01615576a8
* [DOCS] Updates the Dashboard docs for 7.15 * Reformatting * Reformatting * Adds experimental tag to controls * Review comments * Review comments * Removes Labs from Dashboard
219 lines
7 KiB
Text
219 lines
7 KiB
Text
[[add-aggregation-based-visualization-panels]]
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=== Aggregation-based
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Aggregation-based visualizations are the core {kib} panels, and are not optimized for a specific use case.
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With aggregation-based visualizations, you can:
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* Split charts up to three aggregation levels, which is more than *Lens* and *TSVB*
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* Create visualization with non-time series data
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* Use a <<save-open-search,saved search>> as an input
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* Sort data tables and use the summary row and percentage column features
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* Assign colors to data series
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* Extend features with plugins
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Aggregation-based visualizations include the following limitations:
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* Limited styling options
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* Math is unsupported
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* Multiple indices is unsupported
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[float]
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[[types-of-visualizations]]
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==== Types of aggregation-based visualizations
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{kib} supports the following types of aggregation-based visualizations.
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[cols="50, 50"]
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|===
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a| *Area*
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Displays data points, connected by a line, where the area between the line and axes are shaded.
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Use area charts to compare two or more categories over time, and display the magnitude of trends.
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| image:images/area.png[Area chart]
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a| *Data table*
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Displays your aggregation results in a tabular format. Use data tables to display server configuration details, track counts, min,
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or max values for a specific field, and monitor the status of key services.
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| image:images/data_table.png[Data table]
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a| *Gauge*
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Displays your data along a scale that changes color according to where your data falls on the expected scale. Use the gauge to show how metric
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values relate to reference threshold values, or determine how a specified field is performing versus how it is expected to perform.
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| image:images/gauge.png[Gauge]
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a| *Goal*
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Displays how your metric progresses toward a fixed goal. Use the goal to display an easy to read visual of the status of your goal progression.
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| image:images/goal.png[Goal]
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a| *Heat map*
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Displays graphical representations of data where the individual values are represented by colors. Use heat maps when your data set includes
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categorical data. For example, use a heat map to see the flights of origin countries compared to destination countries using the sample flight data.
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| image:images/heat_map.png[Heat map]
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a| *Horizontal Bar*
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Displays bars side-by-side where each bar represents a category. Use bar charts to compare data across a
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large number of categories, display data that includes categories with negative values, and easily identify
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the categories that represent the highest and lowest values. {kib} also supports vertical bar charts.
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| image:images/bar.png[Bar chart]
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a| *Line*
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Displays data points that are connected by a line. Use line charts to visualize a sequence of values, discover
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trends over time, and forecast future values.
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| image:images/line.png[Line chart]
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a| *Metric*
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Displays a single numeric value for an aggregation. Use the metric visualization when you have a numeric value that is powerful enough to tell
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a story about your data.
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| image:images/metric.png[Metric]
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a| *Pie*
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Displays slices that represent a data category, where the slice size is proportional to the quantity it represents.
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Use pie charts to show comparisons between multiple categories, illustrate the dominance of one category over others,
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and show percentage or proportional data.
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| image:images/pie.png[Pie chart]
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a| *Tag cloud*
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Graphical representations of how frequently a word appears in the source text. Use tag clouds to easily produce a summary of large documents and
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create visual art for a specific topic.
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| image:images/tag_cloud.png[Tag cloud]
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|===
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[float]
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[[create-aggregation-based-panel]]
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==== Create an aggregation-based visualization panel
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Choose the type of visualization you want to create, then use the editor to configure the options.
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. On the dashboard, click *All types > Aggregation based*.
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.. Select the visualization type you want to create.
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.. Select the data source you want to visualize.
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. Add the <<aggregation-reference,aggregations>> you want to visualize using the editor, then click *Update*.
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+
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NOTE: For the *Date Histogram* to use an *auto interval*, the date field must match the primary time field of the index pattern.
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. To change the order, drag and drop the aggregations in the editor.
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+
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[role="screenshot"]
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image:images/bar-chart-tutorial-3.png[Option to change the order of aggregations]
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. To customize the series colors, click the series in the legend, then select the color you want to use.
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+
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[role="screenshot"]
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image:images/aggregation-based-color-picker.png[Color picker]
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[float]
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[[try-it-aggregation-based-panel]]
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==== Try it: Create an aggregation-based bar chart
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You collected data from your web server, and you want to visualize and analyze the data on a dashboard. To create a dashboard panel of the data, create
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a bar chart that displays the top five log traffic sources for every three hours.
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[float]
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===== Add the data and create the dashboard
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Add the sample web logs data that you'll use to create the bar chart, then create the dashboard.
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. From the *Home* page, click *Try our sample data*.
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. From *Sample web logs*, click *Add data*.
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. Open the main menu, then click *Dashboard*.
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. On the *Dashboards* page, click *Create dashboard*.
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[float]
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===== Open and set up the aggregation-based bar chart
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Open the *Aggregation based* editor and change the time range.
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. On the dashboard, click *All types > Aggregation based*, select *Vertical bar*, then select *kibana_sample_data_logs*.
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. Make sure the <<set-time-filter, time filter>>> is *Last 7 days*.
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[float]
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[[tutorial-configure-the-bar-chart]]
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===== Create the bar chart
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To create the bar chart, add a <<bucket-aggregations,bucket aggregation>>, then add the terms sub-aggregation to display the top values.
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. Add a *Buckets* aggregation.
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.. Click *Add*, then select *X-axis*.
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.. From the *Aggregation* dropdown, select *Date Histogram*.
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.. Click *Update*.
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[role="screenshot"]
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image:images/bar-chart-tutorial-1.png[Bar chart with sample logs data]
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. To show the top five log traffic sources, add a sub-bucket aggregation.
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.. Click *Add*, then select *Split series*.
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TIP: Aggregation-based panels support a maximum of three *Split series*.
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.. From the *Sub aggregation* dropdown, select *Terms*.
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.. From the *Field* dropdown, select *geo.src*.
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.. Click *Update*.
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+
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[role="screenshot"]
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image:images/bar-chart-tutorial-2.png[Bar chart with sample logs data]
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[float]
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[[save-the-aggregation-based-panel]]
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===== Save and add the panel
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Save the panel to the *Visualize Library* and add it to the dashboard, or add it to the dashboard without saving.
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To save the panel to the *Visualize Library*:
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. Click *Save to library*.
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. Enter the *Title* and add any applicable <<managing-tags,*Tags*>>.
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. Make sure that *Add to Dashboard after saving* is selected.
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. Click *Save and return*.
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To save the panel to the dashboard:
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. Click *Save and return*.
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. Add an optional title to the panel.
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.. In the panel header, click *No Title*.
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.. On the *Customize panel* window, select *Show panel title*.
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.. Enter the *Panel title*, then click *Save*.
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