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Quiz
Question 1/101/10
A MongoDB data modeler is designing a system for a blogging platform where articles can receive
comments and be tagged with multiple categories. To ensure efficient retrieval of articles by category
and manage comments in a scalable way, which design pattern should the data modeler implement?
Select the answer:Select the answer
1 correct answer
A.
Apply the Outlier Pattern, storing most comments within the article document and exceptionally long
or numerous comments in a separate collection.
B.
Store articles and comments in the same document, using an array for comments and another array
for categories.
C.
Implement the Bucket Pattern by grouping comments into buckets within each article document and
categorize articles using a separate collection.
D.
Use separate collections for articles, comments, and categories, linking them through reference IDs.
Apply the Outlier Pattern, storing most comments within the article document and exceptionally long or
numerous comments in a separate collection. -> Correct. This pattern optimizes for the common case
where articles have a manageable number of comments, while still accommodating outliers without
impacting the document size limit.
Store articles and comments in the same document, using an array for comments and another array for
categories. -> Incorrect. This could lead to document growth issues and potentially hit the BSON
document size limit if an article receives a large number of comments.
Use separate collections for articles, comments, and categories, linking them through reference IDs. ->
Incorrect. While this maintains data normalization, it could increase the complexity of queries and affect
performance due to the need for multiple joins.
Implement the Bucket Pattern by grouping comments into buckets within each article document and
categorize articles using a separate collection. -> Incorrect. The Bucket Pattern is efficient for managing
growing arrays like comments, but using a separate collection for categories might not be necessary.
Right Answer: A
Quiz
Question 2/102/10
A data modeler is tasked with designing a database for a movie streaming service. The database needs
to efficiently store and retrieve information about movies, including the movie's title, director, genre(s),
release year, and average viewer rating. How should the data modeler structure the Movie entity?
Select the answer:Select the answer
1 correct answer
A.
Model Movie as a movie's title, director, genre(s), release year, average viewer rating, and the total
number of viewers.
B.
Model Movie as a movie's title, director, and genre(s).
C.
Model Movie as a movie's title, director, genre(s), release year, and average viewer rating.
D.
Model Movie as the movie's title only.
Model Movie as a movie's title, director, genre(s), release year, and average viewer rating. -> Correct. It
includes all the necessary attributes to efficiently store and retrieve information about movies without
including unnecessary data that can be stored separately if needed.
Model Movie as a movie's title, director, genre(s), release year, average viewer rating, and the total
number of viewers. -> Incorrect. The total number of viewers is a dynamic attribute that can significantly
fluctuate, which might not be necessary for the primary model of the Movie entity and could be stored
separately for scalability.
Model Movie as the movie's title only. -> Incorrect. This does not include other critical information about
the movie that the streaming service needs to store and retrieve, such as director, genre(s), release
year, and average viewer rating.
Model Movie as a movie's title, director, and genre(s). -> Incorrect. It omits some important attributes like
release year and average viewer rating, which are essential for users to make informed viewing choices.
Right Answer: C
Quiz
Question 3/103/10
In a MongoDB database, a query frequently sorts documents based on two fields, createdAt (a
timestamp) and priority (an integer representing the item's urgency), to fulfill a reporting requirement.
This query is critical for daily operations. You notice that the query performance is suboptimal, and upon
reviewing the query plan, you observe that MongoDB is not using an index for sorting. Which of the
following actions would most effectively optimize the query performance?
Select the answer:Select the answer
1 correct answer
A.
Use a compound index that includes both createdAt and priority fields in the same order as they
appear in the sort clause.
B.
Create separate single field indexes on both createdAt and priority.
C.
Increase the RAM of the MongoDB server to ensure that all indexes fit into memory.
D.
Remove all existing indexes on the collection to reduce the overhead of index maintenance.
Use a compound index that includes both createdAt and priority fields in the same order as they appear
in the sort clause. -> Correct. A compound index that matches the sort order of the query can greatly
improve performance by allowing MongoDB to use the index for both filtering and sorting operations.
