For many junior developers, or not any practical experience in the development of people, large data relevant skills looks especially scary, because a bunch of particularly complex English nouns, as well as a variety of sounds extremely difficult "architecture."
But really to learn to get started, you will find this surprising facility was transferred technology, and did not imagine so difficult, even a little bit interesting.
For each technical people who want to go higher level of development, the background data processing, optimization of construction, architecture data performance data, are not around the past skills. Furthermore, with the rapid increase in the amount of enterprise data, background data infrastructure development needs will become more apparent to master big data relevant skills, personal ability to get higher dimensions to improve.
If you are ready to join the big data and big data regarding the current 2019
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Focus on micro-channel public number itdaima get a full set of development tools, as well as large data entry learning materials
Most of the recruitment needs from the point of view, big data related to the development of job skills requirements as follows:
Write code: Java developers / Linux development environment
Database: Mysql / MongoDB, etc., have some tuning experience
Distributed: Hadoop / Hive / Spark / Storm / HBase, etc.
Bonus items: big data analysis, machine learning, troubleshooting ability
Note: In general, the same types of tools to master a
With most mainstream Hadoop big data development, for example, the main skill system breakdown is as follows:
01. Java programming (distributed)
02. Linux development environment
03. Hadoop（HDFS+MapReduce+Yarn ）
04. HBase (JavaAPI operation)
05. Hive (queries, functions, views)
06. Sqoop & Flume (Data Acquisition)
07. Other: Pig, HUE, HA, etc.
How are these skills to use at work? What kind of role to play in the entire process of development of big data in it? A graph can be described.
Big Data architecture background basic flow chart
In fact, the whole process very large data back clear, mainly related to data extraction, file storage, data access, data calculation, process data analysis applications.
The core design of Hadoop framework is: HDFS and MapReduce. HDFS provides storage of vast amounts of data, the calculation conditions for the MapReduce provides vast amounts of data.
With the overall knowledge structure, and familiar with the process Big Data application development, learning path again planning on much clearer. Usually after four stages, we can master big data to develop core skills.
1.Linux and Java foundation
Programming language is the basis for the completion of project development. Java has a sound development of ecological and mainstream big data development are implemented in Java, so it is necessary to master the basic Java programming, and understand Linux development environment, can be used to build infrastructure services.
Java-based, virtual machines, multiple threads
JavaWeb and database
Linux basic syntax, shell programming
2.Hadoop core framework
The main part of the learning system in the core Hadoop HDFS and MapReduce, to grasp the core of large data storage and computing.
Operation of HDFS shell (commonly used commands and parameters)
HDFS Java application development (data collection, storage, file)
MapReduce programming (norm, run, debug)
MapReduce calculation program (ordering, partitioning, optimization)
3.Hadoop ecological data
Primarily a series of important tools around Hadoop database development, such as HBase, Hive, Flume, are primarily training data cleaning, processing, analysis skills.
HBase data operations (read, write, update), the basic architecture
Hive data storage and computing (table structures, partitions, query, function)
Flume & Sqoop acquisition, export the system to achieve
Pig data processing and data analysis
4. Management and Visualization Cluster
Through the above study, the core Hadoop has been mastered, then that is engineered form of thinking, the whole big data management architecture.
Management Visualization HUE (integrated with HBase, Hive)
HA cluster: Zookeeper build a highly available cluster environment
So, in fact, a process down, to form a clear learning plan, and in the process you need to know what each part of the knowledge mastered these skills are applied to achieve what.
Just, Hadoop complete ecological system, and based on this learning path, we have designed an appropriate entry, and deep core curriculum Big Data skills - "Hadoop big data development."
Hadoop core skills system
Courses with the current mainstream big data system architecture, through the "data collection, cleaning, storage, processing, analysis and extraction application" of the whole process. Hadoop big data development in simple terms the various components of the core technology, principles and practice projects.
Including large data collection, storage, distributed computing resource management and a variety of main engines, such as HDFS, Mapreduce, HBase, Hive, HUE, Pig, Sqoop, Flume, Zookeeper and so on.
More Big Data learning resources, please visit public number: ITdaima
Benchmarking job: Hive development engineer, Hadoop development engineer
Extend job: big data analysts, big data development engineer, big data project / product manager
Easy to use Big Data Development
Course covers a comprehensive project development process, from helping you get started, to master the core technology of big data and really start to use real project, a complete development experience.
Courses have an excellent after-school information, covering knowledge, notes, source code, develop important learning resource materials, to reduce the time you collect data to improve learning efficiency.