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Explain about the common workflow of a Spark program?
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Answer Posted / Chandan Singh
The common workflow of a Spark program consists of the following steps:n1. Creating a SparkContext: This is the entry point to the Spark system and establishes a connection between the application and the cluster.n2. Reading data: Data can be read from various file systems or external sources using Spark's built-in APIs like Spark SQL, DataFrames, or Resilient Distributed Datasets (RDDs).n3. Transformations: Perform transformations on the data by applying various functions to create new datasets.n4. Actions: Convert transformations into concrete results by calling an action function such as `count()`, `collect()`, or `saveAsTextFile()`.n5. Caching and Persistence: Cache frequently accessed datasets for faster processing in subsequent iterations or persist them on disk to free up memory.
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