Spark is one of the most popular and widely used big data processing frameworks in the world. It has a large open-source community, with continuous development, updates, and improvements being made to the platform. Spark has gained popularity due to its ability to perform in-memory data processing, which significantly accelerated the data processing times compared to traditional batch processing systems like Hadoop MapReduce.

However, all that glitters is not gold. Spark is well known for being one of the best data processing frameworks available in the market, thanks to its capacity to process batch data, but when it comes to streaming data, Spark can be challenging if you don’t have previous experience working with any streaming framework.

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