# NQL compute The `compute` command aggregates and extracts metrics from the events table and appends it to the results table as a new column with metric per object. It can be used only after a `with` or `include` clause. ### Syntax {% code overflow="wrap" lineNumbers="true" %} ``` ... | include... | compute = . ``` {% endcode %} {% code overflow="wrap" lineNumbers="true" %} ``` ... | with... | compute = . ``` {% endcode %} ### Example {% code overflow="wrap" lineNumbers="true" %} ``` devices during past 7d | include execution.crashes during past 7d | compute nb_crashes = number_of_crashes.sum() ``` {% endcode %} ### Using with the ‘count()’ function When used without a field specified, the `count()` aggregation function applies to the event table. For example, in the following query the `compute` clause appends new column with the number of boots per device. {% code overflow="wrap" lineNumbers="true" %} ``` devices during past 7d | include device_performance.boots during past 7d | compute nb_boots = count() ``` {% endcode %} You can also count the unique inventory objects as a new column, using the `.count()` syntax. It appends a new column with either 1 or 0 as the value, based on whether the object has relevant events or not. In the following example, the compute clause returns 1 for the devices that have been booted during past 7 days, and 0 for devices with no boots recorded in that time period. In the last statement, `summarize` clause is used for computing the ratio of devices with boots. {% code overflow="wrap" lineNumbers="true" %} ``` devices during past 7d | include device_performance.boots during past 7d | compute nb_devices_with_boots = device.count() | summarize ratio_devices_with_boots = nb_devices_with_boots.sum()/count() ``` {% endcode %} --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.nexthink.com/platform/understanding-key-data-platform-concepts/nexthink-query-language-nql/nql-keywords/nql-compute.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.