This minimizes the number of documents MongoDB has to examine and sort in memory, leading to
faster query execution.
Create separate single field indexes on both createdAt and priority. -> Incorrect. While single field
indexes could potentially improve performance for queries filtering on these fields individually, they
wouldn't be as effective for optimizing a sort operation that includes both fields. MongoDB can only use
one index per query for sorting, so separate indexes would not optimize a sort on both fields together.
Increase the RAM of the MongoDB server to ensure that all indexes fit into memory. -> Incorrect. While
having sufficient RAM for indexes to fit into memory is important for overall performance, simply
increasing RAM does not directly address the inefficiency of the sorting operation in the query. The
underlying issue is the lack of an appropriate index for the sort.
Remove all existing indexes on the collection to reduce the overhead of index maintenance. -> Incorrect.
Removing indexes might reduce the overhead of maintaining those indexes during write operations, but
it would also degrade read and sort operation performance. This approach would likely worsen the
performance of the query in question.
Right Answer: A
Quiz
Question 4/104/10
An e-commerce company is redesigning its product catalog database to improve the user experience by
enhancing the speed of product searches and the display of product details, which include descriptions,
images, and customer reviews. How should the developer design the schema to optimize for both query
performance and scalability?
Select the answer:Select the answer
1 correct answer
A.
Apply the Reference Pattern, storing the core product details in one collection and references to
separate collections for images and reviews, optimizing for write efficiency.
B.
Utilize the Pre-Aggregation Pattern, periodically aggregating product data and reviews into summary
documents for quick access, while storing detailed information in separate collections.
C.
Maintain separate collections for product descriptions, images, and customer reviews, linking them
by productId, to facilitate easier updates and scaling.
D.
Combine product descriptions, images, and customer reviews into a single document for each
product, enabling rapid retrieval with a single query.
Combine product descriptions, images, and customer reviews into a single document for each product,
enabling rapid retrieval with a single query. -> Correct. Embedding product descriptions, images, and
customer reviews in a single document per product ensures that all relevant information can be
accessed through a single database query, significantly improving read performance which is critical for
a smooth user experience in an e-commerce platform.
Maintain separate collections for product descriptions, images, and customer reviews, linking them by
productId, to facilitate easier updates and scaling. -> Incorrect. While maintaining separate collections
can facilitate easier updates and scaling, it would require multiple queries to assemble complete product
details, potentially slowing down the user experience.
Utilize the Pre-Aggregation Pattern, periodically aggregating product data and reviews into summary
documents for quick access, while storing detailed information in separate collections. -> Incorrect. The
Pre-Aggregation Pattern can improve access to frequently needed summary information but might not
always provide the most up-to-date details or efficiently support dynamic queries that e-commerce
platforms often require.
Apply the Reference Pattern, storing the core product details in one collection and references to
separate collections for images and reviews, optimizing for write efficiency. -> Incorrect. The Reference
Pattern optimizes for scenarios where write operations are more common than reads. However, in an e-
commerce context, where fast reads are crucial for displaying product details, this approach could lead
to slower performance due to the need for multiple queries to resolve references.
Right Answer: D
Quiz
Question 5/105/10
In designing a database schema for a MongoDB application that handles user-generated content, such
as posts and comments, a data modeler is considering the most efficient way to store comments related
to each post to optimize read operations, as the application experiences significantly more reads than
writes. The application requires frequent retrieval of posts along with their associated comments. What
pattern should the data modeler use to store comments in relation to posts, and why?
Select the answer:Select the answer
1 correct answer
A.
Subset Pattern
B.
Normalized Pattern
C.
Embedded Pattern
D.
Bucket Pattern
E.
Reference Pattern
Embedded Pattern -> Correct. Ensures that posts and their comments are retrieved in a single operation,
significantly optimizing read performance.
Reference Pattern -> Incorrect. Increases read operations due to the necessity of additional queries for
comments, not the most efficient for read-heavy applications.
Bucket Pattern -> Incorrect. More suitable for time-series data, not directly optimal for associating
comments with posts in a way that optimizes read operations.
