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Databricks Certified Professional Data Engineer Exam Sample Questions (Q201-Q206):

NEW QUESTION # 201
The data analyst team had put together queries that identify items that are out of stock based on orders and replenishment but when they run all together for final output the team noticed it takes a really long time, you were asked to look at the reason why queries are running slow and identify steps to improve the performance and when you looked at it you noticed all the code queries are running sequentially and using a SQL endpoint cluster. Which of the following steps can be taken to resolve the issue?
Here is the example query
1.--- Get order summary
2.create or replace table orderssummary
3.as
4.select productid, sum(ordercount) ordercount
5.from
6. (
7. select productid,ordercount from ordersinstore
8. union all
9. select productid,ordercount from ordersonline
10. )
11.group by productid
12.-- get supply summary
13.create or repalce tabe supplysummary
14.as
15.select productid, sum(supplycount) supplycount
16.from supply
17.group by productid
18.
19.-- get on hand based on orders summary and supply summary
20.
21.with stockcte
22.as (
23.select nvl(s.productid,o.productid) as productid,
24. nvl(supplycount,0) - nvl(ordercount,0) as onhand
25.from supplysummary s
26.full outer join orderssummary o
27. on s.productid = o.productid
28.)
29.select *
30.from
31.stockcte
32.where on_hand = 0

• A. Turn on the Auto Stop feature for the SQL endpoint.
• B. Turn on the Serverless feature for the SQL endpoint.
• C. Turn on the Serverless feature for the SQL endpoint and change the Spot Instance Pol-icy to "Reliability Optimized."
• D. Increase the maximum bound of the SQL endpoint's scaling range.
• E. Increase the cluster size of the SQL endpoint.

Answer: E Explanation:
Explanation
The answer is to increase the cluster size of the SQL Endpoint, here queries are running sequentially and since the single query can not span more than one cluster adding more clusters won't improve the query but rather increasing the cluster size will improve performance so it can use additional compute in a warehouse.
In the exam please note that additional context will not be given instead you have to look for cue words or need to understand if the queries are running sequentially or concurrently. if the que-ries are running sequentially then scale up(more nodes) if the queries are running concurrently (more users) then scale out(more clusters).
Below is the snippet from Azure, as you can see by increasing the cluster size you are able to add more worker nodes.

SQL endpoint scales horizontally(scale-out) and vertically (scale-up), you have to understand when to use what.
Scale-up-> Increase the size of the cluster from x-small to small, to medium, X Large....
If you are trying to improve the performance of a single query having additional memory, additional nodes and cpu in the cluster will improve the performance.
Scale-out -> Add more clusters, change max number of clusters
If you are trying to improve the throughput, being able to run as many queries as possible then having an additional cluster(s) will improve the performance.
SQL endpoint
A picture containing diagram Description automatically generated

NEW QUESTION # 202
Below sample input data contains two columns, one cartId also known as session id, and the second column is called items, every time a customer makes a change to the cart this is stored as an array in the table, the Marketing team asked you to create a unique list of item's that were ever added to the cart by each customer, fill in blanks by choosing the appropriate array function so the query produces below expected result as shown below.
Schema: cartId INT, items Array<INT>
Sample Data

1.SELECT cartId, ___ (___(items)) as items
2.FROM carts GROUP BY cartId
Expected result:
cartId items
1 [1,100,200,300,250]

• A. ARRAYUNION, COLLECTSET
• B. ARRAYUNION, ARRAYDISTINT
• C. ARRAYDISTINCT, ARRAYUNION
• D. FLATTEN, COLLECT_UNION
• E. ARRAY_UNION, FLATTEN

Answer: A Explanation:
Explanation
COLLECT SET is a kind of aggregate function that combines a column value from all rows into a unique list ARRAY_UNION combines and removes any duplicates, Graphical user interface, application Description automatically generated with medium confidence

NEW QUESTION # 203
The data engineering team is looking to add a new column to the table, but the QA team would like to test the change before implementing in production, which of the below options allow you to quickly copy the table from Prod to the QA environment, modify and run the tests?

• A. SHADOW CLONE
• B. DEEP CLONE
• C. METADATA CLONE
• D. ZERO COPY CLONE
• E. SHALLOW CLONE

Answer: E Explanation:
Explanation
The answer is SHALLOW CLONE
SHALLOW CLONE If you wish to create a copy of a table quickly to test out applying changes without the risk of modifying the current table, SHALLOW CLONE can be a good option. Shallow clones just copy the Delta transaction logs, meaning that the data doesn't move so it can be very quick.
1.CREATE OR REPLACE TABLE {newtablename} SHALLOW CLONE
{sourcetablename}|[LOCATION path]
DEEP CLONE fully copies data and metadata from a source table to a target. This copy occurs incre-mentally, so executing this command again can sync changes from the source to the target location. It copies all of the data and transaction logs this can take a long time based on the size of the table.
1.CREATE OR REPLACE TABLE {newtablename} DEEP CLONE {sourcetablename}|[LOCATION path]
NEW QUESTION # 204
A data engineer has three notebooks in an ELT pipeline. The notebooks need to be executed in a specific order
for the pipeline to complete successfully. The data engineer would like to use Delta Live Tables to manage this
process.
Which of the following steps must the data engineer take as part of implementing this pipeline using Delta
Live Tables?

• A. They need to create a Delta Live tables pipeline from the Compute page
• B. They need to create a Delta Live Tables pipeline from the Data page
• C. They need to refactor their notebook to use SQL and CREATE LIVE TABLE keyword
• D. They need to create a Delta Live Tables pipeline from the Jobs page
• E. They need to refactor their notebook to use Python and the dlt library

Answer: D
NEW QUESTION # 205
Unity catalog helps you manage the below resources in Databricks at account level

• A. All of the above
• B. Tables
• C. Meta Stores and Catalogs
• D. Dashboards
• E. ML Models

Answer: A Explanation:
Explanation
The answer is all of the above.
Unity Catalog is a unified governance solution for all data and AI assets including files, tables, machine learning models, and dashboards in your lakehouse on any cloud.
NEW QUESTION # 206
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