云计算与大数据题目(大数据与云计算网课试题及答案)

[Answer]: C
Big data promotes software manufacturers engaged in data storage and processing and companies with large amounts of data. Cloud computing promotes manufacturers and owners of computing and storage equipment. Computing and storage resources companies.

The three major supporting technologies for national security are "big data and cloud computing", "artificial intelligence" and "blockchain technology".

1. Big data refers to a collection of data with very large volume, high complexity and fast processing speed, including structured data, semi-structured data and unstructured data. . Cloud computing is an Internet-based computing method that provides scalable computing resources and services through the network, allowing users to quickly obtain computing power and storage resources.

2. Artificial intelligence refers to the use of computer technology to realize the simulation and extension of human intelligence, so that computers can learn, reason, identify, understand and create like humans. Research in the field of artificial intelligence includes machine learning, natural language processing, visual recognition, intelligent decision-making, etc., which involves machine learning algorithms, neural networks, deep learning and other technologies.

3. Blockchain technology is a decentralized distributed ledger technology that uses cryptography technology to record transaction information and data in a node network maintained by multiple nodes to ensure that the data security and non-tamperability. The core features of blockchain technology are decentralization, security, reliability and transparency.

Strengthen the training of talents in the fields related to the three major supporting technologies of national security:

1. Strengthen the education and training of talents in the technical field. We should establish a sound education system, provide high-quality educational resources, strengthen the training and guidance of talents in the technical field, cultivate talents with innovative spirit and practical ability, and have better performance and contribution in the technical field.

2. Strengthen the introduction and retention of talents in the technical field. A sound introduction and retention mechanism should be established to attract high-level talents to engage in research and development in related fields. At the same time, we should provide these talents with a good working environment and treatment, retain high-quality talents, and promote the development of the technical field.

3. Strengthen practical training for talents in technical fields. A complete practical training mechanism should be established to strengthen the training of practical abilities of talents in the technical field, improve their practical ability and response ability, so that they can better adapt to changes and developments in the technical field and serve the cause of national security.

Overview of cloud computing and big data
Cloud computing (cloud computing) is the addition, use and delivery model of Internet-based related services, usually involving the use of the Internet. Provide dynamically scalable and often virtualized resources. Cloud is a metaphor for network and Internet. In the past, cloud was often used to represent telecommunications networks in diagrams, and later it was also used to represent the abstraction of the Internet and underlying infrastructure. Cloud computing in the narrow sense refers to the delivery and use model of IT infrastructure, which refers to obtaining the required resources through the network in an on-demand and easily scalable manner; in the broad sense cloud computing refers to the delivery and use model of services, which refers to the on-demand and easily scalable manner through the network. way to get the services you need. Such services can be IT, software, Internet-related, or other services. It means that computing power can also be circulated as a commodity through the Internet.
Big data, or massive data, refers to the amount of data involved that is so large that it cannot be captured, managed, processed, and organized into helpful information within a reasonable time through current mainstream software tools. Information for a more positive purpose in corporate business decisions. The 4V characteristics of big data: Volume, Velocity, Variety, and Veracity.
From a technical point of view, the relationship between big data and cloud computing is as inseparable as the two sides of the same coin. Big data cannot be processed by a single computer, and a distributed computing architecture must be used. Its characteristic lies in the mining of massive data, but it must rely on distributed processing, distributed database, cloud storage and virtualization technology of cloud computing.
Big data management, distributed file system, such as Hadoop, Mapreduce data segmentation and access execution; at the same time, SQL support, SQL interface support represented by Hive+HADOOP, using cloud computing to build the next generation of big data technology Data warehousing has become a hot topic. From the perspective of system requirements, the architecture of big data poses new challenges to the system:
1. Higher integration. A standard chassis completes a specific task to the maximum extent possible.
2. The configuration is more reasonable and the speed is faster. The balanced design of storage, controller, I/O channel, memory, CPU, and network, as well as the optimal design for data warehouse access, are more than an order of magnitude higher than traditional similar platforms.
3. The overall energy consumption is lower. For the same computing tasks, the energy consumption is the lowest.
4. The system is more stable and reliable. It can eliminate various single points of failure and unify the quality and standards of a component or device.
5. Low management and maintenance costs. Routine management of data collections is fully integrated.
6. Plannable and foreseeable system expansion and upgrade roadmap.
The relationship between cloud computing and big data
To put it simply: cloud computing is the virtualization of hardware resources, while big data is the efficient processing of massive data. Although this explanation is not entirely appropriate, it can help people who don't understand the two names quickly understand the difference. Of course, if the explanation is more vivid, cloud computing is equivalent to our computers and operating systems, which virtualize a large number of hardware resources and then allocate them for use.
It can be said that big data is equivalent to a "database" of massive data. Looking at the development of the field of big data, we can also see that the current development of big data has been developing in a direction similar to the traditional database experience. In one sentence, it is , traditional databases provide enough space for the development of big data.
The overall architecture of big data includes three layers: data storage, data processing and data analysis. The data must first be stored through the storage layer, and then the corresponding data model and data analysis index system can be established according to the data needs and goals to analyze the data to generate value.
The intermediate timeliness is achieved through the powerful parallel computing and distributed computing capabilities provided by the intermediate data processing layer. The three cooperate with each other, which allows big data to generate ultimate value.
Regardless of the current development of cloud computing, the future trend is: cloud computing, as the bottom layer of computing resources, supports upper-layer big data processing, and the development trend of big data is real-time interactive query efficiency and analysis capabilities. , to borrow the words from a Google technical paper: "You can operate PB-level data in Miaji by moving the mouse." It is really exciting.

The relationship between big data and cloud computing. Big data is a data collection that acquires, manages, and analyzes data that is larger than the capabilities of traditional database software tools. It has a large number of The four characteristics are data scale, fast data flow, multiple data types and low value density. Comparing big data to an industry, the key to realizing the benefits of this industry is to improve the processing capabilities of data and realize the added value of data through processing.

The relationship between big data and cloud computing

From a technical point of view, the relationship between big data and cloud computing is as close as the two sides of the coin.

Big data is inevitable It cannot be processed by a single computer and must adopt a distributed structure. It is characterized by distributed data mining of large amounts of data, but it must rely on distributed processing, distributed databases and cloud storage, and virtualization technology of cloud computing.

With the advent of the cloud era, big data is getting more and more attention. The analyst team believes that big data is usually used to represent the large amounts of unstructured data and semi-structured data created by companies.

Big data Analytics is often associated with cloud computing because real-time analysis of large data sets requires frameworks like Mapreduce distributed across tens, hundreds, or even thousands of computers.

Big data requires special techniques to be effective Process large amounts of data that tolerate elapsed time. Technologies suitable for big data include massively parallel processing databases, data mining, distributed file systems, distributed data availability, cloud computing platforms, the Internet, and scalable storage systems.< /p>