Shulou(Shulou.com)06/03 Report--

Big data as the vocabulary of the hot IT industry, the following data development, data warehouse, data security, data analysis, data mining and so on around the use of big data's business value has gradually become the focus of profits sought after by the industry. With the advent of the era of big data, big data development also came into being.

Big data development is actually divided into two kinds, the first is to write some Hadoop, Spark applications, the second is to develop big data processing system itself. The first type of work feels more suitable for positions like data analyst, and now systems like Hive Spark-SQL also provide an interface to SQL. The second type of work is usually available only in large companies, who usually build their own systems or do some secondary development of open source ones. This kind of work requires both theory and practice to be deeper and more technical.

What techniques does big data need to learn for development? The learning roadmap is as follows:

01

Big data Foundation--

Basic aspects of java language

(1) Java language foundation

Introduction to Java development, familiar with Eclipse development tools, Java language fundamentals, Java flow control, Java strings, Java arrays and classes and objects, digital processing classes and core technologies, Imando O and reflection, multithreading, Swing programs and collection classes

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(2) HTML, CSS and Java

PC website layout, HTML5+CSS3 foundation, WebApp page layout, native Java interactive function development, Ajax asynchronous interaction, jQuery application

(3) JavaWeb and database

Database, JavaWeb development core, JavaWeb development insider

02

Linux&Hadoop ecosystem

Linux architecture, Hadoop offline computing outline, distributed database Hbase, data warehouse Hive, data migration tool Sqoop, Flume distributed log framework

03

Distributed computing framework and

Spark&Strom ecosystem

(1) distributed computing framework

Python programming language, Scala programming language, Spark big data processing, Spark-Streaming big data processing, Spark-Mlib machine learning, Spark-GraphX graph calculation, practice 1: recommendation system based on Spark (real project of a first-tier company), practice 2: Sina (www.sina.com.cn)

(2) storm technical architecture

Storm principles and fundamentals, message queuing kafka, Redis tools, zookeeper detailed explanation, practice 1: log alarm system project, practice 2: guess you like recommending system practice

04

Actual combat of big data project

(real projects of front-line companies)

Data acquisition, data processing, data analysis, data presentation, data application

05

Big data Analysis-AI (artificial Intelligence)

Data Analyze working environment preparation & basic data analysis, data visualization, Python machine learning

Python Machine Learning 2, Image recognition & Neural Network, Natural language processing & Social Network processing, practical projects: outdoor equipment recognition Analysis

Big data is the direction of the development of the Internet, big data talent is the future high-paid aristocracy. With the supply of big data talents falling short of demand, the salary and treatment of big data talents is also increasing. Learning from big data development, opportunities and technology are essential!

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