26. dubna 2021 v 02:46
Data engineers and scientists may use Spark Streaming to process real-time data from a number of sources, including (but not limited to) Kafka, Flume, and Amazon Kinesis. Data can be pushed to filesystems, databases, and live dashboards after it has been processed. A Discretized Stream, or DStream, is the main abstraction, which represents a stream of data separated into small batches. RDDs, Spark's central data abstraction, are the foundation for DStreams. This enables Spark Streaming to work in tandem with other Spark components such as MLlib and Spark SQL. Know more about these spark APIs, join the Best Big Data Hadoop Spark Training.
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