exam questions

Exam DP-201 All Questions

View all questions & answers for the DP-201 exam

Exam DP-201 topic 1 question 5 discussion

Actual exam question from Microsoft's DP-201
Question #: 5
Topic #: 1
[All DP-201 Questions]

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You are designing an Azure SQL Database that will use elastic pools. You plan to store data about customers in a table. Each record uses a value for
CustomerID.
You need to recommend a strategy to partition data based on values in CustomerID.
Proposed Solution: Separate data into customer regions by using horizontal partitioning.
Does the solution meet the goal?

  • A. Yes
  • B. No
Show Suggested Answer Hide Answer
Suggested Answer: B 🗳️
We should use Horizontal Partitioning through Sharding, not divide through regions.
Note: Horizontal Partitioning - Sharding: Data is partitioned horizontally to distribute rows across a scaled out data tier. With this approach, the schema is identical on all participating databases. This approach is also called ג€shardingג€. Sharding can be performed and managed using (1) the elastic database tools libraries or
(2) self-sharding. An elastic query is used to query or compile reports across many shards.
Reference:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-elastic-query-overview

Comments

Chosen Answer:
This is a voting comment (?). It is better to Upvote an existing comment if you don't have anything to add.
Switch to a voting comment New
Ankush1994
3 years, 9 months ago
Correct answer is No becuase Separate data into shards by using horizontal partitioning
upvoted 1 times
...
osoroshi
4 years, 3 months ago
harding can be performed and managed using (1) the elastic database tools libraries or (2) self-sharding. An elastic query is used to query or compile reports across many shards. Shards are typically databases within an elastic pool. You can think of elastic query as an efficient way for querying all databases of elastic pool at once, as long as databases share the common schema.
upvoted 1 times
...
redalarm2000
4 years, 4 months ago
Ok i am confused as to the difference between question 4 and question 5 on this site. Question 4 says to use horizontal partitioning but Question 5 says it recommends to use horizontal partition and the wording is the same but they say that answer should be No still why?
upvoted 2 times
Shanmahi
4 years, 4 months ago
Answer : No Applicable solution : Horizontal partitioning (based on customerID not region i.e. using sharding concept) Reference : https://docs.microsoft.com/en-us/azure/architecture/best-practices/data-partitioning
upvoted 6 times
...
...
fmunozse
4 years, 9 months ago
I don't understand why is not recommend horizontal ... Each shard could be the region, no?
upvoted 2 times
stijn5454
4 years, 9 months ago
Horizontal partitioning splits one or more tables by row, usually within a single instance of a schema and a database server. Sharding goes beyond this: it partitions the problematic table(s) in the same way, but it does this across potentially multiple instances of the schema. The obvious advantage would be that search load for the large partitioned table can now be split across multiple servers (logical or physical), not just multiple indexes on the same logical server. Ref: https://en.wikipedia.org/wiki/Shard_(database_architecture)#Shards_compared_to_horizontal_partitioning
upvoted 9 times
...
...
Community vote distribution
A (35%)
C (25%)
B (20%)
Other
Most Voted
A voting comment increases the vote count for the chosen answer by one.

Upvoting a comment with a selected answer will also increase the vote count towards that answer by one. So if you see a comment that you already agree with, you can upvote it instead of posting a new comment.

SaveCancel
Loading ...