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Apache Spark is an open-source program used for data analytics. It's part of a greater set of tools, including Apache Hadoop and other open-source resources for today’s analytics community.
Experts describe this relatively new open-source software as a data analytics cluster computing tool. It can be used with the Hadoop Distributed File System (HDFS), which is a particular Hadoop component that facilitates complicated file handling.
Some IT pros describe the use of Apache Spark as a potential substitute for the Apache Hadoop MapReduce component. MapReduce is also a clustering tool that helps developers process large sets of data. Those who understand the design of Apache Spark point out that it can be many times faster than MapReduce, in some situations.
Those reporting on the modern use of Apache Spark show that companies are using it in various ways. One common use is for aggregating data and structuring it in more refined ways. Apache Spark can also be helpful with analytics machine-learning work or data classification.
Typically, organizations face the challenge of refining data in an efficient and somewhat automated way, where Apache Spark may be used for these kinds of tasks. Some also imply that using Spark can help provide access to those who are less knowledgeable about programming and want to get involved in analytics handling.
Apache Spark includes APIs for Python and related software languages.