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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.
Food intoxication can be caused by
Slime in meat spoilage occurs due to accumulation of _______cells
Which of the following is a Class II product?
The Baudouin test checks adulteration in:
Match the Commodity in Group-1 with present Anti-nutritional factor in Group-2
The flour improver used for improving dough quality is
Black tea is a _________ type of tea exhibiting desirable______ oxidation
Refrigeration is a process keeping food close to freezing point between
Potential applications of Electrodialysis are:
Options:
1. Desalination of water
2. Purification of water
3. Concentration o...
The science most associated with the study of plants grown for food or beautification is