2885e871e3
* Add Inspector feature
* So long, and thanks for all the fish, spy panel
* Fix several functional tests
* Fix unit tests
* Fix spy panel button tests
* Replace old spy panel documentation
* Disable test temporarily until we have dashboard triggers
* Enter edit mode for dark theme test
* Fix some more functional tests
* Fix more functional tests
* More test fixing
* Fix more functional tests
* Allow opening the inspector via loader handler
* Refactor InspectorViewChooser, remove unused CSS
* Remove dead code
* Fix data download button style
* Remove redundant code
* Load inspectorViews for dashboard_viewer
* Extract inspector views to custom core_plugin
* Switch API to TypeScript 🎉
* Design changes
* Remove icons from views
* Design changes
* Improve typings of API
* Add typing to all adapters
* Show loading spinner in request selector
* Rewrite InspectorView to TypeScript
* Fix help text for data view
* Remove deprecated React lifecycle methods
* Embed inspector into dashboard panel actions
* Remove temporary inspector trigger
* Remove old CSS
* Fix dashboard trigger for new panel action
* Add tests for InspectorPanel and DataAdapter
* Produce a hierarchical table if the vis is hierarchical
* Remove allowJs option again
* Add missing Apache license headers
* Close inspector on dashboard when navigating away
* Use proper title for dashboard panels
* Fix functional tests
* Skip broken test for now
* Flush view chooser button
* Add request adapter tests
* Skip more tests, broken due to typescript
* Add Request Time description
* Add description for courier request
* Fix tests
* Replace icon by new (not yet released) icon
* Finalize design of inspector
* Remove discover test, that relied on spy panels
* Change API to be properly mockable in tests
* Add aria-live region for request status
* Replace old method in functional tests
* Replace abitrary magic number
* Use object destructuring in vis
* Fix issue with crashing requests view
* Add request time tooltip
* Get request body of correct search source
* Make filter buttons properly keyboard accessible
* Follow Dave's design suggestions
* Remove redundant request from name
* Remove unneeded comments
* WIP raw-formatted values
* Fix filtering issue
* Fix tests and more license headers
* Add data view tests
* Remove search from table
* Fix typos
* Implement review suggestion
* Remove artificial delays for testing
* Fix new panel action structure
* Minor design adjustments
* Fix failing functional test
* Update failing snapshot test
* Implement final wording
* Apply new EUI styling
* Fix closing inspector in tests
* Fix sorting of table
* Align punctuation between tooltips
168 lines
6.7 KiB
Plaintext
168 lines
6.7 KiB
Plaintext
[[visualize]]
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= Visualize
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[partintro]
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--
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_Visualize_ enables you to create visualizations of the data in your
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Elasticsearch indices. You can then build <<dashboard, dashboards>> that
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display related visualizations.
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Kibana visualizations are based on Elasticsearch queries. By using a
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series of Elasticsearch {ref}/search-aggregations.html[aggregations]
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to extract and process your data, you can create charts that show
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you the trends, spikes, and dips you need to know about.
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You can create visualizations from a search saved from <<discover, Discover>>
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or start with a new search query.
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--
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[[createvis]]
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== Creating a Visualization
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To create a visualization:
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. Click on *Visualize* in the side navigation.
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. Click the *Create new visualization* button or the **+** button.
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. Choose the visualization type:
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+
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* *Basic charts*
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[horizontal]
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<<xy-chart,Line, Area and Bar charts>>:: Compare different series in X/Y charts.
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<<heatmap-chart,Heat maps>>:: Shade cells within a matrix.
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<<pie-chart,Pie chart>>:: Display each source's contribution to a total.
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* *Data*
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[horizontal]
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<<data-table,Data table>>:: Display the raw data of a composed aggregation.
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<<metric-chart,Metric>>:: Display a single number.
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<<goal-chart,Goal and Gauge>>:: Display a gauge.
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* *Maps*
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[horizontal]
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<<tilemap,Coordinate map>>:: Associate the results of an aggregation with geographic locations.
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<<regionmap,Region map>>:: Thematic maps where a shape's color intensity corresponds to a metric's value.
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locations.
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* *Time Series*
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[horizontal]
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<<timelion-getting-started,Timelion>>:: Compute and combine data from multiple time series
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data sets.
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<<time-series-visual-builder,Time Series Visual Builder>>:: Visualize time series data using pipeline aggregations.
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* *Other*
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[horizontal]
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<<controls,Controls>>:: Controls provide the ability to add interactive inputs to Kibana Dashboards.
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<<markdown-widget,Markdown widget>>:: Display free-form information or
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instructions.
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<<tagcloud-chart,Tag cloud>>:: Display words as a cloud in which the size of the word correspond to its importance.
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<<vega-graph,Vega graph>>:: Support for user-defined graphs, external data sources, images, and user-defined interactivity.
