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Question 65

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 rows of 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 modify the files to ensure that each row is less than 1 MB.

Does this meet the goal?

    Correct Answer: B

    While modifying files to ensure that each row is less than 1 MB adheres to the constraints of Polybase, it does not necessarily ensure that the data copies quickly. The overall efficiency of data transfer also depends on various factors such as potential data splitting, the need for compression, network bandwidth, and the configuration of parallel data transfer mechanisms. Simply reducing row sizes without considering these aspects might not be sufficient to achieve the goal of quick data transfer.

Discussion
Tj87Option: B

I think we had this question in the previous pages and the correct answer was set as " compress the files"

dom271219

Exactly compress because a lot of row have more than 1MB length

kim32

The question before was more than that 1 MB but here is less than 1 MB. since, it is less, then answer is Yes.

semauni

More than 1 solution might be right. The question here is: if row size is reduced to 1MB, will loading go faster? The answer then is yes: whether compression is better or not, is not relevant.

PhundOption: A

"ensure that each row is less than 1 MB" and the condition for polybase is <1M, whatever method you used

ExamDestroyer69Option: A

**Variations** Solution: You convert the files to compressed delimited text files. Does this meet the goal? **YES** Solution: You copy the files to a table that has a columnstore index. Does this meet the goal? **NO** Solution: You modify the files to ensure that each row is more than 1 MB. Does this meet the goal? **NO** Solution: You modify the files to ensure that each row is less than 1 MB. Does this meet the goal? **YES**

rocky48Option: A

"You modify the files to ensure that each row is more than 1 MB" and the answer was "No". This particular question asks if "You modify the files to ensure that each row is less than 1 MB", and the answer given is "Yes".

dgerokOption: B

If you modify the files to ensure that each row is less than 1 MB, you might end up truncating or losing data from those rows. To achieve faster data copying, consider alternative approaches such as: Compression: Compress the files before transferring them to Azure Synapse Analytics. This can reduce the overall size of the data and improve transfer speed. Parallelization: Split the data into smaller chunks and copy them in parallel to take advantage of multiple resources. Optimized Data Types: Ensure that numerical values are stored using appropriate data types (e.g., integers, floats) to minimize storage space. Batch Processing: Process the data in batches rather than row by row to optimize data transfer. The question should be read carefully and attentively. You need to prepare the files to ensure that the data copies QUICKLY. Nobody asks if this improve... I agree with rocky48. You need do more to copy the data QUICKLY. So, the answer is B (NO)

stornati

I am with this answer. It should never be a good practise modifying the data at loading time.

Charley92Option: B

No, this solution does not meet the goal. The files contain rows of text and numerical values, and 75% of the rows contain description data that has an average length of 1.1 MB. If you modify the files to ensure that each row is less than 1 MB, you may end up splitting the description data into multiple rows, which could affect the integrity of the data

rocky48Option: B

No, this solution does not meet the goal. While modifying the files to ensure that each row is less than 1 MB might help with individual row sizes, it won’t necessarily improve the overall data transfer speed. The total size of the files in the storage account is still 100 GB, and copying large volumes of data can be time-consuming regardless of individual row sizes. To optimize data transfer speed, consider other strategies such as parallelizing the data transfer, optimizing network bandwidth, or using appropriate data loading techniques in Azure Synapse Analytics.

rocky48Option: B

No, this solution does not meet the goal. While modifying the files to ensure that each row is less than 1 MB might help with individual row sizes, it won’t necessarily improve the overall data transfer speed. The total size of the files in the storage account is still 100 GB, and copying large volumes of data can be time-consuming regardless of individual row sizes. To optimize data transfer speed, consider other strategies such as parallelizing the data transfer, optimizing network bandwidth, or using appropriate data loading techniques in Azure Synapse Analytics.

auwiaOption: A

Yes, with less of 1Mb file we increase performance.

e5019c6Option: B

i thought that polybase just query the tables and dont do any process of ETL or ELT.

esaadeOption: B

No, modifying the files to ensure that each row is less than 1 MB does not necessarily meet the goal of ensuring that the data copies quickly. While it is true that large row sizes can impact data copy performance, simply reducing the row size to less than 1 MB may not be enough to optimize the data copy process. The performance of the data copy process can also be affected by factors such as network bandwidth, database design, and the method used to copy the data. To ensure that the data copies quickly, you could consider other techniques such as compressing the data, using parallel data copy processes, and optimizing the database schema for efficient data loading. Therefore, the correct answer is B. No.

akk_1289Option: B

B. No Modifying the files to ensure that each row is less than 1 MB may not be enough to ensure that the data copies quickly to Azure Synapse Analytics. Other factors such as network bandwidth, data compression, and parallel processing of data can also impact the speed of data transfer. To optimize data transfer, it may be necessary to implement data compression techniques, increase network bandwidth, or parallelize the data transfer process.

ItsABOption: A

Given the large size of the table, I will utilize PolyBase for data transfer. Additionally, considering PolyBase's constraint that it cannot load rows exceeding 1MB in size, I will compress rows to ensure compliance with this requirement, thereby making PolyBase the optimal choice for data transfer. => Option A: yes

stickslingerOption: B

Shouldn't this be "B: No". Where does the question ask about Polybase? Modifying the rows of data could affect the integrity of the data

hcq31818Option: A

PolyBase enables Azure Synapse Analytics to import and export data from Azure Data Lake Store, and from Azure Blob Storage. And it supports row sizes up to 1MB. https://learn.microsoft.com/en-us/sql/relational-databases/polybase/polybase-guide?view=sql-server-ver16#:~:text=Azure%20integration,and%20from%20Azure%20Blob%20Storage. https://learn.microsoft.com/en-us/sql/relational-databases/polybase/polybase-versioned-feature-summary?view=sql-server-ver16

kkk5566Option: A

A is correct

rocky48Option: A

"You modify the files to ensure that each row is more than 1 MB" and the answer was "No". This particular question asks if "You modify the files to ensure that each row is less than 1 MB", and the answer given is "Yes".