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This implements `INLINESTATS`. Most of the heavy lifting is done by `LOOKUP`, with this change mostly adding a new abstraction to logical plans, and interface I'm calling `Phased`. Implementing this interface allows a logical plan node to cut the query into phases. `INLINESTATS` implements it by asking for a "first phase" that's the same query, up to `INLINESTATS`, but with `INLINESTATS` replaced with `STATS`. The next phase replaces the `INLINESTATS` with a `LOOKUP` on the results of the first phase. So, this query: ``` FROM foo | EVAL bar = a * b | INLINESTATS m = MAX(bar) BY b | WHERE m = bar | LIMIT 1 ``` gets split into ``` FROM foo | EVAL bar = a * b | STATS m = MAX(bar) BY b ``` followed by ``` FROM foo | EVAL bar = a * b | LOOKUP (results of m = MAX(bar) BY b) ON b | WHERE m = bar | LIMIT 1 ```
102 lines
3 KiB
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102 lines
3 KiB
Text
[discrete]
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[[esql-inlinestats-by]]
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=== `INLINESTATS ... BY`
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experimental::["INLINESTATS is highly experimental and only available in SNAPSHOT versions."]
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The `INLINESTATS` command calculates an aggregate result and adds new columns
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with the result to the stream of input data.
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**Syntax**
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[source,esql]
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----
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INLINESTATS [column1 =] expression1[, ..., [columnN =] expressionN]
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[BY grouping_expression1[, ..., grouping_expressionN]]
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----
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*Parameters*
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`columnX`::
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The name by which the aggregated value is returned. If omitted, the name is
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equal to the corresponding expression (`expressionX`). If multiple columns
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have the same name, all but the rightmost column with this name will be ignored.
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`expressionX`::
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An expression that computes an aggregated value. If its name coincides with one
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of the computed columns, that column will be ignored.
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`grouping_expressionX`::
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An expression that outputs the values to group by.
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NOTE: Individual `null` values are skipped when computing aggregations.
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*Description*
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The `INLINESTATS` command calculates an aggregate result and merges that result
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back into the stream of input data. Without the optional `BY` clause this will
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produce a single result which is appended to each row. With a `BY` clause this
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will produce one result per grouping and merge the result into the stream based on
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matching group keys.
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All of the <<esql-agg-functions,aggregation functions>> are supported.
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*Examples*
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Find the employees that speak the most languages (it's a tie!):
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[source.merge.styled,esql]
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----
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include::{esql-specs}/inlinestats.csv-spec[tag=max-languages]
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----
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[%header.monospaced.styled,format=dsv,separator=|]
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|===
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include::{esql-specs}/inlinestats.csv-spec[tag=max-languages-result]
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|===
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Find the longest tenured employee who's last name starts with each letter of the alphabet:
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[source.merge.styled,esql]
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----
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include::{esql-specs}/inlinestats.csv-spec[tag=longest-tenured-by-first]
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----
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[%header.monospaced.styled,format=dsv,separator=|]
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|===
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include::{esql-specs}/inlinestats.csv-spec[tag=longest-tenured-by-first-result]
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|===
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Find the northern and southern most airports:
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[source.merge.styled,esql]
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----
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include::{esql-specs}/inlinestats.csv-spec[tag=extreme-airports]
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----
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[%header.monospaced.styled,format=dsv,separator=|]
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|===
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include::{esql-specs}/inlinestats.csv-spec[tag=extreme-airports-result]
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|===
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NOTE: Our test data doesn't have many "small" airports.
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If a `BY` field is multivalued then `INLINESTATS` will put the row in *each*
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bucket like <<esql-stats-by>>:
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[source.merge.styled,esql]
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----
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include::{esql-specs}/inlinestats.csv-spec[tag=mv-group]
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----
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[%header.monospaced.styled,format=dsv,separator=|]
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|===
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include::{esql-specs}/inlinestats.csv-spec[tag=mv-group-result]
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|===
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To treat each group key as its own row use <<esql-mv_expand>> before `INLINESTATS`:
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[source.merge.styled,esql]
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----
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include::{esql-specs}/inlinestats.csv-spec[tag=mv-expand]
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----
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[%header.monospaced.styled,format=dsv,separator=|]
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|===
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include::{esql-specs}/inlinestats.csv-spec[tag=mv-expand-result]
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|===
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