C100DEV Practice Test 3 — 25 Questions

Question 1

When designing a schema for a blog application, you need to store comments for posts. The comments grow indefinitely. Which approach is most effective for long-term scalability?

Accepted Answer

Use the Hybrid pattern for embedded and referenced comments.. The Hybrid pattern is best here. You embed the most recent comments (e.g., the last 10) directly within the post document to allow for fast initial page loads. Simultaneously, you store older comments in a separate collection with a reference to the post ID. This provides a balance between high-speed access for recent content and the ability to scale indefinitely without ever hitting the BSON size limit.

Answer

Embed all comments in the post document.

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Reference all comments in a separate collection.

Answer

Use the Attribute pattern for every comment.

Question 2

A developer wants to remove all documents from the 'logs' collection where the 'level' field equals 'debug'. The collection has an index on level. Which operation should be used, and what does it return?

Accepted Answer

deleteMany({ level: 'debug' }) returns a result whose deletedCount is the number of documents removed.. deleteMany with a filter removes all matching documents and reports how many were deleted via deletedCount. deleteOne only removes the first match, drop destroys the whole collection, and remove is deprecated. When a selective deletion is needed and the filter is indexed, deleteMany preserves unrelated documents and existing indexes.

Answer

drop() removes the collection and its index, which is the recommended way to clear matching documents.

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deleteOne({ level: 'debug' }) returns the number of documents removed.

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remove({ level: 'debug' }) is the modern method and returns a cursor of deleted documents.

Question 3

Refer to the exhibit. Why would an operation attempting to insert the document shown in the exhibit fail?

Accepted Answer

The field '$created' starts with a reserved character.. The document contains a field named '$created'. In MongoDB, field names starting with a '$' symbol are reserved for internal query operators. When the database engine parses a document, it interprets fields beginning with '$' as instructions rather than data fields. This naming conflict is a common trap for developers migrating legacy data or building generic metadata structures without validating field name constraints.

Answer

The '_id' field is invalid.

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The field 'metadata' is a reserved keyword.

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The value 'null' is not allowed for the 'last_login' field.

Question 4

You are designing an e-commerce catalog where products can have a dynamic array of tags. You need to query for documents where the 'tags' array contains both 'electronics' and 'sale' simultaneously, regardless of their order or other elements. Which query operator should you use?

Accepted Answer

{ tags: { $all: ['electronics', 'sale'] } }. The $all operator selects the documents where the value of a field is an array that contains all the specified elements. This is essential when searching arrays for multiple matching criteria without enforcing strict positional indexing or exact array equality.

Answer

{ tags: { $in: ['electronics', 'sale'] } }

Answer

{ tags: ['$electronics', '$sale'] }

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{ tags: { $elemMatch: { $eq: 'electronics', $eq: 'sale' } } }

Question 5

Which schema pattern is demonstrated in the exhibit provided?

Accepted Answer

The Embedding Pattern.. The exhibit shows an array of sub-documents nested directly within a parent document, which is the definition of the embedding pattern. This pattern is used to keep related data together in one physical storage unit. It is highly efficient for read-heavy applications where the parent user record and their order history are almost always required at the same time by the application layer.

Answer

The Linking Pattern.

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The Polymorphic Pattern.

Answer

The Computed Pattern.

Question 6

When using the MongoDB C#/.NET driver, which object is essential for managing the scope and lifecycle of a multi-document transaction?

Accepted Answer

IClientSessionHandle. In the .NET driver, the 'IClientSessionHandle' object is used to represent a session that controls the lifecycle of a transaction. By using the 'StartTransaction' method on this session object, developers can encapsulate multiple operations within a single, atomic unit of work. This session handle is passed to every database operation within the transaction, ensuring that all actions are associated with the correct transactional scope and are properly committed or aborted.

Answer

IMongoDatabase

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MongoClient

Answer

IMongoCollection

Question 7

A MongoDB application stores inventory documents in the 'inventory' collection with fields 'sku', 'on_hand', and 'reserved'. During a flash sale, many concurrent sessions must decrement 'on_hand' by 1 only when on_hand is greater than 0, and each successful decrement must return the resulting document to the client. Which approach guarantees this behavior?

Accepted Answer

db.inventory.findOneAndUpdate({ sku: 'A100', on_hand: { $gt: 0 } }, { $inc: { on_hand: -1 } }, { returnDocument: 'after' }). findOneAndUpdate performs the conditional match, the $inc decrement, and the return of the document in one atomic operation. The on_hand: { $gt: 0 } filter guards against negative inventory under concurrency, and returnDocument: 'after' supplies the resulting state. Separating read and write, or using updateOne or bulkWrite, either introduces races or fails to return the document.

