C100DBA Practice Exam 3 — 20 Questions

Question 1

Which THREE components are mandatory architectural parts of every fully functioning MongoDB sharded cluster deployment? Choose 3 answers.

Accepted Answer

A config server replica set that stores all cluster metadata, chunk ranges, and routing configuration data.. A sharded cluster relies on three core functional components: config servers to maintain cluster metadata, mongos query routers to direct client requests, and shard replicas to store partitioned data safely. Knowing these architecture requirements helps administrators design resilient, highly available production clusters with proper redundancy at every layer of the infrastructure.

Answer

A dedicated primary balancer coordinator node running outside the config server replica set to manage migrations.

Answer

An independent Apache ZooKeeper quorum cluster to coordinate distributed locking across all participating mongod nodes.

Question 2

An application serves users in Europe and North America. The DBA wants to ensure that European user data stays on shards located in Europe to comply with data residency laws. Which feature should be used?

Accepted Answer

Zones and Zone Ranges.. Zones (formerly known as tag-aware sharding) allow administrators to associate specific shard key ranges with particular shards. By tagging shards with geographical identifiers and defining zones for ranges of the shard key, the balancer will automatically move data to the appropriate physical location. This is essential for meeting regulatory requirements and reducing latency.

Answer

Replica set tags for read preferences.

Answer

Hashed sharding with a geo-spatial index.

Answer

The movePrimary command for each database.

Question 3

Which command is used to verify the current replica set configuration and the state of all members?

Accepted Answer

rs.status(). Checking the replica set status is a routine administrative task to ensure high availability and data consistency. The 'rs.status()' command provides a comprehensive view of the cluster, including the state of every member, the current primary, and the sync lag. This command is the primary diagnostic tool for verifying that the replica set is healthy and that all nodes are correctly communicating with each other.

Answer

db.serverStatus()

Answer

rs.conf()

Answer

db.isMaster()

Question 4

Refer to the exhibit. The explain output shows a SORT stage wrapping an IXSCAN stage. What is the performance implication of this execution plan?

Accepted Answer

The query engine performed an in-memory sort because the index did not support the requested sort order.. When a SORT stage wraps an IXSCAN stage, it means the index used for filtering did not satisfy the sort requirement. The query engine had to load the matching documents into memory to sort them, risking memory limit exceptions on large result sets.

Answer

The query is fully optimized because it leverages an index scan for filtering records.

Answer

The query executed a full collection scan across all cluster nodes.

Answer

The storage engine automatically converted the query into a covered query.

Question 5

Which cursor method should you use to sort documents by a field named 'age' in descending order?

Accepted Answer

.sort({age: -1}). The sort() method is used to define the order of results returned by a query. Passing {age: -1} ensures that the documents are ordered from oldest to youngest. Mastering sorting is essential for returning data in a meaningful way to users, such as showing the most recent posts or the highest-rated products first, which are common requirements for almost all web and mobile applications.

Answer

.sort({age: 1})

Answer

.orderBy({age: 'desc'})

Answer

.order({age: 'desc'})

Question 6

How does the 'Replica Set' architecture influence client application design?

Accepted Answer

It enables read distribution across multiple nodes.. Replica sets require the driver to be aware of the topology to perform automatic discovery and routing. Since a replica set has a primary node for writes and multiple secondaries for reads, the application must manage read preferences and connection strings correctly. Understanding this architecture is crucial for writing resilient applications that can handle failover events without losing connection or experiencing data consistency issues during node promotions.

Answer

Applications must manually hardcode all secondary IP addresses.

Answer

It mandates that all reads must be 'strong' consistency.

Answer

It forces the application to implement custom failover logic.

Question 7

A financial services firm is migrating its reporting application from a relational database to MongoDB. The lead architect argues that MongoDB's schema-less design will eliminate the need for data modeling. Which statement best describes MongoDB's philosophy regarding schema design?

Accepted Answer

Schema design is still essential but is driven by application access patterns rather than normalization rules.. MongoDB's schema flexibility does not eliminate the need for data modeling; instead, it shifts the focus to designing documents that align with how the application reads and writes data. Embedding and referencing are chosen based on access patterns, not normalization rules. This approach optimizes performance and scalability while still requiring careful planning to avoid pitfalls like unbounded document growth.

Answer

Schema design is optional because MongoDB automatically infers and enforces relationships between collections.

Answer

Schema design should follow third normal form to minimize data duplication and ensure consistency.

Answer

Schema design is unnecessary because MongoDB validates all documents against a collection schema by default.

Question 8

A media company stores articles with nested comments and tags. The development team wants to retrieve an article along with its comments in a single database round trip. Which MongoDB philosophy supports this design?

Accepted Answer

Embedding related data within a single document. Embedding related data such as comments and tags within the article document allows the application to retrieve everything in one query. This reduces round trips and latency, directly supporting the team's goal of a single database call to render an article page.

