Explanation
The answer is AUTO LOADER,
Use Auto Loader instead of the COPY INTO SQL command when:
*You want to load data from a file location that contains files in the order of millions or higher. Auto Loader can discover files more efficiently than the COPY INTO SQL command and can split file processing into multiple batches.
*COPY INTO only directory listing but AUTO LOADER supports File notification method where the Auto Loader continues to ingest files as they arrive in cloud object storage lever-aging cloud provider(Queues and triggers) and Spark's structured streaming.
*Your data schema evolves frequently. Auto Loader provides better support for schema in-ference and evolution. See Configuring schema inference and evolution in Auto Loader.

Explanation
The answer is, A global temporary view is available only on the cluster it was created.
Two types of temporary views can be created Session scoped and Global
*A session scoped temporary view is only available with a spark session, so another notebook in the same cluster can not access it. if a notebook is detached and re attached the temporary view is lost.
*A global temporary view is available to all the notebooks in the cluster, if a cluster restarts global temporary view is lost.

Explanation
The answer is GRANT MODIFY ON TABLE table_name TO [email protected] , please note INSERT, UPDATE, and DELETE are combined into one role called MODIFY.
Below are the list of privileges that can be granted to a user or a group, SELECT: gives read access to an object.
CREATE: gives the ability to create an object (for example, a table in a schema).
MODIFY: gives the ability to add, delete, and modify data to or from an object.
USAGE: does not give any abilities, but is an additional requirement to perform any action on a schema object.
READ_METADATA: gives the ability to view an object and its metadata.
CREATE_NAMED_FUNCTION: gives the ability to create a named UDF in an existing catalog or schema.
MODIFY_CLASSPATH: gives the ability to add files to the Spark classpath.
ALL PRIVILEGES: gives all privileges (is translated into all the above privileges

Explanation
The answer is They can schedule the query to refresh every 12 hours from the SQL endpoint's page in Databricks SQL, The query pane view in Databricks SQL workspace provides the ability to add or edit and schedule individual queries to run.
You can use scheduled query executions to keep your dashboards updated or to enable routine alerts. By default, your queries do not have a schedule.
Note
If your query is used by an alert, the alert runs on its own refresh schedule and does not use the query schedule.
To set the schedule:
* Click the query info tab.
* Graphical user interface, text, application, email Description automatically generated
* Click the link to the right of Refresh Schedule to open a picker with schedule intervals.
* Graphical user interface, application Description automatically generated
* 3.Set the schedule.
* The picker scrolls and allows you to choose:
* *An interval: 1-30 minutes, 1-12 hours, 1 or 30 days, 1 or 2 weeks
* *A time. The time selector displays in the picker only when the interval is greater than 1 day and the day selection is greater than 1 week. When you schedule a specific time, Databricks SQL takes input in your computer's timezone and converts it to UTC. If you want a query to run at a certain time in UTC, you must adjust the picker by your local offset. For example, if you want a query to execute at 00:00 UTC each day, but your current timezone is PDT (UTC-7), you should select 17:00 in the picker:
* Graphical user interface Description automatically generated

Explanation
The answer is
1.spark\
2..readStream\
3..format("cloudFiles") \# use Auto loader
4..option("cloudFiles.format","csv") \ # csv format files
5..option("cloudFiles.schemaLocation", checkpoint_directory)\
6..load('landing')\
7..writeStream.option("checkpointLocation", checkpoint_directory)\
8..table(raw)
Note: if you chose the below option which is incorrect because it does not have readStream
1.spark.read.format("cloudFiles")
2..option("cloudFiles.format","csv")
3....
4...
5...
Exam focus: Please review the below image and understand the role of each layer(bronze, silver, gold) in medallion architecture, you will see varying questions targeting each layer and its purpose.
Sorry I had to add the watermark some people in Udemy are copying my content.
A diagram of a house Description automatically generated with low confidence