C100DBA Practice Test 18 — 15 Questions

Question 1

A DBA needs to ensure that chunk migrations only occur during a specific maintenance window from 02:00 to 04:00. Which configuration change is required?

Accepted Answer

Update the config.settings collection with an activeWindow document.. MongoDB allows administrators to define a schedule for the balancer using the settings document in the config database. By setting an activeWindow, you can restrict chunk migrations to periods of low application activity. This prevents the performance overhead of data movement from impacting the user experience during peak hours while still ensuring the cluster stays balanced.

Answer

Use a cron job to call sh.stopBalancer() and sh.startBalancer().

Answer

Modify the mongod configuration file to include a balancing schedule.

Answer

Set a TTL index on the chunks collection to expire migrations.

Question 2

An operations engineer notices that a frequently executed aggregation pipeline fails with a 'Exceeded memory limit for $sort' error. Which index configuration best resolves this memory constraint?

Accepted Answer

Create a compound index matching the query's match filter fields followed by the sort fields in exact order.. MongoDB restricts in-memory operations like sorting to a fixed buffer size. When a query cannot satisfy its sort requirements from an index, it loads documents into memory. Providing a compound index containing the query's equality, range, and sort fields allows the execution engine to stream sorted results directly.

Answer

Create a wildcard index across all collection fields to capture unpredictable aggregation pipeline projections.

Answer

Increase the global cluster parameter maxInMemorySortBytes beyond the default allocation limit.

Answer

Enable allowDiskUse on every query connection string globally across the application configuration.

Question 3

When evaluating the performance of a 'hint' in MongoDB, what should you keep in mind?

Accepted Answer

Hints prevent the optimizer from adapting.. Using a hint forces the optimizer to use a specific index, ignoring its own cost-based selection. While this can sometimes be useful for troubleshooting or very specific cases where the optimizer makes a poor choice, it is generally discouraged because it prevents the database from adapting to data changes. As the data distribution evolves, a hinted index might become suboptimal, leading to degraded performance compared to a dynamic plan.

Answer

Hints are always faster than the optimizer's choice.

Answer

Hints should be used for all production queries.

Answer

Hints are only available for aggregation queries.

Question 4

Which THREE components are required to form a functional MongoDB sharded cluster?

Accepted Answer

One or more shards to store the data.. A MongoDB sharded cluster consists of three main components: Shards, Config Servers, and Query Routers (mongos). Shards store the actual data, Config Servers store the cluster's metadata and configuration, and Query Routers act as an interface for applications, directing requests to the appropriate shards. Each plays a distinct and vital role in the cluster's operation.

Answer

A dedicated arbiter node for each shard.

Answer

A central MongoDB Ops Manager instance.

Question 5

Which MongoDB feature allows an application to receive real-time updates when data changes in a collection?

Accepted Answer

Change Streams. Change Streams provide an event-driven way for applications to react to data modifications in real time without polling the database. By using the aggregation framework, applications can filter for specific events like inserts, updates, or deletes. This is vital for modern microservices architectures, as it allows downstream systems to keep their caches or search indexes synchronized with the primary data store immediately after a write occurs.

Answer

Capped collections

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Database Profiler

Answer

GridFS

Question 6

What is the primary motivation for MongoDB's 'WiredTiger' storage engine to provide document-level concurrency control?

Accepted Answer

To increase throughput by reducing write contention.. Early MongoDB versions used a global write lock, which hindered performance by serializing all write requests. Document-level concurrency control allows multiple clients to write to different documents in the same collection simultaneously. This is a critical architectural shift that enables high write throughput, as it drastically reduces contention and allows the database to fully utilize multi-core server architectures, directly supporting MongoDB's promise of high performance at scale.

Answer

To allow for faster reading of large binary objects.

Answer

To support atomic, multi-document transactions.

Answer

To provide automatic index creation in the background.

Question 7

A developer chooses Hashed Sharding for a collection. What is a significant limitation of this sharding strategy compared to Ranged Sharding?

Accepted Answer

Range-based queries on the shard key will result in broadcast operations.. Hashed sharding ensures an even distribution of data across shards by hashing the shard key values, which is excellent for handling monotonically increasing keys. However, because the hash function essentially randomizes the placement of documents, range-based queries cannot be targeted to a single shard. This choice involves a trade-off between write distribution and query efficiency for specific access patterns.

Answer

Hashed sharding does not support compound shard keys.

Answer

Hashed sharding requires the shard key field to be a numeric type.

Answer

Hashed sharding cannot be used with the balancer to move chunks.

Question 8

An application uses a time-series collection. What is the benefit of using the TTL (Time-To-Live) index feature?

