Bucket and history

An example of a query to calculate the distribution of link events towards an internet protocol (IP) address.

You can filter all the link_events with id_dst equal to 192.168.1.11 After this you can sort by time, this is a very important step because bucket and history depend on how the data are sorted.

Then you can use bucket to group the data by time. The final step is to use the history command to draw a chart, we pass count as a value for the Y axis and time for the X axis.

The history command is particularly suited for displaying a big amount of data, in the image below we can see that there are many hours of data to analyze.

link_events | where id_dst == 192.168.1.11 | sort time asc | bucket time 36000 | history count time
Figure 1. Bucket and history example

Bucket and history example