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試験コード：Databricks-Certified-Data-Engineer-Professional

試験名称：Databricks Certified Data Engineer Professional Exam

最近更新時間：2025-01-22

問題と解答：全127問

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質問 1：
A table is registered with the following code:
Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from

Both users and orders are Delta Lake tables. Which statement describes the results of querying recent_orders?
A. All logic will execute when the table is defined and store the result of joining tables to the DBFS; this stored data will be returned when the table is queried.
B. Results will be computed and cached when the table is defined; these cached results will incrementally update as new records are inserted into source tables.
C. All logic will execute at query time and return the result of joining the valid versions of the source tables at the time the query finishes.
D. The versions of each source table will be stored in the table transaction log; query results will be saved to DBFS with each query.
E. All logic will execute at query time and return the result of joining the valid versions of the source tables at the time the query began.
正解：A
解説: (Topexam メンバーにのみ表示されます)

質問 2：
A data ingestion task requires a one-TB JSON dataset to be written out to Parquet with a target Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from part- file size of 512 MB. Because Parquet is being used instead of Delta Lake, built-in file-sizing features such as Auto-Optimize & Auto-Compaction cannot be used.
Which strategy will yield the best performance without shuffling data?
A. Set spark.sql.shuffle.partitions to 2,048 partitions (1TB*1024*1024/512), ingest the data, execute the narrow transformations, optimize the data by sorting it (which automatically repartitions the data), and then write to parquet.
B. Set spark.sql.files.maxPartitionBytes to 512 MB, ingest the data, execute the narrow transformations, and then write to parquet.
C. Set spark.sql.adaptive.advisoryPartitionSizeInBytes to 512 MB bytes, ingest the data, execute the narrow transformations, coalesce to 2,048 partitions (1TB*1024*1024/512), and then write to parquet.
D. Ingest the data, execute the narrow transformations, repartition to 2,048 partitions (1TB*
1024*1024/512), and then write to parquet.
E. Set spark.sql.shuffle.partitions to 512, ingest the data, execute the narrow transformations, and then write to parquet.
正解：A
解説: (Topexam メンバーにのみ表示されます)

質問 3：
A junior developer complains that the code in their notebook isn't producing the correct results in the development environment. A shared screenshot reveals that while they're using a notebook versioned with Databricks Repos, they're using a personal branch that contains old logic. The desired branch named dev-2.3.9 is not available from the branch selection dropdown.
Which approach will allow this developer to review the current logic for this notebook?
A. Use Repos to make a pull request use the Databricks REST API to update the current branch to dev-2.3.9
B. Merge all changes back to the main branch in the remote Git repository and clone the repo again
C. Use Repos to checkout the dev-2.3.9 branch and auto-resolve conflicts with the current branch
D. Use Repos to pull changes from the remote Git repository and select the dev-2.3.9 branch.
E. Use Repos to merge the current branch and the dev-2.3.9 branch, then make a pull request to sync with the remote repository
正解：D
解説: (Topexam メンバーにのみ表示されます)

質問 4：
A Databricks SQL dashboard has been configured to monitor the total number of records present in a collection of Delta Lake tables using the following query pattern:
SELECT COUNT (*) FROM table
Which of the following describes how results are generated each time the dashboard is updated?
A. The total count of records is calculated from the Delta transaction logs
B. The total count of records is calculated from the Hive metastore
C. The total count of records is calculated from the parquet file metadata
D. The total count of rows is calculated by scanning all data files
E. The total count of rows will be returned from cached results unless REFRESH is run
正解：A
解説: (Topexam メンバーにのみ表示されます)

質問 5：
The following code has been migrated to a Databricks notebook from a legacy workload:

The code executes successfully and provides the logically correct results, however, it takes over
20 minutes to extract and load around 1 GB of data.
Which statement is a possible explanation for this behavior?
A. %sh does not distribute file moving operations; the final line of code should be updated to use %fs instead.
B. %sh executes shell code on the driver node. The code does not take advantage of the worker nodes or Databricks optimized Spark.
C. Instead of cloning, the code should use %sh pip install so that the Python code can get executed in parallel across all nodes in a cluster.
D. %sh triggers a cluster restart to collect and install Git. Most of the latency is related to cluster startup time.
E. Python will always execute slower than Scala on Databricks. The run.py script should be refactored to Scala.
正解：B
解説: (Topexam メンバーにのみ表示されます)

質問 6：
The data architect has mandated that all tables in the Lakehouse should be configured as external Delta Lake tables.
Which approach will ensure that this requirement is met?
A. Whenever a database is being created, make sure that the location keyword is used Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from
B. When configuring an external data warehouse for all table storage. leverage Databricks for all ELT.
C. When tables are created, make sure that the external keyword is used in the create table statement.
D. Whenever a table is being created, make sure that the location keyword is used.
E. When the workspace is being configured, make sure that external cloud object storage has been mounted.
正解：D
解説: (Topexam メンバーにのみ表示されます)

質問 7：
Which statement describes the default execution mode for Databricks Auto Loader?
A. Cloud vendor-specific queue storage and notification services are configured to track newly arriving files; new files are incrementally and impotently into the target Delta Lake table.
B. New files are identified by listing the input directory; the target table is materialized by directory querying all valid files in the source directory.
C. Cloud vendor-specific queue storage and notification services are configured to track newly arriving files; the target table is materialized by directly querying all valid files in the source directory.
D. Webhook trigger Databricks job to run anytime new data arrives in a source directory; new data automatically merged into target tables using rules inferred from the data.
E. New files are identified by listing the input directory; new files are incrementally and idempotently loaded into the target Delta Lake table.
正解：E
解説: (Topexam メンバーにのみ表示されます)

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

1. An upstream system is emitting change data capture (CDC) logs that are being written to a cloud object storage directory. Each record in the log indicates the change type (insert, update, or delete) and the values for each field after the change. The source table has a primary key identified by the field pk_id.
For auditing purposes, the data governance team wishes to maintain a full record of all values that have ever been valid in the source system. For analytical purposes, only the most recent value for each record needs to be recorded. The Databricks job to ingest these records occurs once per hour, but each individual record may have changed multiple times over the course of an hour.
Which solution meets these requirements?