Subset Pattern -> Incorrect. Offers a compromise between embedded and reference patterns but may
face limitations with large numbers of comments.
Normalized Pattern -> Incorrect. Increases the complexity of queries and the number of read operations,
which is less desirable for read-heavy applications using NoSQL databases like MongoDB.
Right Answer: C
Quiz
Question 6/106/10
In a MongoDB-based inventory system, a requirement necessitates the simultaneous decrement of a
product's quantity in the products collection and the insertion of a sale record in the sales collection. If
the operation on either collection fails, both operations should be reversed to maintain data integrity.
What action should be taken to fulfill this requirement?
Select the answer:Select the answer
1 correct answer
A.
Start a transaction, use the updateOne() method to decrement the quantity in the products collection
and the insertOne() method for the sales collection, then execute commitTransaction().
B.
Use the updateMany() and insertMany() methods for both collections within a transaction, followed
by an immediate endSession() call.
C.
Independently execute updateOne() for the products collection and insertOne() for the sales
collection without transactions.
D.
Perform a updateOne() on the products collection to decrement quantity, followed by insertOne() on
the sales collection, both outside of a transaction context.
Start a transaction, use the updateOne() method to decrement the quantity in the products collection and
the insertOne() method for the sales collection, then execute commitTransaction(). -> Correct.
Encapsulating both operations within a transaction and committing with commitTransaction() ensures
atomicity. If one operation fails, the transaction can be aborted, preserving data consistency.
Independently execute updateOne() for the products collection and insertOne() for the sales collection
without transactions. -> Incorrect. Without using transactions, the operations are not atomic. If one fails,
the other would not be automatically reverted, leading to potential data inconsistency.
Use the updateMany() and insertMany() methods for both collections within a transaction, followed by an
immediate endSession() call. -> Incorrect. Ending the session with endSession() without explicitly
committing the transaction with commitTransaction() does not ensure the changes are saved. The
operations might not be applied if the transaction is not committed.
Perform a updateOne() on the products collection to decrement quantity, followed by insertOne() on the
sales collection, both outside of a transaction context. -> Incorrect. Executing these operations outside of
a transaction does not offer atomicity. If one operation fails, it does not guarantee the rollback of the
other, risking data integrity.
Right Answer: A
Quiz
Question 7/107/10
In a blogging application, each Article entity is associated with multiple Comment entities. To optimize
query performance for displaying articles along with their comments on a webpage, how should the
developer model this relationship?
Select the answer:Select the answer
1 correct answer
A.
Reference each Comment in an array within the Article document.
B.
Embed Comment documents directly within an Article document as an array of subdocuments.
C.
Store each Comment as a separate document with a field linking to its Article.
D.
Create a separate collection to store both Article and Comment entities together without
distinguishing between them.
Embed Comment documents directly within an Article document as an array of subdocuments. ->
Correct. Embedding comments within an article ensures that data that is accessed together is stored
together, reducing the need for multiple queries and optimizing read performance.
Reference each Comment in an array within the Article document. -> Incorrect. While this approach
maintains a relationship, it does not optimize for reading data that is accessed together by requiring
additional queries to fetch comments.
Store each Comment as a separate document with a field linking to its Article. -> Incorrect. This
approach separates data that is frequently accessed together, leading to multiple query operations to
retrieve a single article and its comments.
Create a separate collection to store both Article and Comment entities together without distinguishing
between them. -> Incorrect. This approach would complicate the retrieval, update, and deletion of
articles and comments due to the lack of a clear structure differentiating the two types of entities.
Right Answer: B
Quiz
Question 8/108/10
In a content management system (CMS) for a news website, articles are frequently accessed with their
associated comments. Given the high volume of comments and the need for efficient article retrieval,
how should the data model be designed to optimize read operations while considering the trade-offs
between embedding and referencing?
Select the answer:Select the answer
1 correct answer
A.
Store comments and articles in the same document.
B.
Use a hybrid model, embedding recent comments in the article document and referencing older
comments.
C.
Reference comments in articles using an array of comment IDs.
D.
Embed all comments within their respective article documents.
