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Native Java API for HDFS - Hadoop Platform and Application Framework
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Native Java API for HDFS - Hadoop Platform and Application Framework
This course is for novice programmers or business people who would like to understand the core tools used to wrangle and analyze big data. With no prior experience, you will have the opportunity to walk through hands-on examples with Hadoop and Spark frameworks, two of the most common in the industry. You will be comfortable explaining the specific components and basic processes of the Hadoop architecture, software stack, and execution environment. In the assignments you will be guided in how data scientists apply the important concepts and techniques such as Map-Reduce that are used to solve fundamental problems in big data. You'll feel empowered to have conversations about big data and the data analysis process.
Python Programming, Apache Hadoop, Mapreduce, Apache Spark
Super hands on introduction to key Hadoop components, such as Spark, Map Reduce, Hive, Pig, HBase, HDFS, YARN, Squoop and Flume. I can't wait to the next course on the specialization.,Easy into into big data architecture with minimal previous development requirements. Relevant to anyone who wants to grasp basic concepts of how data flows/processed/analyzed in hadoop.
In this module we will take a detailed look at the Hadoop Distributed File System (HDFS). We will cover the main design goals of HDFS, understand the read/write process to HDFS, the main configuration parameters that can be tuned to control HDFS performance and robustness, and get an overview of the different ways you can access data on HDFS.
Native Java API for HDFS - Hadoop Platform and Application Framework
Copyright Disclaimer under Section 107 of the copyright act 1976, allowance is made for fair use for purposes such as criticism, comment, news reporting, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favour of fair use.
Native Java API for HDFS - Hadoop Platform and Application Framework
This course is for novice programmers or business people who would like to understand the core tools used to wrangle and analyze big data. With no prior experience, you will have the opportunity to walk through hands-on examples with Hadoop and Spark frameworks, two of the most common in the industry. You will be comfortable explaining the specific components and basic processes of the Hadoop architecture, software stack, and execution environment. In the assignments you will be guided in how data scientists apply the important concepts and techniques such as Map-Reduce that are used to solve fundamental problems in big data. You'll feel empowered to have conversations about big data and the data analysis process.
Python Programming, Apache Hadoop, Mapreduce, Apache Spark
Super hands on introduction to key Hadoop components, such as Spark, Map Reduce, Hive, Pig, HBase, HDFS, YARN, Squoop and Flume. I can't wait to the next course on the specialization.,Easy into into big data architecture with minimal previous development requirements. Relevant to anyone who wants to grasp basic concepts of how data flows/processed/analyzed in hadoop.
In this module we will take a detailed look at the Hadoop Distributed File System (HDFS). We will cover the main design goals of HDFS, understand the read/write process to HDFS, the main configuration parameters that can be tuned to control HDFS performance and robustness, and get an overview of the different ways you can access data on HDFS.
Native Java API for HDFS - Hadoop Platform and Application Framework
Copyright Disclaimer under Section 107 of the copyright act 1976, allowance is made for fair use for purposes such as criticism, comment, news reporting, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favour of fair use.
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