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Because Prometheus topk returns more results than expected, and because https://github.com/prometheus/prometheus/issues/586 requires client-side processing that has not yet been made available via https://github.com/grafana/grafana/issues/7664, I'm trying to pursue a different near-term work-around to my similar problem.
In my particular case most of the metric values that I want to graph will be zero most of the time. Only when they are above zero are they interesting.
I can find ways to write prometheus queries to filter data points based on the value of a label, but I haven't yet been able to find a way to tell prometheus to return time series data points only if the value of the metric meets a certain condition. In my case, I want to filter for a value greater than zero.
Can I add a condition to a prometheus query that filters data points based on the metric value? If so, where can I find an example of the syntax to do that?
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Wildcards in queries Prometheus uses a Regex-like pattern and the wildcard character is . + (read: dot plus) combined with tilde character ( ~ ) instead of just the equal sign ( = ). So the query becomes http_status{job~="customer-. +"} .
PromQL, short for Prometheus Querying Language, is the main way to query metrics within Prometheus. You can display an expression's return either as a graph or export it using the HTTP API. PromQL uses three data types: scalars, range vectors, and instant vectors. It also uses strings, but only as literals.
Prometheus provides a functional query language called PromQL (Prometheus Query Language) that lets the user select and aggregate time series data in real time.
There are four primary Prometheus metric types to query for via PromQL: counters, gauges, histograms, and summaries. These metric types fulfill the needs or requirements for most use cases, and are found in Prometheus' official client libraries: Go, Java, Ruby, and Python.
If you're confused by brian's answer: The result of filtering with a comparison operator is not a boolean, but the filtered series. E.g.
min(flink_rocksdb_actual_delayed_write_rate > 0)
Will show the minimum value above 0.
In case you actually want a boolean (or rather 0 or 1), use something like
sum (flink_rocksdb_actual_delayed_write_rate >bool 0)
which will give you the non-zero count.
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Filtering is done with the comparison operators, for example x > 0.
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