What is Spark Streaming and what can it be used for?

Spark Streaming is a component provided by Apache Spark for real-time data processing. It is capable of handling real-time data streams and can seamlessly integrate with other Spark components like Spark SQL and Spark MLlib.

Spark Streaming can be used for a variety of real-time data processing tasks, including real-time log analysis, real-time recommendation systems, real-time monitoring, and alerts. Its key features include high fault tolerance, high throughput, low latency, and easy integration. Spark Streaming supports various data sources such as Kafka, Flume, Kinesis, HDFS, etc., and can process different real-time data streams. By utilizing Spark Streaming, users can transform real-time data streams into batch jobs, enabling a mix of real-time and batch processing computations.

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