Spark's integrated and diversified solution greatly reduces the human cost of development and maintenance and the material cost of the deployment platform, and has great performance advantages, especially for iterative computing, such as machine learning and graph computing At the same time, Spark's support for Scala and Python interactive shells is also greatly facilitated by using the shell directly to validate the problem-solving approach with the spark cluster, which is critical to prototyping and has an unacceptable appeal to data analysts!
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