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Parallel Database Clusters (PDB)

Oracle RAC Cluster Tips by Burleson Consulting

This is an excerpt from the bestselling book Oracle Grid & Real Application Clusters.  To get immediate access to the code depot of working RAC scripts, buy it directly from the publisher and save more than 30%.

The Parallel Clustered Database (PDB) is a complex application, which provides access to the same database, or group of data tables, indexes and other objects, from any server in the cluster concurrently without compromising data integrity. Well known examples include Oracle Real Application Cluster (Oracle RAC), the subject matter of this book, IBM UDB DB2 Enterprise Extended Edition (EEE), and IBM S/390 Parallel Sysplex Clusters.

Parallel Databases typically contain multiple nodes or servers accessing the same physical storage or data concurrently. PDB Architecture allows multi-server data sharing technology, allowing direct concurrent read/write access to shared data from all the processing nodes in the parallel configuration. However, this necessitates complex lock management to maintain the data integrity and resource coordination.

In terms of storage access type, a Parallel Clustered System is implemented in two ways, the Shared Nothing Model and the Shared Disk Model.

Shared Nothing Model

In the Shared Nothing model, also referred to as the Data Partitioning Model, each system owns a portion of the database and each partition can only be read or modified by the owning system as shown in Figure 3.10. Data Partitioning enables each system to locally cache its portion of the database in processor memory without requiring cross-system communication to provide data access concurrency and coherency controls.

Each server in the cluster has its own independent subset of the data called a partition it can work on independently without encountering resource contention from other servers. The clustered nodes communicate by passing messages through a network that interconnects the servers. Client requests are automatically routed to the system that owns the particular resource, memory or disk for example. Only one of the clustered systems can own and access a particular resource at a time. In the event of a failure, resource ownership can be dynamically transferred to another system in the cluster.

Figure 3.10: Shared Nothing Mode ? Three Node database cluster

This architecture has several advantages:

* Shared nothing systems provide for incremental growth.

* Good for read-only databases and decision support applications.

* Failure is local - if one node fails, the other nodes stay up. However, disk system of failed node moves over to the surviving node.

It does suffer from some drawbacks as well:

* More coordination is required.

* More overhead is required in terms of processing or function shipping for a SQL operation working on a data/disk belonging to another node.

* Data skew is a potential problem. As data is added to the database and access patterns change, data re-partition is needed to balance IO.

Shared-Disk model

In the Shared-Disk model, all the disks containing data are accessible by all nodes of the cluster. Disk sharing architecture requires suitable lock management techniques to control the update concurrency control. Each of the nodes in the cluster has direct access to all disks on which shared data is placed.  Figure 3.11 shows a typical three node parallel database cluster. Each node has local database buffer cache. IBM Parallel Sysplex and Oracle RAC systems follow this approach of shared-disk.

Advantages of shared-disk systems are as follows:

* Shared-disk systems permit high availability. All data is accessible even if one node fails.

* These systems have the concept of One Database and multiple access points. In other words, one can say it is multi-instance and single database. There is no issue such as data skew as the data is located and accessed at a common location.

* It provides for incremental growth of nodes and thus adds to processing power.

Figure 3.11: Shared Disk Parallel Database Cluster

Disadvantages of shared disk systems are these:

* Inter-node synchronization is required and involves complex lock management and greater dependency on high-speed interconnect.

* If the workload is not partitioned well among the processing nodes, there may be high synchronization overhead.

* There is operating system overhead of running shared disk software.

This is an excerpt from the bestselling book Oracle Grid & Real Application Clusters, Rampant TechPress, by Mike Ault and Madhu Tumma.

You can buy it direct from the publisher for 30%-off and get instant access to the code depot of Oracle tuning scripts.


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