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Engineering, Data / ML

How Uber Scaled Data Replication to Move Petabytes Every Day

Uber prioritizes a reliable data lake, which is distributed across on-premise and cloud environments. This multi-region setup presents challenges for ensuring reliable and timely data access due to limited network bandwidth and the need for seamless data availability, particularly for disaster recovery. Uber uses the Hive Sync service, which uses Apache HadoopⓇ Ditscp (Distributed Copy) for data replication. However, with Uber’s Data Lake exceeding 350 PB, Distcp’s limitations became apparent. This blog explores the optimizations made to Distcp to enhance its performance and meet Uber’s growing data replication and disaster recovery needs across its distributed infrastructure.

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