Process large data sets with Hadoop and MapReduce in the cloud.
Start coding free →Apache Hadoop is an open-source framework for distributed storage and parallel processing of large data sets. It provides HDFS for distributed file storage and MapReduce for batch data processing. Built on Java and designed to scale horizontally across commodity servers, it is used in finance, healthcare, and e-commerce for data mining, warehousing, and large-scale analytics. A RunCode workspace gives you Hadoop and Java preinstalled.
Open a Hadoop workspace →Hadoop splits a workload across many nodes so that large data sets are processed in parallel. HDFS stores data across the cluster, and MapReduce coordinates the computation. The framework handles unstructured and semi-structured data well, which is why it appears in big data pipelines across many industries. It also includes tools for data mining, warehousing, and large-scale machine learning jobs.
To run a Hadoop application on RunCode, compile your Java code and submit it with the hadoop jar command. The hadoop command-line utility controls job submission, monitors progress, and lets you inspect the output on HDFS.