MCQs

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Overall MCQs for Reference

Which of the following is a type of NoSQL database?
a. Document
b. Relational
c. Network
d. Hierarchical
Answer: a. Documentgeeksforgeeks+1
NoSQL databases were primarily designed to handle:
a. Transactional data
b. Static data
c. Unstructured and semi-structured data
d. Graphical data
Answer: c. Unstructured and semi-structured datamongodb+1
What kind of schema do NoSQL databases typically use?
a. Fixed
b. Hierarchical
c. Dynamic
d. Normalized
Answer: c. Dynamicgeeksforgeeks+1
Which popular NoSQL database uses JSON-like documents for storage?
a. Cassandra
b. Neo4j
c. MongoDB
d. Oracle
Answer: c. MongoDBsanfoundry+1
Which NoSQL type organizes data in rows and columns, similar to spreadsheets?
a. Document
b. Key-value
c. Wide-column
d. Graph
Answer: c. Wide-columnmongodb+1
Which of the following is NOT a NoSQL database?
a. SQL Server
b. Cassandra
c. MongoDB
d. Couchbase
Answer: a. SQL Servergtu-mcq+1
Key-value stores are best suited for:
a. Complex document queries
b. Storing and retrieving simple values by keys
c. Multi-table joins
d. Hierarchical data navigation
Answer: b. Storing and retrieving simple values by keysjavainuse+1
Machine learning applications often use NoSQL databases for:
a. Scalability with big data
b. Strict data consistency
c. Detailed relational modeling
d. Lack of query capabilities
Answer: a. Scalability with big dataarxiv+2
Data denormalization in NoSQL databases is used to:
a. Reduce join operations
b. Enforce strict schema
c. Support ACID transactions
d. Normalize data for analytics
Answer: a. Reduce join operationsjavainuse+1
Which characteristic of NoSQL databases is MOST beneficial for real-time machine learning?
a. Fixed schema
b. Horizontal scalability
c. Complex joins
d. Centralized storage
Answer: b. Horizontal scalabilityflexiple+1
The CAP theorem in NoSQL databases addresses:
a. Consistency, Availability, Partition tolerance
b. Compression, Authentication, Performance
c. Computation, Analysis, Partitioning
d. Competition, Allocation, Planning
Answer: a. Consistency, Availability, Partition toleranceflexiple
Graph databases store data as:
a. Tables
b. Nodes and edges
c. Documents
d. Key-value pairs
Answer: b. Nodes and edgessanfoundry+1
Eventual consistency in NoSQL means:
a. All replicas eventually contain the same data
b. Data is consistent after each transaction
c. Immediate synchronization between nodes
d. Data is never consistent
Answer: a. All replicas eventually contain the same datajavainuse+1
Which NoSQL database is optimized for analytics and machine learning tasks?
a. Redis
b. MongoDB
c. SQL Server
d. IMS
Answer: b. MongoDBstudocu+1
Sharding in NoSQL databases refers to:
a. Encrypting data
b. Partitioning data across multiple servers
c. Joining related tables
d. Creating hierarchical models
Answer: b. Partitioning data across multiple serversarxiv+1
A big advantage of key-value stores in machine learning tasks is:
a. Complexity of structure
b. Speed of access
c. Support for relational joins
d. Built-in ACID transactions
Answer: b. Speed of accessgeeksforgeeks+1
NoSQL databases are preferred in ML pipelines because:
a. They only support text data
b. They scale horizontally across nodes
c. They require strict schema
d. They limit scalability
Answer: b. They scale horizontally across nodesarxiv+2
Which NoSQL type is ideal for storing social network relationships?
a. Wide-column
b. Key-value
c. Document
d. Graph
Answer: d. Graphsanfoundry+1
What is a common indexing technique in NoSQL databases like MongoDB?
a. B-tree only
b. Inverted indexes
c. Hash index
d. Clustered index
Answer: b. Inverted indexesadaface+1
How do NoSQL databases often improve read performance for ML use cases?
a. Data denormalization
b. Foreign keys
c. Packed columns
d. Transaction locks
Answer: a. Data denormalizationmongodb+1
Which NoSQL database is commonly used in recommendation systems?
a. Cassandra
b. MariaDB
c. Oracle
d. MS Access
Answer: a. Cassandrastudocu+1
Which NoSQL type is suitable for storing and querying large graphs in ML?
a. Document
b. Column-family
c. Graph
d. Key-value
Answer: c. Graphsanfoundry+1
In ML-driven database tuning, what is optimized using machine learning algorithms?
a. Storage capacity
b. Query latency and throughput
c. Table relationships
d. Disk partitioning
Answer: b. Query latency and throughputarxiv
NoSQL databases often sacrifice which of the following for scalability?
a. Availability
b. Data redundancy
c. Consistency
d. Partition tolerance
Answer: c. Consistencyflexiple+1
What is a primary reason for using NoSQL databases in large-scale ML experiments?
a. Ability to handle ACID transactions
b. Flexible schema for evolving data types
c. Fixed reporting structure
d. Automatic normalization
Answer: b. Flexible schema for evolving data typesgeeksforgeeks+1
Hive and HBase are examples of:
a. Relational databases
b. Document stores
c. NoSQL databases
d. OLAP cubes
Answer: c. NoSQL databasesexamveda+1
