Description: This time, the developer community welfare - the offer of high-quality collection compiled some articles on big data technologies in the field of comparative welcomed by developers as being "home home office" little friends.
Whether are new to the field, or already have some understanding, I believe can benefit from the article. Come learn it ~
1. Data engineers need to master seven real big data projects
- Worth collecting, data engineers must master seven real big data projects
2. Ali cloud big data + AI technology Sharon Shanghai Station Review | Secret behind first place in the list of TPC-DS powerful engine
- Big data November 16th of + AI Salon Shanghai station complete success! EMR team operating in the country's largest Spark community, in order to better disseminate and share the latest technologies and industry best practices, is now a joint open source community counterparts, to create the next line purely technical exchanges Sharon "big data + AI", on a regular basis for everyone do public share. The share TPC-DS Secret powerful engine behind the first list, explore how big data Pyboot get through ecology, learning together the industry's latest storage solutions and machine-learning platform.
3. The value of the digital data in the table thinking - Xu Jiqiu
- It refers to the table data, mass data acquisition, calculation, memory, a data-processing, and at the same time unified standard caliber. After the data in the data sets unified, standard form data, and then storing the formation of large data assets layer, thus providing customers with efficient service. Data in the narrow sense refers to single-data technology, such as mass data collection, computing, storage, and processing of a series of technical collection nowadays we talk about the data table also includes data models, algorithms services, data products, data management and methodology. Data in this chapter from the perspective of the traditional enterprise digital transformation, analyzed the value of the digital platform.
4. [Q] Large quality data Q TECHNIQUES 1000
- Developer community planning big data computing technology 1000 asked content, including Flink, Spark and other flow calculation (calculated in real time), off-line calculation, Hbase and other technical problems encountered in practice interview questions and other dimensions and content.
5. How to analyze and deal with Flink back pressure?
- Backpressure (backpressure) is calculated in real time application development, especially the flow calculation, a very common problem. Back pressure means that a node in the data pipeline becomes a bottleneck, the processing rate to keep up with the rate of the upstream transmission data, and the need for speed upstream.
6. available for download! "Ali Baba combat AI and big data," the depth of analysis of large data practices typical scene
- Depth analysis of Taobao, High German, League of Friends +, 1688, Youku, Ali Mama, Ali Pictures Big Data combat scenes, 2020 not to be missed large enterprise data practical manual.
7. Exclusive Download | "big data engineers must read the manual," How to Break Ali Secret Big Data
- How Alibaba Fun Big Data? Ten Alibaba depth expert analysis of large data, Legend eight products the latest data platform play, not to be missed 2019's big data sheet - "Big Data Engineer reading Handbook" is available for free download to read it, and quickly preview it.
8. Exclusive Download | "big data engineers must read the manual," How to Break Ali Secret Big Data
- How Alibaba Fun Big Data? Ten Alibaba depth expert analysis of large data, Legend eight products the latest data platform play, is not fault tolerant 2019
9. take you read one of "Apache Kylin Definitive Guide": Apache Kylin Overview
- From the earliest use of Big Data technologies to do batch processing, and now more and more people require large data platform can also be the same as traditional data warehouse technology to support interactive analysis, with the ever-expanding amount of data, the data continues to advance civilians , low-latency, high concurrency provides standard SQL query capabilities become necessary to break through the technical problems on Hadoop. The birth of the Apache Kylin is precisely this background, and successfully completed a lot of people think that a breakthrough can not be achieved.
10. The two take you read "Apache Kylin Definitive Guide" is: Getting Started
- This chapter introduces the basic concepts you must understand before using Apache Kylin, such as the star data model, fact tables, dimension tables, dimensions, metrics, etc., and based on the understanding of these basic concepts quickly create a Sample Data based model, constructing Cube Finally, execute SQL queries. He takes the reader to experience the Apache Kylin main course.
11. take you read the third "Apache Kylin Definitive Guide" is: Cube optimization
- This chapter describes the optimization method from multiple angles Cube: Cuboid prune from the perspective view, from the perspective of particle size concurrency control, from Rowkey design, as well as from the viewpoint of the accuracy of the selected metric. Overall, Cube Cube optimization requires the administrator to have a more profound understanding and awareness of the Kylin, which also indirectly raises the threshold for the use and management of Kylin.
New Challenges 12. Jayantha talk big data & AI development and new opportunities
- 2019 Yunqi Big Data & AI General Assembly Session, Alibaba Senior Fellow Jayantha clear to us "big data AI development of new opportunities and new challenges" to share. This paper will start with the concept of artificial intelligence, he spoke about the development of model training and depth of learning, and the explosive growth of data, focuses on the closed-loop algorithms, data and calculation power.
13. Large groups of data from 0 to 1
- "Big Data" is the word, we have not unfamiliar, has become a staple of people will talk to the concept from a new vocabulary. A variety of large and small Internet companies will also create their own big data team, I have also worked on development and team management in the field of big data companies, here to write about my own experiences and feelings.
14. Detailed Ali cloud data in the table, an article in a comprehensive understanding of big data "red network"
- Always wanted to write an article about the data in the front desk, there are at leisure to do sum up, think about the full interpretation of how to look at insider data DT in Taiwan. Data in the table is the first concept first proposed by Alibaba, in response to numerous internal business needs and ever-changing high-speed data timeliness requirements grow up, it has to meet the business daily data of multiple business front desk demand, but also to meet like two-eleven, six hundred and eighteen such business summit to deal with large-scale data linear scalability issues to deal with complex issues decoupling active scene of business systems, and to take in terms of technology, organizational structure, etc. Some change.
15. Big Data talent cultivation experience sharing
- Summed up in the past 5 years experience in big data talent cultivation in various colleges and universities.
