Stats 415

[Terresa Cherrie]

Thestats option lets you precisely control what bundle information gets displayed. This can be a nice middle ground if you don't want to use quiet or noInfo because you want some bundle information, but not all of it.

Tells stats to exclude the matching assets information. This can be done with a string, a RegExp, a function that is getting the assets name as an argument and returns a boolean. stats.excludeAssets can be an array of any of the above.

Tells stats to exclude the matching modules information. This can be done with a string, a RegExp, a function that is getting the module's source as an argument and returns a boolean. stats.excludeModules can be an array of any of the above. stats.excludeModules's configuration is merged with the stats.exclude's configuration value.

Tells stats to sort the modules by a given field. All of the sorting fields are allowed to be used as values for stats.modulesSort. Use ! prefix in the value to reverse the sort order by a given field.

Tells stats to exclude the warnings that are matching given filters. This can be done with a string, a RegExp, a function that is getting a warning as an argument and returns a boolean. stats.warningsFilter can be an array of any of the above.

Calculates aggregate statistics, such as average, count, and sum, over the results set. This is similar to SQL aggregation.If the stats command is used without a BY clause, only one row is returned, which is the aggregation over the entire incoming result set. If a BY clause is used, one row is returned for each distinct value specified in the BY clause.

Sparklines are inline charts that appear within table cells in search results to display time-based trends associated with the primary key of each row. Read more about how to "Add sparklines to your search results" in the Search Manual.

When you use the stats command, you must specify either a statistical function or a sparkline function. When you use a statistical function, you can use an eval expression as part of the statistical function. For example:

With the exception of the count function, when you pair the stats command with functions that are not applied to specific fields or eval expressions that resolve into fields, the search head processes it as if it were applied to a wildcard for all fields. In other words, when you have stats avg in a search, it returns results for stats avg(*).

During calculations, numbers are treated as double-precision floating-point numbers, subject to all the usual behaviors of floating point numbers. If the calculation results in the floating-point special value NaN, it is represented as "nan" in your results. The special values for positive and negative infinity are represented in your results as "inf" and "-inf" respectively. Division by zero results in a null field.

There are situations where the results of a calculation contain more digits than can be represented by a floating- point number. In those situations precision might be lost on the least significant digits. For an example of how to correct this, see Example 2 of the basic examples for the sigfig(X) function.

Ideally, when you run a stats search that aggregates results on a time function such as latest(), latest_time(), or rate(), the search should not return results when _time or _origtime fields are missing from the input data. However, searches that fit this description return results by default, which means that those results might be incorrect or random.

Some functions are inherently more expensive, from a memory standpoint, than other functions. For example, the distinct_count function requires far more memory than the count function. The values and list functions also can consume a lot of memory.

If you are using the distinct_count function without a split-by field or with a low-cardinality split-by by field, consider replacing the distinct_count function with the the estdc function (estimated distinct count). The estdc function might result in significantly lower memory usage and run times.

A pair of limits.conf settings strike a balance between the performance of stats searches and the amount of memory they use during the search process, in RAM and on disk. If your stats searches are consistently slow to complete you can adjust these settings to improve their performance, but at the cost of increased search-time memory usage, which can lead to search failures.

The BY clause returns one row for each distinct value in the BY clause fields. In this search, because two fields are specified in the BY clause, every unique combination of status and host is listed on separate row.

If you click the Visualization tab, the status field forms the X-axis and the host and count fields form the data series. The problem with this chart is that the host values (www1, www2, www3) are strings and cannot be measured in a chart.

With the chart command, the two fields specified after the BY clause change the appearance of the results on the Statistics tab. The BY clause also makes the results suitable for displaying the results in a chart visualization.

Search for earthquakes in and around California. Calculate the number of earthquakes that were recorded. Use statistical functions to calculate the minimum, maximum, range (the difference between the min and max), and average magnitudes of the recent earthquakes. List the values by magnitude type.

Search for earthquakes in and around California. Calculate the number of earthquakes that were recorded. Use statistical functions to calculate the mean, standard deviation, and variance of the magnitudes for recent earthquakes. List the values by magnitude type.

This example uses the values() function to display the corresponding categoryId and productName values for each productId. Then, it uses the sum() function to calculate a running total of the values of the price field.

Also, this example renames the various fields, for better display. For the stats functions, the renames are done inline with an "AS" clause. The rename command is used to change the name of the product_id field, since the syntax does not let you rename a split-by field.

This search uses the top command to find the ten most common referer domains, which are values of the referer field. Some events might use referer_domain instead of referer. The top command returns a count and percent value for each referer.

Please try to keep this discussion focused on the content covered in this documentation topic. If you have a more general question about Splunk functionality or are experiencing a difficulty with Splunk, consider posting a question to Splunkbase Answers.

The above aggregation computes the grades statistics over all documents. The aggregation type is stats and the field setting defines the numeric field of the documents the stats will be computed on. The above will return the following:

This feature requires usage of the following information and data: WordPress.com user ID, WordPress.com-connected blog ID, domain name, site timezone, blog charset, blog admin color preference, Jetpack version, site title and description, and permalink settings.Additionally, for activity tracking (detailed below): IP address, WordPress.com user ID (if logged in), WordPress.com username (if logged in), user agent, visiting URL, referring URL, timestamp of event, browser language, country code.

IP address, WordPress.com user ID (if logged in), WordPress.com username (if logged in), user agent, visiting URL, referring URL, timestamp of event, browser language, country code. Please also see Data Visibility and Retention information for this feature.

We track when, and by which user, the feature is activated and deactivated. We also track when, and which, configuration settings are modified (and by which user). If the user viewing the stats explicitly requests to view them without JavaScript turned on, we will set a cookie to remember this preference.

Post and page views, video plays (if videos are hosted by WordPress.com), outbound link clicks, referring URLs and search engine terms, and country. When this feature is enabled, Jetpack also tracks performance on each page load that includes the JavaScript file we use for Stats. This is exclusively for aggregate performance tracking across Jetpack sites in order to make sure that our plugin and code is not causing performance issues. This includes the tracking of page load times and resource loading duration (image files, JavaScript files, CSS files, etc.).

Any piece of data explicitly identifying a specific user (IP address, WordPress.com ID, WordPress.com username, etc.) is not visible to the site owner when using this feature. For example, a site owner can see that a specific post has 285 views, but he/she cannot see which specific users/accounts viewed that post.

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