Databricks Databricks Certification Databricks-Certified-Data-Engineer-Professional

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Databricks Certified Data Engineer Professional 認定 Databricks-Certified-Data-Engineer-Professional 試験問題:

1. A data engineer wants to create a cluster using the Databricks CLI for a big ETL pipeline. The cluster should have five workers, one driver of type i3.xlarge, and should use the '14.3.x- scala2.12' runtime. Which command should the data engineer use?

A) databricks clusters create 14.3.x-scala2.12 --num-workers 5 --node-type-id i3.xlarge --cluster- name DataEngineer_cluster
B) databricks compute create 14.3.x-scala2.12 --num-workers 5 --node-type-id i3.xlarge --cluster- name Data Engineer_cluster
C) databricks compute add 14.3.x-scala2.12 --num-workers 5 --node-type-id i3.xlarge --cluster-name Data Engineer_cluster
D) databricks clusters add 14.3.x-scala2.12 --num-workers 5 --node-type-id i3.xlarge --cluster-name Data Engineer_cluster

2. Which statement characterizes the general programming model used by Spark Structured Streaming?

A) Structured Streaming leverages the parallel processing of GPUs to achieve highly parallel data throughput.
B) Structured Streaming is implemented as a messaging bus and is derived from Apache Kafka.
C) Structured Streaming relies on a distributed network of nodes that hold incremental state values for cached stages.
D) Structured Streaming uses specialized hardware and I/O streams to achieve sub-second latency for data transfer.
E) Structured Streaming models new data arriving in a data stream as new rows appended to an unbounded table.

3. A platform team is creating a standardized template for Databricks Asset Bundles to support CI/CD. The template must specify defaults for artifacts, workspace root paths, and a run identity, while allowing a "dev" target to be the default and override specific paths. How should the team use databricks.yml to satisfy these requirements?

A) Use bundle, artifacts, workspace, run_as, and targets at the top level; set one target with default:true and override workspace paths or artifacts under that target.
B) Use project, packages, environment, identity, and stages; set dev as default stage and override workspace under environment.
C) Use roots, modules, profiles, actor, and targets; where profiles contain workspace and artifacts defaults and actor sets run identity.
D) Use deployment, builds, context, identity, and environments; set dev as default environment and override paths under builds.

4. A company stores account transactions in a Delta Lake table. The company needs to apply frequent account-level correlations (e.g., UPDATE statements) but wants to avoid rewriting entire Parquet files for each change to reduce file churn and improve write performance. Which Delta Lake feature should they enable?

A) Enable change data feed on the Delta table
B) Partition the Delta table by account_id
C) Enable deletion vectors on the Delta table
D) Enable automatic file compaction on writes

5. 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) Partition the table with: ALTER TABLE orders PARTITION BY user_id, product_id, event_timestamp
B) Z-order the table with OPTIMIZE orders ZORDER 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

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