What is the primary consideration for choosing between HDDs and SSDs for MongoDB storage?
Data Redundancy
Cost per Gigabyte
Random Read/Write Performance
Storage Capacity
What is a common reason for slow query performance despite having an index on the queried field?
The query uses a projection to select only a subset of fields
The collection has a large number of documents
The index is too large to fit entirely in RAM
The indexed field has low cardinality (many documents share the same value)
Which stage allows for conditional execution of pipeline stages in MongoDB's aggregation framework?
$switch
$cond
$case
$ifNull
When are transactions in MongoDB typically considered essential?
For improving the performance of individual queries.
For all database operations to guarantee data integrity.
When performing read-only operations to ensure consistent snapshots of data.
When ACID properties are crucial, such as when multiple operations need to succeed or fail together to maintain data consistency.
Which of the following is a disadvantage of using the MongoDB In-Memory Storage Engine?
Increased complexity in configuration
Limited data size capacity
Lack of support for indexing
Slower write speeds compared to WiredTiger
What happens to a multi-document transaction in MongoDB if one of the operations within the transaction fails?
The transaction continues, ignoring the failed operation and proceeding with the rest.
The entire transaction is rolled back, ensuring atomicity and data consistency.
The transaction partially succeeds, applying only the successful operations.
The transaction enters a paused state, allowing the user to manually resolve the error before resuming.
Which aggregation stage allows you to perform complex data transformations within a group in MongoDB?
$group
$match
$sort
$project
How does creating indexes on appropriate fields impact the performance of aggregation queries in MongoDB?
Indexes can negatively affect aggregation performance
Indexes are only relevant for find() queries, not aggregation
Indexes can significantly improve aggregation performance
Indexes have no impact on aggregation performance
How can you ensure optimal memory allocation for the MongoDB WiredTiger storage engine?
Disable journaling for improved write performance
Manually configure the size of the WiredTiger internal cache
Regularly compact the database to reclaim unused space
Set the --noprealloc flag during mongod startup
--noprealloc
What is a key consideration for optimizing aggregation pipelines with large datasets in MongoDB?
Minimizing the use of indexes
Using JavaScript functions for complex logic
Avoiding the $match stage for optimal performance
Performing joins as early as possible in the pipeline