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Partitioning Figure 4-1 compares a single partition database, and a multi-partition database. DB2 UDB database partitioning refers to the ability to divide the database into separate distinct physical partitions. Database partitioning has the characteristic of storing large amounts of data at a very detailed level while keeping the database manageable. Database utilities also run faster by operating on individual partitions concurrently. Figure 4-1: Single partition database compared to a multi-partition database The physical database partitions can then be allocated across a massively parallel processor (MPP) server, as depicted in Figure 4-2, a single symmetric multi-processor (SMP) server, as shown in Figure 4-3, or a cluster of SMP servers, as shown in Figure 4-4 on page 55.

Perhaps we need information from large external data sources such as from various search engines which would be absolutely impractical to store locally. Figure 3-7: Obtaining data on-demand That is where data integration technology comes into play. This technology provides data access to much more than relational, or even local, data. Once federated access is set up for these various data sources, they appear as relational structures that you can access as if they were part of the data warehouse - and by using the same SQL language used to access the tables in the data warehouse.

The 44 Chapter 4: Products for Near-Realtime BI Chapter 4: Products for Near-Realtime BI 45 database partition to which the transaction has a physical connection is known as the coordinator node. The coordinator node sends the database request to all required partitions and collects and integrates any results. If required the coordinator will assign subagents to work on the request. There are three different scenarios for accessing data in a partitioned environment: • Local bypass • Non-local • Non-collocated Where local bypass has the best performance and non-collocated has the worst performance.

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