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Oracle 11g Parallel Execution

Oracle Database Tips by Donald Burleson

Parallel Databases

Modern relational database systems are typically architected with parallel capable software that is well suited to take advantage of the parallel architecture of SMP systems. The Oracle database system is a multi-process application in UNIX systems and is a multi-threaded application under the Windows architecture.


Databases have a component called the query optimizer, which selects a sequence of inputs, joins, and scans to produce the desired output table or data set. The query optimizer is aware of the underlying hardware architecture to utilize the suitable path for invoking parallel execution. Thus, from the database point-of-view, parallel execution is useful for all types of operations that access significant amounts of data.


Generally, parallel execution improves performance for:

  • queries

  • creation of large indexes

  • bulk inserts, updates, and deletes

  • aggregations and copying

Parallel processing involves the use of multiple processors to reduce the time needed to complete a given task. Instead of one processor executing an entire task, several processors work on separate tasks which are subordinate to the main task. There are several architectural approaches for multiple processor systems. They are:

  • Symmetric Multi-Processors (SMP)

  • Clustered Systems

  • NUMA (or DSM - Distributed Share Model) servers

  • MPP (Massively Parallel Processing)

Types of Parallelism

There are two types of parallelism.  They are inter-query parallelism and intra-query parallelism.

  • Inter-Query Parallelism - Individual transactions are independent, and no transaction requires the output of another transaction to complete. Many CPUs can be kept busy by assigning each task or query to a separate CPU. This type of parallelism, where many separate independent queries are active at the same time, is called inter-query parallelism. In an OLTP environment, each query is fairly small, small enough to complete on a single process utilizing a single CPU.

  • Intra-Query Parallelism - To speed up execution of a large, complex query, it must first be decomposed into smaller problems, and these smaller problems execute concurrently (in parallel) by assigning each sub-problem concurrently to its CPUs. This is called intra-query parallelism.  Decision support systems (DSS) need this kind of facility. Data warehousing applications often deal with huge data sets, involving data capture, analysis and summaries, so these operations also require this capability.

Oracle Grid and Real Application Clusters

See working examples of Oracle Grid and RAC in the book Oracle Grid and Real Application Clusters.

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