Evan Ward Evan Ward's صفحة الملف الشخصي

Evan Ward Evan Ward

0 دورة ملتحَق بها • 0 اكتملت الدورة

سيرة شخصية

Valid Databricks-Certified-Professional-Data-Engineer Exam Dumps - Valid Databricks-Certified-Professional-Data-Engineer Test Pattern

Try our best to get the related Databricks-Certified-Professional-Data-Engineer certification is the best way to show our professional ability, however, the exam is hard nut to crack and there are so many Databricks-Certified-Professional-Data-Engineer preparation questions related to the exam, it seems impossible for us to systematize all of the key points needed for the exam by ourselves. We would like to help you out with the Databricks-Certified-Professional-Data-Engineer Training Materials compiled by our company. There are so many strong points of our Databricks-Certified-Professional-Data-Engineer training materials, you will be bound to pass the Databricks-Certified-Professional-Data-Engineer exam with high scores.

Our Databricks-Certified-Professional-Data-Engineer training materials are excellent. The quality is going through official authentication. So your money paid for our Databricks-Certified-Professional-Data-Engineer practice engine is absolutely worthwhile. In addition, you are advised to invest on yourselves. After all, no one can be relied on except yourself. And you can rely on our Databricks-Certified-Professional-Data-Engineer learning quiz. We can claim that if you study with our Databricks-Certified-Professional-Data-Engineer exam questions for 20 to 30 hours, then you are bound to pass the exam for we have high pass rate as 98% to 100%.

>> Valid Databricks-Certified-Professional-Data-Engineer Exam Dumps <<

Valid Databricks Databricks-Certified-Professional-Data-Engineer Test Pattern - Simulations Databricks-Certified-Professional-Data-Engineer Pdf

If you keep delivering, your company will give you more opportunity and more money to manage. I don't think you will be a clerk forever. You must do your best to pass IT certification and to be elevated people. TorrentExam Databricks Databricks-Certified-Professional-Data-Engineer practice test will help you to open the door to the success. You can download pdf real questions and answers. What's more, you can also refer to our free demo. More and more IT people have taken action to purchase our Databricks Databricks-Certified-Professional-Data-Engineer test. 100% guarantee to pass Databricks-Certified-Professional-Data-Engineer test. I think you will not miss it.

The Databricks Databricks-Certified-Professional-Data-Engineer Exam is designed to test the candidate's ability to work with Databricks in a real-world setting. Candidates are required to demonstrate their ability to design and implement data pipelines that are scalable, efficient, and reliable. They must also be able to troubleshoot issues that arise during the data engineering process and optimize performance to ensure that pipelines run smoothly.

Databricks is a cloud-based data engineering platform that allows organizations to process large amounts of data quickly and efficiently. The platform leverages Apache Spark to perform data processing tasks and offers a wide range of tools and services to support data engineering workflows. Databricks also provides certification programs for data professionals who want to demonstrate their expertise in using the platform. One of these certifications is the Databricks Certified Professional Data Engineer exam.

Databricks Certified Professional Data Engineer Exam Sample Questions (Q44-Q49):

NEW QUESTION # 44
You are currently working on reloading customer_sales tables using the below query
1. INSERT OVERWRITE customer_sales
2. SELECT * FROM customers c
3. INNER JOIN sales_monthly s on s.customer_id = c.customer_id
After you ran the above command, the Marketing team quickly wanted to review the old data that was in the table. How does INSERT OVERWRITE impact the data in the customer_sales table if you want to see the previous version of the data prior to running the above statement?

A. Appends the data to the current version, you can time travel to previous versions
B. Overwrites the data in the table, all historical versions of the data, you can not time travel to previous versions
C. Overwrites the data in the table but preserves all historical versions of the data, you can time travel to previous versions
D. By default, overwrites the data and schema, you cannot perform time travel
E. Overwrites the current version of the data but clears all historical versions of the data, so you can not time travel to previous versions.

Answer: C

Explanation:
Explanation
The answer is, INSERT OVERWRITE Overwrites the current version of the data but preserves all historical versions of the data, you can time travel to previous versions.
1.INSERT OVERWRITE customer_sales
2.SELECT * FROM customers c
3.INNER JOIN sales s on s.customer_id = c.customer_id
Let's just assume that this is the second time you are running the above statement, you can still query the prior version of the data using time travel, and any DML/DDL except DROP TABLE creates new PARQUET files so you can still access the previous versions of data.
SQL Syntax for Time travel
SELECT * FROM table_name as of [version number]
with customer_sales example
SELECT * FROM customer_sales as of 1 -- previous version
SELECT * FROM customer_sales as of 2 -- current version
You see all historical changes on the table using DESCRIBE HISTORY table_name Note: the main difference between INSERT OVERWRITE and CREATE OR REPLACE TABLE(CRAS) is that CRAS can modify the schema of the table, i.e it can add new columns or change data types of existing columns. By default INSERT OVERWRITE only overwrites the data.
INSERT OVERWRITE can also be used to update the schema when
spark.databricks.delta.schema.autoMerge.enabled is set true if this option is not enabled and if there is a schema mismatch command INSERT OVERWRITEwill fail.
Any DML/DDL operation(except DROP TABLE) on the Delta table preserves the historical ver-sion of the data.

