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Co-authored-by: Arik Chakma <arikchangma@gmail.com>
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# Spark
Apache Spark is an open-source distributed computing system used for big data processing and analytics. It provides an interface for programming entire clusters with implicit data parallelism and fault tolerance.
Apache Spark is an open-source distributed computing system designed for big data processing and analytics. It offers a unified interface for programming entire clusters, enabling efficient handling of large-scale data with built-in support for data parallelism and fault tolerance. Spark excels in processing tasks like batch processing, real-time data streaming, machine learning, and graph processing. It’s known for its speed, ease of use, and ability to process data in-memory, significantly outperforming traditional MapReduce systems. Spark is widely used in big data ecosystems for its scalability and versatility across various data processing tasks.
Visit the following resources to learn more:
- [@official@ApacheSpark](https://spark.apache.org/documentation.html)
- [@article@Spark By Examples](https://sparkbyexamples.com)
- [@feed@Explore top posts about Apache Spark](https://app.daily.dev/tags/spark?ref=roadmapsh)

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