Databricks Certification Databricks-Certified-Data-Engineer-Professional

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IT업계 엘리트한 강사들이 퍼펙트한 Databricks-Certified-Data-Engineer-Professional시험응시 Databricks Certified Data Engineer Professional Exam덤프문제집을 제작하여 디테일한 Databricks-Certified-Data-Engineer-Professional문제와 답으로 여러분이 아주 간단히 Databricks Certified Data Engineer Professional Exam시험응시를 패스할 수 있도록 최선을 다하고 있습니다.덤프구매후 2,3일 정도만 공부하시면 바로 시험보셔도 되기에 가장 짧은 시간을 투자하여 시험에서 패스할수 있습니다.

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최신 Databricks Certification Databricks-Certified-Data-Engineer-Professional 무료샘플문제:

1. A Delta Lake table representing metadata about content from user has the following schema:
Based on the above schema, which column is a good candidate for partitioning the Delta Table?

A) Post_id
B) Date
C) Post_time
D) latitude
E) User_id

2. The data engineering team maintains the following code:
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Assuming that this code produces logically correct results and the data in the source table has been de-duplicated and validated, which statement describes what will occur when this code is executed?

A) A batch job will update the gold_customer_lifetime_sales_summary table, replacing only those rows that have different values than the current version of the table, using customer_id as the primary key.
B) The gold_customer_lifetime_sales_summary table will be overwritten by aggregated values calculated from all records in the silver_customer_sales table as a batch job.
C) The silver_customer_sales table will be overwritten by aggregated values calculated from all records in the gold_customer_lifetime_sales_summary table as a batch job.
D) An incremental job will detect if new rows have been written to the silver_customer_sales table; if new rows are detected, all aggregates will be recalculated and used to overwrite the gold_customer_lifetime_sales_summary table.
E) An incremental job will leverage running information in the state store to update aggregate values in the gold_customer_lifetime_sales_summary table.

3. The data science team has created and logged a production model using MLflow. The following code correctly imports and applies the production model to output the predictions as a new DataFrame named preds with the schema "customer_id LONG, predictions DOUBLE, date DATE".
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The data science team would like predictions saved to a Delta Lake table with the ability to compare all predictions across time. Churn predictions will be made at most once per day.
Which code block accomplishes this task while minimizing potential compute costs?

A)

B)

C) preds.write.mode("append").saveAsTable("churn_preds")
D)

E) preds.write.format("delta").save("/preds/churn_preds")

4. An external object storage container has been mounted to the location /mnt/finance_eda_bucket.
The following logic was executed to create a database for the finance team:

After the database was successfully created and permissions configured, a member of the finance team runs the following code:

If all users on the finance team are members of the finance group, which statement describes how the tx_sales table will be created?

A) A logical table will persist the physical plan to the Hive Metastore in the Databricks control plane.
B) A managed table will be created in the DBFS root storage container.
C) An external table will be created in the storage container mounted to /mnt/finance eda bucket.
D) An managed table will be created in the storage container mounted to /mnt/finance_eda_bucket.
E) A logical table will persist the query plan to the Hive Metastore in the Databricks control plane.

5. A large company seeks to implement a near real-time solution involving hundreds of pipelines with parallel updates of many tables with extremely high volume and high velocity data.
Which of the following solutions would you implement to achieve this requirement?

A) Store all tables in a single database to ensure that the Databricks Catalyst Metastore can load balance overall throughput.
B) Use Databricks High Concurrency clusters, which leverage optimized cloud storage connections to maximize data throughput.
C) Partition ingestion tables by a small time duration to allow for many data files to be written in parallel.
D) Isolate Delta Lake tables in their own storage containers to avoid API limits imposed by cloud vendors.
E) Configure Databricks to save all data to attached SSD volumes instead of object storage, increasing file I/O significantly.

질문과 대답: