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

1. A data engineer is facing performance issues with a complex analytical query in Snowflake. The query joins several large tables and uses multiple window functions. The query profile indicates that a significant amount of time is spent in the 'Remote Spill' stage. This means the data from one of the query stages is spilling to the remote disk. What are the possible root causes for 'Remote Spill' and what steps can be taken to mitigate this issue? Select two options.

A) The virtual warehouse is not appropriately sized for the volume of data and complexity of the query. Increasing the virtual warehouse size might provide sufficient memory to avoid spilling.
B) The data being queried is stored in a non-Snowflake database, making it difficult to optimize the join.
C) The query is using a non-optimal join strategy. Review the query profile and consider using join hints to force a different join order or algorithm.
D) The 'Remote Spill' indicates network latency issues between compute nodes. There is nothing the data engineer can do to fix this; it is an infrastructure issue.
E) The window functions are operating on large partitions of data, exceeding the available memory on the compute nodes. Try to reduce the partition size by pre- aggregating the data or using filtering before applying the window functions.

2. You are responsible for monitoring the performance of a Snowflake data pipeline that loads data from S3 into a Snowflake table named 'SALES DATA. You notice that the COPY INTO command consistently takes longer than expected. You want to implement telemetry to proactively identify the root cause of the performance degradation. Which of the following methods, used together, provide the MOST comprehensive telemetry data for troubleshooting the COPY INTO performance?

A) Use Snowflake's partner connect integrations to monitor the virtual warehouse resource consumption and query the 'VALIDATE function to ensure data quality before loading.
B) Query the 'COPY HISTORY view in the 'INFORMATION SCHEMA' and monitor CPU utilization of the virtual warehouse using the Snowflake web I-Jl.
C) Query the ' LOAD_HISTORY function and monitor the network latency between S3 and Snowflake using an external monitoring tool.
D) Query the 'COPY HISTORY view in the 'INFORMATION SCHEMA' and enable Snowflake's query profiling for the COPY INTO statement.
E) Query the 'COPY_HISTORY view and the view in 'ACCOUNT_USAG Also, check the S3 bucket for throttling errors.

3. Consider a scenario where you have a Snowflake external table 'ext_logs' pointing to log files in an S3 bucket. The log files are continuously being updated, and new files are added frequently. You want to ensure that your external table always reflects the latest data available in S3. Which of the following actions and configurations are required or recommended to keep the external table synchronized with the underlying data source? (Select all that apply)

A) Enable auto-refresh on the external table using the 'AUTO_REFRESH = TRUE parameter during creation.
B) Configure an event notification service (e.g., AWS SQS) to trigger an external table refresh whenever new files are added to S3.
C) Implement a stored procedure that periodically executes a query on the external table to force a metadata refresh.
D) Periodically execute the 'ALTER EXTERNAL TABLE ext_logs REFRESH' command to update the metadata about the files in S3.
E) Create a Snowpipe that continuously loads data from the S3 bucket into a Snowflake table instead of using an external table.

4. A Data Engineer needs to implement dynamic data masking for a PII column named in a table 'CUSTOMERS. The masking policy should apply only to users with the role 'ANALYST. If the user is not an 'ANALYST, the full 'EMAIL' address should be displayed. Which of the following is the MOST efficient and secure way to achieve this using Snowflake's masking policies?

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

5. You are designing a data pipeline that involves unloading large amounts of data (hundreds of terabytes) from Snowflake to AWS S3 for archival purposes. To optimize cost and performance, which of the following strategies should you consider? (Select ALL that apply)

A) Partition the data during the unload operation based on a high-cardinality column to maximize parallelism in S3.
B) Use a large Snowflake warehouse size to parallelize the unload operation and reduce the overall unload time.
C) Choose a file format such as Parquet or ORC with compression enabled to reduce storage costs and improve query performance in S3.
D) Enable client-side encryption with KMS in S3 and specify the encryption key in the 'COPY INTO' command to enhance security.
E) Utilize the 'MAX FILE SIZE parameter in the 'COPY INTO' command to control the size of individual files unloaded to S3. Smaller files generally improve query performance in S3.

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