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ClickHouse gets lazier and faster: Introducing lazy materialization
ClickHouse learned to procrastinate strategically. Discover how lazy materialization skips unnecessary column reads to accelerate queries.
This seemingly "lazy" behavior turns out to be extremely effective in real-world workloads, especially for Top N queries that sort large datasets and apply LIMIT clauses, a common pattern in observability and general analytics. To give a complete picture, we’ll also briefly demonstrate the other key building blocks of I/O efficiency in ClickHouse, highlighting not just what lazy materialization does, but how it differs from and complements the techniques already in place. To demonstrate this, we remove all filters from our example query to find the reviews with the highest number of helpful votes, regardless of date, product, rating, or verification status, returning the top 3 along with their title, headline, and full text.
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