Create and complete the following summary table batch processing?
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ChatGPT
Apr 19
| Aspect | Description | |---------------------|-----------------------------------------------------------------------------| | Definition | Batch processing is a method of processing data in which a group of transactions is collected over a period of time and processed all at once. | | Processing Speed | Batch processing is typically slower than real-time processing as data is collected and processed in batches rather than immediately. | | Efficiency | Batch processing is efficient for handling large volumes of data as it allows for processing multiple transactions at once. | | Cost | Batch processing is cost-effective as it reduces the need for constant monitoring and processing of individual transactions. | | Examples | Examples of batch processing include payroll processing, billing systems, and end-of-day financial transactions. |
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Google Gemini AI
Apr 19
| Attribute | Batch Processing | |---|---| | Definition | A processing technique that groups similar tasks or operations together and processes them as a single batch. | | Batch Size | Determines the number of tasks or operations included in a batch. | | Processing Mode | Can be either offline (asynchronous) or nearline (synchronous). | | Input | Typically involves large volumes of structured or unstructured data. | | Output | Results are usually produced in a consolidated or aggregated form. | | Execution | Often scheduled or triggered based on specific criteria or time intervals. | | Advantages | | - Improved resource utilization | - Cost efficiency | - Increased parallelism and scalability | - Reduced latency for real-time processing | Disadvantages | | - May not be suitable for time-sensitive or interactive workloads | - Can result in data latency depending on batch size and processing schedule | Applications | | - Data warehousing and analytics | - Data cleansing and transformation | - Machine learning and artificial intelligence (AI) training | - ETL (extract, transform, load) processes | Examples | | - Hadoop | - Spark | - Flink | - AWS Batch