what are the roles and responsibilities of hadoop developer?
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["Meeting with the development team to assess the company's Big Data infrastructure.", 'Designing and coding Hadoop applications to analyze data collections.', 'Creating data processing frameworks.', 'Extracting data and isolating data clusters.', 'Testing scripts and analyzing results.']
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Apache Hadoop is a software framework employed for clustered file system and handling of big data. ... Hadoop is an open-source framework that is written in Java and it provides cross-platform support. No doubt, this is the topmost big data tool. In fact, over half of the Fortune 50 companies use Hadoop.
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A big data architect is required to solve problems that are quite big by analyzing the data, using Hadoop, which is a data technology. A big data architect is required to handle database on a large scale and analyse the data in order to make the right business decision.
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Hadoop is a database framework, which allows users to save, process Big Data in a fault tolerant, low latency ecosystem using programming models. ... On the other hand, Python is a programming language and it has nothing to do with the Hadoop ecosystem.
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Java Developer responsibilities include: Designing and developing high-volume, low-latency applications for mission-critical systems and delivering high-availability and performance. Contributing in all phases of the development lifecycle. Writing well designed, testable, efficient code.
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In Hadoop, Reducer takes the output of the Mapper (intermediate key-value pair) process each of them to generate the output. The output of the reducer is the final output, which is stored in HDFS. Usually, in the Hadoop Reducer, we do aggregation or summation sort of computation.
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['Work with developers to design algorithms and flowcharts.', 'Produce clean, efficient code based on specifications.', 'Integrate software components and third-party programs.', 'Verify and deploy programs and systems.', 'Troubleshoot, debug and upgrade existing software.', 'Gather and evaluate user feedback.']
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mrjob is a Python 2.7/3.4+ package that helps you write and run Hadoop Streaming jobs. Stable version (v0.7.3) documentation. Development version documentation. mrjob fully supports Amazon's Elastic MapReduce (EMR) service, which allows you to buy time on a Hadoop cluster on an hourly basis.
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['Provide technical support for both hardware and software issues our users encounter.', 'Manage the configuration and operation of client-based computer operating systems.', 'Monitor the system daily and respond immediately to security or usability concerns.']
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Big Data is treated like an asset, which can be valuable, whereas Hadoop is treated like a program to bring out the value from the asset, which is the main difference between Big Data and Hadoop. Big Data is unsorted and raw, whereas Hadoop is designed to manage and handle complicated and sophisticated Big Data.
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['Code and test programming for software and mobile apps.', 'Develop and deploy computer applications.', 'Execute code builds to test and production environments.', 'Fix bugs in existing code.', 'Collaborate with product, design, and marketing teams.']
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The Hadoop Distributed File System (HDFS) is the primary data storage system used by Hadoop applications. It employs a NameNode and DataNode architecture to implement a distributed file system that provides high-performance access to data across highly scalable Hadoop clusters.
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Job Duties ETL developers are responsible for designing and creating the data warehouse and all related extraction, transformation and load of data functions in the company. After the groundwork has been laid, developers also must test their designs to ensure the system runs smoothly.
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Hadoop is not a type of database, but rather a software ecosystem that allows for massively parallel computing. It is an enabler of certain types NoSQL distributed databases (such as HBase), which can allow for data to be spread across thousands of servers with little reduction in performance.
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Hadoop Daemons. Daemons in computing terms is a process that runs in the background. Hadoop has five such daemons. They are NameNode, Secondary NameNode, DataNode, JobTracker and TaskTracker.
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Sqoop (SQL-to-Hadoop) is a big data tool that offers the capability to extract data from non-Hadoop data stores, transform the data into a form usable by Hadoop, and then load the data into HDFS. This process is called ETL, for Extract, Transform, and Load. ... Like Pig, Sqoop is a command-line interpreter.
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There is no strict prerequisite to start learning Hadoop. You need to understand Linux Operating Systems. (Any one from Ubuntu, CentOS, RedHat etc. Learn any one programming language Java or Python.