Which is a disadvantage of NoSQL for ML workloads?
a. High scalability
b. Lack of strict schema enforcement
c. Fast read/writes
d. Integrated analytics engine
Answer: b. Lack of strict schema enforcementstudocu+1
Which component of NoSQL databases enables distributed storage?
a. Normalization
b. Sharding
c. Denormalization
d. Aggregation
Answer: b. Shardingflexiple+1
Which is commonly used for data ingestion into NoSQL databases for ML?
a. ETL pipelines
b. Spreadsheets
c. Manual transfers
d. Data marts
Answer: a. ETL pipelinesgeeksforgeeks+1
Which NoSQL model is best for storing time-series data in ML?
a. Key-value
b. Wide-column
c. Document
d. Graph
Answer: b. Wide-columnarxiv+1
When tuning NoSQL databases with machine learning, the main objective is:
a. Schema hardening
b. Performance optimization
c. Strict normalization
d. Enhanced relational joins
Answer: b. Performance optimizationumu.diva-portal+1
What kind of queries does MongoDB support in ML environments?
a. Only SELECT queries
b. Flexible, complex document queries
c. Strictly defined queries
d. ACID transactional queries only
Answer: b. Flexible, complex document queriesstudocu+1
Which NoSQL store is generally fastest for simple key/value ML tasks?
a. Cassandra
b. Redis
c. Neo4j
d. CouchDB
Answer: b. Redisflexiple+1
Which feature makes columnar NoSQL databases attractive for ML analytics?
a. Row-level security
b. Column-level flexibility
c. Fixed table schema
d. Denormalized structures
Answer: b. Column-level flexibilitymongodb+1
NoSQL databases are advantageous for ML models requiring:
a. Real-time data ingestion
b. Data warehousing only
c. Strict relational structure
d. Complex multi-table joins
Answer: a. Real-time data ingestionumu.diva-portal+1
Which NoSQL type is often used for storing IoT sensor data in ML systems?
a. Document
b. Wide-column
c. Key-value
d. Network
Answer: b. Wide-columngeeksforgeeks+1
NoSQL databases often employ replication for:
a. Lower memory use
b. High availability
c. Strict schema adherence
d. Limited scalability
Answer: b. High availabilityflexiple+1
Machine learning can help tune a NoSQL DBMS by:
a. Modifying table structures
b. Optimizing configuration settings for throughput and latency
c. Increasing schema rigidity
d. Disabling partitioning
Answer: b. Optimizing configuration settings for throughput and latencyarxiv
In NoSQL injection detection for ML security, a commonly used model is:
a. Linear Regression
b. k-Nearest Neighbor
c. Decision Tree
d. PCA
Answer: b. k-Nearest Neighborumu.diva-portal
Big Data applications favor NoSQL over RDBMS for ML because:
a. NoSQL supports joins
b. NoSQL scales horizontally and handles diverse data types
c. RDBMS handles unstructured data better
d. RDBMS is schema-free
Answer: b. NoSQL scales horizontally and handles diverse data typesmongodb+1
A common ML use case for graph NoSQL databases is:
a. Product recommendation
b. Log analysis
c. Website indexing
d. Document versioning
Answer: a. Product recommendationmongodb+1
Time-to-consistency in eventual consistency NoSQL models affects:
a. Data replication delay
b. Query performance exclusively
c. Disk usage only
d. Security enforcement
Answer: a. Data replication delayjavainuse+1
NoSQL databases are usually preferred over SQL in ML when:
a. Data is strictly structured
b. Data is unstructured or rapidly evolving
c. Data fits fixed relational models
d. Data has low velocity
Answer: b. Data is unstructured or rapidly evolvinggeeksforgeeks+1
Which machine learning model was found effective for NoSQL injection detection in MongoDB?
a. Neural Network
b. k-Nearest Neighbor
c. SVM
d. Logistic Regression
Answer: b. k-Nearest Neighborumu.diva-portal
In column-family NoSQL DBs, each row can have:
a. Fixed columns only
b. Different columns for each row
c. No columns
d. Unique column identifiers only
Answer: b. Different columns for each rowmongodb+1
In ML, storing feature vectors in NoSQL is beneficial because:
a. Rigid schema
b. Flexible schema supports evolving feature sets
c. Supports only numeric data
d. Supports synchronous joins
Answer: b. Flexible schema supports evolving feature setsgeeksforgeeks+1
Which feature distinguishes NoSQL DBs in handling big, fast, diverse ML data?
a. Centralized architecture
b. Schema flexibility and distributed design
c. ACID compliance
d. Relational mapping
Answer: b. Schema flexibility and distributed designmongodb+1
Which model can optimize NoSQL performance for ML workflows?
a. Black-box optimization
b. K-Means
c. Naive Bayes
d. Ridge Regression
Answer: a. Black-box optimizationarxiv
Which NoSQL DB type is ideal for graph traversal algorithms used in ML?
a. Key-value
b. Wide-column
c. Document
d. Graph
Answer: d. Graphsanfoundry+1
Compared to SQL, NoSQL offers machine learning practitioners:
a. More rigid data modeling
b. Simpler evolution of schema and data types
c. Less scalability
d. Single-user optimization
Answer: b. Simpler evolution of schema and data typesgeeksforgeeks+1

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