mirror of
https://github.com/VictoriaMetrics/VictoriaMetrics.git
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246 lines
5.6 KiB
Plaintext
246 lines
5.6 KiB
Plaintext
{% import (
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"github.com/VictoriaMetrics/metricsql"
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) %}
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{% stripspace %}
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// ExpandWithExprsResponse returns a webpage, which expands with templates in q MetricsQL.
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{% func ExpandWithExprsResponse(q string) %}
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<html>
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<head>
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<title>Expand WITH expressions</title>
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<style>
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p { font-weight: bold }
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textarea { margin: 1em }
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</style>
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</head>
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<body>
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<div>
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<form method="get">
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<div>
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<p>
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<a href="https://docs.victoriametrics.com/MetricsQL.html">MetricsQL</a> query with optional WITH expressions:
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</p>
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<textarea name="query" style="height: 15em; width: 90%">{%s q %}</textarea><br/>
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<input type="submit" value="Expand" />
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<p>
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<a href="https://docs.victoriametrics.com/MetricsQL.html">MetricsQL</a> query after expanding WITH expressions and applying other optimizations:
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</p>
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<textarea style="height: 5em; width: 90%" readonly="readonly">{%= expandWithExprs(q) %}</textarea>
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</div>
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</form>
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</div>
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<div>{%= withExprsTutorial() %}</div>
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</body>
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</html>
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{% endfunc %}
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{% func expandWithExprs(q string) %}
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{% if len(q) == 0 %}
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{% return %}
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{% endif %}
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{% code expr, err := metricsql.Parse(q) %}
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{% if err != nil %}
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Cannot parse query: {%v err %}
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{% else %}
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{% code expr = metricsql.Optimize(expr) %}
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{%z expr.AppendString(nil) %}
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{% endif %}
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{% endfunc %}
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{% endstripspace %}
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{% func withExprsTutorial() %}
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<h3>Tutorial for WITH expressions in <a href="https://docs.victoriametrics.com/MetricsQL.html">MetricsQL</a></h3>
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<p>
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Let's look at the following real query from <a href="https://grafana.com/dashboards/1860">Node Exporter Full</a> dashboard:
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</p>
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<pre>
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(
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(
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node_memory_MemTotal_bytes{instance=~"$node:$port", job=~"$job"}
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-
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node_memory_MemFree_bytes{instance=~"$node:$port", job=~"$job"}
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)
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/
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node_memory_MemTotal_bytes{instance=~"$node:$port", job=~"$job"}
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)
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*
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100
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</pre>
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<p>
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It is clear the query calculates the percentage of used memory
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for the given $node, $port and $job. Isn't it? :)
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</p>
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<p>
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What's wrong with this query? Copy-pasted label filters for distinct timeseries
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which makes it easy to mistype these filters during modification.
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Let's simplify the query with WITH expressions:
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</p>
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<pre>
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WITH (
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commonFilters = {instance=~"$node:$port",job=~"$job"}
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)
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(
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node_memory_MemTotal_bytes{commonFilters}
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-
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node_memory_MemFree_bytes{commonFilters}
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)
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/
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node_memory_MemTotal_bytes{commonFilters} * 100
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</pre>
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<p>
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Now label filters are located in a single place instead of three distinct places.
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The query mentions node_memory_MemTotal_bytes metric twice and {commonFilters}
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three times. WITH expressions may improve this:
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</p>
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<pre>
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WITH (
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my_resource_utilization(free, limit, filters) = (limit{filters} - free{filters}) / limit{filters} * 100
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)
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my_resource_utilization(
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node_memory_MemFree_bytes,
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node_memory_MemTotal_bytes,
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{instance=~"$node:$port",job=~"$job"},
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)
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</pre>
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<p>
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Now the template function my_resource_utilization() may be used for monitoring arbitrary
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resources - memory, CPU, network, storage, you name it.
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</p>
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<p>
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Let's take another nice query from <a href="https://grafana.com/dashboards/1860">Node Exporter Full</a> dashboard:
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</p>
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<pre>
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(
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(
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(
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count(
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count(node_cpu_seconds_total{instance=~"$node:$port",job=~"$job"}) by (cpu)
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)
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)
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-
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avg(
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sum by (mode) (rate(node_cpu_seconds_total{mode='idle',instance=~"$node:$port",job=~"$job"}[5m]))
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)
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)
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*
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100
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)
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/
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count(
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count(node_cpu_seconds_total{instance=~"$node:$port",job=~"$job"}) by (cpu)
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)
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</pre>
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<p>
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Do you understand what does this mess do? Is it manageable? :) WITH expressions are happy to help in a few iterations.
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<br/>
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<br/>
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1. Extract common filters used in multiple places into a commonFilters variable:
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</p>
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<pre>
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WITH (
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commonFilters = {instance=~"$node:$port",job=~"$job"}
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)
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(
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(
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(
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count(
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count(node_cpu_seconds_total{commonFilters}) by (cpu)
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)
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)
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-
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avg(
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sum by (mode) (rate(node_cpu_seconds_total{mode='idle',commonFilters}[5m]))
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)
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)
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*
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100
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)
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/
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count(
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count(node_cpu_seconds_total{commonFilters}) by (cpu)
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)
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</pre>
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<p>
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2. Extract "count(count(...) by (cpu))" into cpuCount variable:
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</p>
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<pre>
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WITH (
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commonFilters = {instance=~"$node:$port",job=~"$job"},
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cpuCount = count(count(node_cpu_seconds_total{commonFilters}) by (cpu))
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)
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(
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(
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cpuCount
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-
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avg(
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sum by (mode) (rate(node_cpu_seconds_total{mode='idle',commonFilters}[5m]))
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)
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)
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*
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100
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) / cpuCount
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</pre>
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<p>
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3. Extract rate(...) part into cpuIdle variable, since it is clear now that this part calculates the number of idle CPUs:
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</p>
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<pre>
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WITH (
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commonFilters = {instance=~"$node:$port",job=~"$job"},
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cpuCount = count(count(node_cpu_seconds_total{commonFilters}) by (cpu)),
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cpuIdle = sum(rate(node_cpu_seconds_total{mode='idle',commonFilters}[5m]))
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)
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((cpuCount - cpuIdle) * 100) / cpuCount
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</pre>
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<p>
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4. Put node_cpu_seconds_total{commonFilters} into its own varialbe with the name cpuSeconds:
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</p>
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<pre>
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WITH (
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cpuSeconds = node_cpu_seconds_total{instance=~"$node:$port",job=~"$job"},
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cpuCount = count(count(cpuSeconds) by (cpu)),
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cpuIdle = sum(rate(cpuSeconds{mode='idle'}[5m]))
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)
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((cpuCount - cpuIdle) * 100) / cpuCount
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</pre>
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<p>
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Now the query became more clear comparing to the initial query.
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</p>
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<p>
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WITH expressions may be nested and may be put anywhere. Try expanding the following query:
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</p>
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<pre>
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WITH (
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f(a, b) = WITH (
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f1(x) = b-x,
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f2(x) = x+x
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) f1(a)*f2(b)
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) f(foo, with(x=bar) x)
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</pre>
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{% endfunc %}
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