Free SNOWPRO-ADVANCED-DATA-ENGINEER – Snowflake SNOWPRO-ADVANCED-DATA-ENGINEER Practice Test Question

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• ○ The results must be reused within 72 hours.
• ○ The query must be executed using the same virtual warehouse.
• ○ The USED_CACHED_RESULT parameter must be included in the query.
• ○ The table structure contributing to the query result cannot have changed.
• ○ The new query must have the same syntax as the previously executed query.
• ○ The micro-partitions cannot have changed due to changes to other data in the table.

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• ○ Increase the size of the virtual warehouse used by Snowpipe.
• ○ Split the files before loading them and set the SIZE_LIMIT option to 250 MB.
• ○ Change the file compression size and increase the frequency of the Snowpipe loads.
• ○ Decrease the buffer size to trigger delivery of files sized between 100 to 250 MB in Kinesis Firehose.

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• ○ Snapshot
• ○ Repeatable read
• ○ Read committed
• ○ Read uncommitted

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• ○ Grant OWNERSHIP to the user on the table.
• ○ Revoke grant decisions from the user on the table.
• ○ Revoke grant decisions from the user on the schema.
• ○ Add the WITH MANAGED ACCESS parameter on the schema.

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• ○ 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.
• ○ 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.
• ○ 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.
• ○ 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.

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• ○ initialize()
• ○ processRow()
• ○ handler()
• ○ finalize()

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• ○ Use the USERADMIN role to give all the required grants to the users.
• ○ Use the SECURITYADMIN role to configure the required parameters for the users at the account level.
• ○ Use the ACCOUNTADMIN role to create the new users that will be granted the new roles.
• ○ Assign the custom roles to the SYSADMIN role.

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• ○ Calculations are not stored in the results cache.
• ○ Large results are not stored in the results cache.
• ○ Date functions are not stored in the results cache.
• ○ Non-deterministic calculations are not stored in the results cache.

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• ○ Increase the warehouse size to speed up the cloning process and avoid DML conflicts.
• ○ Set the DATA_RETENTION_TIME_IN_DAYS = 1 for the table in the source environment before starting the cloning process, and revert it to = 0 after the clone is completed.
• ○ Avoid all DML transactions on the source table until the cloning operation is complete.
• ○ Disable Time Travel on the cloned table to reduce storage costs once the cloning is complete.
• ○ Use a CREATE TABLE AS SELECT STATEMENT to create a new table, instead of creating a clone.

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• ○ The columns cannot be used to insert data into another table.
• ○ The columns will be masked and will only be visible to a defined user role.
• ○ These columns cannot pass an argument to an external function or external stored procedure.
• ○ The data in these columns will not be included in query results.
• ○ Tags can now be placed on these columns.
• ○ The columns cannot be used in a WHERE clause.

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• ○ Incorporate additional pruning options when the table is being accessed by reporting queries.
• ○ Identify and purge duplicate data in the table.
• ○ Use the ORDER BY SALES_DT parameter when inserting the data into the table.
• ○ Perform a one-time insert overwrite with the ORDER BY SALES_DT parameter.