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

1. You are tasked with sharing a subset of a customer table (CUSTOMER DATA') residing in your organization's Snowflake account with a partner organization. You need to mask personally identifiable information (PII) while providing near real-time updates. You decide to use a secure view. Which of the following SQL statements is the MOST efficient and secure way to accomplish this, assuming the partner only needs 'customer id', 'masked_email', 'city', and 'state'? The email should be masked using SHA256.

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

2. A Snowflake table 'CUSTOMER ORDERS is clustered by 'ORDER DATE. You have observed the clustering depth increasing over time, impacting query performance. To improve performance, you decide to recluster the table. However, you need to minimize the impact on concurrent DML operations and cost. Which of the following strategies would be MOST effective in managing this reclustering process?

A) Create a new table clustered by 'ORDER_DATE, copy data in parallel, and then swap tables.
B) Recluster the entire table in a single transaction during off-peak hours.
C) Leverage Snowflake's automatic reclustering feature, monitor its performance, and adjust warehouse size as needed.
D) Use 'CREATE OR REPLACE TABLE with SELECT FROM CUSTOMER ORDERS to rebuild the table with optimized clustering.
E) Implement a continuous reclustering process using Snowpipe to automatically recluster new data as it arrives.

3. A data engineer observes that a daily data transformation pipeline in Snowflake, which processes data from external stage 's3://my- bucket/raw_dataP , is consistently taking longer to complete. Upon investigation, the engineer finds that the COPY INTO statement is the bottleneck. The COPY INTO statement is as follows:

Which of the following could be the root cause of the performance degradation and how would you address them? Select two options.

A) The 'ON_ERROR = 'CONTINUE" option is causing the COPY INTO statement to perform additional error handling, slowing down the process. Remove the 'ON ERROR clause to improve performance.
B) The external stage contains a large number of small files. Snowflake's COPY INTO statement performs best with fewer, larger files. Consolidate the small files into larger files before loading.
C) The virtual warehouse used for the COPY INTO operation is undersized. Increase the virtual warehouse size to improve performance.
D) Snowflake automatically optimizes COPY INTO operations. No specific action is needed.
E) The PATTERN '. .csv' is inefficient. Refine the PATTERN to be more specific, targeting only the necessary files, potentially using date-based partitioning. If date partitioning is used, leverage partition pruning by including the appropriate date criteria in the COPY INTO statement.

4. You have a Snowflake Task that is designed to transform and load data into a target table. The task relies on a Stream to detect changes in a source table. However, you notice that the task is intermittently failing with a 'Stream STALE' error, even though the data in the source table is continuously updated. What are the most likely root causes and the best combination of solutions to prevent this issue? (Select TWO)

A) The Task is not running frequently enough, causing the Stream to accumulate too many changes before being consumed, exceeding its retention period. Increase the task's execution frequency or increase the stream's 'DATA RETENTION TIME IN DAYS
B) The Stream is not configured with 'SHOW INITIAL ROWS = TRUE, causing initial changes to be missed and eventually leading to staleness. Recreate the stream with this parameter set to TRUE.
C) The source table is being modified with DDL operations (e.g., ALTER TABLE ADD COLUMN), which are not supported by Streams. Use Table History to track schema changes and manually adjust the Stream's query if needed. Use 'COPY GRANTS' during the DDL.
D) The Stream has reached its maximum age (default 14 days) and expired. There is no way to recover data from an expired Stream. You need to recreate the Stream and reload the source table.
E) DML operations (e.g., UPDATE, DELETE) being performed on the source table are affecting rows older than the Stream's retention period. Reduce the stream's 'DATA RETENTION TIME IN DAYS' to match the oldest DML operation on the source table.

5. You have a Snowflake table called 'ORDERS' with a column named 'ORDER DETAILS that contains JSON data'. You need to create a UDF to extract a specific value from the JSON and return it. The JSON structure is consistent: '{'customer': {'name': 'John Doe', 'email': '[email protected]'}, 'items': [{'item id': 1, 'quantity': 2}, {'item id': 2, 'quantity': You want to extract the customer's email address. Which of the following UDF definitions is the most efficient and correct?

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

Solutions: