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This article mainly introduces "what are the advantages of Hadoop". In daily operation, I believe many people have doubts about what the advantages of Hadoop are. Xiaobian consulted all kinds of materials and sorted out simple and easy operation methods. I hope to help you answer the doubts of "what are the advantages of Hadoop"! Next, please follow the small series to learn together!

Definition of Hadoop

In a nutshell: Hadoop is a tool for storing and analyzing massive amounts of data.

Hadoop is an open source framework written in java language that stores massive data and runs distributed analytics applications on distributed server clusters. Its core components are HDFS and MapReduce.

HDFS is a distributed file system: it introduces a server NameNode that stores file metadata information and a server Datanode that actually stores data, and stores and reads data distributed.

MapReduce is a computational framework: The core idea of MapReduce is to distribute computational tasks to servers within a cluster. Through the split of computing tasks (Map computing/Reduce computing), distributed computing is performed on tasks according to the task scheduler (JobTracker).

Advantages of Hadoop

High reliability: Hadoop's ability to store and process data bitwise is something people can trust.

Highly scalable: Hadoop distributes data and performs computing tasks among clusters of available computers that can be easily scaled to thousands of nodes.

Efficiency: Hadoop can dynamically move data between nodes and keep the dynamic balance of each node, so the processing speed is very fast.

High fault tolerance: Hadoop automatically saves multiple copies of data and automatically redistributes failed tasks.

Low cost: Compared with all-in-one computers, commercial data warehouses, and data marts such as QlikView and Yonghong Z-Suites, Hadoop is open source, so the software cost of the project will be greatly reduced.

Hadoop comes with a framework written in Java, so it is ideal to run on Linux production platforms, and applications on Hadoop can also be written in other languages, such as C++.

What Hadoop can do

Big Data Storage: Distributed Storage

Log processing: good at log analysis

ETL: Data extraction to Oracle, MySQL, DB2, MongDB and mainstream databases

Machine Learning: Apache Mahout Project

Search engine:Hadoop + lucene implementation

Data mining: currently popular advertising recommendations, personalized advertising recommendations

Hadoop is designed for offline and large-scale data analysis and does not fit into online transaction processing patterns that read and write randomly to several records.

At this point, the study of "What are the advantages of Hadoop" is over, hoping to solve everyone's doubts. Theory and practice can better match to help everyone learn, go and try it! If you want to continue learning more relevant knowledge, please continue to pay attention to the website, Xiaobian will continue to strive to bring more practical articles for everyone!

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