preface

This paper discusses how to learn big data in detail from three aspects:

Big data direction work introduction

Skills required for big data engineers

Big data learning path

I. Introduction of big data

The work on big data is currently divided into three main directions:

01. Big data engineer

02. Data analyst

Big data scientist

04. Others (Data mining is machine learning in nature, but related to data, can also be understood as a direction of big data)

2. Skill requirements of big data engineers

Attached are two more authoritative big data engineer skills chart

The summary is as follows:

10 required skills:

Java advanced (VMS and concurrent), Linux basic operations, Hadoop (HDFS+MapReduce+Yarn), HBase (JavaAPI operation +Phoenix) Hive(Hql basic Operation and principle understanding), Kafka, Storm, Scala needs, Python, Spark (Core+ SparkSQL +Spark Streaming), some small tools (Sqoop, etc.)

6 Advanced skills:

Machine learning algorithm and Mahout library plus MLlib, R language, Lambda architecture, Kappa architecture, Kylin, Aluxio

As a programmer who wants to learn big data, it is particularly important to have a learning atmosphere and a communication circle. This is my big data learning exchange group 710219868 (invitation code: Silence). Friends who want to learn and exchange big data and plan to have a deeper understanding of this industry are welcome to join, no matter you are small white or big oxen. We can exchange and learn together

Every day, there are big names to bring you big data knowledge and learning routes and methods. Welcome to join us

3. Learning path

Related study books: Java Advanced Learning (In-depth Understanding of Java VMS, Java High-Concurrency Combat), Hadoop, HBase (HBase Authoritative Guide), Hive (Hive Development Guide), Scala (Learn Scala Quickly), Spark (Spark Quick Big Data Analysis)

For other skills, please go to the Internet to collect more information. I have told you the most important thing (what to learn).

The rest is that you go to collect the corresponding information to learn OK

conclusion

Of course, if you find yourself too slow to read, you can collect some lessons online and follow them. It all depends on your situation. If you can’t read efficiently, read online. If you can’t read on your own.