Is an open-source engine developed specifically for handling large-scale data processing and analytics.
Apache Spark is an open-source engine developed specifically for handling large-scale data processing and analytics. Spark offers the ability to access data in a variety of sources, including Hadoop Distributed File System (HDFS), OpenStack Swift, Amazon S3 and Cassandra. Apache Spark is an open-source, distributed processing system commonly used for big data workloads. Spark utilizes in-memory caching and optimized execution for fast performance, and it supports general batch processing, streaming analytics, machine learning, graph databases, and ad hoc queries. Apache Spark is an open source parallel processing framework that enables users to run large-scale data analytics applications across clustered computers. Apache Spark™ is a powerful open source processing engine built around speed, ease of use, and sophisticated analytics. It was originally developed at UC Berkeley in 2009. Since its release, Spark has seen rapid adoption by enterprises across a wide range of industries. Apache Spark is an open source processing framework that runs large-scale data analytics applications. Built on an in-memory compute engine, Spark is known for high performance querying on big data. Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. Apache Spark can process data from a variety of data repositories, including the Hadoop Distributed File System (HDFS), NoSQL databases and relational data stores such as Apache Hive.
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what is apache spark