100% PASS QUIZ 2025 DATABRICKS MARVELOUS DATABRICKS-CERTIFIED-DATA-ENGINEER-PROFESSIONAL RELIABLE EXAM LABS

100% Pass Quiz 2025 Databricks Marvelous Databricks-Certified-Data-Engineer-Professional Reliable Exam Labs

100% Pass Quiz 2025 Databricks Marvelous Databricks-Certified-Data-Engineer-Professional Reliable Exam Labs

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Databricks Certified Data Engineer Professional Exam Sample Questions (Q73-Q78):

NEW QUESTION # 73
The data engineering team is migrating an enterprise system with thousands of tables and views into the Lakehouse. They plan to implement the target architecture using a series of bronze, silver, and gold tables. Bronze tables will almost exclusively be used by production data engineering workloads, while silver tables will be used to support both data engineering and machine learning workloads. Gold tables will largely serve business intelligence and reporting purposes. While personal identifying information (PII) exists in all tiers of data, pseudonymization and anonymization rules are in place for all data at the silver and gold levels.
The organization is interested in reducing security concerns while maximizing the ability to collaborate across diverse teams.
Which statement exemplifies best practices for implementing this system?

  • A. Isolating tables in separate databases based on data quality tiers allows for easy permissions management through database ACLs and allows physical separation of default storage locations for managed tables.
  • B. Because databases on Databricks are merely a logical construct, choices around database organization do not impact security or discoverability in the Lakehouse.
  • C. Because all tables must live in the same storage containers used for the database they're created in, organizations should be prepared to create between dozens and thousands of databases depending on their data isolation requirements.
  • D. Working in the default Databricks database provides the greatest security when working with managed tables, as these will be created in the DBFS root.
  • E. Storinq all production tables in a single database provides a unified view of all data assets available throughout the Lakehouse, simplifying discoverability by granting all users view privileges on this database.

Answer: A

Explanation:
This is the correct answer because it exemplifies best practices for implementing this system. By isolating tables in separate databases based on data quality tiers, such as bronze, silver, and gold, the data engineering team can achieve several benefits. First, they can easily manage permissions for different users and groups through database ACLs, which allow granting or revoking access to databases, tables, or views. Second, they can physically separate the default storage locations for managed tables in each database, which can improve performance and reduce costs. Third, they can provide a clear and consistent naming convention for the tables in each database, which can improve discoverability and usability.


NEW QUESTION # 74
What is a method of installing a Python package scoped at the notebook level to all nodes in the currently active cluster?

  • A. Use &Pip install in a notebook cell
  • B. Run source env/bin/activate in a notebook setup script
  • C. Install libraries from PyPi using the cluster UI
  • D. Use &sh install in a notebook cell

Answer: C

Explanation:
Installing a Python package scoped at the notebook level to all nodes in the currently active cluster in Databricks can be achieved by using the Libraries tab in the cluster UI. This interface allows you to install libraries across all nodes in the cluster. While the %pip command in a notebook cell would only affect the driver node, using the cluster UI ensures that the package is installed on all nodes.


NEW QUESTION # 75
The business intelligence team has a dashboard configured to track various summary metrics for retail stories. This includes total sales for the previous day alongside totals and averages for a variety of time periods. The fields required to populate this dashboard have the following schema:

For Demand forecasting, the Lakehouse contains a validated table of all itemized sales updated incrementally in near real-time. This table named products_per_order, includes the following fields:

Because reporting on long-term sales trends is less volatile, analysts using the new dashboard only require data to be refreshed once daily. Because the dashboard will be queried interactively by many users throughout a normal business day, it should return results quickly and reduce total compute associated with each materialization.
Which solution meets the expectations of the end users while controlling and limiting possible costs?

  • A. Define a view against the products_per_order table and define the dashboard against this view.
  • B. Populate the dashboard by configuring a nightly batch job to save the required to quickly update the dashboard with each query.
  • C. Use the Delta Cache to persists the products_per_order table in memory to quickly the dashboard with each query.
  • D. Use Structure Streaming to configure a live dashboard against the products_per_order table within a Databricks notebook.
  • E. Configure a webhook to execute an incremental read against products_per_order each time the dashboard is refreshed.

Answer: B


NEW QUESTION # 76
Which configuration parameter directly affects the size of a spark-partition upon ingestion of data into Spark?

  • A. spark.sql.files.maxPartitionBytes
  • B. spark.sql.files.openCostInBytes
  • C. spark.sql.autoBroadcastJoinThreshold
  • D. spark.sql.adaptive.advisoryPartitionSizeInBytes
  • E. spark.sql.adaptive.coalescePartitions.minPartitionNum

Answer: A

Explanation:
Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from This is the correct answer because spark.sql.files.maxPartitionBytes is a configuration parameter that directly affects the size of a spark-partition upon ingestion of data into Spark. This parameter configures the maximum number of bytes to pack into a single partition when reading files from file- based sources such as Parquet, JSON and ORC. The default value is 128 MB, which means each partition will be roughly 128 MB in size, unless there are too many small files or only one large file.


NEW QUESTION # 77
A production cluster has 3 executor nodes and uses the same virtual machine type for the driver and executor.
When evaluating the Ganglia Metrics for this cluster, which indicator would signal a bottleneck caused by code executing on the driver?

  • A. Total Disk Space remains constant
  • B. Network I/O never spikes
    Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from
  • C. Overall cluster CPU utilization is around 25%
  • D. The five Minute Load Average remains consistent/flat
  • E. Bytes Received never exceeds 80 million bytes per second

Answer: C

Explanation:
This is the correct answer because it indicates a bottleneck caused by code executing on the driver. A bottleneck is a situation where the performance or capacity of a system is limited by a single component or resource. A bottleneck can cause slow execution, high latency, or low throughput. A production cluster has 3 executor nodes and uses the same virtual machine type for the driver and executor. When evaluating the Ganglia Metrics for this cluster, one can look for indicators that show how the cluster resources are being utilized, such as CPU, memory, disk, or network. If the overall cluster CPU utilization is around 25%, it means that only one out of the four nodes (driver + 3 executors) is using its full CPU capacity, while the other three nodes are idle or underutilized. This suggests that the code executing on the driver is taking too long or consuming too much CPU resources, preventing the executors from receiving tasks or data to process. This can happen when the code has driver-side operations that are not parallelized or distributed, such as collecting large amounts of data to the driver, performing complex calculations on the driver, or using non-Spark libraries on the driver.


NEW QUESTION # 78
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