Snowflake Certified SnowPro Specialty - Snowpark

문제1
Consider the following Snowpark Python code snippet intended to operationalize a stored procedure:

This code results in an error during registration. Which of the following actions would be MOST appropriate to fix the registration issue and ensure the stored procedure can be successfully operationalized?

A. Remove the 'input_data' parameter from the 'main' function definition and access the input data directly using within the function.

B. Add 'session.close()' at the end of the main function.

C. Move the 'session.sproc.register' call outside of the 'main' function and execute it separately after the 'main' function definition.

D. Define 'session' as a global variable before calling 'session.sproc.register' .

E. Add in sproc.register.

정답: C

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문제2
You have a Snowpark DataFrame containing customer transaction data'. Your goal is to save this DataFrame as a set of Parquet files in an existing Snowflake stage named , partitioned by the 'transaction_date' column. You want to ensure that the files are automatically compressed using the Zstandard codec and that existing files with the same name are overwritten. Which of the following Snowpark code snippet achieves this with the most optimal approach and respects best practices?

A. Option E

B. Option B

C. Option A

D. Option D

E. Option C

정답: C

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문제3
Consider the following Snowpark Python code snippet designed to create a DataFrame and then register a custom function (UDF):

This code runs successfully. However, you need to deploy this as a stored procedure. What minimal changes are required to make this code runnable as a Snowpark Python stored procedure and callable from SQL?

A. The 'return df.collect()' line must be replaced with 'return df and create a DataFrame. The rest of the code remains unchanged.

B. The 'return df.collect()' line must be replaced with 'return and the Snowflake session object must be explicitly passed to the UDF when it is called.

C. The 'return df.collect()' line must be replaced with 'return and 'return_type' and 'input_typeS arguments of udf must be removed. The rest of the code remains unchanged.

D. The 'return df.collect()' line must be replaced with 'return and the 'return_type' and 'input_typeS arguments of udf must be removed to allow inference. The rest of the code remains unchanged.

E. No changes are required; the code will function as a stored procedure as is.

정답: D

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문제4
You have a Snowpark DataFrame containing customer data'. You need to create a stored procedure that accepts the DataFrame and a list of column names as input and returns a new DataFrame containing only the specified columns. Which of the following approaches correctly implement this functionality and handles data types effectively (Select all that apply)?

A.

B.

C.

D.

E.

정답: C,E

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문제5
You are developing a Snowpark application that processes high-volume event data stored in a Snowflake table named 'raw events'. The application aggregates data by session ID. You observe significant performance degradation during peak hours. Analyzing Snowflake query history reveals that the 'session_id' column has high cardinality and data skew. Which of the following strategies, or combination of strategies, would be MOST effective in optimizing the aggregation performance?

A. Pre-aggregate the raw event data into smaller batches using a scheduled task before the main Snowpark application runs, and then aggregate the pre- aggregated data in the Snowpark application.

B. Use a 'GROUP clause in the Snowpark DataFrame to perform the aggregation.

C. Use a 'GROUP BY' clause in the Snowpark DataFrame combined with a 'hint' to specify the ' for optimized parallel processing.

D. Implement a custom UDF (User-Defined Function) in Python to perform the aggregation and then apply the 'GROUP clause in the Snowpark DataFrame.

E. Increase the warehouse size to a larger tier (e.g., from X-Small to Small).

정답: A,C

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문제6
A Snowpark application needs to authenticate to Snowflake using OAuth. The application is running on an Azure Function and uses a client ID, client secret, and refresh token obtained previously. Which of the following connection parameter dictionaries is correctly configured for OAuth authentication?

A.

B.

C.

D.

E.

정답: E

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문제7
You have a Snowpark DataFrame with columns 'sale_date', 'product_id', and 'revenue'. You need to calculate the cumulative revenue for each product over time. Which of the following approaches will accomplish this in Snowpark using window functions?

A.

B.

C.

D.

E.

정답: A,C

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문제8
You have a Snowpark Python application that reads data from a Snowflake table, performs several transformations, and then writes the results back to a new Snowflake table. The transformations involve complex calculations and aggregations. During testing, you observe that the application is consuming a significant amount of credits. Which of the following optimization strategies would be MOST effective in reducing the credit consumption of your Snowpark application?

A. Optimize the SQL queries generated by Snowpark by explicitly specifying join hints and using appropriate indexes.

B. Convert all Python User-Defined Functions (UDFs) to Java User-Defined Table Functions (UDTFs) for improved performance.

C. Use the 'cache()' method on intermediate Snowpark DataFrames to avoid recomputation of transformations.

D. Minimize the amount of data transferred between Snowpark and Snowflake by pushing down transformations and using stored procedures where appropriate.

E. Disable auto-scaling on the Snowpark-optimized warehouse to prevent it from scaling up unnecessarily.

정답: B,D

설명: (KoreaDumps 회원만 볼 수 있음)

문제9
You are tasked with creating a Snowpark Python stored procedure that reads data from a Snowflake table, performs a complex data transformation using a 3rd party Python library (e.g., pandas, scikit-learn), and writes the transformed data to another Snowflake table.
The data transformation requires significant memory. You need to register this stored procedure in Snowflake. Which of the following approaches is the MOST appropriate for registering the stored procedure and managing the dependencies?

A. Use the function to add the required Python libraries before registering the stored procedure with the '@sproc' decorator.

B. Use the '@sproc' decorator without specifying any dependencies, assuming that the necessary libraries are pre-installed on the Snowflake worker nodes.

C. Install the required Python libraries directly on the Snowflake compute warehouse using a SQL command.

D. Create a conda environment file ('environment.yml') specifying the dependencies, upload it to a stage, and then use the '@sproc' decorator with the 'packages' argument referencing the conda environment.

E. Create a Snowflake stage, upload the Python libraries as .zip files to the stage, and specify the stage path in the '@sproc' decorator's 'imports' parameter.

정답: D

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문제10
You are developing a Snowpark Python application that processes streaming data using a dynamic table. The application is experiencing frequent 'net.snowflake.client.jdbc.SnowflakeSQLException: SQL compilation error: Unsupported feature 'Streaming Dynamic Table'. ' errors, even though dynamic tables are enabled in your Snowflake account and the user has the necessary privileges. Which of the following are potential causes and solutions for this error? (Select TWO)

A. The warehouse being used for the Snowpark session is not configured with the feature enabled. Verify that the warehouse configuration includes = TRUE'.

B. The user role lacks the 'EXECUTE MANAGED TASK privilege. Grant this privilege to the user role executing the Snowpark application.

C. The dynamic table definition contains unsupported SQL syntax, such as 'QUALIFY with complex window functions. Rewrite the dynamic table definition to use standard SQL constructs.

D. The Snowpark Python client version is outdated and does not support streaming dynamic tables. Upgrade to the latest version of the 'snowflake-snowpark- python' package.

E. The dynamic table materialization schedule is too frequent, overwhelming the Snowflake warehouse. Increase the 'WAREHOUSE_SIZE' parameter of the dynamic table definition.

정답: A,D

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