The rightmost point in a downsampled price series is the last value returned or drawn by the chart—not necessarily the latest raw price or the price at the present moment. Its timestamp may identify a time bucket, while the value summarizes observations within that bucket. To assess freshness, compare the newest underlying observation time with the query’s evaluation time.
Why isn’t the last point necessarily current?
Downsampling combines observations over time intervals to produce fewer points. The resulting point has at least three relevant times:
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- Observation time: when the underlying price was recorded.
- Bucket time: the timestamp assigned to the interval’s aggregate.
- Evaluation time: the time the query is evaluated, often bounded by a query’s end time or “now.”
These times can differ. A point might be labeled with a bucket boundary even though its value summarizes earlier observations. Or a query evaluated at a later time might use an older sample. So a point at the chart’s right edge does not, by itself, establish that its underlying price observation is current.
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What time does a downsampled point represent?
There is no universal timestamp convention: it depends on the database and query.
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InfluxDB OSS v1: grouped timestamps mark the interval start
InfluxQL’s GROUP BY time() replaces original timestamps with interval timestamps. In InfluxData’s example for GROUP BY time(12m), result timestamps indicate the start of each 12-minute interval; the last result covers the interval from 2015-08-18T00:24:00Z to just before 2015-08-18T00:36:00Z. That displayed timestamp is the bucket’s start, not a claim that a raw observation occurred at that exact time. See InfluxDB OSS v1 InfluxQL functions.
InfluxDB OSS v2: aggregate timestamps can use the window stop
Flux’s aggregateWindow() has a timeSrc option that selects the column used for a new aggregate timestamp. Its documented default is _stop, so the aggregate can be labeled with the window’s stop time even though its value summarizes observations from inside that window. See InfluxDB OSS v2 Process data.
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Other systems can make different choices
These InfluxDB behaviors are product- and query-specific examples, not rules for all charting or time-series systems. Check the timestamp convention used by the actual query and tool rather than assuming every aggregate is labeled at its start or end.
Does “last” mean the latest price or “now”?
Not necessarily. “Last” can describe how a value is selected from data already available to a query, without saying how recently that data was observed.
Grafana’s expression reduction defines Last as the last number in the series. That is the final value in the series presented to the reduction; it does not guarantee a new measurement at the current time. InfluxQL’s LAST(), by contrast, selects the newest field value by timestamp. Even then, the newest stored value can be old relative to the query’s evaluation time. See Grafana’s expression query documentation and InfluxDB OSS v1 InfluxQL functions.
How can the query use older data than its evaluation time?
Evaluation time and source-sample time are separate. In Prometheus, an instant query evaluated at a timestamp can use the newest sample within its lookback period. Prometheus documents a five-minute default lookback, configurable with --query.lookback-delta or the per-query lookback_delta parameter. If a series becomes stale, it eventually yields no value instead. This is Prometheus-specific behavior; the default does not mean every graph’s last point is five minutes old, nor is it caused by downsampling. See Prometheus Querying basics.
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How to tell whether the displayed price is fresh
- Identify the window and aggregation. Record the downsampling interval and function. A mean summarizes values across a window; a maximum reports the highest value in it; a last-value selector chooses a value according to its timestamp or position. These answer different questions.
- Check the timestamp convention. Determine whether the aggregate is labeled with the bucket start, bucket end, or another configured timestamp. Do not infer that from the chart alone.
- Inspect the raw observations in the final bucket. Find the newest source-observation timestamp that contributed to the rightmost aggregate. The aggregate’s label is not a substitute for this timestamp.
- Compare with the query’s upper bound and evaluation time. A query may end at a specified time rather than the moment you view the chart; some systems also select an earlier sample under their lookback rules.
- Check how empty windows are handled. A system may leave a gap, fill it, or carry a prior value forward. Grafana resampling can pad empty windows with the last known value, backfill from the next known value, or represent them as NaN. A filled point is not a new measurement. See Grafana’s expression query documentation.
- Report observation age when freshness matters. Calculate the time between the newest underlying observation and the query’s evaluation time. State that age rather than calling the chart endpoint “current” based only on where it appears.
What to disclose when showing a downsampled price
For a chart or report to communicate freshness accurately, state the window, aggregation function, timestamp convention, and query upper bound. If the question is whether the price is current, give the age of the newest underlying observation and disclose whether missing windows are filled or values carried forward. InfluxDB 3 Core also documents interval aggregation options for downsampling, but those details should be interpreted according to that system’s own implementation: InfluxDB 3 Core Downsampler plugin. In InfluxQL, server-side now() has query-specific semantics; see Explore data using InfluxQL.
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