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jKQL is an English like query and stream processing language for analyzing machine data in flight (Fast Data) and at rest. Use JKQL to analyze anomalies, behavior, flows, relationships and patterns in your data as it relates to your business. The only requirements is that your data must have timestamps.

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jKQL in an English-like query language that lets users directly analyze their data, respond to trends and make better informed business decisions.
jKql> Get relatives show as topology
jKQL can instantly find the relationships in data, here showing the order processing flow.

jKQL can instantly find the relationships in data, here showing the order processing flow.

jKql> Get relatives show as geomap
jKool’s GeoFencing capability is highlighted as jKQL is used to get relationships and display the results on a map. jKool understands latitude and longitude and automatically converts them to locales.

jKool’s GeoFencing capability is highlighted as jKQL is used to get relationships and display the results on a map. jKool understands latitude and longitude and automatically converts them to locales.

jKql> Get events fields location where eventname contains ‘rder’ group by location show as barchart
jKql> Get Event for This Month where Location =’London, England’
jKQL is searching for Order events and grouping them by location. We then can drill into these to see the event details

jKQL is searching for Order events and grouping them by location. We then can drill into these to see the event details

jKql> Compare ONLY DIFFS event for this month where eventID in (‘4c738615-f38e-4d07-af94-e266fa49cfac’,’df2412d9-9ee9-41f3-a37a-51ed0cd4c900′,’67c1a236-0c91-4778-b33d-9220448c2cc2′) show as table
jKQL support comparisons showing in this case only the differences between events. Any one of the events can be designated as the Master and the others are compared to that one.

jKQL support comparisons showing in this case only the differences between events. Any one of the events can be designated as the Master and the others are compared to that one.

jKql> Get number of events group by starttime bucketed by hours show as anomalychart
This query shows how jKool automatically detects anomalies. The Anomaly Chart uses Bollinger Bands and Exponential Moving Averages (EMA’s) to detect anomalies when an event cross either the lower or upper bands.

This query shows how jKool automatically detects anomalies. The Anomaly Chart uses Bollinger Bands and Exponential Moving Averages (EMA’s) to detect anomalies when an event cross either the lower or upper bands.

jKql> Get events for This Week where Severity =’HALT’
jKQL is displaying the events that have halted and offering the user the option to analyze them further, show them topologically or compare their attributes.

jKQL is displaying the events that have halted and offering the user the option to analyze them further, show them topologically or compare their attributes.

jKql> Get events fields avg elapsedtime, min elapsedtime, max elapsedtime where elapsedtime exists group by starttime bucketed by day show as colchart
jKool summarizes events calculating the average, minimum and maximum elapsed times and then buckets them by day.

jKool summarizes events calculating the average, minimum and maximum elapsed times and then buckets them by day.

jKql> Get number of events from Payment group by severity show as piechart
Find the Payment events with errors and then drilldown to find the root cause.

Find the Payment events with errors and then drilldown to find the root cause.

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