Shulou(Shulou.com)05/31 Report--

Big data in how to solve the real-time problem of data processing, in view of this problem, this article introduces the corresponding analysis and solution in detail, hoping to help more partners who want to solve this problem to find a more simple and feasible method.

In the era of big data, business data precipitation and data computing have penetrated into various industries and created new business value. The real-time streaming computing cloud service released by Baidu Intelligent Cloud was born in this environment.

Before introducing this cloud service, let's take a look at what real-time streaming computing is. Subsequently, we will focus on the product features and application scenarios released by Baidu Intelligent Cloud to help enterprises make good use of real-time streaming computing.

one

The core of real-time stream computing is "real-time"

The traditional data processing process has been well known by the public, that is, first collect the data and store it in the database, and then query the data when needed to get the data results. Such a process seems very reasonable, but the timeliness of data processing is not high. In a real business scenario, the result of this approach is that the value of a lot of data disappears over time. Therefore, big data computing platform needs to improve the timeliness of computing as much as possible and obtain the maximum value of data.

Traditional offline processing processes such as MapReduce can not solve the timeliness problem, which leads to the data computing structure of real-time stream computing. Real-time streaming computing can analyze and output the results of massive streaming data in real time, and the whole process is only one second or even subseconds.

The value of real-time stream computing in the actual business data processing can not be underestimated, and the convenience it brings to the enterprise is also obvious. In order to cope with this trend, Baidu Intelligent Cloud released a Serverless cloud service for real-time cloud streaming data processing: Baidu Intelligent Cloud streaming Computing BSC product (hereinafter referred to as "BSC") can help enterprises easily access the massive data stored in a variety of Baidu intelligent cloud storage services (such as Baidu messaging service), eliminating a series of basic work such as infrastructure operation and maintenance and upgrading.

two

Provide full lifecycle services

As can be seen from the figure below, BSC connects and deeply integrates cloud storage services of various Baidu intelligent clouds as upstream and downstream, which can be easily accessed with simple configuration.

In addition to opening up a variety of cloud services mentioned above, BSC products also have the following features:

► fully hosted service

BSC provides Serverless services for enterprises. When enterprises use BSC for streaming data processing, they do not need to create clusters, avoiding the heavy day-to-day operation and maintenance of the underlying infrastructure; enterprises do not even need to allocate computing resources in advance.

► is easy to use.

Compared with traditional Spark jobs, BSC provides zero-code job creation mode, allowing users to achieve complex business logic data processing through SQL statements; and BSC provides SQL online editor with a variety of auxiliary functions, which greatly reduces the threshold of use, improves ease of use and efficiency.

► on-demand service

BSC will set corresponding computing resources for streaming jobs according to the changes of enterprise business data, which not only ensures that business data is processed in time, but also avoids the waste of resources.

three

Typical application scenario

1. Physical equipment monitoring

In the Internet of things industry, the sensors on the equipment will report the data regularly. BSC can calculate and analyze the reported data in real time, filter out the data beyond the normal range, output in time and trigger the alarm. In order to achieve real-time monitoring and detection of equipment failures, in time to avoid the occurrence of potential business risks.

2. Financial risk control

Financial risk control is another typical real-time computing application scenario. For the financial business with high risk sensitivity, it is not enough to count the business data and operate the business data only through data visualization. For financial fraud and other risk control business, BSC can play a huge role. By analyzing the massive data flow of user behavior in real time, and combining with some matching rules of risk models, BSC can help customers find abnormal events and judge the risk level in time, so as to make corresponding risk control measures, such as automatic alarm notification to avoid loss.

3. Personalized recommendation

In general, the demands of Internet users for information, music, shopping and so on are thousands of people, and this demand has a certain timeliness. Take shopping as an example, when consumers buy the goods they are satisfied with, they no longer need other similar goods. In order to perceive the changes of consumers' needs in real time, it is necessary to carry out real-time calculation and analysis according to their browsing behavior data. After the application of BSC products, enterprises can update consumers' preferences in real time, constantly find users' new preferences, and make personalized recommendations in time.

In addition to the above classic business scenarios, BSC can also be widely used in more timely scenarios.

This is the answer to the problem of how to solve the real-time problem of data processing in big data. I hope the above content can be of some help to you, if you still have a lot of doubts to be solved. You can follow the industry information channel for more related knowledge.

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