With nested aggregation, you can complete a NRQL query then make additional computations using the results of that query. Nested aggregation provides NRQL capabilities similar to the class of SQL subqueries or subselects where the subquery is in the FROM clause of the outer query.
Answer complex questions with a single query
Nested aggregation can help you to answer questions like these without building multiple queries:
- Can I count the requests per minute for my application, then get the maximum requests per minute for the last hour?
- Can I compute the average CPU usage of all my servers, and list only the ones with usage over 90%?
- From all my user sessions, can I figure out what percentage bounced immediately?
Nested aggregation query structure and clauses
Every NRQL query must begin with a
SELECT statement or a
FROM clause. A nested aggregation query uses both a
SELECT statement and a
FROM clause and applies them to a whole query or queries contained within parentheses.
A complete and properly formatted nested aggregation query will look something like this:
SELECT function(attribute) FROM ( SELECT function(attribute) FROM dataType WHERE attribute TIMESERIES integer units )
A few other details about query and clause behavior:
- Nested queries can be more than two levels.
FACETcan be applied to any part of the nested query, and don’t need to be identical at all levels.
COMPARE WITHclauses apply to the entire query and can only be used at the outermost level.
Nested aggregation query examples
Here are some examples of nested queries.
- Total transactions and highest one-minute response rate
In this example, the inner query first counts the transactions for myApp for each of the last 60 minutes, then the outer query returns the highest 1-minute request rate.
Also, by giving a name to the result of the first query (as rpm), you can create a label for the value returned. Without adding the label, this query will return the value as count for use in the outer query.
SELECT max(rpm) FROM ( SELECT count(*) as rpm FROM Transaction WHERE appName = 'myApp' TIMESERIES 1 minute )
- Average CPU usage and CPU usage over 90%
In this example, the inner query calculates the average CPU usage for all hosts, then the outer query filters the results down to only hosts with CPU usage over a risky threshold (90%).
SELECT hostname, cpu FROM ( SELECT average(cpuPercent) as cpu FROM SystemSample FACET hostname TIMESERIES integer units ) WHERE cpu > 90
- Page views in each user session and number of sessions with only one page view
In this example, the inner query calculates the number of PageView events in each user session, then the outer query computes what percentage of those sessions only had a single associated view.
SELECT percentage(count (*), WHERE sessionLength = 1) FROM ( SELECT count(*) as sessionLength FROM PageView FACET session )