Databricks Databricks-Certified-Data-Engineer-Professional - PDF電子當

Databricks-Certified-Data-Engineer-Professional pdf
  • 考試編碼:Databricks-Certified-Data-Engineer-Professional
  • 考試名稱:Databricks Certified Data Engineer Professional Exam
  • 更新時間:2025-11-27
  • 問題數量:127 題
  • PDF價格: $59.98
  • 電子當(PDF)試用

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  • 考試編碼:Databricks-Certified-Data-Engineer-Professional
  • 考試名稱:Databricks Certified Data Engineer Professional Exam
  • 更新時間:2025-11-27
  • 問題數量:127 題
  • PDF電子當 + 軟件版 + 在線測試引擎(免費送)
  • 套餐價格: $119.96  $79.98
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  • 考試編碼:Databricks-Certified-Data-Engineer-Professional
  • 考試名稱:Databricks Certified Data Engineer Professional Exam
  • 更新時間:2025-11-27
  • 問題數量:127 題
  • 軟件版價格: $59.98
  • 軟件版

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最新的 Databricks Certification Databricks-Certified-Data-Engineer-Professional 免費考試真題:

1. A Delta table of weather records is partitioned by date and has the below schema:
date DATE, device_id INT, temp FLOAT, latitude FLOAT, longitude FLOAT
To find all the records from within the Arctic Circle, you execute a query with the below filter:
latitude > 66.3
Which statement describes how the Delta engine identifies which files to load?

A) All records are cached to attached storage and then the filter is applied Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from
B) The Delta log is scanned for min and max statistics for the latitude column
C) The Parquet file footers are scanned for min and max statistics for the latitude column
D) All records are cached to an operational database and then the filter is applied
E) The Hive metastore is scanned for min and max statistics for the latitude column


2. The view updates represents an incremental batch of all newly ingested data to be inserted or updated in the customers table.
The following logic is used to process these records.
Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from

Which statement describes this implementation?

A) The customers table is implemented as a Type 2 table; old values are overwritten and new customers are appended.
B) The customers table is implemented as a Type 0 table; all writes are append only with no changes to existing values.
C) The customers table is implemented as a Type 3 table; old values are maintained as a new column alongside the current value.
D) The customers table is implemented as a Type 2 table; old values are maintained but marked as no longer current and new values are inserted.
E) The customers table is implemented as a Type 1 table; old values are overwritten by new values and no history is maintained.


3. When evaluating the Ganglia Metrics for a given cluster with 3 executor nodes, which indicator would signal proper utilization of the VM's resources?

A) Bytes Received never exceeds 80 million bytes per second
B) Network I/O never spikes
C) CPU Utilization is around 75% Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from
D) Total Disk Space remains constant
E) The five Minute Load Average remains consistent/flat


4. A team of data engineer are adding tables to a DLT pipeline that contain repetitive expectations for many of the same data quality checks.
One member of the team suggests reusing these data quality rules across all tables defined for this pipeline.
What approach would allow them to do this?

A) Maintain data quality rules in a Delta table outside of this pipeline's target schema, providing the schema name as a pipeline parameter.
B) Add data quality constraints to tables in this pipeline using an external job with access to pipeline configuration files.
C) Use global Python variables to make expectations visible across DLT notebooks included in the same pipeline.
D) Maintain data quality rules in a separate Databricks notebook that each DLT notebook of file.


5. 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 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.
B) 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.
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.


問題與答案:

問題 #1
答案: B
問題 #2
答案: D
問題 #3
答案: C
問題 #4
答案: A
問題 #5
答案: C

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