Answer

db.inventory.bulkWrite([{ updateOne: { filter: { sku: 'A100', on_hand: { $gt: 0 } }, update: { $inc: { on_hand: -1 } } } }])

Answer

db.inventory.find({ sku: 'A100', on_hand: { $gt: 0 } }) followed by db.inventory.updateOne({ sku: 'A100' }, { $inc: { on_hand: -1 } })

Answer

db.inventory.updateOne({ sku: 'A100', on_hand: { $gt: 0 } }, { $inc: { on_hand: -1 } }, { returnDocument: 'after' })

Question 8

A developer needs to perform a point-in-time backup of a MongoDB replica set while the database remains online and serving reads and writes. Which MongoDB Database Tool is designed for this task?

Accepted Answer

mongodump with --oplog. mongodump with --oplog is the MongoDB Database Tool that captures both data and oplog entries during a live dump, enabling point-in-time restore. It runs against a running replica set without downtime. mongoexport lacks oplog capture, mongorestore applies dumps rather than creating them, and mongostat is a monitoring tool, so none of those meet the backup requirement.

Answer

mongostat with --discover

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mongorestore with --archive

Answer

mongoexport with --query

Question 9

A developer wants to query MongoDB Atlas Search for documents where the 'description' field contains the phrase 'wireless headphones'. Which Atlas Search operator should be used to achieve this?

Accepted Answer

The phrase operator.. To search for an exact phrase in Atlas Search, the phrase operator is the correct choice. It ensures that the terms appear in the specified order and adjacent to each other. Other operators like text, wildcard, or compound serve different purposes and would not guarantee phrase matching.

Answer

The compound operator.

Answer

The wildcard operator.

Answer

The text operator.

Question 10

A social media platform stores posts in a collection named posts. Each post document contains an array field `comments`, where each comment is a subdocument with fields `user` and `text`. The development team needs to generate a report that lists each comment as a separate document, including the post's `_id` and the comment's `user` and `text`. Which aggregation stage should be used to achieve this?

Accepted Answer

$unwind. The $unwind stage is specifically designed to deconstruct an array field, outputting one document per array element. In this case, unwinding the `comments` array will produce a document for each comment, retaining the parent post's `_id`. This is the correct stage to flatten the comments array and meet the reporting requirement.

Answer

$project

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$replaceRoot

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$group

Question 11

An inventory system stores each product's supplier as an embedded subdocument containing the supplier name, address, and contact email. The supplier's address changes frequently, and updates now require scanning and updating thousands of product documents. Which data modeling change best resolves this maintenance problem?

Accepted Answer

Convert the supplier subdocument to a reference by storing the supplier's ObjectId in the product document and keeping supplier details in a suppliers collection.. Referencing is appropriate when a subdocument represents a shared entity that changes independently of its parent. Keeping supplier details in their own collection means one update fixes every product, removes duplicate mutable data, and keeps product documents lean. Indexing the embedded field, versioning the schema, or archiving supplier history all leave the core duplication and mass-update cost in place.

Answer

Add an index on the embedded supplier.address field so updates to that field become faster.

Answer

Move the supplier subdocument into an array field so all supplier versions are retained for auditing.

Answer

Use the Schema Versioning Pattern by adding a version field to each product document and migrating documents lazily.

Question 12

A development team is designing a schema for a chat application where each conversation contains messages that grow continuously. Messages are read in chronological order, and the application must display the most recent 50 messages quickly while retaining the full history. Which TWO design decisions best support these requirements? (Choose two.)

Accepted Answer

Embed only the most recent 50 messages in the conversation document and store the full history in a separate collection.. The requirements split into two needs: fast access to recent messages and complete retention of history. Referencing messages in a dedicated collection with an indexed timestamp satisfies retention and efficient recent-message queries, while the Subset Pattern's bounded embedded window gives the fastest possible read for the latest 50. Together they keep conversation documents small and preserve the full message log without hitting the 16MB limit.

Answer

Store each message as its own document in the conversations collection using a message-specific discriminator field.

Answer

Embed messages in the conversation document and rely on the 16MB limit to naturally cap growth.

Answer

Store all messages in a single capped collection so older messages are automatically overwritten.

Question 13

A developer needs to ensure that a `users` collection does not contain two documents with the same email address. Which index type should be created on the `email` field?

Accepted Answer

A unique index. To prevent duplicate email addresses, a unique index on the email field is required. Unique indexes enforce that each value appears at most once. Other index types like sparse, partial, or hashed do not provide this guarantee. A unique index is the correct choice to maintain data integrity for the email field.

Answer

A sparse index

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A partial index

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A hashed index

Question 14

A developer is using mongosh to connect to a MongoDB Atlas cluster and needs to run several administrative commands. The developer wants to ensure that the connection uses the correct authentication database and that all commands are executed with the appropriate read preference. Which mongosh command-line option should be used to specify the authentication database?

Accepted Answer

--authenticationDatabase. In mongosh, the --authenticationDatabase option explicitly sets the database used for authentication. This is necessary when user credentials reside in a database other than the default (often admin). Other options like --db or --readPreference affect connection behavior but not authentication. Specifying the correct authentication database ensures that the provided username and password are validated against the intended database.

