Big data network
Big data applications need to process large-scale information, and when data is replicated to multiple locations for flexibility, the scale of information becomes larger and larger.
However, the most important attribute of big data is not its size, but its ability to divide big jobs into many small jobs. It can spread the resources for processing a task to multiple locations and become parallel processing.
Network Elasticity And Big Data Applications
- If a group of distributed resources must be coordinated through the Internet, availability becomes critical. If the network fails, the result is discontinuous bad computing resources and data sets.
- Big data applications are not only large in scale, but also have a feature I call burst.
Network Consistency
- In fact, most big data applications are not sensitive to network latency
- If the order of magnitude of computing time is seconds or minutes, it doesn’t matter even if there is a large delay on the network – the order of magnitude is about thousands of milliseconds
- Big data applications generally have high synchronization.
The Future f Big Data
- Network segmentation is an important condition for creating a big data environment.
- Although the concept of big data is closely related to Hadoop deployment, it has become synonymous with cluster environment
- According to the characteristics of different applications, these cluster environments have different requirements
Application awareness of big data network
Although the concept of big data is closely related to Hadoop deployment, it has become a synonym for cluster environment. According to the characteristics of different applications, these cluster environments have different requirements. Some may have high bandwidth requirements, while others may be sensitive to latency.
In short, if a network wants to support multiple applications and multiple tenants, it must be able to distinguish its workload and correctly handle each workload.
Frequently Asked Questions
Still open questions?
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