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Snowflake SnowPro Advanced: Data Engineer (DEA-C02) Sample Questions:

1. Consider a scenario where you have a Snowflake table named 'CUSTOMER DATA' containing customer IDs (INTEGER) and encrypted credit card numbers (VARCHAR). You need to create a secure JavaScript UDF to decrypt these credit card numbers using a custom encryption key stored securely within Snowflake's internal stage, and then mask all but the last four digits of the decrypted number for data protection. Which of the following actions are necessary to ensure both functionality and security while adhering to Snowflake's best practices for UDF development and security?

A) Use Snowflake's Secure Vault (Secret) feature to store the encryption key and retrieve it securely within the UDF.
B) Store the encryption key in a separate file on an internal stage accessible only by the UDF's service account and load the key from the file within the UDF at runtime.
C) Store the encryption key directly within the JavaScript UDF code as a string variable.
D) Encrypt the key using a weaker encryption algorithm before storing it in an internal stage to balance security and performance.
E) Pass the encryption key as an argument to the UDF each time it is called.

2. You are designing a Snowpipe pipeline to ingest data from an AWS SQS queue. The queue contains notifications about new files arriving in an S3 bucket. However, due to network issues, some notifications are delayed, causing Snowpipe to potentially miss files. Which of the following strategies, when combined, will BEST address the problem of delayed notifications and ensure data completeness?

A) Use 'VALIDATE()' function periodically to identify files that have not been loaded and trigger manual data loads for missing data.
B) Set 'MAX FILE_AGE to 'DEFAULT' and utilize the 'SYSTEM$PIPE FORCE RESUME' procedure in conjunction with a separate process that lists the S3 bucket and compares it to the files already loaded in Snowflake, loading any missing files.
C) Configure the SQS queue with a longer retention period and implement an event bridge rule with a retry policy to resend notifications.
D) Implement a Lambda function that triggers the 'SYSTEM$PIPE FORCE RESUME procedure after a certain delay.
E) Increase the 'MAX FILE AGE parameter in the Snowpipe definition and implement a periodic 'ALTER PIPE ... REFRESH' command.

3. You are tasked with ingesting data from an external stage into Snowflake. The data is in JSON format and compressed using GZIP. The JSON files contain nested arrays. You need to create a file format object that Snowflake can use to properly parse the dat a. Which of the following options represents the MOST efficient and correct file format definition to achieve this? Assume the stage is already created and accessible.

A) Option B
B) Option E
C) Option D
D) Option C
E) Option A

4. You are ingesting data from an AWS S3 bucket into a Snowflake table using a COPY INTO statement. The COPY INTO command fails with an error indicating 'Invalid stage location specified'. You have verified that the stage name is correct and the Snowflake user has the necessary privileges to access the stage. However, the error persists. Which of the following are potential causes and solutions for this issue?

A) The S3 bucket is encrypted using KMS and the Snowflake integration lacks the necessary key grant. Check the KMS key policy to ensure the storage integration IAM role has decrypt permission.
B) The IAM role associated with the Snowflake stage is incorrect or does not have sufficient permissions to access the S3 bucket. Verify the IAM role configuration and permissions.
C) The S3 bucket policy is not correctly configured to allow Snowflake to assume the IAM role. Review the bucket policy to ensure it grants access to the Snowflake IAM role.
D) The network policy configured in Snowflake is blocking access to the AWS S3 endpoint. Check the network policy rules and ensure they allow outbound traffic to the S3 region.
E) The external stage definition in Snowflake includes an incorrect storage integration. Examine and correct the STORAGE INTEGRATION parameter in the CREATE STAGE statement.

5. A data engineer is tasked with migrating data from a large on-premise Hadoop cluster to Snowflake using Spark. The Hadoop cluster contains nested JSON dat a. To optimize performance and minimize data transformation in Spark, what is the most efficient approach to read the JSON data into a Spark DataFrame and write it directly to a Snowflake table?

A) Read the JSON data as text files, then use Spark to parse and flatten the JSON structure before writing to Snowflake using the Snowflake JDBC connector.
B) Define a schema manually in Spark, then read the JSON data into a Spark DataFrame. Use the Snowflake Spark connector to write the data to Snowflake, specifying the schema explicitly.
C) Use the 'STORAGE_INTEGRATION' feature in Snowflake to directly access the JSON files in Hadoop (via an external stage) and load the data without using Spark at all.
D) Use the Snowflake Spark connector with the 'inferSchema' option set to 'true' when reading the JSON data. This allows Spark to automatically infer the schema and write directly to Snowflake.
E) Read the JSON data as strings and utilize Snowflake's 'PARSE JSON' function within a Spark SQL query to transform and load the data into a variant column in Snowflake.

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