Snowflake DEA-C01 Exam Dumps - Valid Questions Answers

This option is the best way to ensure that Snowpipe is performant while minimizing costs. By splitting the files before loading them, the Data Engineer can reduce the size of each file and increase the parallelism of loading. By setting the SIZE_LIMIT option to 250 MB, the Data Engineer can specify the maximum file size that can be loaded bySnowpipe, which can prevent performance degradation or errors due to large files. The other options are not optimal because:

• Increasing the size of the virtual warehouse used by Snowpipe will increase the performance but also increase the costs, as larger warehouses consume more credits per hour.
• Changing the file compression size and increasing the frequency of the Snowpipe loads will not have much impact on performance or costs, as Snowpipe already supports various compression formats and automatically loads files as soon as they are detected in the stage.
• Decreasing the buffer size to trigger delivery of files sized between 100 to 250 MB in Kinesis Firehose will not affect Snowpipe performance or costs, as Snowpipe does not depend on Kinesis Firehose buffer size but rather on its own SIZE_LIMIT option.

This option is the best way to improve the situation, as using a loop construct to run SQL queries for each customer is very inefficient and slow. Instead, the report should be rewritten to use a single SQL query that joins the customer and sales data tables and applies the query parameters as filters. This way, the report can leverage Snowflake’s parallel processing and optimization capabilities and reduce the network overhead and latency.

The characteristics of Snowpark Python packages are:

• Third-party packages can be registered as a dependency to the Snowpark session using the session.import() method.
• The SQL command DESCRIBE FUNCTION will list the imported Python packages of the Python User-Defined Function (UDF).
• Querying information_schema.packages will provide a list of supported Python packages and versions.

These characteristics indicate how Snowpark Python packages can be imported, inspected, and verified in Snowflake. The other options are not characteristics of Snowpark Python packages. Option B is incorrect because Python packages can be loaded in both local and remote environments using Snowpark. Option C is incorrect because third-party supported Python packages are not locked down to prevent hitting external endpoints, but rather restricted by network policies and security settings.