What is the primary advantage of using a compound index in MongoDB?
Reduced memory consumption for storing index data.
Improved performance for text search queries.
Faster retrieval of documents matching multiple fields.
Simplified management of index structures.
What is the primary purpose of using transactions in MongoDB?
To ensure atomicity, consistency, isolation, and durability (ACID) properties for multiple operations.
To create backups and restore data in case of failures.
To improve query performance for individual operations.
To enable data replication across multiple MongoDB clusters.
Which stage of the MongoDB write path is responsible for applying write operations to the journal?
Apply Operation
Release Locks
Write to Journal
Intent Shared Lock
What is the primary consideration for choosing between HDDs and SSDs for MongoDB storage?
Data Redundancy
Cost per Gigabyte
Storage Capacity
Random Read/Write Performance
Which geospatial query operator in MongoDB finds documents within a specific radius?
$geoIntersects
$geoWithin
$nearSphere
$near
In WiredTiger, what data structure is used to store data on disk?
B-Tree
Log-Structured Merge Tree
Skip List
Hash Table
What is a key consideration when choosing the order of fields in a compound index?
Alphabetical order of field names.
Size of the data stored in each field.
Data type of the fields (e.g., string, number).
Frequency and selectivity of query conditions.
What is the purpose of using the 'sparse' option when creating an index in MongoDB?
To compress the index data for reduced storage space.
To limit the index to only documents containing the indexed field.
To create a case-insensitive index for text search.
To distribute the index data across multiple shards.
What MongoDB tool is most suitable for visualizing and analyzing query performance?
MongoDB Profiler
mongostat
mongoimport
mongoexport
What is the significance of regularly rotating encryption keys used with MongoDB?
It prevents data corruption within the database.
It improves query performance by reducing index size.
It enables faster data recovery after a server failure.
It mitigates the impact of a potential key compromise.