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Databricks Certified Professional Data Engineer Exam Sample Questions (Q50-Q55):

NEW QUESTION # 50
The data engineering team is using a bunch of SQL queries to review data quality and monitor the ETL job every day, which of the following approaches can be used to set up a schedule and auto-mate this process?

• A. They can schedule the query to run every 1 day from the Jobs UI
• B. They can schedule the query to refresh every 12 hours from the SQL endpoint's page in Databricks SQL
• C. They can schedule the query to run every 12 hours from the Jobs UI.
• D. They can schedule the query to refresh every 1 day from the SQL endpoint's page in Databricks SQL.
• E. They can schedule the query to refresh every 1 day from the query's page in Databricks SQL.

Answer: E Explanation:
Explanation
Explanation
Individual queries can be refreshed on a schedule basis,
To set the schedule:
1. 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

* 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

* Click OK.
Your query will run automatically.
If you experience a scheduled query not executing according to its schedule, you should manually trigger the query to make sure it doesn't fail. However, you should be aware of the following:
* If you schedule an interval-for example, "every 15 minutes"-the interval is calculated from the last successful execution. If you manually execute a query, the scheduled query will not be executed until the interval has passed.
* If you schedule a time, Databricks SQL waits for the results to be "outdated". For example, if you have a query set to refresh every Thursday and you manually execute it on Wednesday, by Thursday the results will still be considered "valid", so the query wouldn't be scheduled for a new execution. Thus, for example, when setting a weekly schedule, check the last query execution time and expect the scheduled query to be executed on the selected day after that execution is a week old. Make sure not to manually execute the query during this time.
If a query execution fails, Databricks SQL retries with a back-off algorithm. The more failures the further away the next retry will be (and it might be beyond the refresh interval).
Refer documentation for additional info,
https://docs.microsoft.com/en-us/azure/databricks/sql/user/queries/schedule-query
NEW QUESTION # 51
What steps need to be taken to set up a DELTA LIVE PIPELINE as a job using the workspace UI?

• A. Select Workflows UI and Delta live tables tab, under task type select Delta live tables pipeline and select the notebook
• B. Select Workflows UI and Delta live tables tab, under task type select Delta live tables pipeline and select the pipeline JSON file
• C. DELTA LIVE TABLES do not support job cluster
• D. Use Pipeline creation UI, select a new pipeline and job cluster

Answer: A Explanation:
Explanation
The answer is,
Select Workflows UI and Delta live tables tab, under task type select Delta live tables pipeline and select the notebook.
Create a pipeline
To create a new pipeline using the Delta Live Tables notebook:
1.Click Workflows in the sidebar, click the Delta Live Tables tab, and click Create Pipeline.
2.Give the pipeline a name and click to select a notebook.
3.Optionally enter a storage location for output data from the pipeline. The system uses a de-fault location if you leave Storage Location empty.
4.Select Triggered for Pipeline Mode.
5.Click Create.
The system displays the Pipeline Details page after you click Create. You can also access your pipeline by clicking the pipeline name in the Delta Live Tables tab.
NEW QUESTION # 52
How do you check the location of an existing schema in Delta Lake?

• A. Check unity catalog UI
• B. Use Data explorer
• C. Run SQL command DESCRIBE SCHEMA EXTENDED schema_name
  E Schemas are internally in-store external hive meta stores like MySQL or SQL Server
• D. Run SQL command SHOW LOCATION schema_name

Answer: C Explanation:
Explanation
Here is an example of how it looks
Graphical user interface, text, application, email Description automatically generated

NEW QUESTION # 53
Which of the following scenarios is the best fit for the AUTO LOADER solution?

• A. Efficiently copy data from data lake location to another data lake location
• B. Incrementally process new streaming data from Apache Kafa into delta lake
• C. Efficiently process new data incrementally from cloud object storage
• D. Efficiently move data incrementally from one delta table to another delta table
• E. Incrementally process new data from relational databases like MySQL

Answer: C Explanation:
Explanation
The answer is, Efficiently process new data incrementally from cloud object storage.
Please note: AUTO LOADER only works on data/files located in cloud object storage like S3 or Azure Blob Storage it does not have the ability to read other data sources, although AU-TO LOADER is built on top of structured streaming it only supports files in the cloud object stor-age. If you want to use Apache Kafka then you can just use structured streaming.
Diagram Description automatically generated

Auto Loader and Cloud Storage Integration
Auto Loader supports a couple of ways to ingest data incrementally
1.Directory listing - List Directory and maintain the state in RocksDB, supports incremental file listing
2.File notification - Uses a trigger+queue to store the file notification which can be later used to retrieve the file, unlike Directory listing File notification can scale up to millions of files per day.
[OPTIONAL]
Auto Loader vs COPY INTO?
Auto Loader
Auto Loader incrementally and efficiently processes new data files as they arrive in cloud storage without any additional setup. Auto Loader provides a new Structured Streaming source called cloudFiles. Given an input directory path on the cloud file storage, the cloudFiles source automatically processes new files as they arrive, with the option of also processing existing files in that directory.
When to use Auto Loader instead of the COPY INTO?
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.
You do not plan to load subsets of previously uploaded files. With Auto Loader, it can be more difficult to reprocess subsets of files. However, you can use the COPY INTO SQL command to reload subsets of files while an Auto Loader stream is simultaneously running.
Refer to more documentation here,
https://docs.microsoft.com/en-us/azure/databricks/ingestion/auto-loader
NEW QUESTION # 54
Which of the following functions can be used to convert JSON string to Struct data type?

• A. CONVERT (json value, schema of json)
• B. CAST (json value as STRUCT)
• C. TO_STRUCT (json value)
• D. FROM_JSON (json value, schema of json)
• E. FROM_JSON (json value)

Answer: D Explanation:
Explanation
Syntax
Copy
1.fromjson(jsonStr, schema [, options])
Arguments
jsonStr: A STRING expression specifying a row of CSV data.
schema: A STRING literal or invocation of schemaofjson function (Databricks SQL).
*options: An optional MAP<STRING,STRING> literal specifying directives.
Refer documentation for more details,
https://docs.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/fromjson
NEW QUESTION # 55
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