Use a hybrid model, embedding recent comments in the article document and referencing older
comments. -> Correct. The hybrid model offers a balanced approach, enabling efficient access to recent
comments while avoiding the large document size issue by referencing older comments. This method
provides fast access to the most relevant comments without compromising performance.
Embed all comments within their respective article documents. -> Incorrect. While embedding comments
provides fast read access to articles and their comments, it could lead to document size exceeding the
MongoDB document size limit, especially for articles with a very high number of comments.
Reference comments in articles using an array of comment IDs. -> Incorrect. This approach avoids large
document sizes but requires additional queries to fetch comments, potentially reducing read efficiency
for articles and their associated comments.
Store comments and articles in the same document. -> Incorrect. Storing all comments and articles in a
single document would significantly increase document size, risking exceeding the MongoDB document
size limit and making updates inefficient.
Right Answer: B
Quiz
Question 9/109/10
A developer is optimizing a MongoDB database for an e-commerce application that requires efficient
retrieval of product information based on various attributes, including category, price range, and ratings.
The database needs to support high read volumes with minimal impact on performance. Which of the
following indexing strategies would best support this requirement?
Select the answer:Select the answer
1 correct answer
A.
Individual indexes on category, price, and ratings.
B.
A compound index on category, price, and ratings.
C.
A geospatial index on the storeLocation field to optimize all queries.
D.
A text index on the description field to support all query patterns.
A compound index on category, price, and ratings. -> Correct. This strategy supports queries filtered by
these attributes in combination, providing efficient retrieval by using a single index for common query
patterns.
Individual indexes on category, price, and ratings. -> Incorrect. While this approach offers flexibility, it
may not be as efficient for queries that filter on multiple attributes simultaneously, potentially leading to
less optimal query performance due to the database having to scan multiple indexes.
A text index on the description field to support all query patterns. -> Incorrect. Text indexes are designed
for full-text search in text content and are not optimized for queries based on numerical ranges or exact
matches of category names.
A geospatial index on the storeLocation field to optimize all queries. -> Incorrect. Geospatial indexes are
designed to optimize queries that involve geographical location data. While useful for location-based
queries, they do not directly address the requirement to efficiently filter by category, price, and ratings.
Right Answer: B
Quiz
Question 10/1010/10
In developing a MongoDB schema for a vehicle tracking system that monitors and records data on
vehicles, trips, and locations in real-time, you are challenged to design a schema that optimizes the
storage and retrieval of data for real-time monitoring, historical trip analysis, and vehicle management.
The system needs to handle frequent updates for vehicle locations, efficiently query trip histories by
vehicle, and support CRUD operations for vehicle information. Considering the high-velocity data
ingestion and the need for efficient data retrieval, what schema design best accommodates these
requirements?
Select the answer:Select the answer
1 correct answer
A.
Embed trip and location data within each vehicle document.
B.
Embed all trip data within vehicle documents, including locations as subdocuments of trips.
C.
Store each vehicle, trip, and location as separate documents within their respective collections,
linking them with references.
D.
Embed location data within trip documents and reference trips from vehicle documents.
Store each vehicle, trip, and location as separate documents within their respective collections, linking
them with references. -> Correct. This approach offers flexibility in managing high-velocity data updates
and efficient querying by segregating high-frequency update data (locations) from less frequently
updated data (vehicles, trips), allowing for optimized performance in both real-time updates and historical
data analysis.
Embed trip and location data within each vehicle document. -> Incorrect. While embedding could
potentially reduce read operations for fetching a vehicle's trip history, this approach may lead to large
documents and hinder performance due to the frequent location updates.
Embed location data within trip documents and reference trips from vehicle documents. -> Incorrect. This
partially embedded design simplifies querying trip histories with locations but may not efficiently handle
the real-time update load for locations, potentially impacting the system's performance.
Embed all trip data within vehicle documents, including locations as subdocuments of trips. -> Incorrect.
This approach would likely result in very large documents due to the volume of location updates, which
could degrade performance, especially for write operations and when querying for specific trip details or
historical analysis.
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