Continuous Aggregate Refresh, Demystified: Invalidation, Lookback, and Late-Arriving Data

This story was originally published on HackerNoon at: https://hackernoon.com/continuous-aggregate-refresh-demystified-invalidation-lookback-and-late-arriving-data. Learn why late-arriving time-series data can leave aggregates stale and how TimescaleDB continuous aggregate refresh windows determine reconciling corrections. Check more stories related to tech-stories at: https://hackernoon.com/c/tech-stories. You can also check exclusive content about #timescaledb, #continuous-aggregate, #timescaledb-invalidation-log, #time-series-aggregation, #incremental-time-series-data, #time-series-view, #time-series-data, #good-company, and more. This story was written by: @tigerdata. Learn more about this writer by checking @tigerdata's about page, and for more stories, please visit hackernoon.com. Late-arriving and corrected time-series data can make pre-computed dashboards report plausible but stale numbers. This article compares four aggregation strategies, from scheduled materialized views and insert-triggered views to streaming dataflows and TimescaleDB continuous aggregates. It explains how invalidation tracking works and why the start_offset and end_offset of a refresh policy determine whether late data is ever reconciled.