As one of the most mainstream technology systems in the field of big data, Hadoop is of self-evident importance. Most of us have encountered various emergent problems in actual development, so what causes the frequent occurrence of problems?

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Because you don’t understand the underlying principles of Big data Hadoop, 80% of the people only stay at the level of using the framework and don’t know the underlying framework at all. The open source nature of Hadoop makes it more difficult for developers to choose the right tool. It is conceivable that the choice and use of technology is also a headache for big data developers.

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When we usually learn big data, the most easy to ignore is the bottom part of the framework. Many engineers who have worked for 1-3 years do not have a good grasp of Hadoop, so it is difficult to further break through the technical bottleneck. However, it is exactly one of the questions that BAT and other first-line large factories like to investigate in the interview.

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So, learning the Hadoop framework at the bottom will give you a qualitative leap in the Hadoop ecosystem and the Hadoop framework at the bottom.

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How can we better understand the Hadoop architecture? **** you need a good teacher who can simplify complex problems and make obscure ones easy to understand. Qi Nantang (flower name) is such a person.

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About the old qi

Former chief big data architect of JINGdong, with more than ten years of experience in software development and architecture, led the design and implementation of several sets of big data systems with tens of millions of daily lives and tens of millions of data pieces per day. He has a lot of practical experience in dealing with high concurrency and massive data.

He has served as the head of big data technology in Baidu, focusing on real-time/offline computing, warehousing, computing, cleaning, multi-latitude computing, data mining and machine learning related to big data for a long time.

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What do you learn from following a big data development teacher with more than 10 years of architecture experience?

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1. How to deeply understand the underlying platform of big data architecture, the relationship between big data application development and platforms; * * * *

2. How to better combine the corresponding platform knowledge with application development. * * * * * * * *

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Now we have started the course together with the old family, which has spent two months polishing a big data development course “Big Data Hadoop Basic Principle Practical Road” worth 399 yuan, limited to 300 students for free, at the same time, the top 50 students will share PPT courseware for consolidation and review.

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The content to be shared includes:

1 What does Hadoop do

01. One command is MapReduce

02. HDFS, MapReduce, and YARN

2 Hadoop ecosystem

What are the core components of Hadoop?

02. What is Hadoop in a broad sense?

03. What is the connection between Spark and Hadoop?

04. Detailed introduction of common components in the ecosystem

05. Typical combined use scenarios

3 Java and Python examples of Hadoop

01. Based on Java examples

02. Based on Python examples

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Ten million daily active APP user actual combat cases

01. Data burying point

02. Load Balancing \

03. Consume data written to HDFS

04. Extract fixed format data

05. User similarity calculation

06. User portrait storage

07. Real-time computing

5 A large number of Nginx logs are imported to Hive

01. log format\

02. Segmentation

03. Warehousing \

04. hive QL\

05. Subdue an enemy without fighting

6 Solutions to common problems in actual big data development

01. High availability of namenode \

02. High availability of Resource Manager \

03. What can I do if a Data Node is faulty or added? \

04. To what extent can Hadoop permission control be controlled? \

05. raid or jbod\

6. The balancer? According to what criteria balance? \

07. How to import Hadoop into nginx data source? \

08. Should you consider Hive? \

09. Hive powerful re \

10. What can I do about hive high Availability? \

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Quota is limited to 300 persons!

Long press the QR code to add qi assistant

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The first 10Km is easy for everyone, including beginners, so steadily increase your speed. **** In the last 10Km, everyone gets tired, including the great ones, so you have to grit your teeth.