Comparison of Partitioning Techniques(Cont.) Range partitioning: Provides data clustering by partitioning attribute value. Good for sequential access Good for point queries on partitioning attribute:only one node needs to be accessed. For range queries on partitioning attribute,one to a few nodes may need to be accessed Remaining nodes are available for other queries. Good if result tuples are from one to a few blocks. But if many blocks are to be fetched,they are still fetched from one to a few nodes,and potential parallelism in disk access is wasted Example of execution skew. Database System Concepts-7th Edition 21.10 @Silberschatz,Korth and SudarshanDatabase System Concepts - 7 21.10 ©Silberschatz, Korth and Sudarshan th Edition Comparison of Partitioning Techniques (Cont.) Range partitioning: ▪ Provides data clustering by partitioning attribute value. • Good for sequential access • Good for point queries on partitioning attribute: only one node needs to be accessed. ▪ For range queries on partitioning attribute, one to a few nodes may need to be accessed • Remaining nodes are available for other queries. • Good if result tuples are from one to a few blocks. • But if many blocks are to be fetched, they are still fetched from one to a few nodes, and potential parallelism in disk access is wasted ▪ Example of execution skew