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You are planning a streaming data solution that will use Azure Databricks. The solution will stream sales transaction data from an online store. The solution has the following specifications: * The output data will contain items purchased, quantity, line total sales amount, and line total tax amount. * Line total sales amount and line total tax amount will be aggregated in Databricks. * Sales transactions will never be updated. Instead, new rows will be added to adjust a sale. You need to recommend an output mode for the dataset that will be processed by using Structured Streaming. The solution must minimize duplicate data. What should you recommend?
Correct Answer: A
Explanation Append Mode: Only new rows appended in the result table since the last trigger are written to external storage. This is applicable only for the queries where existing rows in the Result Table are not expected to change. Reference: https://docs.microsoft.com/en-us/azure/databricks/getting-started/spark/streaming