repartitioning

Repartitioning is the process of changing how data or resources are divided into partitions, shards, or segments and redistributed across computing resources. It involves altering the partitioning key, the number of partitions, or the rules that determine which records or items belong to which partition, as well as moving data between partitions. Repartitioning is typically undertaken to improve performance, balance load, accommodate growth, or adapt to changes in hardware or workload.

In databases and data warehousing, repartitioning is used to enhance scalability and query performance. It may involve splitting large partitions into smaller ones, merging small partitions, or redefining the partitioning strategy (for example from range to hash). Online repartitioning tries to move data with minimal downtime, while offline repartitioning may require pausing writes. Challenges include maintaining data consistency, updating metadata, and minimizing disruption to ongoing queries and transactions.

In distributed storage and cloud environments, repartitioning corresponds to rebalancing data shards across servers or nodes when nodes are added, removed, or when data becomes unevenly distributed. Techniques include rehashing, incremental data movement, and rolling rebalancing to limit service interruption. Effective repartitioning aims to reduce hotspots, improve throughput, and ensure even resource utilization.

In storage management, repartitioning can refer to resizing or reorganizing disk partitions on physical or virtual disks, altering partition boundaries, or converting between partitioning schemes. This can carry risks to data integrity and may require backup, validation, and careful planning.

Best practices for repartitioning include modeling workload characteristics, testing performance impacts, planning for compatibility with applications, implementing gradual data movement, and ensuring a rollback path. The goal is to achieve better balance and scalability with acceptable operational cost and risk.