Answer

--readPreference

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--username

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--db

Question 15

A developer is working with a MongoDB collection that stores user profiles. The collection has an index on the `email` field. The developer runs a query to find a user by email and then examines the query plan using `explain()`. The output shows that the query used an `IXSCAN` stage. What does this indicate about the query execution?

Accepted Answer

The query used the index to find the matching documents without scanning the entire collection.. The `IXSCAN` stage in the explain output signifies that MongoDB used an index scan to retrieve the documents matching the query. This is the expected behavior when querying on an indexed field like `email`. It means the query did not perform a full collection scan, which would be indicated by `COLLSCAN`. Using an index allows MongoDB to efficiently locate the relevant documents, reducing the number of documents examined and improving query performance.

Answer

The query returned all documents from the collection because the index was not selective.

Answer

The query used the index to sort the results but still had to scan the collection to filter documents.

Answer

The query performed a collection scan because no suitable index was found.

Question 16

A developer is using the MongoDB Node.js driver to insert a document into a collection. The document includes a field `_id` set to a custom string value. After the insert, the developer checks the returned result and notices that the `insertedId` matches the custom string. What does this indicate about MongoDB's handling of the `_id` field?

Accepted Answer

MongoDB automatically generates an ObjectId for the `_id` field if it is not provided, but if provided, it must be unique within the collection.. The `_id` field is the primary key for MongoDB documents. If omitted, the driver generates an ObjectId; if provided, it can be any BSON type except an array, but it must be unique within the collection. MongoDB automatically creates a unique index on `_id`. The scenario confirms that a custom string was accepted and used as the `_id`, demonstrating this flexibility.

Answer

The `_id` field is always an ObjectId and cannot be overridden with a custom value.

Answer

The `_id` field is only unique per shard, not across the entire collection.

Answer

MongoDB automatically indexes the `_id` field only if it is an ObjectId.

Question 17

A developer maintains a collection of sensor readings. Queries almost always filter on `status` and then sort by `timestamp` descending. The current index is { status: 1, timestamp: 1 }. The developer observes that the query planner selects a COLLSCAN even though the index covers both fields. Which index change should be made to allow an efficient index scan for this query?

Accepted Answer

Create a new index { status: 1, timestamp: -1 } and drop the existing index.. The query combines an equality predicate on `status` with a descending sort on `timestamp`. Following equality-sort-range ordering, the equality field belongs first and the sort field must match the query direction, giving `{ status: 1, timestamp: -1 }`. That lets the planner walk the index in the requested order without a blocking sort, which is why the reversed or split alternatives fail.

Answer

Add a separate index { timestamp: -1 } and keep the existing compound index.

Answer

Create a new index { timestamp: -1, status: 1 } and drop the existing index.

Answer

Create a hashed index on `status` combined with `timestamp` to improve selectivity.

Question 18

A developer is designing a collection to store catalog items. Different item categories have different attributes: books have 'isbn' and 'pageCount', while electronics have 'wattage' and 'warrantyMonths'. All items share '_id', 'name', 'price', and 'category'. Which data modeling approach best fits this requirement?

Accepted Answer

Store all items in one collection and include only the attributes relevant to each item's category.. The Polymorphic pattern stores documents with a shared core plus category-specific fields in one collection. It supports queries across all items using common fields and queries within a category using the discriminator field. This is the natural fit when different document shapes share a meaningful set of fields and are queried together.

Answer

Create one collection per category, such as 'books' and 'electronics', and never query across them.

Answer

Normalize all attributes into a separate 'attributes' collection referenced by item documents.

Answer

Store all category-specific attributes in a single 'attributes' array of key-value pairs for every item.

Question 19

A developer is designing a MongoDB collection to store blog posts. Each post document includes an array of comments, and each comment has fields such as 'author', 'text', and 'timestamp'. The developer wants to optimize for queries that retrieve posts along with their comments, and also wants to ensure that comments are stored efficiently. Which two of the following statements are true regarding the document model in this scenario? (Choose two.)

Accepted Answer

Embedding comments as an array within the post document allows retrieving the post and its comments in a single query.. Embedding comments within the post document allows retrieving the post and comments in one query, which is efficient for read-heavy access patterns. However, the 16MB document size limit must be considered if comments grow unbounded. The other statements are either incorrect or not directly related to the document model design in this scenario.

Answer

Storing comments in a separate collection and referencing them from the post document reduces data duplication.

Answer

Embedding comments always improves write performance because it requires only a single document update.

Answer

Using the $slice operator in a query can limit the number of comments returned from an embedded array.

Question 20

A developer is designing a MongoDB collection to store blog posts. Each post has a title, content, and an array of tags. The developer wants to ensure that the tags field is always an array of strings. Which BSON data type should be used for the tags field?

Accepted Answer

Array. MongoDB's document model supports arrays natively, allowing a field to hold multiple values. For a tags field that should contain multiple strings, the Array BSON type is the correct choice. It enables efficient querying (e.g., finding posts with a specific tag) and indexing (multikey indexes), and it aligns with the flexible schema design that MongoDB encourages.

Answer

Object

Answer

BinData

Answer

String