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Data Table

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Data Table

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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.
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 rows of the data table are called buckets. You can define buckets to split the table into rows or to split the table into additional tables.

Each bucket type supports the following aggregations:

Date Histogram: A date histogram is built from a numeric field and organized by date. You can specify a time frame for the intervals in seconds, minutes, hours, days, weeks, months, or years. You can also specify a custom interval frame by selecting Custom as the interval and specifying a number and a time unit in the text field. Custom interval time units are s for seconds, m for minutes, h for hours, d for days, w for weeks, and y for years. Different units support different levels of precision, down to one second. Intervals are labeled at the start of the interval, using the date-key returned by Elasticsearch. For example, the tooltip for a monthly interval will show the first day of the month.
Histogram: A standard histogram is built from a numeric field. Specify an integer interval for this field. Select the Show empty buckets checkbox to include empty intervals in the histogram.
Range: With a range aggregation, you can specify ranges of values for a numeric field. Click Add Range to add a set of range endpoints. Click the red (x) symbol to remove a range.
Date Range: A date range aggregation reports values that are within a range of dates that you specify. You can specify the ranges for the dates using date math expressions. Click Add Range to add a set of range endpoints. Click the red (/) symbol to remove a range.
IPv4 Range: The IPv4 range aggregation enables you to specify ranges of IPv4 addresses. Click Add Range to add a set of range endpoints. Click the red (/) symbol to remove a range.
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.
Filters: You can specify a set of filters for the data. You can specify a filter as a query string or in JSON format, just as in the Discover search bar. Click Add Filter to add another filter. Click the label button to open the label field, where you can type in a name to display on the visualization.
Significant Terms: Displays the results of the experimental significant terms aggregation. The value of the Size parameter defines the number of entries this aggregation returns.
Geohash: The geohash aggregation displays points based on the geohash coordinates.

Once you’ve specified a bucket type aggregation, you can define sub-buckets to refine the visualization. Click + Add sub-buckets to define a sub-bucket, then choose Split Rows or Split Table, then select an aggregation from the list of types.

You can use the up or down arrows to the right of the aggregation’s type to change the aggregation’s priority.

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

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

Exclude Pattern: Specify a pattern in this field to exclude from the results.
Include Pattern: Specify a pattern in this field to include in the results.
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.

The availability of these options varies depending on the aggregation you choose.

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

Per Page: This field controls the pagination of the table. The default value is ten rows per page.

Checkboxes are available to enable and disable the following behaviors:

Show metrics for every bucket/level: Check this box to display the intermediate results for each bucket aggregation.
Show partial rows: Check this box to display a row even when there is no result.

Enabling these behaviors may have a substantial effect on performance.

Viewing Detailed Information

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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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