C100DBA Practice Test 10 — 10 Questions

Question 1

A global IoT platform ingests sensor readings from millions of devices. The team must choose a database that can store semi-structured data, scale horizontally, and provide high write throughput. Which TWO MongoDB features directly support these requirements? (Choose two.)

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Sharding with a well-chosen shard key. Sharding distributes data across shards for horizontal scale and high write throughput, while the dynamic schema accommodates heterogeneous sensor payloads without migrations. Together, these features address the platform's need to ingest semi-structured data from millions of devices and scale out as volume grows.

Answer

Mandatory multi-document ACID transactions for every insert

Answer

Strict table-level locking for all write operations

Answer

Automatic sharding based on the first field alphabetically

Question 2

A DBA is troubleshooting a sharded cluster where the balancer is not migrating chunks even though there is an imbalance. The DBA runs `sh.getBalancerState()` and it returns `true`. Which of the following is the most likely reason the balancer is not migrating chunks?

Accepted Answer

The balancer window is configured to a time period outside of the current time.. The balancer only runs during the configured balancing window. Even if `sh.getBalancerState()` returns `true`, migrations will not occur outside that window. The DBA should check the balancer window settings and ensure they align with the desired migration times. Other options would either cause broader failures or are not relevant to the balancer's operation.

Answer

The config servers are in a read-only state.

Answer

The collection has no indexes on the shard key, so the balancer cannot identify chunks to migrate.

Answer

The shard key is hashed, and hashed shard keys prevent the balancer from migrating chunks.

Question 3

A DBA observes that a query with filter { a: 5, b: { $gt: 10 } } and sort { c: 1 } is using a collection scan despite the existence of an index { a: 1, b: 1, c: 1 }. The DBA wants to improve performance. Which action is most likely to allow the index to support both the filter and the sort?

Accepted Answer

Create a new index { a: 1, c: 1, b: 1 } so that the sort field c comes before the range field b.. The index { a: 1, b: 1, c: 1 } cannot support the sort on c because b is a range predicate, which means the index order after the equality on a is determined by b, not c. To support both the filter and the sort, the index should be reordered so that the sort field c follows the equality field a, and the range field b comes last. The index { a: 1, c: 1, b: 1 } allows the equality on a to bound the prefix, then the sort on c to be satisfied by the index order, and finally the range on b to be applied as an index filter.

Answer

Create a partial index on { a: 1, b: 1, c: 1 } with a filter on b > 10, which will allow the sort to use the index.

Answer

Add a separate index on { c: 1 } and rely on the query planner to perform an index intersection with the existing index.

Answer

Modify the query to remove the range condition on b, so the existing index can support the sort on c.

Question 4

A developer is using the MongoDB Node.js driver and wants to ensure that a write operation is acknowledged by a majority of replica set members and is also written to the on-disk journal before returning success. Which write concern should be specified?

Accepted Answer

{ w: "majority", j: true }. The developer needs both majority acknowledgment and journaling. The write concern { w: "majority", j: true } ensures that a majority of replica set members have applied the write and that it has been written to the on-disk journal on those members. This provides the strongest durability guarantee, preventing data loss even if the primary crashes. Other options either lack majority acknowledgment or journaling.

Answer

{ w: 2, j: true }

Answer

{ w: 1, j: true }

Answer

{ w: "majority", j: false }

Question 5

A DBA is configuring a replica set with three members: one primary and two secondaries. The DBA wants to ensure that a write concern of { w: 'majority' } is acknowledged only after the write has been applied to a majority of voting members and has been written to the on-disk journal on those members. Which write concern should the DBA use?

