HOTSPOT - For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point. Hot Area:
Suggested Answer:
Box 1: Yes - Batch processing refers to processing of high volume of data in batch within a specific time span. It processes large volume of data all at once. Batch processing is used when data size is known and finite. It takes little longer time to processes data.
Box 2: Yes - Stream processing refers to processing of continuous stream of data immediately as it is produced. It analyzes streaming data in real time. Stream processing is used when the data size is unknown and infinite and continuous.
Box 3: No - Reference: https://www.geeksforgeeks.org/difference-between-batch-processing-and-stream-processing/
Yes – This is a batch workload because it processes data in predefined chunks, typically on a scheduled basis (daily in this case).
Yes – This is a streaming workload because it involves continuously processing incoming data, typically in real-time or near real-time.
No – This is more likely a batch workload since it processes historical data over a specific time period (last month), which is typically done in batches.
Yes – This is a batch workload because it processes data in predefined chunks, typically on a scheduled basis (daily in this case).
Yes – This is a streaming workload because it involves continuously processing incoming data, typically in real-time or near real-time.
No – This is more likely a batch workload since it processes historical data over a specific time period (last month), which is typically done in batches.
I thought it was yes on the second statement and according to chatGPT here is the scoop for your consideration: "Yes, a job that calculates a rolling average of temperature readings can be considered an example of a streamed workload. In this context, a streaming workload typically involves processing and analyzing data in real-time or near-real-time as it is generated."
When dealing with temperature readings, a streaming workload might involve continuously receiving and processing data from sensors or sources providing temperature information. Calculating a rolling average in real-time allows for dynamic and up-to-date insights into temperature trends without the need to wait for batch processing.
So, in summary, calculating a rolling average for temperature readings aligns with the characteristics of a streaming workload, especially if the analysis occurs as new data is continuously generated.
The second one is indeed streaming, upon searching on it Microsoft has a good resource that proofs that an average calculation that is done over a period of time uses Streaming analytics, for example a taxi company that wants to know average tip on a 5 minutes window. In this case the rolling avg temperature it is processed as it arrives which is why is streaming. There is NO waiting time in this case.
https://learn.microsoft.com/en-us/azure/architecture/reference-architectures/data/stream-processing-stream-analytics
Yes - periodical jobs use batching
Yes - a rolling average will use a sized set that is updated with newest data.
No - Last month sales are past data only, so this is a batch job.
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