NEW QUESTION # 45
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.
MERGE INTO customers
USING (
SELECT updates.customer_id as merge_ey, updates .*
FROM updates
UNION ALL
SELECT NULL as merge_key, updates .*
FROM updates JOIN customers
ON updates.customer_id = customers.customer_id
WHERE customers.current = true AND updates.address <> customers.address ) staged_updates ON customers.customer_id = mergekey WHEN MATCHED AND customers. current = true AND customers.address <> staged_updates.
address THEN
UPDATE SET current = false, end_date = staged_updates.effective_date
WHEN NOT MATCHED THEN
INSERT (customer_id, address, current, effective_date, end_date)
VALUES (staged_updates.customer_id, staged_updates.address, true, staged_updates.effective_date, null) Which statement describes this implementation?
* The customers table is implemented as a Type 2 table; old values are overwritten and new customers are appended.

A. The customers table is implemented as a Type 1 table; old values are overwritten by new values and no history is maintained.
B. 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.
C. The customers table is implemented as a Type 0 table; all writes are append only with no changes to existing values.

Answer: C

Explanation:
The providedMERGEstatement is a classic implementation of a Type 2 SCD in a data warehousing context.
In this approach, historical data is preserved by keeping old records (marking them as not current) and adding new records for changes. Specifically, when a match is found and there's a change in the address, the existing record in thecustomerstable is updated to mark it as no longer current (current = false), and an end date is assigned (end_date = staged_updates.effective_date). A new record for the customer is then inserted with the updated information, marked as current. This method ensures that the full history of changes to customer information is maintained in the table, allowing for time-based analysis of customer data.References:
Databricks documentation on implementing SCDs using Delta Lake and theMERGEstatement (https://docs.
databricks.com/delta/delta-update.html#upsert-into-a-table-using-merge).

NEW QUESTION # 46
How to determine if a table is a managed table vs external table?

A. All managed tables are stored in unity catalog
B. Run IS_MANAGED('table_name') function
C. Run SQL command SHOW TABLES to see the type of the table
D. All external tables are stored in data lake, managed tables are stored in DELTA lake
E. Run SQL command DESCRIBE EXTENDED table_name and check type

Answer: E

Explanation:
Explanation
The answer is Run SQL command DESCRIBE EXTENDED table_name and check type Example of External table Graphical user interface, text, application Description automatically generated

Example of managed table
Graphical user interface, text, application, Teams Description automatically generated

NEW QUESTION # 47
Which of the following statements are correct on how Delta Lake implements a lake house?

A. Delta lake uses a proprietary format to write data, optimized for cloud storage
B. Delta lake stores data and meta data in computes memory
C. Delta lake uses open source, open format, optimized cloud storage and scalable meta data
D. Delta lake always stores meta data in memory vs storage
E. Using Apache Hadoop on cloud object storage

Answer: C

Explanation:
Explanation
Delta lake is
* Open source
* Builds up on standard data format
* Optimized for cloud object storage
* Built for scalable metadata handling
Delta lake is not
* Proprietary technology
* Storage format
* Storage medium
* Database service or data warehouse

NEW QUESTION # 48
A nightly job ingests data into a Delta Lake table using the following code:

The next step in the pipeline requires a function that returns an object that can be used to manipulate new records that have not yet been processed to the next table in the pipeline.
Which code snippet completes this function definition?
def new_records():

A.
B. return spark.read.option("readChangeFeed", "true").table ("bronze")
C. return spark.readStream.load("bronze")
D.
E. return spark.readStream.table("bronze")

Answer: A

Explanation:
https://docs.databricks.com/en/delta/delta-change-data-feed.html

NEW QUESTION # 49
......

In order to meet different needs for Databricks-Certified-Professional-Data-Engineer exam bootcamp, three versions are available. You can choose the most suitable one according to your own exam needs. All three have free demo for you to have a try before buying. Databricks-Certified-Professional-Data-Engineer PDF version is printable, you can study them anytime. Databricks-Certified-Professional-Data-Engineer Soft test engine supports MS operating system, and have two modes for practice, and it can also stimulate the real exam environment, therefore, this version can build you exam confidence. Databricks-Certified-Professional-Data-Engineer Online test engine is convenient to learn, and it also supports offline practice.

Valid Databricks-Certified-Professional-Data-Engineer Test Pattern: https://www.torrentexam.com/Databricks-Certified-Professional-Data-Engineer-exam-latest-torrent.html

Blog

Evan Ward Evan Ward

سيرة شخصية