What is Hadoop and why should you learn it

Hadoop is a distributed systems infrastructure developed by Apache.

Hadoop implements a distributed file system, or Hadoop Distributed File System, which is highly fault-tolerant and designed to be deployed on low-cost hardware. It also provides high throughput to access the application's data, which is suitable for applications with large data sets. HDFS relaxes the PoSix requirement to access data in the file system in the form of streams.

The core design of the Hadoop framework is that HDFS provides storage for massive amounts of data, and MapReduce provides computation for massive amounts of data.

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Hadoop is a distributed systems infrastructure developed by Apache. Users can develop distributed programs without understanding the underlying details of distribution. Harness the power of clusters, high-speed computing, and storage.

Hadoop implements a Hadoop Distributed File System, or simply Hadoop, that is highly fault-tolerant and designed to be deployed on low-cost hardware. It also provides a high throughput to access the application's data, which is suitable for applications with large data sets. HDFS relaxes the POSIX requirements so that data in the file system can be accessed in the form of streams.

Hadoop is a distributed computing solution and an open-source framework.

Hadoop writes and runs distributed applications to process large-scale data and is designed for offline and large-scale data analysis, but is not suitable for the transaction mode of reading and writing to a few records at random. Hadoop = HDFS (file system, data storage technology related) + MapReduce (data processing), Hadoop data ** can be in any form, has better performance than relational databases in processing semi-structured and unstructured data, has more flexible processing capabilities, and any data form will eventually be converted into key value, which is the basic data unit. Use functions to become mapreduce instead of SQL, SQL is a query statement, and mapreduce is to use scripts and **, and for relational databases, Hadoop, which is used to SQL, has an open-source tool Hive instead.

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Hadoop is a framework for running applications on inexpensive hardware devices in large clusters. Hadoop transparently provides a stable and reliable set of interfaces and data movements for applications. Google's MapReduce algorithm is implemented in Hadoop, which is able to divide the application into many small units of work, each of which can be executed on any cluster node or repeatedly.

In addition, Hadoop provides a distributed file system for storing data on individual compute nodes and provides a high throughput rate for data reads and writes. The Hadoop framework is highly fault-tolerant due to the application of Map Reduce and distributed file system, and it automatically handles failed nodes. The Hadoop framework has been tested in clusters with 600 nodes.

Hadoop is a programming model designed for offline and large-scale data analysis to deal with real-world problems. Specific uses are generally divided into distributed storage of data, log processing, ETL, machine learning, search engines, data mining, etc.