A table is loaded using Snowpipe and truncated afterwards Later, a Data Engineer finds that the table needs to be reloaded but the metadata of the pipe will not allow the same files to be loaded again.
How can this issue be solved using the LEAST amount of operational overhead?

1. A. Wait until the metadata expires and then reload the file using Snowpipe
2. B. Modify the file by adding a blank row to the bottom and re-stage the file
3. C. Set the FORCE=TRUE option in the Snowpipe COPY INTO command
4. D. Recreate the pipe by using the create or replace pipe command

Correct Answer: C
The FORCE=TRUE option in the Snowpipe COPY INTO command allows Snowpipe to load files that have already been loaded before, regardless of the metadata. This is the easiest way to reload the same files without modifying them or recreating the pipe.

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 processedand 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?

1. A. Create a stream on the staging table and schedule a task that transforms data from the stream only when the stream has data.
2. 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 andJOIN'S.
3. C. Schedule a task that dynamically retrieves the last time the task was run from information_schema-rask_hiSwOry and use that timestamp to process the delta of the new rows since the last time the task was run.
4. D. Use a create ok replace table as statement that references the staging table and includes all the transformation SQ
5. E. Use a task to run the full create or replace table as statement on a scheduled basis

Correct Answer: A
The most efficient way to process the incoming CDC on an ongoing basis is to create a stream on the staging table and schedule a task that transforms data from the stream only when the stream has data. A stream is a Snowflake object that records changes made to a table, such as inserts, updates, or deletes. A stream can be queried like a table and can provide information about what rows have changed since the last time the stream was consumed. A task is a Snowflake object that can execute SQL statements on a schedule without requiring a warehouse. A task can be configured to run only when certain conditions are met, such as when a stream has data or when another task has completed successfully. By creating a stream on the staging table and scheduling a task that transforms data from the stream, the Data Engineer can ensure that only new or modified rows are processed and that no unnecessary computations are performed.

Which callback function is required within a JavaScript User-Defined Function (UDF) for it to execute successfully?

1. A. initialize ()
2. B. processRow ()
3. C. handler
4. D. finalize ()

Correct Answer: B
The processRow () callback function is required within a JavaScript UDF for it to execute successfully. This function defines how each row of input data is processed and what output is returned. The other callback functions are optional and can be used for initialization, finalization, or error handling.

What is the purpose of the BUILD_FILE_URL function in Snowflake?

1. A. It generates an encrypted URL foe accessing a file in a stage.
2. B. It generates a staged URL for accessing a file in a stage.
3. C. It generates a permanent URL for accessing files in a stage.
4. D. It generates a temporary URL for accessing a file in a stage.

Correct Answer: B
The BUILD_FILE_URL function in Snowflake generates a temporary URL for accessing a file in a stage. The function takes two arguments: the stage name and the file path. The generated URL is valid for 24 hours and can be used to download or view the file contents. The other options are incorrect because they do not describe the purpose of the BUILD_FILE_URL function.

A Data Engineer needs to ingest invoice data in PDF format into Snowflake so that the data can be queried and used in a forecasting solution.
..... recommended way to ingest this data?

1. A. Use Snowpipe to ingest the files that land in an external stage into a Snowflake table
2. B. Use a COPY INTO command to ingest the PDF files in an external stage into a Snowflake table with a VARIANT column.
3. C. Create an external table on the PDF files that are stored in a stage and parse the data nto structured data
4. D. Create a Java User-Defined Function (UDF) that leverages Java-based PDF parser libraries to parse PDF data into structured data

Correct Answer: D
The recommended way to ingest invoice data in PDF format into Snowflake
is to create a Java User-Defined Function (UDF) that leverages Java-based PDF parser libraries to parse PDF data into structured data. This option allows for more flexibility and control over how the PDF data is extracted and transformed. The other options are not suitable for ingesting PDF data into Snowflake. Option A and B are incorrect because Snowpipe and COPY INTO commands can only ingest files that are in supported file formats, such as CSV, JSON, XML, etc. PDF files are not supported by Snowflake and will cause errors or unexpected results. Option C is incorrect because external tables can only query files that are in supported file formats as well. PDF files cannot be parsed by external tables and will cause errors or unexpected results.