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最新的 SnowPro Advanced DEA-C02 免費考試真題:

1. You have a Snowflake Stream named 'PRODUCT CHANGES' created on a table 'PRODUCTS'. A downstream task attempts to consume records from the stream, but occasionally fails with a 'Table PRODUCTS has been altered' error. The 'PRODUCTS' table undergoes DDL changes (e.g., adding/dropping columns) infrequently, but these changes are necessary for evolving business requirements. How can you design a more resilient data pipeline that minimizes disruptions caused by DDL changes to the 'PRODUCTS' table while still leveraging the 'PRODUCT CHANGES' stream?

A) Create a task that monitors the 'PRODUCTS' table for DDL changes using 'INFORMATION SCHEMA. TABLES'. When a change is detected, pause the downstream task, execute the DDL change, and then resume the downstream task after a short delay.
B) Implement error handling in the downstream task to automatically retry consuming records from the 'PRODUCT CHANGES' stream after a delay, assuming the DDL changes will be completed quickly.
C) Create a new Stream on the 'PRODUCTS' table after each DDL change. The downstream task should dynamically switch to consuming from the new stream when the old stream encounters an error.
D) Before executing any DDL changes on the 'PRODUCTS' table, drop and recreate the 'PRODUCT CHANGES' stream. This ensures the stream definition is always in sync with the table structure.
E) Use a materialized view instead of a standard view as the source for the stream. Materialized views are less susceptible to issues when the underlying base table changes

2. You are using Snowpipe to load data from an AWS S3 bucket into Snowflake. The data files are compressed using GZIP and are being delivered frequently. You have observed that the pipe's backlog is increasing and data latency is becoming unacceptable. Which of the following actions could you take to improve Snowpipe's performance? (Select all that apply)

A) Increase the virtual warehouse size associated with the pipe.
B) Reduce the number of columns in the target Snowflake table. Fewer columns reduce the overhead of data loading.
C) Optimize the file size of the data files in S3. Smaller files are processed faster by Snowpipe.
D) Ensure that the S3 event notifications are correctly configured and that there are no errors in the event delivery mechanism.
E) Check if the target table has any active clustering keys defined which could be causing slow down

3. A data engineer is tasked with creating a Snowpark Python UDF to perform sentiment analysis on customer reviews. The UDF, named 'analyze_sentiment' , takes a string as input and returns a string indicating the sentiment ('Positive', 'Negative', or 'Neutral'). The engineer wants to leverage a pre-trained machine learning model stored in a Snowflake stage called 'models'. Which of the following code snippets correctly registers and uses this UDF?

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

4. You're building a data product on the Snowflake Marketplace that includes a view that aggregates data from a table containing Personally Identifiable Information (PII). You need to ensure that consumers of your data product CANNOT directly access the underlying PII data but can only see the aggregated results from the view. What is the MOST secure and recommended approach to achieve this?

A) Grant the 'SELECT privilege directly on the underlying PII table to the share used for the Marketplace listing, along with the 'SELECT privilege on 'sensitive data view'.
B) Grant 'READ privilege on the internal stage containing the data files backing the PII table.
C) Grant USAGE privilege on the database containing the PII table and to the share.
D) Grant the 'SELECT privilege only on the to the share used for the Marketplace listing. Do not grant any privileges on the underlying PII table.
E) Create a stored procedure that returns the aggregated data, and grant EXECUTE privilege on the stored procedure to the share. The stored procedure SELECTs from the PII table.

5. You have a table 'ORDERS in your Snowflake database. You are implementing a new data transformation pipeline. Before deploying the pipeline to production, you want to validate the changes in a development environment. You decide to use Time Travel to create a snapshot of the 'ORDERS' table before the transformation and compare it with the transformed data'. Which sequence of SQL commands would best facilitate this validation, assuming your development database and schema structure mirrors production?

A)

B)

C)

D)

E)

問題與答案：