141 lines
8.4 KiB
Plaintext
141 lines
8.4 KiB
Plaintext
[[search-aggregations]]
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== Aggregations
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Aggregations grew out of the <<search-facets, facets>> module and the long experience of how users use it
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(and would like to use it) for real-time data analytics purposes. As such, it serves as the next generation
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replacement for the functionality we currently refer to as "faceting".
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<<search-facets, Facets>> provide a great way to aggregate data within a document set context.
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This context is defined by the executed query in combination with the different levels of filters that can be defined
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(filtered queries, top level filters, and facet level filters). While powerful, their implementation is not designed
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from ground up to support complex aggregations and thus limited.
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.Are facets deprecated?
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**********************************
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As the functionality facets offer is a subset of the the one offered by aggregations, over time, we would like to
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see users move to aggregations for all realtime data analytics. That said, we are well aware that such
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transitions/migrations take time, and for this reason we are keeping the facets around for the time being.
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Nonetheless, facets are and should be considered deprecated and will likely be removed in one of the future major
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releases.
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**********************************
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The aggregations module breaks the barriers the current facet implementation put in place. The new name ("Aggregations")
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also indicate the intention here - a generic yet extremely powerful framework for building aggregations - any types of
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aggregations.
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An aggregation can be seen as a _unit-of-work_ that builds analytic information over a set of documents. The context of
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the execution defines what this document set is (e.g. a top level aggregation executes within the context of the executed
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query/filters of the search request).
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There are many different types of aggregations, each with its own purpose and output. To better understand these types,
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it is often easier to break them into two main families:
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_Bucketing_::
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A family of aggregations that build buckets, where each bucket is associated with a _key_ and a document
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criteria. When the aggregations is executed, the buckets criterias are evaluated on every document in
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the context and when matches, the document is considered to "fall in" the relevant bucket. By the end of
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the aggreagation process, we'll end up with a list of buckets - each one with a set of documents that
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"belong" to it.
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_Metric_::
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Aggregations that keep track and compute metrics over a set of documents
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The interesting part comes next, since each bucket effectively defines a document set (all documents belonging to
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the bucket), one can potentially associated aggregations on the bucket level, and those will execute within the context
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of that bucket. This is where the real power of aggregations kicks in: *aggregations can be nested!*
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NOTE: Bucketing aggregations can have sub-aggregations (bucketing or metric). The sub aggregations will be computed for
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each of the buckets their parent aggregation generates. There is not hard limit on the level/depth of nested
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aggregations (one can nest an aggregation under a "parent" aggregation which is itself a sub-aggregation of
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another higher aggregations)
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[float]
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=== Structuring Aggregations
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The following snippet captures the basic structure of aggregations:
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[source,js]
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--------------------------------------------------
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"aggregations" : {
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"<aggregation_name>" : {
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"<aggregation_type>" : {
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<aggregation_body>
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}
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[,"aggregations" : { [<sub_aggregation>]+ } ]?
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}
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[,"<aggregation_name_2>" : { ... } ]*
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}
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--------------------------------------------------
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The `aggregations` object (a.k.a `aggs` for short) in the json holds the aggregations to be computed. Each aggregation
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is associated with a logical name that the user defines (e.g. if the aggregation computes the average price, then it'll
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make sense to name it `avg_price`). These logical names will also be used to uniquely identify the aggregations in the
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response. Each aggregation has a specific type (`<aggregation_type>` in the above snippet) and is typically the first
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key within the named aggregation body. Each type of aggregation define its own body, depending on the nature of the
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aggregation (eg. an `avg` aggregation on a specific field will define the field on which the avg will be calculated).
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At the same level of the aggregation type definition, one can optionally define a set of additional aggregations,
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though this only makes sense if the aggregation you defined is of a bucketing nature. In this scenario, the
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sub-aggregations you define on the bucketing aggregation level will be computed for all the buckets built by the
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bucketing aggregation. For example, if the you define a set of aggregations under the `range` aggregation, the
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sub-aggregations will be computed for each of the range buckets that are defined.
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[float]
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==== Values Source
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Some aggregations work on values extracted from the aggregated documents. Typically, the values will be extracted from
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a sepcific document field which is set under the `field` settings for the aggrations. It is also possible to define a
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<<modules-scripting,`script`>> that will generate the values (per document).
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When both `field` and `script` settings are configured for the aggregation, the script will be treated as a
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`value script`. While normal scripts are evaluated on a document level (i.e. the script has access to all the data
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associated with the document), value scripts are evaluated on the *value* level. In this mode, the values are extracted
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from the configured `field` and the `script` is used to apply a "transformation" over these value/s
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["NOTE",id="aggs-script-note"]
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===============================
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When working with scripts, the `lang` and `params` settings can also be defined. The former defines the scripting
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language that is used (assuming the proper language is available in es either by default or as a plugin). The latter
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enables defining all the "dynamic" expressions in the script as parameters, and by that keep the script itself static
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between calls (this will ensure the use of the cached compiled scripts in elasticsearch).
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===============================
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Scripts can generate a single value or multiple values per documents. When generating multiple values, once can use the
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`script_values_sorted` settings to indicate whether these values are sorted or not. Internally, elasticsearch can
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perform optimizations when dealing with sorted values (for example, with the `min` aggregations, knowing the values are
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sorted, elasticsearch will skip the iterations over all the values and rely on the first value in the list to be the
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minimum value among all other values associated with the same document).
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[float]
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=== Metrics Aggregations
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The aggregations in this family compute metrics based on values extracted in one way or another from the documents that
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are being aggregated. The values are typically extracted from the fields of the document (using the field data), but
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can also be generated using scripts. Some aggregations output a single metric (e.g. `avg`) and are called `single-value
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metrics aggregation`, others generate multiple metrics (e.g. `stats`) and are called `multi-value metrics aggregation`.
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The distinction between single-value and multi-value metrics aggregations plays a role when these aggregations serve as
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direct sub-aggregations of some bucket aggregations (some bucket aggregation enable you to sort the returned buckets based
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on the metrics in each bucket).
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[float]
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=== Bucket Aggregations
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Bucket aggregations don't calculate metrics over fields like the metrics aggregations do, but instead, they create
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buckets of documents. Each bucket is associated with a criteria (depends on the aggregation type) that determines
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whether or not a document in the current context "falls" in it. In other words, the buckets effectively define document
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sets. In addition to the buckets themselves, the `bucket` aggregations also compute and return the number of documents
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that "fell in" each bucket.
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Bucket aggregations, as opposed to `metrics` aggregations, can hold sub-aggregations. These sub aggregations will be
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aggregated for each of the buckets created by their "parent" bucket aggregation.
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There are different bucket aggregators, each with a different "bucketing" strategy. Some define a single bucket, some
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define fixed number of multiple buckets, and others dynamically create the buckets during the aggregation process.
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include::aggregations/metrics.asciidoc[]
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include::aggregations/bucket.asciidoc[]
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