#TimescaleTuesday
In this #TimescaleTuesday video, Developer Advocate @ryanbooz finishes a three-part series looking at some of the common misunderstandings around how Continuous Aggregates work. In this final video, he demonstrates how incorrect settings for the refresh window in a refresh policy might not be materializing the data you expect. When refresh policies or time buckets don't align properly, you can actually get caught in a situation where data isn't being materialized in the way you think, leading to slower queries as time goes on.
If you're new to TimescaleDB or haven't thought much about how real-time continuous aggregates work, please follow along to make sure your refresh policies are keeping the proper buckets of data up-to-date!
🛠 𝗥𝗲𝗹𝗲𝘃𝗮𝗻𝘁 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀
Resources
📌 Surprised by Real-time Continuous Aggregates (Part 1) ⇒ • Video
📌 What data is actually stored in Continuous Aggregates? (Part 2) ⇒ • Video
📌 Continuous aggregates in TimescaleDB 2.0 ⇒ • Video
📌 What’s new in TimescaleDB 2.0 docs ⇒ https://tsdb.co/2-0-changes-guide
📌 TimescaleDB 2.0 announcement blog post ⇒ https://tsdb.co/timescaledb-2-0-blog
🐯 𝗔𝗯𝗼𝘂𝘁 𝗧𝗶𝗺𝗲𝘀𝗰𝗮𝗹𝗲
At Timescale, we are dedicated to serving developers worldwide, enabling them to build exceptional data-driven products that measure everything that matters. Analyzing this data across the time dimension ("time-series data") enables developers to understand what is happening right now, how that is changing, and why that is changing. We are backed by top-tier investors with a track record of success in the industry.
💻 𝗙𝗶𝗻𝗱 𝗨𝘀 𝗢𝗻𝗹𝗶𝗻𝗲!
🔍 Website ⇒ https://tsdb.co/homepage
🔍 Slack ⇒ https://slack.timescale.com
🔍 GitHub ⇒ https://github.com/timescale
🔍 Twitter ⇒ / timescaledb
🔍 Twitch ⇒ / timescaledb
🔍 LinkedIn ⇒ / timescaledb
🔍 Timescale Blog ⇒ https://tsdb.co/blog
🔍 Timescale Documentation ⇒ https://tsdb.co/docs
#PostgreSQL #Database #ContinuousAggregates #Timeseries
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