MySQL Cluster

Introduction to MySQL Cluster

The main purpose of the database is to store the data required by the user and make it available for use and manipulation whenever required. Even though, this statement seems to be easy to say and fulfill in reality it is very tough to make sure that the single database is available to all the users present in huge numbers. High availability is always a challenge faced by database engineers. To overcome these multiple techniques are used. One of the crucial ones is the clustering of the tables of the database. In this article, we will learn about MySQL cluster features, advantages, performance metrics, prerequisites, and when we should use the clusters.

Features of MySQL Cluster

The current and latest version of MySQL cluster is 703 and it comes integrated and bundled in Mysql 5.6 version.

Mysql clusters have the following features in it:

• It is real-time functionality that is highly scalable and is completely compliant as a transactional database that follows all the ACID (Atomicity, Consistency, Isolation, and Durability) properties.
• It is open-source and provides 99.999% availability for the database.
• Mysql clusters are designed keeping in mind the multi-master structure that makes it distributed which results in no chances of single-point failure.
• Intensive transactions and read/write operations are served easily as MySQL clusters are scaled horizontally.
• Mysql clusters are accessible through both types of interfaces SQL and NoSQL interfaces.
• Mysql cluster can serve millions of operations within a second in real-time implementation with predictable response times that range to some milliseconds.
• Mysql clusters come up with the feature of automatic partitioning of the database called sharding technique that balances the load and data can be stored in memory or disk.
• Web-based workloads that are unpredictable can be handled easily due to linear database scalability and new nodes to the network of clusters can be added even when the cluster is running and it has zero downtime that leads to linear scalability.

Pre-requisites

There are certain system requirements that your machine should fulfill for using the MySQL clusters that are listed below:

• CPU: Intel/AMD x86 or higher, UltraSPARC or higher.
• Hard disk capacity: Minimum 3 GB.
• RAM capacity: Minimum 1 GB.
• Network: The network should be of gigabit ethernet following TCP/IP protocol and should contain more than 1 node in it.

When Should we Use MySQL Cluster?

It is necessary to understand when we should approach using the MySQL clusters according to our requirements.

Below are some of the points that can be considered while deciding whether you should use clusters to manage your database:

• If your database application involves a lot many transactions that have started creating load on the MySQL server then to meet with growing numbers of the CRUD operations to your database you can use the sharding technique of clusters.
• Clusters can be used to make sure that the consistency is maintained irrespective of which node is serving the select operations for data retrieval.
• In case, if some failure occurs in database service will result in the downtime of the application, and whether it is affordable to handle such downtimes.
• If a failure occurs will there be the data loss that is worth needed to be taken into consideration in those several seconds of the failure?
• A replication facility needs to be provided across the geographical regions that will facilitate the read and write operations on each node for that particular region.
• The number of the operations involved in the transaction should be greater in the count(such as 1000 operations in a single transaction) to run them parallelly on different nodes to increase performance. However, if the number of operations is less such as 10 operations in a single transaction then it will not be preferable to distribute the task on multiple nodes to run the operations of the transaction parallelly and collect the results as it will negatively affect the performance.
• Taking into consideration the type of request of data from the applications. Such as whether the retrieval is based upon the primary key of database tables involving few joins on multiple tables or the complete scan of the table records involving joins on other tables that return huge volumes of data in ten thousand of rows. For applications with the second case as the scenario, clusters can be preferred as a solution to it for increasing the performance of the application.

Performance Metrics of MySQL Cluster

Using the MySQL clusters in huge databases to manage them surely proves to be much profitable and there is a significant increase in the performance of the application if it is data-centric which is mostly the case in real-time applications.

Some of the performance metrics of MySQL clusters are listed below:

• Scalability: We can scale-dynamically, scale-out, or scale-in. For cost-effectiveness, we generally scale out by using more applications and nodes of data per cluster or increasing the number of CPU threads, or adding more space/ memory to each of the data nodes.
• Failover: Whenever there is any failure of the database, the sub-second failover facility makes sure that the service is not interrupted.
• Performance: The response time for the request of data retrieval is greatly improved with a maximum of 5 seconds. Further, One of the NoSQL access methodologies can be used to improve the response time. Update operations can also be performed on huge scales without worrying about the load on the database as the throughput of the database system is increased after the usage of MySQL clusters.
• Availability: Mysql cluster usage provides 99.999% of availability that means less than 5 minutes of downtime/unavailability per year.

Conclusion

Clustering highly increases the performance and makes the retrieval of the query resultset very quick as the execution time lowers down because the records are now present in the single location after clustering and are not in the distorted format. This gradually affects the availability of the database for users. As execution time decreases, the access time decreases making the database available for other users and thus achieving high performance and availability of database for users.

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