Читать книгу Big Data - Seifedine Kadry - Страница 71

Scalability is the ability of the system to meet the increasing demand for storage capacity. A system capable of scaling delivers increased performance and efficiency. With the advent of the big data era there is an imperative need to scale data storage platforms to make them capable of storing petabytes of data. The storage platforms can be scaled in two ways:

 Scaling‐up (vertical scalability)

 Scaling‐out (horizontal scalability)

Scaling‐up. The vertical scalability adds more resources to the existing server to increase its capacity to hold more data. The resources can be computation power, hard drive, RAM, and so on. This type of scaling is limited to the maximum scaling capacity of the server. Figure 2.13 shows a scale‐up architecture where the RAM capacity of the same machine is upgraded from 32 GB to 128 GB to meet the increasing demand.

Scaling‐out. The horizontal scalability adds new servers or components to meet the demand. The additional component added is termed as node. Big data technologies work on the basis of scaling out storage. Horizontal scaling enables the system to scale wider to meet the increasing demand. Scaling out storage uses low cost commodity hardware and storage components. The components can be added as required without much complexity. Multiple components connect together to work as a single entity. Figure 2.14 shows the scale‐out architecture where the capacity is increased by adding additional commodity hardware to the cluster to meet the increasing demand.

Figure 2.13 Scale‐up architecture.

Figure 2.14 Scale‐out architecture.