--- title: Aggregate RUM events description: Datadog, the leading service for cloud-scale monitoring. breadcrumbs: Docs > API Reference > RUM --- # Aggregate RUM events{% #aggregate-rum-events %} Copy pageCopied {% tab title="v2" %} | Datadog site | API endpoint | | ----------------- | ----------------------------------------------------------------- | | ap1.datadoghq.com | POST https://api.ap1.datadoghq.com/api/v2/rum/analytics/aggregate | | ap2.datadoghq.com | POST https://api.ap2.datadoghq.com/api/v2/rum/analytics/aggregate | | app.datadoghq.eu | POST https://api.datadoghq.eu/api/v2/rum/analytics/aggregate | | app.ddog-gov.com | POST https://api.ddog-gov.com/api/v2/rum/analytics/aggregate | | us2.ddog-gov.com | POST https://api.us2.ddog-gov.com/api/v2/rum/analytics/aggregate | | app.datadoghq.com | POST https://api.datadoghq.com/api/v2/rum/analytics/aggregate | | us3.datadoghq.com | POST https://api.us3.datadoghq.com/api/v2/rum/analytics/aggregate | | us5.datadoghq.com | POST https://api.us5.datadoghq.com/api/v2/rum/analytics/aggregate | ### Overview The API endpoint to aggregate RUM events into buckets of computed metrics and timeseries. This endpoint requires the `rum_apps_read` permission. ### Request #### Body Data (required) {% tab title="Model" %} | Parent field | Field | Type | Description | | ------------ | ----------------------------- | ------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | | compute | [object] | The list of metrics or timeseries to compute for the retrieved buckets. | | compute | aggregation [*required*] | enum | An aggregation function. Allowed enum values: `count,cardinality,pc75,pc90,pc95,pc98,pc99,sum,min,max` | | compute | interval | string | The time buckets' size (only used for type=timeseries) Defaults to a resolution of 150 points. | | compute | metric | string | The metric to use. | | compute | type | enum | The type of compute. Allowed enum values: `timeseries,total` | | | filter | object | The search and filter query settings. | | filter | from | string | The minimum time for the requested events; supports date (in [ISO 8601](https://www.w3.org/TR/NOTE-datetime) format with full date, hours, minutes, and the `Z` UTC indicator - seconds and fractional seconds are optional), math, and regular timestamps (in milliseconds). | | filter | query | string | The search query following the RUM search syntax. | | filter | to | string | The maximum time for the requested events; supports date (in [ISO 8601](https://www.w3.org/TR/NOTE-datetime) format with full date, hours, minutes, and the `Z` UTC indicator - seconds and fractional seconds are optional), math, and regular timestamps (in milliseconds). | | | group_by | [object] | The rules for the group by. | | group_by | facet [*required*] | string | The name of the facet to use (required). | | group_by | histogram | object | Used to perform a histogram computation (only for measure facets). Note: At most 100 buckets are allowed, the number of buckets is (max - min)/interval. | | histogram | interval [*required*] | double | The bin size of the histogram buckets. | | histogram | max [*required*] | double | The maximum value for the measure used in the histogram (values greater than this one are filtered out). | | histogram | min [*required*] | double | The minimum value for the measure used in the histogram (values smaller than this one are filtered out). | | group_by | limit | int64 | The maximum buckets to return for this group-by. | | group_by | missing | | The value to use for logs that don't have the facet used to group by. | | missing | Option 1 | string | The missing value to use if there is string valued facet. | | missing | Option 2 | double | The missing value to use if there is a number valued facet. | | group_by | sort | object | A sort rule. | | sort | aggregation | enum | An aggregation function. Allowed enum values: `count,cardinality,pc75,pc90,pc95,pc98,pc99,sum,min,max` | | sort | metric | string | The metric to sort by (only used for `type=measure`). | | sort | order | enum | The order to use, ascending or descending. Allowed enum values: `asc,desc` | | sort | type | enum | The type of sorting algorithm. Allowed enum values: `alphabetical,measure` | | group_by | total | | A resulting object to put the given computes in over all the matching records. | | total | Option 1 | boolean | If set to true, creates an additional bucket labeled "$facet_total". | | total | Option 2 | string | A string to use as the key value for the total bucket. | | total | Option 3 | double | A number to use as the key value for the total bucket. | | | options | object | Global query options that are used during the query. Note: Only supply timezone or time offset, not both. Otherwise, the query fails. | | options | time_offset | int64 | The time offset (in seconds) to apply to the query. | | options | timezone | string | The timezone can be specified as GMT, UTC, an offset from UTC (like UTC+1), or as a Timezone Database identifier (like America/New_York). | | | page | object | Paging attributes for listing events. | | page | cursor | string | List following results with a cursor provided in the previous query. | | page | limit | int32 | Maximum number of events in the response. | {% /tab %} {% tab title="Example" %} ```json { "compute": [ { "aggregation": "pc90", "metric": "@view.time_spent", "type": "total" } ], "filter": { "from": "now-15m", "query": "@type:view AND @session.type:user", "to": "now" }, "group_by": [ { "facet": "@view.time_spent", "limit": 10, "total": false } ], "options": { "timezone": "GMT" }, "page": { "limit": 25 } } ``` {% /tab %} ### Response {% tab title="200" %} OK {% tab title="Model" %} The response object for the RUM events aggregate API endpoint. | Parent field | Field | Type | Description | | -------------------- | ---------- | ------------- | ----------------------------------------------------------------------------------------------------------------------------------------- | | | data | object | The query results. | | data | buckets | [object] | The list of matching buckets, one item per bucket. | | buckets | by | object | The key-value pairs for each group-by. | | additionalProperties | | string | The values for each group-by. | | buckets | computes | object | A map of the metric name to value for regular compute, or a list of values for a timeseries. | | additionalProperties | | | A bucket value, can be either a timeseries or a single value. | | | Option 1 | string | A single string value. | | | Option 2 | double | A single number value. | | | Option 3 | [object] | A timeseries array. | | Option 3 | time | date-time | The time value for this point. | | Option 3 | value | double | The value for this point. | | | links | object | Links attributes. | | links | next | string | Link for the next set of results. Note that the request can also be made using the POST endpoint. | | | meta | object | The metadata associated with a request. | | meta | elapsed | int64 | The time elapsed in milliseconds. | | meta | page | object | Paging attributes. | | page | after | string | The cursor to use to get the next results, if any. To make the next request, use the same parameters with the addition of `page[cursor]`. | | meta | request_id | string | The identifier of the request. | | meta | status | enum | The status of the response. Allowed enum values: `done,timeout` | | meta | warnings | [object] | A list of warnings (non-fatal errors) encountered. Partial results may return if warnings are present in the response. | | warnings | code | string | A unique code for this type of warning. | | warnings | detail | string | A detailed explanation of this specific warning. | | warnings | title | string | A short human-readable summary of the warning. | {% /tab %} {% tab title="Example" %} ```json { "data": { "buckets": [ { "by": { "": "string" }, "computes": { "": { "description": "undefined", "type": "undefined" } } } ] }, "links": { "next": "https://app.datadoghq.com/api/v2/rum/event?filter[query]=foo\u0026page[cursor]=eyJzdGFydEF0IjoiQVFBQUFYS2tMS3pPbm40NGV3QUFBQUJCV0V0clRFdDZVbG8zY3pCRmNsbHJiVmxDWlEifQ==" }, "meta": { "elapsed": 132, "page": { "after": "eyJzdGFydEF0IjoiQVFBQUFYS2tMS3pPbm40NGV3QUFBQUJCV0V0clRFdDZVbG8zY3pCRmNsbHJiVmxDWlEifQ==" }, "request_id": "MWlFUjVaWGZTTTZPYzM0VXp1OXU2d3xLSVpEMjZKQ0VKUTI0dEYtM3RSOFVR", "status": "done", "warnings": [ { "code": "unknown_index", "detail": "indexes: foo, bar", "title": "One or several indexes are missing or invalid, results hold data from the other indexes" } ] } } ``` {% /tab %} {% /tab %} {% tab title="400" %} Bad Request {% tab title="Model" %} API error response. | Field | Type | Description | | ------------------------ | -------- | ----------------- | | errors [*required*] | [string] | A list of errors. | {% /tab %} {% tab title="Example" %} ```json { "errors": [ "Bad Request" ] } ``` {% /tab %} {% /tab %} {% tab title="403" %} Not Authorized {% tab title="Model" %} API error response. | Field | Type | Description | | ------------------------ | -------- | ----------------- | | errors [*required*] | [string] | A list of errors. | {% /tab %} {% tab title="Example" %} ```json { "errors": [ "Bad Request" ] } ``` {% /tab %} {% /tab %} {% tab title="429" %} Too many requests {% tab title="Model" %} API error response. | Field | Type | Description | | ------------------------ | -------- | ----------------- | | errors [*required*] | [string] | A list of errors. | {% /tab %} {% tab title="Example" %} ```json { "errors": [ "Bad Request" ] } ``` {% /tab %} {% /tab %} ### Code Example ##### \## default # \# Curl command curl -X POST "https://api.datadoghq.com/api/v2/rum/analytics/aggregate" \ -H "Accept: application/json" \ -H "Content-Type: application/json" \ -H "DD-API-KEY: ${DD_API_KEY}" \ -H "DD-APPLICATION-KEY: ${DD_APP_KEY}" \ -d @- << EOF { "compute": [ { "aggregation": "pc90", "interval": "5m", "metric": "@duration", "type": "timeseries" } ], "filter": { "from": "now-15m", "query": "@type:session AND @session.type:user", "to": "now" }, "group_by": [ { "facet": "@view.time_spent", "histogram": { "interval": 10, "max": 100, "min": 50 }, "sort": { "aggregation": "count", "order": "asc" } } ], "options": { "timezone": "GMT" }, "page": { "cursor": "eyJzdGFydEF0IjoiQVFBQUFYS2tMS3pPbm40NGV3QUFBQUJCV0V0clRFdDZVbG8zY3pCRmNsbHJiVmxDWlEifQ==", "limit": 25 } } EOF ##### ```go // Aggregate RUM events returns "OK" response package main import ( "context" "encoding/json" "fmt" "os" "github.com/DataDog/datadog-api-client-go/v2/api/datadog" "github.com/DataDog/datadog-api-client-go/v2/api/datadogV2" ) func main() { body := datadogV2.RUMAggregateRequest{ Compute: []datadogV2.RUMCompute{ { Aggregation: datadogV2.RUMAGGREGATIONFUNCTION_PERCENTILE_90, Metric: datadog.PtrString("@view.time_spent"), Type: datadogV2.RUMCOMPUTETYPE_TOTAL.Ptr(), }, }, Filter: &datadogV2.RUMQueryFilter{ From: datadog.PtrString("now-15m"), Query: datadog.PtrString("@type:view AND @session.type:user"), To: datadog.PtrString("now"), }, GroupBy: []datadogV2.RUMGroupBy{ { Facet: "@view.time_spent", Limit: datadog.PtrInt64(10), Total: &datadogV2.RUMGroupByTotal{ RUMGroupByTotalBoolean: datadog.PtrBool(false)}, }, }, Options: &datadogV2.RUMQueryOptions{ Timezone: datadog.PtrString("GMT"), }, Page: &datadogV2.RUMQueryPageOptions{ Limit: datadog.PtrInt32(25), }, } ctx := datadog.NewDefaultContext(context.Background()) configuration := datadog.NewConfiguration() apiClient := datadog.NewAPIClient(configuration) api := datadogV2.NewRUMApi(apiClient) resp, r, err := api.AggregateRUMEvents(ctx, body) if err != nil { fmt.Fprintf(os.Stderr, "Error when calling `RUMApi.AggregateRUMEvents`: %v\n", err) fmt.Fprintf(os.Stderr, "Full HTTP response: %v\n", r) } responseContent, _ := json.MarshalIndent(resp, "", " ") fmt.Fprintf(os.Stdout, "Response from `RUMApi.AggregateRUMEvents`:\n%s\n", responseContent) } ``` #### Instructions First [install the library and its