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Concurrent Database Access

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%.

Before beginning a detailed evaluation of the features of failover database clusters and high performance parallel database clusters, how the database maintains consistent data in a multi-user environment will be highlighted.

While dealing with the setup of a database in a clustered environment, guaranteed data integrity and provision of consistent data results are most crucial.

Relational Database systems allow concurrent access to the database content such as rows and tables. The same data is retrieved and updated by many users. This concurrent access requires a meaningful control of access and should provide consistent results. There are two major concepts for database access. They are Data concurrency and Data Consistency. Data concurrency allows unhindered access by any number of users to the same data at the same time. Data consistency means that each user sees a consistent view of data, including visible changes made by the user?s own transactions and transactions of other users. To provide consistent transaction behavior, database systems follow appropriate transaction isolation models. For example, Oracle automatically provides read consistency to queries so that all the data a query sees comes from a single point in time, also called statement level read consistency. It can also provide transaction-level read consistency as an option. Oracle makes use of rollback segments to provide these consistent views. The local cache of the instance has all the relevant data blocks to satisfy consistent results for database operations. Figure 3.6 shows the simultaneous access of data blocks by many users through same and different instances.

Figure 3.6:  Data Concurrency and Data Consistency

In a failover database cluster environment, all nodes actively access the disk storage unit that provides data volumes or file systems. The active node is where the database instance is running. The database instance, with memory structures and processes, is nothing but a front end for physical data blocks or data pages.  The database instance?s local cache on the active node is the place where blocks are fetched into, modified and flushed back to physical storage unit. The local cache is where active buffers are handled for processing by SQL statements.  Since this process deals with a single instance and only one set of cache buffers, the consistency mechanism is confined to this local cache.

However, in a parallel database clustered environment where there are multiple instances located on multiple nodes, data consistency mechanisms go beyond one instance and cover the database caches of all the nodes. Multiple caches are joined virtually to provide a single cache image and used to process SQL operations. When a user modifies a set of data blocks on one node, another user accessing the same set of blocks on a second node still gets read consistent blocks. The caches from both these nodes act as if they are one single entity. For instance, Oracle Real Application Cluster uses cache-to-cache block transfer, known as Cache Fusion, to move read-consistent images of data blocks from one instance cache to another instance cache. To support such an activity, there has to be some form of data locking.

Cache Fusion and locking mechanism will be explored in more detail in Chapter 7, Cache Fusion and Inter-Instance Coordination.


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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