Accepted Answer

{ w: 'majority', j: true }. The requirement is for a write concern that ensures acknowledgment after a majority of voting members have applied the write and written it to the on-disk journal. The write concern { w: 'majority', j: true } achieves both: w: 'majority' dynamically requires a majority of voting members, and j: true forces journaling on those members before acknowledgment. Using a fixed w: 2 may not adapt to membership changes, and omitting j: true does not guarantee journaling. (Explanation length: 65 words)

Answer

{ w: 'majority' }

Answer

{ w: 2, j: true }

Answer

{ w: 'majority', j: false }

Question 6

A financial application requires that read operations never return data that could later be rolled back, even if it means reading from a secondary. The application connects to a replica set with readPreference=secondary. Which read concern level should be used to guarantee that the data read has been acknowledged by a majority of replica set members and cannot be rolled back?

Accepted Answer

readConcern: { level: "majority" }. majority read concern guarantees that the data read has been acknowledged by a majority of replica set members, making it durable and not subject to rollback. It can be used with readPreference=secondary, allowing the application to read from secondaries while still ensuring that the data is majority-committed. linearizable is stronger but only works with primary reads.

Answer

readConcern: { level: "local" }

Answer

readConcern: { level: "available" }

Answer

readConcern: { level: "linearizable" }

Question 7

You are maintaining an inventory collection where each document has a field named `stock` (integer). A nightly job needs to atomically decrement `stock` by 1 for the document with `sku: "A100"` and also insert the current timestamp into a `lastUpdated` field in the same operation, without overwriting any other fields. Which update operation should you use?

Accepted Answer

db.inventory.updateOne({ sku: "A100" }, { $inc: { stock: -1 }, $currentDate: { lastUpdated: true } }). The $inc operator atomically increments or decrements a field by a specified amount, and $currentDate sets a field to the current date/time. Combining them in a single updateOne call ensures both modifications happen atomically on the matched document without altering other fields. This directly satisfies the need to decrement stock and add a timestamp in one operation.

Answer

db.inventory.replaceOne({ sku: "A100" }, { stock: 0, lastUpdated: new Date() })

Answer

db.inventory.updateOne({ sku: "A100" }, { $set: { stock: stock - 1, lastUpdated: true } })

Answer

db.inventory.updateMany({ sku: "A100" }, { $inc: { stock: -1 }, $set: { lastUpdated: new Date() } })

Question 8

A DBA needs a query that returns only the fields name and email from a 'users' collection, filtered by an equality on email, to avoid fetching full documents from disk. Which index design supports this efficiently?

Accepted Answer

A compound index { email: 1, name: 1 } so the query can be covered by the index.. A covered query is one whose filter and projection are both satisfied by the index, so no document fetch is needed. Including every projected field in the index, as with { email: 1, name: 1 }, lets the engine return results straight from index keys. Single-field, hashed, and text indexes cannot supply the projected name field, so they cannot cover this query.

Answer

A single-field index on email, relying on the query's projection to fetch name from the document.

Answer

A text index on name and email to cover both fields.

Answer

A hashed index on email to speed equality matching.

Question 9

A DBA needs to grant a new application service account the ability to read and write data in any database except the admin database on a MongoDB 6.0 replica set. The account should not be able to perform administrative actions such as managing users or shutting down the server. Which built-in role should the DBA assign?

Accepted Answer

readWriteAnyDatabase. The readWriteAnyDatabase built-in role provides read and write access to all non-system databases without granting administrative privileges. It is the least-privilege role that satisfies the requirement. The other roles either grant excessive privileges, are scoped to a single database, or do not provide the needed access across all application databases.

Answer

root

Answer

dbOwner on each application database

Answer

readWrite on the admin database

Question 10

A MongoDB application requires that reads never see data that could be rolled back, even in the event of a replica set failover. The application also needs to read from secondary nodes to distribute load. Which read concern should be used with a secondary read preference?

Accepted Answer

"majority". The application needs to read from secondaries while ensuring that the data returned is not subject to rollback. "majority" read concern guarantees that the data has been acknowledged by a majority of replica set members, making it durable across failover. It is compatible with secondary read preferences, unlike "linearizable", which requires primary reads. Therefore, "majority" is the correct choice.

Answer

"linearizable"

Answer

"available"

Answer

"local"