10 Commits (8a34c43515fc0b9452ecf4f238c44a9f249d5da3)

Author	SHA1	Message	Date
jyz0309	02e032884a	add doc ... Signed-off-by: jyz0309 <45495947@qq.com>	3 years ago
David N Perkins	52662e8105	Added metric name to histogram quartile binning and associated unit test ... Signed-off-by: David N Perkins <David.N.Perkins@ibm.com>	3 years ago
beorn7	c00c6ed01f	promql: Add more test cases for `histogram_quantile` ... This is motivated by the doubts raised in #7970. Signed-off-by: beorn7 <beorn@grafana.com>	3 years ago
Ganesh Vernekar	9199fcb8d1	'@ <timestamp>' modifier (#8121) ... This commit adds `@ <timestamp>` modifier as per this design doc: https://docs.google.com/document/d/1uSbD3T2beM-iX4-Hp7V074bzBRiRNlqUdcWP6JTDQSs/edit. An example query: ``` rate(process_cpu_seconds_total[1m]) and topk(7, rate(process_cpu_seconds_total[1h] @ 1234)) ``` which ranks based on last 1h rate and w.r.t. unix timestamp 1234 but actually plots the 1m rate. Signed-off-by: Ganesh Vernekar <cs15btech11018@iith.ac.in>	4 years ago
Linas Medžiūnas	7eaffa7180	Fix off-by-one error in funcHistogramQuantile / ensureMonotonic (#7393) ... * Fix off-by-one error in funcHistogramQuantile / ensureMonotonic * Additional coverage for nonmonotonic histogram buckets Signed-off-by: Linas Medziunas <linas.medziunas@gmail.com>	5 years ago
B++	d6374ae1b6	Return NaN for histogram_quantile when buckets have 0 observations (#7318) ... Signed-off-by: jberny <f.bernardi89@gmail.com>	5 years ago
Brian Brazil	c66aeb3fff	In histogram_quantile merge buckets with equivalent le values (#5158) ... This makes things generally more resilient, and will help with OpenMetrics transitions (and inconsistencies). Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>	6 years ago
Jack Neely	896f951e68	Force buckets in a histogram to be monotonic for quantile estimation (#2610) ... * Force buckets in a histogram to be monotonic for quantile estimation The assumption that bucket counts increase monotonically with increasing upperBound may be violated during: * Recording rule evaluation of histogram_quantile, especially when rate() has been applied to the underlying bucket timeseries. * Evaluation of histogram_quantile computed over federated bucket timeseries, especially when rate() has been applied This is because scraped data is not made available to RR evalution or federation atomically, so some buckets are computed with data from the N most recent scrapes, but the other buckets are missing the most recent observations. Monotonicity is usually guaranteed because if a bucket with upper bound u1 has count c1, then any bucket with a higher upper bound u > u1 must have counted all c1 observations and perhaps more, so that c >= c1. Randomly interspersed partial sampling breaks that guarantee, and rate() exacerbates it. Specifically, suppose bucket le=1000 has a count of 10 from 4 samples but the bucket with le=2000 has a count of 7, from 3 samples. The monotonicity is broken. It is exacerbated by rate() because under normal operation, cumulative counting of buckets will cause the bucket counts to diverge such that small differences from missing samples are not a problem. rate() removes this divergence.) bucketQuantile depends on that monotonicity to do a binary search for the bucket with the qth percentile count, so breaking the monotonicity guarantee causes bucketQuantile() to return undefined (nonsense) results. As a somewhat hacky solution until the Prometheus project is ready to accept the changes required to make scrapes atomic, we calculate the "envelope" of the histogram buckets, essentially removing any decreases in the count between successive buckets. * Fix up comment docs for ensureMonotonic * ensureMonotonic: Use switch statement Use switch statement rather than if/else for better readability. Process the most frequent cases first.	8 years ago
Fabian Reinartz	0d3012a605	Migrate matrix tests, remove old test files.	10 years ago
Fabian Reinartz	eba07a7d3d	Migrate histogram tests to test language.	10 years ago