VQV Signal
According to a post on X by @tsenart, Prometheus has merged another Perfloop pull request. The change means PromQL range functions with scalar arguments, such as predict_linear and quantile_over_time, no longer build a fresh one-sample vector for every argument, series and step. On Prometheus's own range-query benchmark, with 100 series and 1,000 steps, the post reports 52% fewer bytes and 89% fewer allocations.
According to a post on X by @tsenart, Prometheus has merged another Perfloop pull request. The change means PromQL range functions with scalar arguments, such as predict_linear and quantile_over_time, no longer build a fresh one-sample vector for every argument, series and step. On Prometheus's own range-query benchmark, with 100 series and 1,000 steps, the post reports 52% fewer bytes and 89% fewer allocations.
AI-assisted summary based on the listed source.
@tsenart said Prometheus merged another Perfloop PR: PromQL range functions with scalar arguments, such as predict_linear and quantile_over_time, no longer build a fresh one-sample vector for every argument, series and step. On Prometheus's own range-query benchmark (100 series, 1,000 steps) that means 52% fewer...
Teams running heavy Prometheus range queries could see lower memory use and allocation overhead for these functions once they run a build that includes the merged change. Platform and observability engineers should check the release notes before assuming the same gains for their own workloads. The figures come from Prometheus's benchmark setup, so real-world results will depend on query shape and scale.
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