Databricks-Certified-Professional-Data-Engineer Exam Dumps : Databricks Certified Data Engineer Professional Exam

It marks a column as having low enough cardinality to properly map distinct values to available partitions, allowing a broadcast join.

It marks a column as small enough to store in memory on all executors, allowing a broadcast join.

It caches a copy of the indicated table on attached storage volumes for all active clusters within a Databricks workspace.

It marks a DataFrame as small enough to store in memory on all executors, allowing a broadcast join.

It caches a copy of the indicated table on all nodes in the cluster for use in all future queries during the cluster lifetime.

Send all users notice that the schema for the table will be changing; include in the communication the logic necessary to revert the new table schema to match historic queries.

Configure a new table with all the requisite fields and new names and use this as the source for the customer-facing application; create a view that maintains the original data schema and table name by aliasing select fields from the new table.

Create a new table with the required schema and new fields and use Delta Lake's deep clone functionality to sync up changes committed to one table to the corresponding table.

Replace the current table definition with a logical view defined with the query logic currently writing the aggregate table; create a new table to power the customer-facing application.

Add a table comment warning all users that the table schema and field names will be changing on a given date; overwrite the table in place to the specifications of the customer-facing application.

The job_id and number of times the job has been run are concatenated and returned.

The globally unique ID of the newly triggered run.

The job_id is returned in this field.

The number of times the job definition has been run in this workspace.