The Apache Hadoop ecosystem is a robust, flexible, and low-cost way to organize big data and can be used alongside a relational database model. It uses a data storage system called the Hadoop Distributed File System (HDFS) to help you organize your data the way you want it. This data can be stored over multiple server systems, which reduces the risk of issues related to hardware failure. This sophisticated management system is an incredible big data helper!
HDFS is where data is stored in the Hadoop ecosystem and can be easily accessed in FME. Use FME to upload, download, list, or delete your Hadoop file system data files like CSV or JSON with the HDFSConnector. Put data in, or take data out for use in other applications. With FME, you can parse your data to simplify processing tasks and keep your data structured in your own customized way.
Hadoop lets you process your data quickly and continue to add more data without limitations. With FME you can organize and optimize your data in an intuitive drag-and-drop interface. Use FME to enhance your data without coding! Automate your workflows with FME Server to increase efficiency and consistency throughout your big data sets.
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Why does FME support the HDFS format? Because it’s what our users wanted! We listen to our customers and their suggestions to make sure that FME is always meeting their needs. With the data world forever changing, we want to make sure that we provide the best product to help you keep up with that change.
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The Hadoop Distributed File System (HDFS) is the storage system used by Hadoop-related applications. Through parallel processing it provides high-performance access to large datasets for applications using big data.