Author: Roman Nozdrin
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Trying DuckDB for Magento Analytics: An Experiment with One Million Orders
Magento normally uses InnoDB for orders, order items, invoices, and other transactional data. However, analytical reports have another workload. I wanted to check whether DuckDB can improve a real Magento report without replacing the operational database.
For this experiment, I generated one million Magento orders and two million order items. Then I executed two complete Magento Orders Report queries in three storage configurations.
Short result
Why I started this experiment
The Magento database has a mostly transactional workload. It creates […]
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From a Chocolate Wrapper to Concurrent InnoDB Page Splits
This work started from a conversation with Monty Widenius at Meet Magento Czech in August. We discussed possible ways to improve the scalability of the InnoDB B+Tree, especially its insert path and page splits.
Monty explained several ideas about reducing synchronization during structural changes and allowing independent parts of the tree to make progress concurrently. We did not have a whiteboard, so we made the first design sketch on the back of a dark chocolate wrapper.
The sketch contained a […]
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Extending MariaDB with Native Aggregate Plugins: Laying the Groundwork for HyperLogLog
MariaDB already allows developers to add new Pluggable Data Types and scalar Plugin Functions. One missing piece has been Pluggable Aggregate Functions operating on PDTs. That matters for functionality such as HyperLogLog, where an extension needs to aggregate values into a custom statistical sketch while preserving its native SQL type.
MDEV-40672 closes that architectural gap. Aggregate functions can now participate in MariaDB’s native aggregation infrastructure, including DISTINCT, window execution, prepared statements and Pluggable Data Types.
MariaDB already supports MariaDB_FUNCTION_PLUGIN, a […]
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DuckDB Storage Engine for MariaDB. When the Sea Lion Learns to Quack.
An early look at the DuckDB storage engine for MariaDB — columnar, vectorized analytics that live right next to your transactional tables.
The problem
MariaDB’s InnoDB is excellent at what it was built for: transactions. Row-by-row inserts, updates, point lookups, strong consistency. But the moment you ask it to scan tens of millions of rows for a multi-way join with a few aggregations, a row store has to work hard.
The usual answer is to stand up a separate analytical […]