The Dup After Restart

Concepts covered: paStreamProcessing

The incident report is always the same shape. A stream ran fine for weeks, restarted for some ordinary reason, and now the downstream table has duplicates: the same order events twice, revenue double-counted for a 20-minute window, an analyst asking why Tuesday looks so good. Nobody changed the code. The restart is blamed, and the restart is innocent. The duplicates were latent in the pipeline's design from the day it shipped; the restart merely collected the debt. Walk the timeline with the checkpoint protocol in hand. The engine writes the offsets file for batch N, declaring its slice. The batch runs and writes its output to the sink; the rows are now durably in the downstream system. And then, in the gap before the commit file for N lands, the process dies. On restart the engine does ex

About This Interactive Section

This section is part of the Structured Streaming: Intermediate lesson on DataDriven, a free data engineering interview prep platform. Each section includes explanations, worked examples, and hands-on code challenges that execute in real time. SQL queries run against a live database. Python runs in a sandboxed Docker container. Data modeling problems validate against interactive schema canvases. All content is framed around what data engineering interviewers actually test at companies like Meta, Google, Amazon, Netflix, Stripe, and Databricks.

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