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Question 101 - ARA-C01 discussion

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An Architect has designed a data pipeline that Is receiving small CSV files from multiple sources. All of the files are landing in one location. Specific files are filtered for loading into Snowflake tables using the copy command. The loading performance is poor.

What changes can be made to Improve the data loading performance?

A.
Increase the size of the virtual warehouse.
Answers
A.
Increase the size of the virtual warehouse.
B.
Create a multi-cluster warehouse and merge smaller files to create bigger files.
Answers
B.
Create a multi-cluster warehouse and merge smaller files to create bigger files.
C.
Create a specific storage landing bucket to avoid file scanning.
Answers
C.
Create a specific storage landing bucket to avoid file scanning.
D.
Change the file format from CSV to JSON.
Answers
D.
Change the file format from CSV to JSON.
Suggested answer: B

Explanation:

According to the Snowflake documentation, the data loading performance can be improved by following some best practices and guidelines for preparing and staging the data files. One of the recommendations is to aim for data files that are roughly 100-250 MB (or larger) in size compressed, as this will optimize the number of parallel operations for a load. Smaller files should be aggregated and larger files should be split to achieve this size range. Another recommendation is to use a multi-cluster warehouse for loading, as this will allow for scaling up or out the compute resources depending on the load demand. A single-cluster warehouse may not be able to handle the load concurrency and throughput efficiently. Therefore, by creating a multi-cluster warehouse and merging smaller files to create bigger files, the data loading performance can be improved.Reference:

Data Loading Considerations

Preparing Your Data Files

Planning a Data Load

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asked 23/09/2024
Reza Mirabrishami
39 questions
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