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Tag Clouds

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Tag Clouds

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A tag cloud visualization is a visual representation of text data, typically used to visualize free form text. Tags are usually single words, and the importance of each tag is shown with font size or color.

The font size for each word is determined by the metrics aggregation. The following aggregations are available for this chart:

Metric Aggregations:

Count: The count aggregation returns a raw count of the elements in the selected index pattern.
Average: This aggregation returns the average of a numeric field. Select a field from the drop-down.
Sum: The sum aggregation returns the total sum of a numeric field. Select a field from the drop-down.
Min: The min aggregation returns the minimum value of a numeric field. Select a field from the drop-down.
Max: The max aggregation returns the maximum value of a numeric field. Select a field from the drop-down.
Unique Count: The cardinality aggregation returns the number of unique values in a field. Select a field from the drop-down.
Standard Deviation: The extended stats aggregation returns the standard deviation of data in a numeric field. Select a field from the drop-down.
Top Hit: The top hits aggregation returns one or more of the top values from a specific field in your documents. Select a field from the drop-down, how you want to sort the documents and choose the top fields, and how many values should be returned.
Percentiles: The percentile aggregation divides the values in a numeric field into percentile bands that you specify. Select a field from the drop-down, then specify one or more ranges in the Percentiles fields. Click the X to remove a percentile field. Click + Add to add a percentile field.
Percentile Rank: The percentile ranks aggregation returns the percentile rankings for the values in the numeric field you specify. Select a numeric field from the drop-down, then specify one or more percentile rank values in the Values fields. Click the X to remove a values field. Click +Add to add a values field.

Parent Pipeline Aggregations:

For each of the parent pipeline aggregations you have to define the metric for which the aggregation is calculated. That could be one of your existing metrics or a new one. You can also nest this aggregations (for example to produce 3rd derivative)

Derivative: The derivative aggregation calculates the derivative of specific metrics.
Cumulative Sum: The cumulative sum aggregation calculates the cumulative sum of a specified metric in a parent histogram
Moving Average: The moving average aggregation will slide a window across the data and emit the average value of that window
Serial Diff: The serial differencing is a technique where values in a time series are subtracted from itself at different time lags or period

Sibling Pipeline Aggregations:

Just like with parent pipeline aggregations you need to provide a metric for which to calculate the sibling aggregation. On top of that you also need to provide a bucket aggregation which will define the buckets on which the sibling aggregation will run

Average Bucket: The avg bucket calculates the (mean) average value of a specified metric in a sibling aggregation
Sum Bucket: The sum bucket calculates the sum of values of a specified metric in a sibling aggregation
Min Bucket: The min bucket calculates the minimum value of a specified metric in a sibling aggregation
Max Bucket: The max bucket calculates the maximum value of a specified metric in a sibling aggregation

You can add an aggregation by clicking the + Add Metrics button.

Enter a string in the Custom Label field to change the display label.

The buckets aggregations determine what information is being retrieved from your data set.

Before you choose a buckets aggregation, select the Split Tags option.

You can specify the following bucket aggregations for tag cloud visualization:

Terms: A terms aggregation enables you to specify the top or bottom n elements of a given field to display, ordered by count or a custom metric.

You can click the Advanced link to display more customization options for your metrics or bucket aggregation:

JSON Input: A text field where you can add specific JSON-formatted properties to merge with the aggregation definition, as in the following example:

{ "script" : "doc['grade'].value * 1.2" }

In Elasticsearch releases 1.4.3 and later, this functionality requires you to enable dynamic Groovy scripting.

Select the Options tab to change the following aspects of the chart:

Text Scale: You can select linear, log, or square root scales for the text scale. You can use a log scale to display data that varies exponentially or a square root scale to regularize the display of data sets with variabilities that are themselves highly variable.
Orientation: You can select how to orientate your text in the tag cloud. You can choose one of the following options: Single, right angles and multiple.
Font Size: Allows you to set minimum and maximum font size to use for this visualization.

To display the raw data behind the visualization, click the bar at the bottom of the container. Tabs with detailed information about the raw data replace the visualization:

TableA representation of the underlying data, presented as a paginated data grid. You can sort the items in the table by clicking on the table headers at the top of each column.

RequestThe raw request used to query the server, presented in JSON format.

ResponseThe raw response from the server, presented in JSON format.

StatisticsA summary of the statistics related to the request and the response, presented as a data grid. The data grid includes the query duration, the request duration, the total number of records found on the server, and the index pattern used to make the query.

To export the raw data behind the visualization as a comma-separated-values (CSV) file, click on either the Raw or Formatted links at the bottom of any of the detailed information tabs. A raw export contains the data as it is stored in Elasticsearch. A formatted export contains the results of any applicable Kibana field formatters.

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