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. Specify a search query to retrieve the data for your visualization:
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** To enter new search criteria, select the index pattern for the indices that
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contain the data you want to visualize. This opens the visualization builder
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with a wildcard query that matches all of the documents in the selected
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indices.
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** To build a visualization from a saved search, click the name of the saved
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search you want to use. This opens the visualization builder and loads the
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selected query.
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+
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NOTE: When you build a visualization from a saved search, any subsequent
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modifications to the saved search are automatically reflected in the
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visualization. To disable automatic updates, you can disconnect a visualization
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from the saved search.
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. In the visualization builder, choose the metric aggregation for the
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visualization's Y axis:
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* *Metric Aggregations*:
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* {ref}/search-aggregations-metrics-valuecount-aggregation.html[count]
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* {ref}/search-aggregations-metrics-avg-aggregation.html[average]
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* {ref}/search-aggregations-metrics-sum-aggregation.html[sum]
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* {ref}/search-aggregations-metrics-min-aggregation.html[min]
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* {ref}/search-aggregations-metrics-max-aggregation.html[max]
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* {ref}/search-aggregations-metrics-stats-aggregation.html[standard deviation]
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* {ref}/search-aggregations-metrics-cardinality-aggregation.html[unique count]
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* {ref}/search-aggregations-metrics-percentile-aggregation.html[median] (50th percentile)
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* {ref}/search-aggregations-metrics-percentile-aggregation.html[percentiles]
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* {ref}/search-aggregations-metrics-percentile-rank-aggregation.html[percentile ranks]
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* {ref}/search-aggregations-metrics-top-hits-aggregation.html[top hit]
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* {ref}/search-aggregations-metrics-geocentroid-aggregation.html[geo centroid]
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* *Parent Pipeline Aggregations*:
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* {ref}/search-aggregations-pipeline-derivative-aggregation.html[derivative]
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* {ref}/search-aggregations-pipeline-cumulative-sum-aggregation.html[cumulative sum]
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* {ref}/search-aggregations-pipeline-movavg-aggregation.html[moving average]
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* {ref}/search-aggregations-pipeline-serialdiff-aggregation.html[serial diff]
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* *Sibling Pipeline Aggregations*:
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* {ref}/search-aggregations-pipeline-avg-bucket-aggregation.html[average bucket]
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* {ref}/search-aggregations-pipeline-sum-bucket-aggregation.html[sum bucket]
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* {ref}/search-aggregations-pipeline-min-bucket-aggregation.html[min bucket]
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* {ref}/search-aggregations-pipeline-max-bucket-aggregation.html[max bucket]
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. For the visualizations X axis, select a bucket aggregation:
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+
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* {ref}/search-aggregations-bucket-datehistogram-aggregation.html[date histogram]
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* {ref}/search-aggregations-bucket-range-aggregation.html[range]
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* {ref}/search-aggregations-bucket-terms-aggregation.html[terms]
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* {ref}/search-aggregations-bucket-filters-aggregation.html[filters]
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* {ref}/search-aggregations-bucket-significantterms-aggregation.html[significant terms]
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For example, if you're indexing Apache server logs, you could build bar chart
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that shows the distribution of incoming requests by geographic location by
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specifying a terms aggregation on the `geo.src` field:
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image::images/bar-terms-agg.jpg[]
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The y-axis shows the number of requests received from each country, and the
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countries are displayed across the x-axis.
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Bar, line, or area chart visualizations use _metrics_ for the y-axis and
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_buckets_ for the x-axis. Buckets are analogous to SQL `GROUP BY`
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statements. Pie charts, use the metric for the slice size and the bucket
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for the number of slices.
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You can futher break down the data by specifying sub aggregations. The first
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aggregation determines the data set for any subsequent aggregations. Sub
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aggregations are applied in order--you can drag the aggregations to change the
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order in which they're applied.
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For example, you could add a terms sub aggregation on the `geo.dest` field to
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the Country of Origin bar chart to see the locations those requests were
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targeting.
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image::images/bar-terms-subagg.jpg[]
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For more information about working with sub aggregations, see
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https://www.elastic.co/blog/kibana-aggregation-execution-order-and-you[Kibana,
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Aggregation Execution Order, and You].
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include::visualize/xychart.asciidoc[]
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include::visualize/controls.asciidoc[]
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include::visualize/datatable.asciidoc[]
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include::visualize/markdown.asciidoc[]
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include::visualize/metric.asciidoc[]
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include::visualize/goal.asciidoc[]
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include::visualize/pie.asciidoc[]
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include::visualize/tilemap.asciidoc[]
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include::visualize/regionmap.asciidoc[]
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include::visualize/time-series-visual-builder.asciidoc[]
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include::visualize/tagcloud.asciidoc[]
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include::visualize/heatmap.asciidoc[]
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include::visualize/vega.asciidoc[]
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include::visualize/inspector.asciidoc[]
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