Big data development course focuses on content? What skills large learning data to learn?
Take a look at learning syllabus big data training institutions, allowing you to have a clear learning path in the self-study.
Do you have a clear understanding of what big data program should contain thing? Which is where the focus will learn the content of it?
Big Data to develop the core curriculum is the Hadoop framework, can almost be said that Big Data Hadoop development. This framework is similar to SSH / SSM framework for Java application development, is an open source Java framework capable cattle Apache Foundation or other open-source Java community groups to contribute to the development of everyone to use.
Java language is king is the truth, Java's core code is open source, is the result of the global cattle were capable of learning together to jointly develop a common test, so that Java is the most stand the test of language, but anyone can learn Java core and the use of technology as the core technology to develop android same system and the same Hadoop framework.
The concept of big data and artificial intelligence are vague, in accordance with what the line to learn where to completion of the development, want to learn, want to learn the students welcome to join the Big Data learning qq group: 606 859 705, there are a lot of dry goods ( zero-based combat and advanced classical) share to everyone, so that we know the most complete large domestic high-end real practical learning data process system. Starting from java and linux, followed by gradually deep into HADOOP-hive-oozie-web-flume-python-hbase-kafka-scala-SPARK eleven other related knowledge to share!
If the program in the world compared to a tree, then Java is the root, SSH, and so are its Hadoop framework bloom branches and leaves too. Due to the large data development engineer is the most popular IT training industry professionals, technical personnel is leading the Big Data revolution smart beach-goers, is the most direct beneficiaries of the era of intelligent, detailed and thorough so important professional must give you on to Hadoop ecosystem-based, introduced all the technical level at present big data application development engineers at work which are used, suggest that you learn before the big data development engineer professional, have a certain experience of learning Java syntax and basic framework.
Big Data zero-based course content includes java + big data development in two parts, to improve the curriculum for friends java development experience of large data contain only part. Because the foregoing description that you should know, big data is the need to learn some java-based.
Big Data Hadoop open source development platform
hadoop is a large amount of data can be software framework for distributed processing, hadoop in a reliable, efficient and scalable approach to data processing, the reason why the user can easily develop and run the application data processing huge amounts of data on hadoop, because hadoop with high reliability, scalability, high efficiency, high fault tolerance advantages.
Distributed File System -HDFS
Lift hadoop file system, the first thought is to HDFS (Hadoop Distributed File System), HDFS is the main hadoop file system, data is stored in Hadoop platform, the establishment of a distributed storage system on the network. hadoop also integrates other file systems, hadoop file system is an abstract concept, HDFS is just one implementation.
Distributed computing framework -MapReduce
MapReduce is a programming model, is the platform Hadoop data processing. For large data sets (greater than 1TB) parallel computing. The concept "Map (Mapping)" and "Reduce (reduction)", and their main idea is borrowed, and borrowed from the vector programming language properties from functional programming languages. It is very easy for programmers in the case will not be distributed and parallel programming will own programs running on a distributed system.
Distributed open source database -Hbase
HBase - Hadoop Database, HBase is a distributed, column-oriented open-source database. Suitable for unstructured data storage, data retention periods multiple versions. Hbase greatly facilitate the expansion of the Hadoop for data processing and application.
Hive
Hive is a data warehouse Hadoop-based tool, SQL structured query processing functions. You can map the structure of the data file to a database table, and provides a simple sql queries, sql statement can be converted to run MapReduce task execution and submitted to the cluster up. The advantage is the low cost of learning, you can quickly achieve a simple MapReduce statistics by type of SQL statements, without having to develop specialized MapReduce applications, without the use of Java programming, statistical analysis of the data warehouse is very suitable. Share Big Data learning materials group: 606 859 705
Learning Hive, The Hive QL basis for DDL and DML that must be mastered; the definition of the table, and export data to master common query is the basis for the completion of large data statistical analysis. Learn to be programmed for Hive: Use Java API open operating Hive, developed Hive UDF function. Master some advanced features Hive can greatly enhance the efficiency of the Hive. Hive distinguish clearly between the various metadata table; in the optimization process may well be analyzed by means of the execution plan, you need to pay attention to Hive performance optimization is the most important link in the production of learning Hive, the key is how to solve the data skew the association can also enhance the ability to grasp the Hive.
Zookeeper coordination Hadoop ecosystem modules work together
From the English meaning point of view is a little like Hadoop, Hive bees, pig is a pig, Zookeeper is a zoo keeper. Then it is clear Zookeeper role is to coordinate distributed application services to provide consistent service for each module.
Importing and exporting data frame Sqoop
Sqoop is an open source tool, the English meaning of the mahout, the elephant is feeding people, mainly used between Hadoop (Hive) and the traditional database (mysql, postgresql ...) for delivery of data, it can be a relational data in the database to guide into the Hadoop HDFS, it is also possible to enter data HDFS leads to a relational database.
learning target:
1. Know what Sqoop that can do what and architecture;
2. Sqoop environment can be deployed;
3. Master Sqoop use in production;
4 can be used for Sqoop ETL operations.
Scala programming development
Scala is a functional object-oriented language, and similar RUBY GROOVY language, seamlessly combines many features never before forming more than one language paradigm, wherein the high-level concurrency model for large data development. While at the same time running on the JAVA virtual machine.
Spark
Spark is the most popular big data processing framework, in a simple, excellent ease of use, performance known. Rich APIs and libraries also makes Spark become an indispensable tool industry fast data processing and distributed machine learning.
Extended Skills:
python development infrastructure, data analysis and data mining
Sklearn learning data mining tools, data mining familiar naive Bayes algorithm and data mining SVM classification algorithm, and end-use Sklearn achieve Bayes and SVM algorithm.
Storm big data distributed real-time computing
Storm framework of distributed data processing, Storm and expansion can be easily prepared in complex real-time calculation of a cluster of computers, Storm for real-time processing, like Hadoop for batch processing. If MapReduce parallel batch processing reduces the complexity, Storm is to reduce the complexity of real-time processing.