From 5a1fce108146454d35d820a8dd9cb907f2717079 Mon Sep 17 00:00:00 2001 From: Mohit Nain Date: Thu, 26 Mar 2020 12:30:10 +0530 Subject: [PATCH] Fix language in docs/sources/features/panels/heatmap.md --- docs/sources/features/panels/heatmap.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/sources/features/panels/heatmap.md b/docs/sources/features/panels/heatmap.md index 7d9ec81342e..bc5b7b0b0ff 100755 --- a/docs/sources/features/panels/heatmap.md +++ b/docs/sources/features/panels/heatmap.md @@ -15,7 +15,7 @@ weight = 4 > New panel only available in Grafana v4.3+ -The Heatmap panel allows you to view histograms over time. To fully understand and use this panel you need +The Heatmap panel allows you to view histograms over time. To fully understand and use this panel you need to understand what Histograms are and how they are created. Read on below to for a quick introduction to the term Histogram. @@ -74,7 +74,7 @@ the time range `1h`. This will make the cells 1h wide on the X-axis. ### Pre-bucketed data If you have a data that is already organized into buckets you can use the `Time series buckets` data format. This format -requires that your metric query return regular time series and that each time series has a numeric name that represent +requires that your metric query returns regular time series and that each time series has a numeric name that represents the upper or lower bound of the interval. There are a number of data sources supporting histogram over time like Elasticsearch (by using a Histogram bucket @@ -108,7 +108,7 @@ change with the bucket count. ## Raw data vs aggregated If you use the heatmap with regular time series data (not pre-bucketed). Then it's important to keep in mind that your data -is often already by aggregated by your time series backend. Most time series queries do not return raw sample data +is often already aggregated by your time series backend. Most time series queries do not return raw sample data but include a group by time interval or maxDataPoints limit coupled with an aggregation function (usually average). This all depends on the time range of your query of course. But the important point is to know that the Histogram bucketing