Spark is so popular because it is faster compared to other big data tools with capabilities of more than 100 jobs for fitting Spark’s in-memory model better. Sparks’s in-memory processing saves a lot of time and makes it easier and efficient. Spark can be used to implement ML tasks like Naïve Bayes and K-means computations and can save time and operational costs. Spark also has APIS and packages for graph processing, streaming, Machine learning to operate on large datasets. Spark can be integrated with Scala, Java, Python, SQL, and R programming languages.
If you are interested to learn Apache Spark, I recommend this Spark Course program by Intellipaat by Intellipaat that provides instructor-led training, hands-on exercises, certification, and job assistance.
Also, check out this video on Spark:
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