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How is the processing of streaming data achieved in Apache Spark? Explain.
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Answer Posted / Pranai Toppo
Apache Spark processes streaming data using Spark Streaming, a module that enables scalable, high-throughput, fault-tolerant stream processing of live data streams. It extends the core Spark API to enable batch and stream processing of live data. The basic unit of data in Spark Streaming is Discretized Stream (DStream), which is an ordered sequence of RDDs (Resilient Distributed Datasets). Each RDD represents a snapshot of data taken at some point in time, and the system creates a new RDD every batch interval. By default, Spark Streaming processes data in micro-batch increments, accumulating incoming data into RDDs before applying transformations.
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