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This article mainly explains "analyzing Oracle RAC Cluster". The content of the explanation is simple and clear, and it is easy to learn and understand. Please follow the editor's train of thought to study and learn "analyze Oracle RAC Cluster".

What is Oracle RAC (Real Application Cluster)?

Oracle RAC is a cluster database with shared cache architecture, which overcomes the limitations of traditional non-shared methods and shared disk methods, and provides a database solution with high scalability and availability for all your business applications. Oracle RAC is a key component of the Oracle private cloud architecture.

Oracle Real Application Clusters can eliminate the single point of failure of the database server, thus providing customers with excellent database availability. In a clustered server environment, the database itself is shared between server pools, which means that if any server in the pool fails, the database will continue to run on the normal server. Oracle RAC not only enables customers to continue to handle database load in the event of server failure, but also helps to reduce planned offline maintenance time of the database, thereby reducing downtime costs.

Oracle Real Application Clusters supports transparent deployment of Oracle databases on a clustered server pool. This allows customers to easily redeploy Oracle databases from a single server to a database server cluster, making full use of the consolidated memory capacity and processing power provided by the clustered database servers.

Oracle Real Application Clusters provides all the necessary software components that allow you to easily deploy Oracle Database on a server pool, taking full advantage of the performance, scalability, and availability provided by the cluster. Oracle RAC uses Oracle Grid Infrastructure as the foundation of the Oracle RAC database system. Oracle Grid Infrastructure includes Oracle Clusterware and Oracle Automated Storage Management (ASM) to efficiently share server and storage resources in a highly available and scalable database cloud environment.

II. The architecture of Oracle RAC

The biggest difference between RAC and a single instance is that multiple instances manage a database. This database must be installed on shared storage. Such an architecture has the following advantages:

The downtime of one or some of the highly available instances does not affect the service provided by the system.

The transaction processing function of high-performance cluster is greatly enhanced, and multiple instances can work concurrently.

Scalable when the system performance encounters a bottleneck, the performance of the database can be improved by adding nodes.

Instances in RAC, in addition to those background processes inherent in a single instance, will also have more processes for interaction between RAC instances. In RAC, each instance has its own redo log and undo tablespaces. Because each instance has to handle the transaction alone. But these redo and undo files should also be placed on the shared disk, because once the instance crashes, other instances need to be able to read the redo and undo of the instance for transaction recovery.

A mechanism called cache fusion has been introduced into RAC. That is, the memory of all machines is managed as a large whole memory.

To manage this memory, Oracle introduces three concepts: GCS (Global Cache Service), GES (Global Enqueue Service), and GRD (Global Resource Directory).

GRD: used to record the distribution of database cached block on each instance, as well as the status of block.

GRD is distributed across instances, and each instance maintains a portion of the GRD.

GRD is managed by GCS and GES, GCS manages the consistency of block cache in buffer cache, and GES manages block lock information.

Since each instance maintains only a portion of the GRD, when I request a block, do I have to request it on every machine? Obviously this is not the case, because it will be very inefficient. Then GCS and GES will select one of the nodes in RAC as Resource Master according to a certain algorithm. This Resource Master is responsible for processing requests for blocks. And Resource Master records the index of the GRD in each instance in memory.

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