Latest Databricks-Certified-Professional-Data-Engineer Study Guide & Databricks-Certified-Professional-Data-Engineer Test Objectives Pdf
Our company constantly increases the capital investment on the research and innovation of our Databricks-Certified-Professional-Data-Engineer study materials and expands the influences of our study materials in the domestic and international market. Because the high quality and passing rate of our Databricks-Certified-Professional-Data-Engineer study materials more than 90 percent that clients choose to buy our study materials when they prepare for the test Databricks-Certified-Professional-Data-Engineer Certification. We have established a good reputation among the industry and the constantly-enlarged client base. Our sales volume and income are constantly increasing and the clients’ credibility towards our Databricks-Certified-Professional-Data-Engineer study materials stay high.
Databricks Certified Professional Data Engineer Exam covers a wide range of topics related to data engineering using Databricks, including data ingestion, data transformation, data storage, and data orchestration. Databricks-Certified-Professional-Data-Engineer Exam also tests the candidate's proficiency in using Databricks tools and technologies such as Delta Lake, Apache Spark, and Databricks Runtime. Successful completion of the exam demonstrates that the candidate has the skills and knowledge required to design, build, and manage efficient and scalable data pipelines using Databricks. Databricks Certified Professional Data Engineer Exam certification also enhances the candidate's credibility and marketability in the job market, as it is recognized by leading organizations in the industry.
>> Latest Databricks-Certified-Professional-Data-Engineer Study Guide <<
Hot Databricks Latest Databricks-Certified-Professional-Data-Engineer Study Guide & Trustable Pass4Leader - Leader in Certification Exam Materials
If you would like to create a second steady stream of income and get your business opportunity in front of more qualified people, please pay attention to Databricks Databricks-Certified-Professional-Data-Engineer latest study dumps. Databricks-Certified-Professional-Data-Engineer useful exam torrents are valid and refined from the previous actual test. You will find the Pass4Leader Databricks-Certified-Professional-Data-Engineer valid and reliable questions & answers are all the key questions, unlike other vendors offering the dumps with lots of useless questions, wasting the precious time of candidates. Pass4Leader Databricks free demo is available and you can download and have a try, then you can make decision to buy the Databricks exam dumps. Do study plan according to the Databricks exam study material, and arrange your time and energy reasonably. I believe that an efficiency and reasonable exam training can help you to pass the Databricks-Certified-Professional-Data-Engineer Exam successfully.
Databricks Certified Professional Data Engineer Exam Sample Questions (Q91-Q96):
NEW QUESTION # 91
You are currently asked to work on building a data pipeline, you have noticed that you are currently working with a data source that has a lot of data quality issues and you need to monitor data quality and enforce it as part of the data ingestion process, which of the following tools can be used to address this problem?
Answer: D
Explanation:
Explanation
The answer is, DELTA LIVE TABLES
Delta live tables expectations can be used to identify and quarantine bad data, all of the data quality metrics are stored in the event logs which can be used to later analyze and monitor.
DELTA LIVE Tables expectations
Below are three types of expectations, make sure to pay attention differences between these three.
Retain invalid records:
Use the expect operator when you want to keep records that violate the expectation. Records that violate the expectation are added to the target dataset along with valid records:
Python
1.@dlt.expect("valid timestamp", "col("timestamp") > '2012-01-01'")
SQL
1.CONSTRAINT valid_timestamp EXPECT (timestamp > '2012-01-01')
Drop invalid records:
Use the expect or drop operator to prevent the processing of invalid records. Records that violate the expectation are dropped from the target dataset:
Python
1.@dlt.expect_or_drop("valid_current_page", "current_page_id IS NOT NULL AND cur-rent_page_title IS NOT NULL") SQL
1.CONSTRAINT valid_current_page EXPECT (current_page_id IS NOT NULL and cur-rent_page_title IS NOT NULL) ON VIOLATION DROP ROW Fail on invalid records:
When invalid records are unacceptable, use the expect or fail operator to halt execution imme-diately when a record fails validation. If the operation is a table update, the system atomically rolls back the transaction:
Python
1.@dlt.expect_or_fail("valid_count", "count > 0")
SQL
1.CONSTRAINT valid_count EXPECT (count > 0) ON VIOLATION FAIL UPDATE
NEW QUESTION # 92
A data analyst has noticed that their Databricks SQL queries are running too slowly. They claim that this issue
is affecting all of their sequentially run queries. They ask the data engineering team for help. The data
engineering team notices that each of the queries uses the same SQL endpoint, but the SQL endpoint is not
used by any other user.
Which of the following approaches can the data engineering team use to improve the latency of the data
analyst's queries?
Answer: A
NEW QUESTION # 93
Although the Databricks Utilities Secrets module provides tools to store sensitive credentials and avoid accidentally displaying them in plain text users should still be careful with which credentials are stored here and which users have access to using these secrets.
Which statement describes a limitation of Databricks Secrets?
Answer: B
Explanation:
Explanation
This is the correct answer because it describes a limitation of Databricks Secrets. Databricks Secrets is a module that provides tools to store sensitive credentials and avoid accidentally displaying them in plain text.
Databricks Secrets allows creating secret scopes, which are collections of secrets that can be accessed by users or groups. Databricks Secrets also allows creating and managing secrets using the Databricks CLI or the Databricks REST API. However, a limitation of Databricks Secrets is that the Databricks REST API can be used to list secrets in plain text if the personal access token has proper credentials. Therefore, users should still be careful with which credentials are stored in Databricks Secrets and which users have access to using these secrets. Verified References: [Databricks Certified Data Engineer Professional], under "Databricks Workspace" section; Databricks Documentation, under "List secrets" section.
NEW QUESTION # 94
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?
Answer: B
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. Verified Reference: [Databricks Certified Data Engineer Professional], under "Spark Core" section; Databricks Documentation, under "View cluster status and event logs - Ganglia metrics" section; Databricks Documentation, under "Avoid collecting large RDDs" section.
In a Spark cluster, the driver node is responsible for managing the execution of the Spark application, including scheduling tasks, managing the execution plan, and interacting with the cluster manager. If the overall cluster CPU utilization is low (e.g., around 25%), it may indicate that the driver node is not utilizing the available resources effectively and might be a bottleneck.
NEW QUESTION # 95
A Delta Lake table was created with the below query:
Consider the following query:
DROP TABLE prod.sales_by_store -
If this statement is executed by a workspace admin, which result will occur?
Answer: E
Explanation:
When a table is dropped in Delta Lake, the table is removed from the catalog and the data is deleted. This is because Delta Lake is a transactional storage layer that provides ACID guarantees. When a table is dropped, the transaction log is updated to reflect the deletion of the table and the data is deleted from the underlying storage. References:
* https://docs.databricks.com/delta/quick-start.html#drop-a-table
* https://docs.databricks.com/delta/delta-batch.html#drop-table
NEW QUESTION # 96
......
Whether you prefer web-based practice exam, desktop-based exam, or PDF real questions, we've got you covered. We believe that variety is key when it comes to Databricks Databricks-Certified-Professional-Data-Engineer Exam Preparation, and that's why we offer three formats that cater to different learning styles and preferences.
Databricks-Certified-Professional-Data-Engineer Test Objectives Pdf: https://www.pass4leader.com/Databricks/Databricks-Certified-Professional-Data-Engineer-exam.html