1.13.0

New experimental features

• #615: Heartbeat aggregate
  Users can use the new heartbeat_agg(timestamp, start_time, agg_interval, heartbeat_interval) to track the liveness of a system in the range (start_time, start_time + agg_interval). Each timestamp seen in that range is assumed to indicate system liveness for the following heartbeat_interval.

  Once constructed, users can query heartbeat aggregates for uptime and downtime, as well as query for live_ranges or dead_ranges. Users can also check for live_at(timestamp).

  Heartbeat aggregates can also interpolated to better see behavior around the boundaries of the individual aggregates.

• #620: Expose TDigest type

  This is a prototype for building TDigest objects client-side, for INSERT into tables.

  This is a lightly tested prototype; try it out at your own risk!

  Examples

• #635: asof joins for timevectors

  This allows users to join two timevectors with the following semantics timevectorA -> asof(timevectorB). This will return records with the LOCF value from timevectorA at the timestamps from timevectorB. Specifically the returned records contain, for each value in timevectorB, {the LOCF value from timevectorA, the value from timevectorB, the timestamp from timevectorB}.

• #609: New approx_percentile_array() function

  Users can use the new toolkit_experimental.approx_percentile_array(percentiles) to generate an array of percentile results instead of having to call and rebuild the aggregate multiple times.

• #636: New timeline_agg aggregate, which is similar to state_agg but tracks the entire state timeline instead of just the duration in each state.

• #640: Support rollup for state_agg and timeline_agg.

• #640: Support integer states for state_agg and timeline_agg.

• #638: Introducing Time Vector Templates.

  Users can use the new experimental function toolkit_experimental.to_text(timevector(time, value),format_string) to render a formatted text representation of their time vector series. These changes also include toolkit_experimental.to_plotly(timevector(time, value)), which will render your time vector series in a format suitable for use with plotly.

Bug fixes

• #644: Fix bug in Candlestick aggregate and reenable partial aggregation.

Other notable changes

• #646: Upgrade to PGX 0.6.1 with experimental support for PostgreSQL 15
• #621: Rocky Linux 9 support

Full Changelog: 1.12.1...1.13.0