Databricks Certified-Data-Engineer-Professional valid exam dumps : Databricks Certified Data Engineer Professional

A data engineer is building a streaming data pipeline to ingest JSON files from cloud storage into a Delta Lake table. The pipeline must process files incrementally, handle schema evolution automatically, ensure exactly-once processing, and minimize manual infrastructure management.
How should the data engineer fulfill these requirements?

• A. Use Auto Loader in batch mode with a daily job to overwrite the Delta table.
• B. Use Lakeflow Spart Declarative Pipelines with Auto Loader and enabling schema inference with
  "cloudFiles.schemaEvolutionMode"= "addNewColumns"
• C. Use traditional Spark Structured Streaming with Auto Loader, manually configuring checkpoints location and enabling schema inference with "mergeSchema"= "true"
• D. Use Lakeflow Spark Declarative Pipelines with a static DataFrame read, merge schema with spark.conf.set ("spark.databricks.delta.schema.autoMerge.enabled", "true")

A developer has successfully configured their credentials for Databricks Repos and cloned a remote Git repository. They do not have privileges to make changes to the main branch, which is the only branch currently visible in their workspace. Which approach allows this user to share their code updates without the risk of overwriting the work of their teammates?

• A. Use repos to create a fork of the remote repository commit all changes and make a pull request on the source repository
• B. Use repos to merge all difference and make a pull request back to the remote repository.
• C. Use Repos to merge all differences and make a pull request back to the remote repository.
• D. Use Repos to create a new branch commit all changes and push changes to the remote Git repertory.
• E. Use Repos to pull changes from the remote Git repository; commit and push changes to a branch that appeared as changes were pulled.

A data team is working to optimize an existing large, fast-growing table 'orders' with high cardinality columns, which experiences significant data skew and requires frequent concurrent writes. The team notice that the columns 'user_id', 'event_timestamp' and 'product_id' are heavily used in analytical queries and filters, although those keys may be subject to change in the future due to different business requirements. Which partitioning strategy should the team choose to optimize the table for immediate data skipping, incremental management over time, and flexibility?

• A. Z-order the table with OPTIMIZE orders ZORDER BY (user_id, product_id, event_timestamp)
• B. Partition the table with: ALTER TABLE orders PARTITION BY user_id, product_id, event_timestamp
• C. Cluster the table with: ALTER TABLE orders CLUSTER BY user_id, product_id, event_timestamp
• D. Use z-order after partitiing the table: OPTIMIZE orders ZORDER BY (user_id, product_id) WHERE event_timestamp = current date () - 1 DAY

A platform engineer needs to report the resource consumption, categorized by SKU tier, across all workspaces. The engineer decides to use the system.billing.usage system table to create a query. Which SQL query will accurately return the daily usage by product?

• A.
  
• B.
  
• C.
  
• D.
  

A junior data engineer has configured a workload that posts the following JSON to the Databricks REST API endpoint 2.0/jobs/create.

Assuming that all configurations and referenced resources are available, which statement describes the result of executing this workload three times?

• A. The logic defined in the referenced notebook will be executed three times on new clusters with the configurations of the provided cluster ID.
• B. Three new jobs named "Ingest new data" will be defined in the workspace, and they will each run once daily.
• C. The logic defined in the referenced notebook will be executed three times on the referenced existing all purpose cluster.
• D. One new job named "Ingest new data" will be defined in the workspace, but it will not be executed.
• E. Three new jobs named "Ingest new data" will be defined in the workspace, but no jobs will be executed.