dependencies](https://docs.datadoghq.com/api/latest.md?code-lang=go) and then save the example to `main.go` and run following commands: DD_SITE="datadoghq.com" DD_API_KEY="" DD_APP_KEY="" go run "main.go" ##### ```java // Aggregate RUM events returns "OK" response import com.datadog.api.client.ApiClient; import com.datadog.api.client.ApiException; import com.datadog.api.client.v2.api.RumApi; import com.datadog.api.client.v2.model.RUMAggregateRequest; import com.datadog.api.client.v2.model.RUMAggregationFunction; import com.datadog.api.client.v2.model.RUMAnalyticsAggregateResponse; import com.datadog.api.client.v2.model.RUMCompute; import com.datadog.api.client.v2.model.RUMComputeType; import com.datadog.api.client.v2.model.RUMGroupBy; import com.datadog.api.client.v2.model.RUMGroupByTotal; import com.datadog.api.client.v2.model.RUMQueryFilter; import com.datadog.api.client.v2.model.RUMQueryOptions; import com.datadog.api.client.v2.model.RUMQueryPageOptions; import java.util.Collections; public class Example { public static void main(String[] args) { ApiClient defaultClient = ApiClient.getDefaultApiClient(); RumApi apiInstance = new RumApi(defaultClient); RUMAggregateRequest body = new RUMAggregateRequest() .compute( Collections.singletonList( new RUMCompute() .aggregation(RUMAggregationFunction.PERCENTILE_90) .metric("@view.time_spent") .type(RUMComputeType.TOTAL))) .filter( new RUMQueryFilter() .from("now-15m") .query("@type:view AND @session.type:user") .to("now")) .groupBy( Collections.singletonList( new RUMGroupBy() .facet("@view.time_spent") .limit(10L) .total(new RUMGroupByTotal(false)))) .options(new RUMQueryOptions().timezone("GMT")) .page(new RUMQueryPageOptions().limit(25)); try { RUMAnalyticsAggregateResponse result = apiInstance.aggregateRUMEvents(body); System.out.println(result); } catch (ApiException e) { System.err.println("Exception when calling RumApi#aggregateRUMEvents"); System.err.println("Status code: " + e.getCode()); System.err.println("Reason: " + e.getResponseBody()); System.err.println("Response headers: " + e.getResponseHeaders()); e.printStackTrace(); } } } ``` #### Instructions First [install the library and its dependencies](https://docs.datadoghq.com/api/latest.md?code-lang=java) and then save the example to `Example.java` and run following commands: DD_SITE="datadoghq.com" DD_API_KEY="" DD_APP_KEY="" java "Example.java" ##### ```python """ Aggregate RUM events returns "OK" response """ from datadog_api_client import ApiClient, Configuration from datadog_api_client.v2.api.rum_api import RUMApi from datadog_api_client.v2.model.rum_aggregate_request import RUMAggregateRequest from datadog_api_client.v2.model.rum_aggregation_function import RUMAggregationFunction from datadog_api_client.v2.model.rum_compute import RUMCompute from datadog_api_client.v2.model.rum_compute_type import RUMComputeType from datadog_api_client.v2.model.rum_group_by import RUMGroupBy from datadog_api_client.v2.model.rum_query_filter import RUMQueryFilter from datadog_api_client.v2.model.rum_query_options import RUMQueryOptions from datadog_api_client.v2.model.rum_query_page_options import RUMQueryPageOptions body = RUMAggregateRequest( compute=[ RUMCompute( aggregation=RUMAggregationFunction.PERCENTILE_90, metric="@view.time_spent", type=RUMComputeType.TOTAL, ), ], filter=RUMQueryFilter( _from="now-15m", query="@type:view AND @session.type:user", to="now", ), group_by=[ RUMGroupBy( facet="@view.time_spent", limit=10, total=False, ), ], options=RUMQueryOptions( timezone="GMT", ), page=RUMQueryPageOptions( limit=25, ), ) configuration = Configuration() with ApiClient(configuration) as api_client: api_instance = RUMApi(api_client) response = api_instance.aggregate_rum_events(body=body) print(response) ``` #### Instructions First [install the library and its dependencies](https://docs.datadoghq.com/api/latest.md?code-lang=python) and then save the example to `example.py` and run following commands: DD_SITE="datadoghq.com" DD_API_KEY="" DD_APP_KEY="" python3 "example.py" ##### ```ruby # Aggregate RUM events returns "OK" response require "datadog_api_client" api_instance = DatadogAPIClient::V2::RUMAPI.new body = DatadogAPIClient::V2::RUMAggregateRequest.new({ compute: [ DatadogAPIClient::V2::RUMCompute.new({ aggregation: DatadogAPIClient::V2::RUMAggregationFunction::PERCENTILE_90, metric: "@view.time_spent", type: DatadogAPIClient::V2::RUMComputeType::TOTAL, }), ], filter: DatadogAPIClient::V2::RUMQueryFilter.new({ from: "now-15m", query: "@type:view AND @session.type:user", to: "now", }), group_by: [ DatadogAPIClient::V2::RUMGroupBy.new({ facet: "@view.time_spent", limit: 10, total: false, }), ], options: DatadogAPIClient::V2::RUMQueryOptions.new({ timezone: "GMT", }), page: DatadogAPIClient::V2::RUMQueryPageOptions.new({ limit: 25, }), }) p api_instance.aggregate_rum_events(body) ``` #### Instructions First [install the library and its dependencies](https://docs.datadoghq.com/api/latest.md?code-lang=ruby) and then save the example to `example.rb` and run following commands: DD_SITE="datadoghq.com" DD_API_KEY="" DD_APP_KEY="" rb "example.rb" ##### ```rust // Aggregate RUM events returns "OK" response use datadog_api_client::datadog; use datadog_api_client::datadogV2::api_rum::RUMAPI; use datadog_api_client::datadogV2::model::RUMAggregateRequest; use datadog_api_client::datadogV2::model::RUMAggregationFunction; use datadog_api_client::datadogV2::model::RUMCompute; use datadog_api_client::datadogV2::model::RUMComputeType; use datadog_api_client::datadogV2::model::RUMGroupBy; use datadog_api_client::datadogV2::model::RUMGroupByTotal; use datadog_api_client::datadogV2::model::RUMQueryFilter; use datadog_api_client::datadogV2::model::RUMQueryOptions; use datadog_api_client::datadogV2::model::RUMQueryPageOptions; #[tokio::main] async fn main() { let body = RUMAggregateRequest::new() .compute(vec![RUMCompute::new(RUMAggregationFunction::PERCENTILE_90) .metric("@view.time_spent".to_string()) .type_(RUMComputeType::TOTAL)]) .filter( RUMQueryFilter::new() .from("now-15m".to_string()) .query("@type:view AND @session.type:user".to_string()) .to("now".to_string()), ) .group_by(vec![RUMGroupBy::new("@view.time_spent".to_string()) .limit(10) .total(RUMGroupByTotal::RUMGroupByTotalBoolean(false))]) .options(RUMQueryOptions::new().timezone("GMT".to_string())) .page(RUMQueryPageOptions::new().limit(25)); let configuration = datadog::Configuration::new(); let api = RUMAPI::with_config(configuration); let resp = api.aggregate_rum_events(body).await; if let Ok(value) = resp { println!("{:#?}", value); } else { println!("{:#?}", resp.unwrap_err()); } } ``` #### Instructions First [install the library and its dependencies](https://docs.datadoghq.com/api/latest.md?code-lang=rust) and then save the example to `src/main.rs` and run following commands: DD_SITE="datadoghq.com" DD_API_KEY="" DD_APP_KEY="" cargo run ##### ```typescript /** * Aggregate RUM events returns "OK" response */ import { client, v2 } from "@datadog/datadog-api-client"; const configuration = client.createConfiguration(); const apiInstance = new v2.RUMApi(configuration); const params: v2.RUMApiAggregateRUMEventsRequest = { body: { compute: [ { aggregation: "pc90", metric: "@view.time_spent", type: "total", }, ], filter: { from: "now-15m", query: "@type:view AND @session.type:user", to: "now", }, groupBy: [ { facet: "@view.time_spent", limit: 10, total: false, }, ], options: { timezone: "GMT", }, page: { limit: 25, }, }, }; apiInstance .aggregateRUMEvents(params) .then((data: v2.RUMAnalyticsAggregateResponse) => { console.log( "API called successfully. Returned data: " + JSON.stringify(data) ); }) .catch((error: any) => console.error(error)); ``` #### Instructions First [install the library and its dependencies](https://docs.datadoghq.com/api/latest.md?code-lang=typescript) and then save the example to `example.ts` and run following commands: DD_SITE="datadoghq.com" DD_API_KEY="" DD_APP_KEY="" tsc "example.ts" {% /tab %}