You are developing a Snowpark Python application that reads data from a large Snowflake table, performs several transformations, and then writes the results back to a new table. You notice that the write operation is taking significantly longer than the read and transformation steps. The target table is not clustered. Which of the following actions, either individually or in combination, would likely improve the write performance most significantly ?

• A. Disable auto-tuning for the warehouse to ensure consistent performance
• B. Use the FILE SIZE', value)' method to reduce the size of the output files, potentially leading to more parallelism during the write operation.
• C. Increase the size of the Snowflake warehouse used for the Snowpark session.
• D. Cluster the target table on the primary key before writing to it. Then, ensure the data being written is pre-sorted according to the clustering key.
• E. Use the 'DataFrame.repartition(numPartitions)' method before writing to the table. Choose a 'numPartitionS value that is significantly higher than the number of virtual warehouses in your warehouse size.

You are implementing Snowpipe using the REST API for a custom data ingestion process. Your application uploads data files to an internal stage named '@MY STAGE and then calls the Snowpipe REST API to trigger the data load. However, you are encountering 'insufficient privileges' errors when calling the API, even though the role used to authenticate the API requests has the 'USAGE' privilege on the stage and the 'OPERATE' privilege on the pipe. The Pipe name is 'MY PIPE'. Which of the following is the MOST LIKELY cause of this error, and what can you do to resolve it?

• A. The role doesn't have the 'USAGE' privilege on the database and schema containing the stage and pipe. Grant 'USAGE' on the database and schema.
• B. The Snowpipe's 'EXECUTE TASK' privilege has not been granted to the role used for the REST API calls. Grant the 'EXECUTE TASK' privilege to the role.
• C. The role used to authenticate the API requests requires the 'INSERT privilege on the target table in addition to 'USAGE on the stage and 'OPERATE on the pipe. Grant the 'INSERT privilege to the role.
• D. The role used to authenticate the API requests does not have the 'OWNERSHIP' privilege on the Snowpipe.
• E. The role used to authenticate the API requests does not have the 'SELECT' privilege on the underlying table that the Snowpipe is loading data into.

You have a table named 'ORDERS' with a column 'ORDER DETAILS' that contains JSON data'. You want to extract a specific nested value ('customer id') from this JSON data using a SQL UDE The JSON structure varies, and sometimes the 'customer id' field might be missing. You need to create a UDF that handles missing fields gracefully and returns NULL if 'customer id' is not found. Also, You are looking for a performant solution that is highly scalable. Which of the following SQL UDF definitions is most appropriate?

• A.
  
• B.
  
• C.
  
• D.
  
• E.
  

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

You are tasked with building a data pipeline that ingests data from various sources into Snowflake, processes it, and then writes the final results back to a data lake in AWS S3, partitioned by date. The data in S3 should be queryable by other applications outside of Snowflake. You choose to use Snowflake Iceberg tables for this purpose. Which of the following is the correct SQL statement to create an Iceberg table 'analytics.public.daily_summary' in Snowflake, backed by an S3 bucket 's3://your-bucket/data/daily_summary/', partitioned by the column, and specifying 'parquet' as the file format?

• A. Option D
• B. Option E
• C. Option A
• D. Option B
• E. Option C