Unit of Measure
All metrics collected from activities are recorded in nanoseconds and ops per second. All histograms
are recorded with 3 digits of precision using HDR histograms unless otherwise modified with the
--hdr-digits option or the activity-specific
hdr_digits activity param.
Metrics from a scenario run can be gathered in multiple ways:
- In the log output
- In CSV files
- In HDR histogram logs
- In Histogram Stats logs (CSV)
- To a monitoring system via graphite
- via the
- remotely via the
--docker-metrics-at <host> methods are used, they take over the global
options for the other methods. Except these, the others may generally be combined and used in
combination. The command line options for enabling these are documented in the command line docs,
although some examples of these may be found below.
Metrics via Graphite
If you like to have all of your testing data in one place, then you may be interested in reporting your measurements to a monitoring system. For this, NoSQLBench includes a Metrics Library. Graphite reporting is baked in as the default reporter.
In order to enable graphite reporting, use one of these options formats:
--report-graphite-to <host> --report-graphite-to <host>:<port>
Core metrics use the prefix nosqlbench by default. You can override this with the `` --metrics-prefix` option:
Metrics associated with a specific activity will have the activity alias in their name. There is a set of core metrics which are always present regardless of the activity type. The names and types of additional metrics provided for each activity type vary.
Sometimes, an activity type will expose metrics on a per-statement basis, measuring over all
invocations of a given statement as defined in the YAML. In these cases, you will see
separating the name components of the metric. At the most verbose, a metric name could take on the
<activity>.<docname>--<blockname>--<statementname>--<metricname>, although this is rare when you
name your statements, which is recommended. Just keep in mind that the double dash connects an
activity's alias with named statements within
Recording HDR Histogram Logs
You can record details of histograms from any compatible metric (histograms and timers) with an option like this:
If you want to record only certain metrics in this way, then use this form:
Notice that the option is enclosed in single quotes. This is because the second part of the option value is a regex. The '.*suffix' pattern matches any metric name that ends with "suffix". Effectively, leaving out the pattern is the same as using '.*', which matches all metrics. Any valid regex is allowed here.
Metrics may be included in multiple logs, but care should be taken not to overdo this. Keeping higher fidelity histogram reservoirs does come with a cost, so be sure to be specific in what you record as much as possible.
If you want to specify the recording interval, use this form:
If you want to specify the interval, you must use the third form above, although it is valid to leave the pattern empty, such as 'hdrdata.log::5s'.
Each interval specified will be tracked in a discrete reservoir in memory, so they will not interfere with each other in terms of accuracy.
Recording HDR Histogram Stats
You can also record basic snapshots of histogram data on a periodic interval just like above with HDR histogram logs. The option to do this is:
Everything works the same as for hdr histogram logging, except that the format is in CSV as shown in the example below:
#logging stats for session scenario-1479089852022 #[Histogram log format version 1.0] #[StartTime: 1479089852.046 (seconds since epoch), Sun Nov 13 20:17:32 CST 2016] #Tag,Interval_Start,Interval_Length,count,min,p25,p50,p75,p90,p95,p98,p99,p999,p9999,max Tag=diag1.delay,0.457,0.044,1,16,31,31,31,31,31,31,31,31,31,31 Tag=diag1.cycles,0.48,0.021,31,4096,8191,8191,8191,8191,8191,8191,8191,8191,8191,2097151 Tag=diag1.delay,0.501,0.499,1,1,1,1,1,1,1,1,1,1,1,1 Tag=diag1.cycles,0.501,0.499,498,1024,2047,2047,4095,4095,4095,4095,4095,4095,4095,4194303 ...
This includes the metric name (Tag), the interval start time and length (from the beginning of collection time), number of metrics recorded (count), minimum magnitude, a number of percentile measurements, and the maximum value. Notice that the format used is similar to that of the HDR logging, although instead of including the raw histogram data, common percentiles are recorded directly.
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