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.
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The angle at the centre representing Cherry is:
What is the total number of wallets sold by all stores together on Wednesday?
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Find the average number of models promoting Chanel, ZARA and Louis Vuitton.
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Find average number of students participated in sports A, B and D together in 2011.
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The HR division has 15% of the company’s workforce, distributed among Junior, Mid-Level, and Senior employees in the ratio 1:2:3. If each Junior emplo...