Answer

Using a relational foreign key constraint between articles and comments

Answer

Storing comments as a comma-separated string in a single field

Answer

Normalizing comments into a separate collection with manual joins

Question 9

A healthcare analytics team stores patient records in MongoDB. Each record includes a nested array of vital sign readings, and the team frequently queries for patients whose latest blood pressure reading exceeds a threshold. They decide to store each reading as a separate document in a readings collection and reference the patient. Which MongoDB design philosophy does this decision contradict?

Accepted Answer

Data that is accessed together should be stored together.. The team's choice to reference readings instead of embedding them conflicts with the core MongoDB principle that related data accessed together should be stored together. Embedding the readings array within the patient document would allow a single query to retrieve the latest blood pressure without additional lookups, improving performance and simplifying application logic. This principle guides schema design for locality and efficiency.

Answer

Use server-side JavaScript for all data validation.

Answer

Store all data in a single collection to simplify sharding.

Answer

Normalize all data to the third normal form to eliminate redundancy.

Question 10

A social media platform uses MongoDB to store user posts. Each post document contains an array of comments. The platform's engineers notice that some posts have tens of thousands of comments, causing documents to approach the 16 MB size limit and degrading read performance. They want to redesign the schema to handle this growth while preserving the ability to retrieve a post with its most recent comments efficiently. Which approach best aligns with MongoDB's schema design philosophy?

Accepted Answer

Embed only the most recent comments in the post document and store older comments in a separate collection.. The hybrid approach of embedding recent comments and storing older ones separately aligns with MongoDB's philosophy of designing for the common access pattern while managing document growth. By keeping the post document small, reads remain fast, and the application can still retrieve older comments via a separate query when needed. This pattern is recommended for scenarios with unbounded arrays, balancing performance and scalability.

Answer

Store each comment as a separate document in the same collection and use a parent reference to link them to the post.

Answer

Increase the document size limit by configuring the storage engine to allow larger BSON documents.

Answer

Store all comments in a separate collection and use $lookup to join them when needed.

Question 11

A logistics company uses MongoDB to track shipments. Each shipment document includes a status field and an array of location updates. The company wants to ensure that when a shipment's status changes to "delivered," the corresponding location update is also recorded atomically. Which MongoDB feature best supports this requirement while adhering to the philosophy of document atomicity?

Accepted Answer

Single-document atomic operations. Single-document atomic operations allow multiple field updates within one document to be atomic, which is ideal when related data is embedded. By storing location updates within the shipment document, the company can atomically change the status and append a new location in one operation, ensuring consistency without multi-document transactions. This leverages MongoDB's core philosophy of designing documents to match access patterns and using document-level atomicity.

Answer

Write concern "majority"

Answer

Two-phase commit

Answer

Multi-document ACID transactions

Question 12

A DBA is troubleshooting a replica set where the secondary is consistently lagging behind the primary by several hours. The DBA notices that the secondary's optime is far behind the primary's optime, and the secondary's oplog window is only 1 hour. The primary has a heavy write workload. Which action should the DBA take to reduce the replication lag and prevent the secondary from falling off the oplog?

Accepted Answer

Scale the secondary vertically by adding more CPU, RAM, or faster disk I/O.. Replication lag is typically caused by the secondary's inability to apply oplog entries as quickly as the primary generates them. Improving the secondary's hardware resources—CPU, RAM, and especially disk I/O—increases its oplog application throughput, directly reducing lag. Increasing oplog size only buys time, and write concern does not affect replication speed.

Answer

Convert the secondary to an arbiter to reduce its workload.

Answer

Increase the write concern on the primary to ensure the secondary acknowledges writes.

Answer

Increase the size of the oplog on the primary and secondaries.

Question 13

You are the DBA for a MongoDB 6.0 replica set with three voting members: rs0-primary (priority 2), rs0-secondary-1 (priority 1), and rs0-secondary-2 (priority 1). The primary fails and is unavailable for an extended period. You need to ensure that rs0-secondary-1 is elected as the new primary instead of rs0-secondary-2. Which action should you take before the primary fails?

Accepted Answer

Set rs0-secondary-1's priority to 2 and rs0-secondary-2's priority to 0.5 using rs.reconfig().. Election priority determines which eligible secondary is most likely to win an election. By setting rs0-secondary-1's priority higher than rs0-secondary-2's, you make it the preferred candidate. Lowering rs0-secondary-2's priority to a non-zero value keeps it as a voting member but reduces its election chances. This approach is the standard way to control primary election outcomes in a MongoDB replica set without making a member unelectable.

Answer

Set rs0-secondary-1's hidden property to true and rs0-secondary-2's hidden property to false using rs.reconfig().

Answer

Set rs0-secondary-1's slaveDelay to 0 and rs0-secondary-2's slaveDelay to 3600 using rs.reconfig().

