Create Next App

snowflake SNOWPRO_ADVANCED_DATA_ENGINEER

Exam contains 65 questions

Page 9 of 11

Question 49 🔥

A CSV file, around 1 TB in size, is generated daily on an on-premise server. A corresponding table, internal stage, and file format have already been created in Snowflake to facilitate the data loading process.How can the process of bringing the CSV file into Snowflake be automated using the LEAST amount of operational overhead?

Which database solution meets these requirements?

A. Create a task in Snowflake that executes once a day and runs a COPY INTO statement that references the internal stage. The internal stage will read the files directly from the on-premise server and copy the newest file into the table from the on-premise server to the Snowflake table.

Highly voted

B. On the on-premise server, schedule a SQL file to run using SnowSQL that executes a PUT to push a specific file to the internal stage. Create a task that executes once a day in Snowflake and runs a COPY INTO statement that references the internal stage. Schedule the task to start after the file lands in the internal stage.

Highly voted

C. On the on-premise server, schedule a SQL file to run using SnowSQL that executes a PUT to push a specific file to the internal stage. Create a pipe that runs a COPY INTO statement that references the internal stage. Snowpipe auto-ingest will automatically load the file from the internal stage when the new file lands in the internal stage.

Highly voted

D. On the on-premise server, schedule a Python file that uses the Snowpark Python library. The Python script will read the CSV data into a DataFrame and generate an INSERT INTO statement that will directly load into the table. The script will bypass the need to move a file into an internal stage.

Highly voted

Discussion of the question

Question 50 🔥

What are characteristics of Snowpark Python packages? (Choose three.)

Which database solution meets these requirements?

A. Third-party packages can be registered as a dependency to the Snowpark session using the session.import() method.

Highly voted

B. Python packages can access any external endpoints.

Highly voted

C. Python packages can only be loaded in a local environment.

Highly voted

D. Third-party supported Python packages are locked down to prevent hitting.

Highly voted

E. The SQL command DESCRIBE FUNCTION will list the imported Python packages of the Python User-Defined Function (UDF).

Highly voted

F. Querying information_schema.packages will provide a list of supported Python packages and versions.

Highly voted

Discussion of the question

Question 51 🔥

While running an external function, the following error message is received:Error: Function received the wrong number of rowsWhat is causing this to occur?

Which database solution meets these requirements?

A. External functions do not support multiple rows.

Highly voted

B. Nested arrays are not supported in the JSON response.

Highly voted

C. The JSON returned by the remote service is not constructed correctly.

Highly voted

D. The return message did not produce the same number of rows that it received.

Highly voted

Discussion of the question

Question 52 🔥

A Data Engineer enables a result cache at the session level with the following command:ALTER SESSION SET USE_CACHED_RESULT = TRUE;The Engineer then runs the following SELECT query twice without delay:SELECT *FROM SNOWFLAKE_SAMPLE_DATA.TPCH_SF1.CUSTOMERSAMPLE(10) SEED (99);The underlying table does not change between executions.What are the results of both runs?

Which database solution meets these requirements?

A. The first and second run returned the same results, because SAMPLE is deterministic.

Highly voted

B. The first and second run returned the same results, because the specific SEED value was provided.

Highly voted

C. The first and second run returned different results, because the query is evaluated each time it is run.

Highly voted

D. The first and second run returned different results, because the query uses * instead of an explicit column list.

Highly voted

Discussion of the question

Question 53 🔥

A company built a sales reporting system with Python, connecting to Snowflake using the Python Connector. Based on the user's selections, the system generates the SQL queries needed to fetch the data for the report. First it gets the customers that meet the given query parameters (on average 1000 customer records for each report run), and then it loops the customer records sequentially. Inside that loop it runs the generated SQL clause for the current customer to get the detailed data for that customer number from the sales data table.When the Data Engineer tested the individual SQL clauses, they were fast enough (1 second to get the customers, 0.5 second to get the sales data for one customer), but the total runtime of the report is too long.How can this situation be improved?

Which database solution meets these requirements?

A. Increase the size of the virtual warehouse.

Highly voted

B. Increase the number of maximum clusters of the virtual warehouse.

Highly voted

C. Define a clustering key for the sales data table.

Highly voted

D. Rewrite the report to eliminate the use of the loop construct.

Highly voted

Discussion of the question

Question 54 🔥

A company is using Snowpipe to bring in millions of rows every day of Change Data Capture (CDC) into a Snowflake staging table on a real-time basis. The CDC needs to get processed and combined with other data in Snowflake and land in a final table as part of the full data pipeline.How can a Data Engineer MOST efficiently process the incoming CDC on an ongoing basis?

Which database solution meets these requirements?

A. Create a stream on the staging table and schedule a task that transforms data from the stream, only when the stream has data.

Highly voted

B. Transform the data during the data load with Snowpipe by modifying the related COPY INTO statement to include transformation steps such as CASE statements and JOINS.

Highly voted

C. Schedule a task that dynamically retrieves the last time the task was run from information_schema.task_history and use that timestamp to process the delta of the new rows since the last time the task was run.

Highly voted

D. Use a CREATE OR REPLACE TABLE AS statement that references the staging table and includes all the transformation SQL. Use a task to run the full CREATE OR REPLACE TABLE AS statement on a scheduled basis.

Highly voted

Discussion of the question

Ready to Pass Your Certification Test

snowflake SNOWPRO_ADVANCED_DATA_ENGINEER

Exam contains 65 questions

Lorem ipsum dolor sit amet consectetur. Eget sed turpis aenean sit aenean. Integer at nam ullamcorper a.

Company

Product

Resources

Follow us