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Product launchData engineering & the warehouse/lakehouseApache
r/dataengineering · Read source ↗

Apache Spark 4.2 introduces auto change data capture (CDC) directly within the engine, alongside new features like metric views, a Real-Time Mode, and enhanced Python support through Apache Arrow. These updates aim to streamline data engineering workflows and improve pipeline efficiency.

MyDataWork POV — Auto CDC sounds like a boon for data engineering, but integrating it directly into Spark raises alarm bells. When a core engine starts bundling such features, it risks becoming a bloated hub instead of a nimble tool. Metric views and Real-Time Mode are enticing, but the trade-off might be speed and flexibility. Arrow-first Python support is another layer, yet it could complicate debugging. Spark’s strength has been its adaptability; turning it into a Swiss Army knife may dull its edge.
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