Answer

Set rs0-secondary-1's votes to 1 and rs0-secondary-2's votes to 0 using rs.reconfig().

Question 14

A sharded cluster has a collection sharded on `{ location: 1 }`. A query is executed with the filter `{ location: { $in: ["NY", "CA"] } }`. How does MongoDB route this query?

Accepted Answer

The query is routed to the shards that own chunks covering the values "NY" and "CA".. MongoDB's query router, mongos, can target queries that include the shard key, even with `$in`. It looks up the chunk ranges for the specified values and routes the query only to the shards that own those chunks. This is known as a targeted query and is efficient because it avoids contacting unnecessary shards.

Answer

The query is sent to all shards because `$in` cannot be targeted.

Answer

The query is routed to a random shard, and that shard forwards the request to the others as needed.

Answer

The query is routed to the primary shard for the database because `$in` is not a targeted operation.

Question 15

You are a MongoDB DBA and need to retrieve all documents from the 'products' collection where the 'price' field is greater than 100 and the 'category' is 'electronics'. Which query accomplishes this?

Accepted Answer

db.products.find({price: {$gt: 100}, category: 'electronics'}). The implicit AND by combining field conditions in a single query document is the standard way to match documents where multiple criteria must be true. Using $and explicitly is also valid but redundant. $or would match either condition, and .filter() is not a MongoDB method.

Answer

db.products.find({$or: [{price: {$gt: 100}}, {category: 'electronics'}]})

Answer

db.products.find({price: {$gt: 100}}).filter({category: 'electronics'})

Answer

db.products.find({$and: [{price: {$gt: 100}}, {category: 'electronics'}]})

Question 16

A MongoDB 6.0 replica set has a collection called orders with the default read concern. Users occasionally see an order document that still shows status "pending" even though a separate application thread just updated it to "shipped" and received an acknowledgment. The update used default write concern and targeted a single document by _id. Which read concern should you set on the read operation to guarantee the read returns data acknowledged by a majority of replica set members?

Accepted Answer

readConcern: "majority". The symptom is a stale read after an acknowledged single-document update in a replica set. Majority read concern ensures the read only returns data that a majority of members have acknowledged, so the newly committed "shipped" status becomes visible. Local and available provide no such guarantee, and snapshot is aimed at multi-document consistency rather than this single-document visibility problem.

Answer

readConcern: "snapshot"

Answer

readConcern: "available"

Answer

readConcern: "local"

Question 17

Refer to the exhibit. What philosophy regarding client connectivity does this log entry reflect?

Accepted Answer

MongoDB prioritizes universal language and driver support.. The log entry indicates that MongoDB accepts standard TCP connections from client applications. This reflects the philosophy of providing a simple, standard-based interface for developers. By using standard socket-based communication, MongoDB allows drivers to be implemented in virtually any programming language, enabling widespread compatibility and easy integration into diverse application ecosystems without requiring custom protocols or proprietary communication middleware for database interaction.

Answer

MongoDB uses a proprietary, non-standard transport protocol.

Answer

All clients must be authenticated via a central service.

Answer

The database requires persistent, long-lived connections.

Question 18

Which THREE of the following are core pillars of the MongoDB architecture?

Accepted Answer

Horizontal scalability through sharding.. MongoDB's architecture is built on the principles of horizontal scalability, high availability, and developer-focused data modeling. These pillars allow MongoDB to handle massive scale and fluctuating workloads efficiently. By integrating sharding for capacity, replication for reliability, and flexible schemas for agility, the system addresses the common limitations of static relational databases, offering a comprehensive platform for modern, distributed cloud-native applications that require both speed and robustness in dynamic environments.

Answer

Strict, static schema enforcement at the storage layer.

Answer

Global dependency on a single centralized primary node.

Question 19

An administrator needs to create a restricted user for a third-party monitoring tool. The user must be able to perform backups and monitor server status but cannot read actual document data. Which TWO built-in roles should be combined?

Accepted Answer

backup. MongoDB's Role-Based Access Control (RBAC) allows for granular permission management. The 'backup' role provides the necessary privileges to use tools like mongodump without granting general read access to all collections. The 'clusterMonitor' role allows the user to run commands like 'serverStatus' and 'top', which are essential for monitoring performance.

Answer

readAnyDatabase

Answer

dbAdmin

Answer

hostManager

Question 20

An application needs to update a user's balance. Which method ensures the operation is atomic for a single document?

Accepted Answer

Use the $inc operator with the updateOne method.. Atomic updates are a cornerstone of MongoDB's document model. Using update operators like $inc ensures that the update is performed in a single, atomic step at the document level. This prevents race conditions where two threads might attempt to update the same balance simultaneously, ensuring that data integrity is maintained without the need for manual locking mechanisms in the application layer.

Answer

Read the document, update the value in application code, and save the document.

Answer

Wrap the operation in a multi-document transaction every time.

Answer

Use a global application-level mutex lock before updating.