Data Processing Frameworks

Data Processing Frameworks are software frameworks designed to process large volumes of data in a distributed computing environment. These frameworks provide a set of tools and APIs to manage and process data in parallel across a cluster of computers. They are designed to handle structured, semi-structured, and unstructured data and can be used for batch processing, real-time processing, and stream processing. Data Processing Frameworks are used to perform various tasks such as data ingestion, data transformation, data cleaning, data aggregation, and data analysis. Some popular Data Processing Frameworks include Apache Hadoop, Apache Spark, Apache Flink, and Apache Beam.
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