A task orchestrator has been configured to run two hourly tasks. First, an outside system writes Parquet data to a directory mounted at /mnt/raw_orders/. After this data is written, a Databricks job containing the following code is executed:
(spark.readStream
.format("parquet")
.load("/mnt/raw_orders/")
.withWatermark("time", "2 hours")
.dropDuplicates(["customer_id", "order_id"])
.writeStream
.trigger(once=True)
.table("orders")
)
Assume that the fields customer_id and order_id serve as a composite key to uniquely identify each order, and that the time field indicates when the record was queued in the source system. If the upstream system is known to occasionally enqueue duplicate entries for a single order hours apart, which statement is correct?

• A.The orders table will not contain duplicates, but records arriving more than 2 hours late will be ignored and missing from the table.
• B.The orders table will contain only the most recent 2 hours of records and no duplicates will be present.
• C.All records will be held in the state store for 2 hours before being deduplicated and committed to the orders table.
• D.Duplicate records enqueued more than 2 hours apart may be retained and the orders table may contain duplicate records with the same customer_id and order_id.

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The Databricks workspace administrator has configured interactive clusters for each of the data engineering groups. To control costs, clusters are set to terminate after 30 minutes of inactivity. Each user should be able to execute workloads against their assigned clusters at any time of the day.
Assuming users have been added to a workspace but not granted any permissions, which of the following describes the minimal permissions a user would need to start and attach to an already configured cluster.

• A."Can Manage" privileges on the required cluster
• B.Workspace Admin privileges, cluster creation allowed. "Can Attach To" privileges on the required cluster
• C.Cluster creation allowed. "Can Attach To" privileges on the required cluster
• D."Can Restart" privileges on the required cluster
• E.Cluster creation allowed. "Can Restart" privileges on the required cluster

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A data engineer needs to provide access to a group named manufacturing-team. The team needs privileges to create tables in the quality schema.
Which set of SQL commands will grant a group named manufacturing-team to create tables in a schema named production with the parent catalog named manufacturing with the least privileges?

• A.GRANT CREATE TABLE ON SCHEMA manufacturing.quality TO manufacturing-team; GRANT CREATE SCHEMA ON SCHEMA manufacturing.quality TO manufacturing-team; GRANT CREATE CATALOG ON CATALOG manufacturing TO manufacturing-team;
• B.GRANT CREATE TABLE ON SCHEMA manufacturing.quality TO manufacturing-team; GRANT CREATE SCHEMA ON SCHEMA manufacturing.quality TO manufacturing-team; GRANT USE CATALOG ON CATALOG manufacturing TO manufacturing-team;
• C.GRANT CREATE TABLE ON SCHEMA manufacturing.quality TO manufacturing-team; GRANT USE SCHEMA ON SCHEMA manufacturing.quality TO manufacturing-team; GRANT USE CATALOG ON CATALOG manufacturing TO manufacturing-team;
• D.GRANT USE TABLE ON SCHEMA manufacturing.quality TO manufacturing-team; GRANT USE SCHEMA ON SCHEMA manufacturing.quality TO manufacturing-team; GRANT USE CATALOG ON CATALOG manufacturing TO manufacturing-team;

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A junior data engineer is migrating a workload from a relational database system to the Databricks Lakehouse. The source system uses a star schema, leveraging foreign key constrains and multi-table inserts to validate records on write.
Which consideration will impact the decisions made by the engineer while migrating this workload?

• A.All Delta Lake transactions are ACID compliance against a single table, and Databricks does not enforce foreign key constraints.
• B.Databricks only allows foreign key constraints on hashed identifiers, which avoid collisions in highly- parallel writes.
• C.Foreign keys must reference a primary key field; multi-table inserts must leverage Delta Lake's upsert functionality.
• D.Committing to multiple tables simultaneously requires taking out multiple table locks and can lead to a state of deadlock.

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A data engineer needs to capture pipeline settings from an existing in the workspace, and use them to create and version a JSON file to create a new pipeline.
Which command should the data engineer enter in a web terminal configured with the Databricks CLI?

• A.Stop the existing pipeline; use the returned settings in a reset command
• B.Use the get command to capture the settings for the existing pipeline; remove the pipeline_id and rename the pipeline; use this in a create command
• C.Use list pipelines to get the specs for all pipelines; get the pipeline spec from the return results parse and use this to create a pipeline
• D.Use the alone command to create a copy of an existing pipeline; use the get JSON command to get the pipeline definition; save this to git

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