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

In recent years, big data has become popular, attracting more and more people to join the team of learning big data, among which there are many basic rookies, and some even don't even know much about the programming language, so it must be wrong to say that some students have lost confidence in themselves and think that they can't learn big data. So here, I will briefly lead you to understand how big data should learn.

one。 Learn the theoretical knowledge of big data

First of all, we must first lead you to understand what big data is, right? Only when big data is built on what medium and in what scene can you know whether you want to learn from big data? if you only listen to the high-end name to learn, you will find that you don't like it until you have learned it for a period of time. Is it a waste of time and money for you? So we need to know what big data is first!

two。 Basic programming language

When you know enough about what big data is and what big data does, you think you are interested. So congratulations. Next, you are about to enter our entire journey of big data. If you want to enter the big data industry, you must learn to write programs, that is, programming languages, then what programming language should we learn? Yes, it's java, because our road is big data, so we don't need to go deep into java, we just need to finish learning javaSE.

If you want to learn big data well, you'd better join a good learning environment. You can come to this Q Group 251956502 so that it is more convenient for everyone to learn, and you can also communicate and share materials together.

three。 Database and linux operating system

After learning the programming language, we will definitely learn the database next, because our data needs to be stored, so where does the database start? Start with the simplest mysql relational database. Of course, if you still have the energy and time, you can also learn the Oracle database. After learning these two databases, you can also learn the linux operating system, because most of the enterprise servers use the linux operating system and the xxx version.

four。 Big data ecology

Hadoop:

Well, after the previous foundation has been laid, we will enter big data's ecological learning. Starting with hadoop (offline distributed processing Framework), we will start with four core components, namely, hdfs (solving the problem of how to store big data), MapReduce (solving the problem of how to calculate big data), yarn (Resource Scheduler), common (Common Class Library), after the completion of the four core components. We need to learn about the external dependent components of our hadoop, such as Zookeeper (providing sliver services), Sqoop (data migration), hive (data warehouse), and hbase (column storage database).

Spark

After learning our hadoop, we will also learn another distributed offline computing framework: Spark, because our Spark is faster than our hadoop, first of all based on memory, and also because of DAG directed acyclic graphs. So the first thing to learn about Spark is to learn.

Scala (functional programming language), kafka (message Middleware message queue), sparksql,spark core,sparkstreaming (Micro batch Real-time processing), spark Structure streaming (spark batch Fusion), redies (memory Database)

Flink

The current hot, popularized and used in 2016, our branch of Ali launched blink, this year will continue to use flink,flink has supported Ali's entire system, ant, Gao de, Taobao, Cainiao logistics the entire computing model is using flink, last year Ali acquired flink, now it is very hot.

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five。 Project actual combat

Of course, needless to say, people can see the company standards when they go out to look for a job, and they all require work experience in the field. Practical operation is very important, and it is also a consolidation and landing of learning knowledge.

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