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Snowflake DEA-C02 Exam Syllabus Topics:

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

1. You have a data pipeline that loads data from an internal stage into a Snowflake table Craw_data'). The pipeline is experiencing intermittent failures with the error 'SQL compilation error: Stage 'MY INTERNAL STAGE' is immutable'. What are the potential causes of this error and how would you troubleshoot it?

A) The user executing the COPY INTO command lacks the necessary privileges (USAGE on the stage). Grant the appropriate privileges to the user or role.
B) The internal stage is being used by multiple COPY INTO commands simultaneously, causing a resource contention issue. Implement queuing or throttling mechanisms to manage concurrent data loading.
C) Another concurrent process is attempting to drop or alter the internal stage while the COPY INTO command is running. Implement proper locking mechanisms to prevent concurrent modifications.
D) The internal stage has been accidentally dropped and recreated with the same name during the COPY operation. Verify the stage's existence and creation timestamp.
E) This error is caused by insufficient warehouse size. Increase the warehouse size to accommodate the COPY INTO operation.

2. Your company has a Snowflake account in the AWS cloud (us-west-2). You are planning to implement a disaster recovery strategy by replicating data to a separate Snowflake account in the Azure cloud (eastus2). You need to replicate multiple databases and shared objects. Which of the following steps are REQUIRED to configure and manage the replication process successfully? (Choose all that apply)

A) Configure network policies in both AWS and Azure accounts to allow communication between the Snowflake instances, particularly ingress and egress rules.
B) Grant the REPLICATE privilege on the source AWS account to the account locator of the target Azure account.
C) Create a replication group in the source AWS account and add the databases and shared objects to it.
D) Create a storage integration in the target Azure account and grant the 'USAGE privilege on it to the replication group.
E) Create a secondary database in the target Azure account using the 'CREATE DATABASE AS REPLICA OF command.

3. You are responsible for optimizing query performance on a Snowflake table called 'WEB EVENTS, which contains clickstream data'. The table has the following structure: CREATE TABLE WEB EVENTS ( event_id VARCHAR(36), user_id INT, event_time TIMESTAMP NTZ, event_type VARCHAR(50), page_url VARCHAR(255), device_type VARCHAR(50) Users frequently run queries that filter the 'WEB EVENTS table based on a combination of 'event_type', and a date range derived from 'event_time' You observe that these queries are consistently slow Which of the following strategies would be MOST effective in improving the performance of these frequently executed queries?

A) Create a clustering key on 'event_time' .
B) Create a clustering key with the following order: 'event_type' , 'device_type' , 'event_time' .
C) Create a materialized view that pre-aggregates data by 'event_type' , 'device_type' , and day (derived from 'event_time').
D) Create a search optimization service on the 'page_url' column.
E) Add a column to the 'WEB EVENTS' table for the date part of 'event_time' and create a clustering key using the new date column along with and device_type' .

4. You have implemented a row access policy on a 'products' table to restrict access based on the user's group. The policy uses a mapping table 'user_groups' to determine which products a user is allowed to see. After implementing the policy, users are reporting significant performance degradation when querying the 'products' table. What are the MOST likely causes of this performance issue, and what steps can you take to mitigate them? Select all that apply.

A) The row access policy is overly complex and contains computationally expensive functions. Simplify the policy logic and avoid using UDFs or complex subqueries within the policy definition.
B) The row access policy is causing full table scans on the 'products' table. Review the query patterns and consider adding clustering keys to the 'products' table to improve data access patterns.
C) The users do not have sufficient privileges to access the 'user_groups' table. Grant the necessary SELECT privileges to the users on the 'user_groupS table.
D) The 'user_groups' table is not properly indexed, causing slow lookups during policy evaluation. Create an index on the 'username' and 'group' columns of the 'user_groups' table.
E) The row access policy is interfering with Snowflake's data pruning capabilities. Ensure that the policy expression can be evaluated efficiently by Snowflake's query optimizer by using the 'USING' clause of the ROW ACCESS POLICY.

5. You are working with a very large Snowflake table named 'CUSTOMER TRANSACTIONS which is clustered on 'CUSTOMER ID and 'TRANSACTION DATE. After noticing performance degradation on queries that filter by 'TRANSACTION AMOUNT and 'REGION' , you decide to explore alternative clustering strategies. Which of the following actions, when performed individually, will LEAST likely improve query performance specifically for queries filtering by 'TRANSACTION AMOUNT and 'REGION', assuming you can only have one clustering key?

A) Adding ' TRANSACTION_AMOUNT and 'REGIO!V to the existing clustering key while retaining 'CUSTOMER_ID and 'TRANSACTION_DATE
B) Dropping the existing clustering key and clustering on 'TRANSACTION_AMOUNT' and 'REGION'.
C) Creating a search optimization on 'TRANSACTION_AMOUNT' and 'REGION' columns.
D) Creating a materialized view that pre-aggregates data by 'TRANSACTION_AMOUNT and 'REGION'.
E) Creating a new table clustered on 'TRANSACTION_AMOUNT and 'REGION', and migrating the data.

Solutions: