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Stream processing involves continuously analyzing data as it arrives, which is ideal for real-time applications. It processes data in real-time, as opposed to waiting for a complete dataset, making it highly efficient for scenarios requiring immediate insights, such as fraud detection, social media analytics, and sensor data analysis. Stream processing frameworks include Apache Storm, Flink, and Spark Streaming. Batch Processing: Involves processing data in large chunks rather than continuously. It is not real-time. MapReduce: A programming model used for batch processing large datasets, not real-time processing. Hadoop: A framework that supports batch processing but not real-time stream processing. HDFS: The Hadoop Distributed File System (HDFS) is for storing large data sets, not processing them.
Which crop is used as a pulse, fodder and green manure crop?
Ideal gas equation is:
Quiescent centre is found in plants at
For which of the following reasons are shade trees grown in a tea plantation?
Which one the following terminology is used for the process of accumulation of soluble salts at the surface or at some point below the surface of the so...
The list of banned/ restricted agriculture products is provided by
An instrument used to measure the height of tree, is portable and does not uses Pythagoras theorem
Which of the following agriculture commodity are to be known as Shri-Anna?
The application of organic manures in the soil helps in/tends to:
Who did work on the recurrence of wheat rusts in India?