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DP-200 Exam - Question 51


Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.

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You have an Azure Storage account that contains 100 GB of files. The files contain text and numerical values. 75% of the rows contain description data that has an average length of 1.1 MB.

You plan to copy the data from the storage account to an enterprise data warehouse in Azure Synapse Analytics.

You need to prepare the files to ensure that the data copies quickly.

Solution: You convert the files to compressed delimited text files.

Does this meet the goal?

Show Answer
Correct Answer: A

Converting the files to compressed delimited text files will indeed help in copying the data quickly. Compressed delimited text files reduce the file size significantly, which in turn decreases the time and resources required for data transfer. This is a general best practice for optimizing data transfer speeds, particularly when dealing with large volumes of data, such as the 100 GB of files in this scenario.

Discussion

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vrmei
Jun 5, 2021

It should be "No" as the row length should be less than 1 MB

lgtiza
Jun 22, 2021

Check answer 31. It seems that the 1 MB limit is no longer necessary.

hello_there_
Jun 23, 2021

The max 1 MB limit only applies if you plan to use polybase

Marcus1612
Oct 6, 2021

It should be "Yes". Compress the source file is good practice in this use case,. Polybase is not mandatory in this question and the data to transfert is not so huge. As mentionned by Microsoft below, we can turn off "using polybase" which avoid the overhead of splitting the files. "Row size and data type limits PolyBase loads are limited to rows smaller than 1 MB. It cannot be used to load to VARCHR(MAX), NVARCHAR(MAX), or VARBINARY(MAX). For more information, see Azure Synapse Analytics service capacity limits. When your source data has rows greater than 1 MB, you might want to vertically split the source tables into several small ones. Make sure that the largest size of each row doesn't exceed the limit. The smaller tables can then be loaded by using PolyBase and merged together in Azure Synapse Analytics. Alternatively, for data with such wide columns, you can use non-PolyBase to load the data by turning off "allow PolyBase" setting." https://docs.microsoft.com/en-us/azure/data-factory/connector-azure-sql-data-warehouse?tabs=data-factory