Accepted Answer

It allows the database to remove documents based on a timestamp field.. TTL indexes provide an automated mechanism for cleaning up expired data. By setting a TTL index on a date field, MongoDB periodically removes documents that exceed the defined age, which is essential for managing storage and keeping the database size under control in time-series workloads. This reduces administrative manual cleanup tasks and ensures the system maintains a consistent performance level by pruning old, irrelevant data automatically.

Answer

It automatically creates a new collection for every time period.

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It ensures data is compressed automatically to save disk space.

Answer

It prevents duplicate documents from being inserted into the collection.

Question 9

Which query operator matches documents where a field contains a value greater than or equal to a specified value?

Accepted Answer

$gte. The $gte operator (greater than or equal to) is a comparison operator used in query filters. It is essential for range-based queries, such as filtering for dates after a specific threshold, product prices above a minimum, or version numbers. Understanding these comparison operators is fundamental to building expressive and efficient queries that narrow down result sets effectively within the MongoDB document model.

Answer

$gt

Answer

$ge

Answer

$eq

Question 10

When a secondary node is lagging behind the primary, what is the most significant risk to the replica set if the lag time exceeds the length of the oplog?

Accepted Answer

The secondary will enter a 'RECOVERING' state and require a full resync.. If a secondary falls behind the primary beyond the duration of the oplog, the secondary must perform an initial sync. This involves cloning the entire dataset, which is resource-intensive and can significantly degrade performance on the primary. Managing oplog size is a critical operational task to ensure that transient network issues do not force expensive full data copies across the network.

Answer

The secondary will trigger an automatic election to become primary.

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The primary will automatically reduce its write concern to accommodate the lag.

Answer

The replica set will automatically increase the oplog size to compensate.

Question 11

Which feature of MongoDB allows it to scale horizontally by distributing data across multiple physical servers?

Accepted Answer

Sharding to partition data across a cluster.. Sharding is the native MongoDB architecture for horizontal scaling, partitioning data into chunks across a cluster of shards. This strategy addresses storage limitations and throughput bottlenecks that single-node or replica set architectures cannot handle. By distributing read and write operations across multiple nodes, sharding maintains performance as datasets grow to terabyte or petabyte scales, fulfilling the philosophy of providing seamless, scalable infrastructure for global applications.

Answer

Vertical scaling via hardware upgrades.

Answer

Replica sets for high availability.

Answer

Index prefixing for faster query execution.

Question 12

Refer to the exhibit. If the primary node fails, which node is most likely to be elected the next primary based on optime?

Accepted Answer

Member[2] will likely be elected because it is more up-to-date.. Elections prioritize the node with the most up-to-date data. The optime (operation time) represents the latest operation applied by the node. Member[2] is the most advanced secondary with a timestamp of 95, compared to Member[1] at 90. Therefore, Member[2] has the highest probability of winning the election, ensuring the new primary has the most current data available in the set.

Answer

Member[1] will always be elected.

Answer

No node can be elected because the timestamps are all different.

Answer

The election will trigger a full re-sync for all nodes.

Question 13

Which operator is used to perform a logical OR operation across multiple query conditions?

Accepted Answer

$or. The $or operator enables the evaluation of multiple conditions, returning documents that satisfy at least one of them. It is essential for complex filtering where data might fall into different categories. By nesting conditions within an $or array, developers can perform sophisticated queries that are not possible with simple key-value pairs, allowing for flexible data retrieval patterns in diverse application environments.

Answer

$and

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$not

Answer

$nor

Question 14

What is the primary function of the 'projection' parameter in the find() method?

Accepted Answer

To specify which fields to return in the documents.. Projections allow you to limit the data returned by a query, which is a best practice for reducing network traffic and memory consumption on both the client and the server. By requesting only the fields required for the current task, you optimize application performance and security. This is a foundational concept in database interaction that helps maintain efficient data flow in large-scale applications.

Answer

To filter which documents are returned.

Answer

To sort the returned documents.

Answer

To limit the number of documents returned.

Question 15

What is the primary purpose of an Arbiter in a MongoDB replica set?

Accepted Answer

To participate in elections and help achieve a majority.. An arbiter's sole purpose is to participate in elections to help reach a majority vote without storing any data. By not storing data, it remains lightweight and requires minimal hardware resources, providing a cost-effective way to fulfill the voting requirements of a replica set in scenarios where an extra full-data node is not needed for capacity or redundancy.

Answer

To serve as a standby node for automatic failover.

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To provide read-only access to the database.

Answer

To replicate data from the primary to secondary nodes.