. Allows to retrieve time series of calculated variable values from events for a given Time Series ID and search span. |
QueryResultPage
A single page of query results. If query has not finished yet, a page will have continuation token set. In this case, to get the next page of results, send the same request again with continuation token parameter. If query has completed, the continuation token is null. It is also possible to get an empty page with only continuation token set when no query results have been computed yet. If paging has completed (continuation token is null), then timestamps and properties may be empty if there is no data to return.
| Name | Type | Description |
|---|---|---|
| continuationToken |
string |
If returned, this means that current results represent a partial result. Continuation token allows to get the next page of results. To get the next page of query results, send the same request with continuation token parameter in "x-ms-continuation" HTTP header. |
| progress |
number |
Approximate progress of the query in percentage. It can be between 0 and 100. When the continuation token in the response is null, the progress is expected to be 100. |
| properties |
Collection of time series properties and values for each of the timestamps. Can be null if server was unable to fill the page in this request, or can be empty if there are no more objects when continuation token is null. |
|
| timestamps |
string[] |
The timestamps of the values of the time series. If an aggregation over intervals is used, timestamps represent the start of corresponding intervals. If events are retrieved, timestamps are values of timestamp $ts property of events. Can be null if server was unable to fill the page in this request, or can be empty if there are no more objects when continuation token is null. |
TimeSeriesAggregateCategory
Category used in categorical variables. A category is defined by 'label' and the 'values' that are assigned this label.
| Name | Type | Description |
|---|---|---|
| label |
string |
The name of the category which will be used in constructing the output variable names. |
| values |
object[] |
The list of values that a category maps to. Can be either a unique list of string or list of long. |
TimeSeriesDefaultCategory
Represents the default category.
| Name | Type | Description |
|---|---|---|
| label |
string |
The name of the default category which will be assigned to the values that does not match any of those that are defined in the 'categories'. |
TsiError
Information about an API error.
| Name | Type | Description |
|---|---|---|
| error |
A particular API error with an error code and a message. |
TsiErrorBody
A particular API error with an error code and a message.
| Name | Type | Description |
|---|---|---|
| code |
string |
Language-independent, human-readable string that defines a service-specific error code. This code serves as a more specific indicator for the HTTP error code specified in the response. Can be used to programmatically handle specific error cases. |
| details |
Contains additional error information. May be null. |
|
| innerError |
Contains more specific error that narrows down the cause. May be null. |
|
| message |
string |
Human-readable, language-independent representation of the error. It is intended as an aid to developers and is not suitable for exposure to end users. |
| target |
string |
Target of the particular error (for example, the name of the property in error). May be null. |
TsiErrorDetails
Additional error information.
| Name | Type | Description |
|---|---|---|
| code |
string |
Language-independent, human-readable string that defines a service-specific error code. This code serves as a more specific indicator for the HTTP error code specified in the response. Can be used to programmatically handle specific error cases. |
| message |
string |
Human-readable, language-independent representation of the error. It is intended as an aid to developers and is not suitable for exposure to end users. |
Tsx
Time series expression (TSX) written as a single string. Examples: "$event.Status.String='Good'", "avg($event.Temperature)". Refer to the documentation on how to write time series expressions.
| Name | Type | Description |
|---|---|---|
| tsx |
string |
Time series expression (TSX) written as a single string. Examples: "$event.Status.String='Good'", "avg($event.Temperature)". Refer to the documentation on how to write time series expressions. |