![]() If data is unevenly spread, it is called skewed.The goal in partitioning is to try and spread the data around as evenly as possible.They noted that the partitioning scheme is mostly independent of the replication used.įigure 6-1 in the book shows this leader / follower scheme for partitioning among multiple nodes.Nodes can also be a leader for some partitions and a follower for others.A single node may store more than one partition.While partitioning means that records belong to a single partition, those partitions can still be replicated to other nodes for fault tolerance.These can be set up for either analytic or transactional workloads.Examples of these are NoSQL databases and Hadoop data warehouses.For more processing power, spread the data across more nodes. ![]()
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