A) Use Delta Lake's change data feed to automatically process CDC data from an external system, propagating all changes to all dependent tables in the Lakehouse.
B) Use merge into to insert, update, or delete the most recent entry for each pk_id into a bronze table, then propagate all changes throughout the system.
C) Ingest all log information into a bronze table; use merge into to insert, update, or delete the most recent entry for each pk_id into a silver table to recreate the current table state.
D) Iterate through an ordered set of changes to the table, applying each in turn; rely on Delta Lake's versioning ability to create an audit log.
E) Create a separate history table for each pk_id resolve the current state of the table by running a Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from union all filtering the history tables for the most recent state.

2. A small company based in the United States has recently contracted a consulting firm in India to implement several new data engineering pipelines to power artificial intelligence applications. All the company's data is stored in regional cloud storage in the United States.
The workspace administrator at the company is uncertain about where the Databricks workspace used by the contractors should be deployed.
Assuming that all data governance considerations are accounted for, which statement accurately informs this decision?

A) Cross-region reads and writes can incur significant costs and latency; whenever possible, compute should be deployed in the same region the data is stored.
B) Databricks leverages user workstations as the driver during interactive development; as such, users should always use a workspace deployed in a region they are physically near.
C) Databricks workspaces do not rely on any regional infrastructure; as such, the decision should be Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from made based upon what is most convenient for the workspace administrator.
D) Databricks notebooks send all executable code from the user's browser to virtual machines over the open internet; whenever possible, choosing a workspace region near the end users is the most secure.
E) Databricks runs HDFS on cloud volume storage; as such, cloud virtual machines must be deployed in the region where the data is stored.

3. The data engineering team has configured a job to process customer requests to be forgotten (have their data deleted). All user data that needs to be deleted is stored in Delta Lake tables using default table settings.
The team has decided to process all deletions from the previous week as a batch job at 1am each Sunday. The total duration of this job is less than one hour. Every Monday at 3am, a batch job executes a series of VACUUM commands on all Delta Lake tables throughout the organization.
The compliance officer has recently learned about Delta Lake's time travel functionality. They are concerned that this might allow continued access to deleted data.
Assuming all delete logic is correctly implemented, which statement correctly addresses this concern?

A) Because the default data retention threshold is 24 hours, data files containing deleted records will be retained until the vacuum job is run the following day.
B) Because the default data retention threshold is 7 days, data files containing deleted records will be retained until the vacuum job is run 8 days later.Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from
C) Because Delta Lake time travel provides full access to the entire history of a table, deleted records can always be recreated by users with full admin privileges.
D) Because the vacuum command permanently deletes all files containing deleted records, deleted records may be accessible with time travel for around 24 hours.
E) Because Delta Lake's delete statements have ACID guarantees, deleted records will be permanently purged from all storage systems as soon as a delete job completes.

4. The data engineering team has configured a Databricks SQL query and alert to monitor the values in a Delta Lake table. The recent_sensor_recordings table contains an identifying sensor_id alongside the timestamp and temperature for the most recent 5 minutes of recordings.
The below query is used to create the alert:

The query is set to refresh each minute and always completes in less than 10 seconds. The alert is set to trigger when mean (temperature) > 120. Notifications are triggered to be sent at most Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from every 1 minute.
If this alert raises notifications for 3 consecutive minutes and then stops, which statement must be true?

A) The average temperature recordings for at least one sensor exceeded 120 on three consecutive executions of the query
B) The recent_sensor_recordingstable was unresponsive for three consecutive runs of the query
C) The maximum temperature recording for at least one sensor exceeded 120 on three consecutive executions of the query
D) The total average temperature across all sensors exceeded 120 on three consecutive executions of the query
E) The source query failed to update properly for three consecutive minutes and then restarted

5. A data engineer wants to join a stream of advertisement impressions (when an ad was shown) with another stream of user clicks on advertisements to correlate when impression led to monitizable clicks.

Which solution would improve the performance?

A)

B)

C)

D)

質問と回答：

質問 # 1
正解： C

質問 # 2
正解： A

質問 # 3
正解： B

質問 # 4
正解： A

質問 # 5
正解： A

Databricks-Certified-Data-Engineer-Professional 関連試験: Associate-Developer-Apache-Spark - Databricks Certified Associate Developer for Apache Spark 3.0 Exam; Databricks-Certified-Professional-Data-Scientist - Databricks Certified Professional Data Scientist Exam; Databricks-Certified-Professional-Data-Engineer - Databricks Certified Professional Data Engineer Exam; Databricks-Certified-Data-Engineer-Associate - Databricks Certified Data Engineer Associate Exam

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