Название: Python And Hadoop Basics: Programming For Beginners - 2 Books In 1 - Learn Coding Fast! Python And Hadoop Crash Course, A Quickstart Guide, Tutorial Book By Program Examples, In Easy Steps! Автор: J. King, Tam Sel
Издательство: Amazon.com Services LLC
Год: 2020
Страниц: 146
Язык: английский
Формат: pdf, azw3, epub
Размер: 10.1 MB
"Python Basics" covers all essential Python language knowledge. You can learn complete primary skills of Python programming fast and easily. By this book you can learn fundamentals of Python.
"Hadoop Basics" covers all essential Hadoop language knowledge. You can learn complete primary skills of Hadoop programming fast and easily. The book includes practical examples for beginners.
Python makes the development and debugging fast because the compilation step is not included in the development of Python, and the edit-test-debug cycle is very fast. Compared with other programming languages Python is easy to learn. Its syntax is direct and much the same as the English language. The semicolon or curly-bracket is not used, and the indentation defines the block of code. It is the recommended language for beginners in the programming. Using a few lines of code Python can perform complex tasks. A simple example, you simply type print("Hello World”) to the hello world program. It'll take one line to execute, while Java or C will take multiple lines.
"Hadoop Basics" includes basics of Big Data Hadoop with HDFS, MapReduce, Yarn, Hive, HBase, Pig, Sqoop etc. Hadoop is a framework which is open source. The processing and analysis of very huge volumes of data is provided by Apache. It's written in Java and used by Google, Facebook, LinkedIn, Yahoo, Twitter and so on. It can also be scaled up merely by adding nodes to the cluster.
Modules:
• Yarn: Another Resource Negotiator is used for job planning and the cluster management.
• HDFS:Google published its GFS paper and was developed based on that HDFS. It states that, over the distributed architecture, the files are broken into blocks and stored in nodes. HDFS Hadoop means Distributed File System.
• Hadoop Common: These Java libraries are used to start Hadoop and other Hadoop modules are used for this.
• Map Reduce: This is a framework that helps Java programs use key value pair to do the parallel data computation. The Map task takes data from input and converts it into a set of data that can be computed in key value pair. Map task output is consumed by reducing task, and then the reducer output gives the desired outcome.
The Hadoop architecture is a file system package, MapReduce engine, and HDFS (Hadoop Distributed File System) package. The MapReduce motor may be either MapReduce / MR1 or YARN / MR2. A Hadoop cluster comprises a single master and several slave nodes. The master node includes Job Tracker, Task Tracker, NameNode, and DataNode, while DataNode and TaskTracker are included as the slave node.
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