A data engineer has created a new cluster using shared access mode with default configurations. The data engineer needs to allow the development team access to view the driver logs if needed.
What are the minimal cluster permissions that allow the development team to accomplish this?

• A.CAN ATTACH TO
• B.CAN MANAGE
• C.CAN VIEW
• D.CAN RESTART

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You are asked to set up an alert to notify in an email every time a KPI indicater increases beyond a threshold value, team also asked you to include the actual value in the alert email notification.

• A.Use notebook and python code to run every minute, using python variables to capture send the information in an email
• B.Setup an alert but use the default template to notify the message in email's subject
• C.Setup an alert but use the custom template to notify the message in email's subject
• D.Use the webhook destination instead so alert message can be customized
• E.Use custom email hook to customize the message

Correct Answer: C

Explanation
Alerts support custom template supports using variables to customize the default message, set up the query to compare the KPI current value to the threshold and use the variable QUE-RY_RESULT_VALUE to display the value in the email notification.
here is a simple alert, that uses variables in the custom template to present these values in the email notification message, when the alert is fired these variables get replaced with actual values.
Alert with custom template
Graphical user interface, application Description automatically generated

When you enable preview you can see how the alert looks when you substitute the variables.
Graphical user interface, text, application, email Description automatically generated

Below are additional template variables available to you with the custom template.
Alerts | Databricks on AWS
Graphical user interface, text, application, email Description automatically generated

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A transactions table has been liquid clustered on the columns product_id, user_id, and event_date.
Which operation lacks support for cluster on write?

• A.spark.writestream.format('delta').mode('append')
• B.CTAS and RTAS statements
• C.INSERT INTO operations
• D.spark.write.format('delta').mode('append')

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A junior data engineer is working to implement logic for a Lakehouse table named silver_device_recordings.
The source data contains 100 unique fields in a highly nested JSON structure.
The silver_device_recordings table will be used downstream for highly selective joins on a number of fields, and will also be leveraged by the machine learning team to filter on a handful of relevant fields, in total, 15 fields have been identified that will often be used for filter and join logic.
The data engineer is trying to determine the best approach for dealing with these nested fields before declaring the table schema.
Which of the following accurately presents information about Delta Lake and Databricks that may Impact their decision-making process?

• A.Because Delta Lake uses Parquet for data storage, Dremel encoding information for nesting can be directly referenced by the Delta transaction log.
• B.Tungsten encoding used by Databricks is optimized for storing string data: newly-added native support for querying JSON strings means that string types are always most efficient.
• C.Schema inference and evolution on Databricks ensure that inferred types will always accurately match the data types used by downstream systems.
• D.By default Delta Lake collects statistics on the first 32 columns in a table; these statistics are leveraged for data skipping when executing selective queries.

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How do you upgrade an existing workspace managed table to a unity catalog table?

• A.ALTER TABLE table_name SET UNITY_CATALOG = TRUE
• B.Create table catalog_name.schema_name.table_name
  as select * from hive_metastore.old_schema.old_table
• C.Create table table_name as select * from hive_metastore.old_schema.old_table
• D.Create table table_name format = UNITY as select * from old_table_name
• E.Create or replace table_name format = UNITY using deep clone old_table_name

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