Circonus aggregations let you tap into our powerful analytics engine to analyze your data and extract statistics from it.
The use cases for aggregations vary from analyzing data in real time to taking some action and visualizing data within a dashboard.
Circonus can perform aggregations on massive datasets in milliseconds. Compared to queries, aggregations consume more CPU cycles and memory.
Aggregations on text fields
By default, Circonus doesn't support aggregations on a text field. Because text fields are tokenized, an aggregation on a text field has to reverse the tokenization process back to its original string and then formulate an aggregation based on that. This type of operation consumes significant memory and degrades cluster performance.
While you can enable aggregations on text fields by setting the
fielddata parameter to
true in the mapping, the aggregations are still based on the tokenized words and not on the raw text.
We recommend keeping a raw version of the text field as a
keyword field that you can aggregate.
In this case, you can perform aggregations on the
title.raw field, instead of on the
General aggregation structure
The structure of an aggregation query is as follows:
If you’re only interested in the aggregation result and not in the results of the query, set
size to 0.
aggs property (you can use
aggregations if you want), you can define any number of aggregations. Each aggregation is defined by its name and one of the types of aggregations that Circonus supports.
The name of the aggregation helps you to distinguish between different aggregations in the response. The
AGG_TYPE property is where you specify the type of aggregation.
This section uses sample eCommerce and web log data. To add the sample data, log in to Circonus, navigate to Home within the main menu, and then choose Try our sample data. For Sample eCommerce orders and Sample weblogs, choose Add data.
To find the average value of the
The aggregation block in the response shows the average value for the
Types of aggregations
There are three main types of aggregations:
- Metric aggregations - Calculate metrics such as
avgon numeric fields.
- Bucket aggregations - Sort query results into groups based on some criteria.
- Pipeline aggregations - Pipe the output of one aggregation as an input to another.
Aggregations within aggregations are called nested or sub-aggregations.
Metric aggregations produce simple results and can't contain nested aggregations.
Bucket aggregations produce buckets of documents that you can nest in other aggregations. You can perform complex analysis on your data by nesting metric and bucket aggregations within bucket aggregations.
General nested aggregation syntax
aggs keyword begins a new nested aggregation. The syntax of the parent aggregation and the nested aggregation is the same. Nested aggregations run in the context of the preceding parent aggregations.
You can also pair your aggregations with search queries to narrow down things you’re trying to analyze before aggregating. If you don't add a query, Circonus implicitly uses the