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Update aggregation reference docs for 7.13 (elastic#101913)
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* Update aggregation reference docs for 7.13

* Add more reference about filtered metrics
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Wylie Conlon authored and kibanamachine committed Jun 10, 2021
1 parent 15fe0f9 commit b6f7736
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18 changes: 12 additions & 6 deletions docs/user/dashboard/aggregation-reference.asciidoc
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Expand Up @@ -188,6 +188,12 @@ For information about {es} metrics aggregations, refer to {ref}/search-aggregati

| Type | Agg-based | Markdown | Lens | TSVB

| Metrics with filters
|
^| X
|
|

| Average
^| X
^| X
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| Percentiles
^| X
^| X
|
^| X
^| X

| Percentiles Rank
Expand All @@ -230,10 +236,10 @@ For information about {es} metrics aggregations, refer to {ref}/search-aggregati
|
^| X

| Top hit
| Top hit (Last value)
^| X
^| X
^| X
|
^| X

| Value count
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| Derivative
^| X
^| X
|
^| X
^| X

| Max bucket
Expand All @@ -290,13 +296,13 @@ For information about {es} pipeline aggregations, refer to {ref}/search-aggregat
| Moving average
^| X
^| X
|
^| X
^| X

| Cumulative sum
^| X
^| X
|
^| X
^| X

| Bucket script
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14 changes: 12 additions & 2 deletions docs/user/dashboard/lens.asciidoc
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Expand Up @@ -147,14 +147,24 @@ For the answers to common *Lens* questions, review the following.

[float]
[[kql-]]
===== When should I use the Filter function instead of KQL filters?
===== When should I use the top filter bar, filters function, or "Filter by"?

The easiest way to apply KQL filters is to use <<semi-structured-search>>, but you can also use the *Filters* function in the following scenarios:
Using the top <<semi-structured-search>> bar is best when you want to focus on a known set of
data for all the visualization results. These top level filters are combined with other filters
using AND logic.

Use the *Filters* function in the following scenarios:

* When you want to apply more than one KQL filter to the visualization.

* When you want to apply the KQL filter to a single layer, which allows you to visualize filtered and unfiltered data.

Use the *Filter by* advanced option in the following scenarios:

* When you want to assign a custom color to each filter in a bar, line or area chart.

* When you want to build a complex table, such as showing both failure rate and overall.

[float]
[[when-should-i-normalize-the-data-by-unit-or-use-a-custom-interval]]
===== When should I normalize the data by unit or use a custom interval?
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