MCQs

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Overall MCQs for Reference

1. Which type of machine learning application commonly benefits from fast local storage?
   a. Real-time analytics
   b. Video streaming
   c. Image compression
   d. Text translation
   Answer: a. Real-time analyticscloud.google​
2. Local SSD drives attached to compute nodes in cloud platforms are mainly used to improve:
   a. Model accuracy
   b. Input/output operations per second (IOPS)
   c. GPU utilization
   d. Feature selection
   Answer: b. Input/output operations per second (IOPS)cloud.google​
3. What is a significant advantage of using local storage for ML training?
   a. Lower network latency
   b. Data retention for backup
   c. Simpler algorithms
   d. Increased model interpretability
   Answer: a. Lower network latencyweka​
4. Local storage in distributed machine learning can serve as:
   a. Ephemeral cache
   b. Permanent archival
   c. Networked object storage
   d. Remote file system
   Answer: a. Ephemeral cachecloud.google​
5. What is a common challenge when using local storage in ML workflows?
   a. High latency
   b. Data synchronization
   c. Increased disk space
   d. Improved scalability
   Answer: b. Data synchronizationtdcommons​
6. NVMe drives are sometimes used for local storage during ML experiments to provide:
   a. Slow access to archived data
   b. Persistent cloud storage
   c. Fast disk operations
   d. GPU memory extension
   Answer: c. Fast disk operationscsc​
7. Which statement about local storage in the context of model training is correct?
   a. Local storage is always persistent across jobs
   b. Data must be copied to local storage for faster training
   c. Local storage is unsuitable for neural networks
   d. Only cloud object storage is used
   Answer: b. Data must be copied to local storage for faster trainingcsc​
8. What happens to local ephemeral storage after job completion in a compute cluster?
   a. Data remains indefinitely
   b. Storage is automatically cleaned
   c. Data is sent to remote cloud servers
   d. Storage becomes read-only
   Answer: b. Storage is automatically cleanedcsc​
9. When does local storage provide optimal results in ML applications?
   a. When models require slow data access
   b. When datasets are small and fit in memory
   c. When jobs are data-intensive
   d. With text-based models only
   Answer: c. When jobs are data-intensivecsc​
10. How can ML pipelines utilize distributed local storage?
    a. For data marshaling between processing steps
    b. For storing model weights permanently
    c. For cloud dataset sharing
    d. For online inference
    Answer: a. For data marshaling between processing stepstdcommons​
11. Which option describes a limitation of local storage in ML?
    a. Cannot be used on-premises
    b. Limited scalability for large datasets
    c. Automatic migration to cloud
    d. Persistent backups
    Answer: b. Limited scalability for large datasetsweka​
12. Local storage can be dynamically provisioned in ML systems based on:
    a. Algorithm type
    b. Data temperature (access frequency)
    c. Model accuracy
    d. Framework used
    Answer: b. Data temperature (access frequency)tdcommons​
13. What ML use case best fits ephemeral local SSD storage in Kubernetes?
    a. Batch processing
    b. Long-term archiving
    c. Real-time model serving
    d. Feature engineering
    Answer: a. Batch processingcloud.google​
14. Storing frequently accessed datasets locally can help by:
    a. Reducing network traffic
    b. Increasing algorithm complexity
    c. Lowering CPU load
    d. Improving user interface design
    Answer: a. Reducing network traffictdcommons​
15. In ML, which storage system gives lowest latency for training data access?
    a. Object storage
    b. Local NVMe drives
    c. Tape archives
    d. Cloud database
    Answer: b. Local NVMe drivescsc+1​
16. Which storage device is commonly used for fast local storage in ML clusters?
    a. Magnetic tapes
    b. Floppy disks
    c. SSD/NVMe drives
    d. CD-ROMs
    Answer: c. SSD/NVMe drivescsc​
17. When using GKE, local storage can be provisioned as a(n):
    a. Ephemeral volume tied to pod lifecycle
    b. Shared network drive
    c. Immutable volume
    d. Permanent database
    Answer: a. Ephemeral volume tied to pod lifecyclecloud.google​
18. Copying ML training data to local storage on compute nodes is recommended when:
    a. Data is rarely accessed
    b. Data is small and static
    c. Data is large and processing is repetitive
    d. Only pre-trained models are used
    Answer: c. Data is large and processing is repetitivecsc​
19. The localPersistentVolume API in Kubernetes enables local storage to be:
    a. Provided as a node-level cache
    b. Used as permanent backup
    c. Shared globally across clusters
    d. Deleted automatically each hour
    Answer: a. Provided as a node-level cachecloud.google​
20. Which machine learning process benefits most from local cache storage?
    a. Inference with small models
    b. Batch training with large datasets
    c. Model visualization
    d. Data labeling
    Answer: b. Batch training with large datasetstdcommons​
21. Local storage use is preferred over cloud object storage when:
    a. Models train on highly volatile data
    b. Low-latency access is critical
    c. Results need long-term archiving
    d. Data is rarely updated
    Answer: b. Low-latency access is criticalweka​
22. What is a key attribute of node-local NVMe storage in ML workloads?
    a. Shared among all nodes
    b. Only available for metadata storage
    c. Dedicated to a single node
    d. Automatically replicated to cloud
    Answer: c. Dedicated to a single nodetdcommons​
23. What factor should be considered when allocating local storage for ML workloads?
    a. Disk encryption only
    b. Frequency of data access (hot/cold)
    c. License cost
    d. Programming language used
    Answer: b. Frequency of data access (hot/cold)tdcommons​
24. Storing subsets of ML datasets locally helps in:
    a. Speeding up training
    b. Increasing annotation errors
    c. Preventing overfitting
    d. Reducing data redundancy
    Answer: a. Speeding up trainingtdcommons​
25. What is local storage’s typical role during the execution of ML jobs on HPC systems?
    a. Temporary workspace
    b. Continuous cloud mirroring
    c. Permanent database
    d. Model deployment
    Answer: a. Temporary workspacecsc​
26. Which statement about local storage scalability is true?
    a. Unlimited scalability by default
    b. Scalability depends on available local disk size
    c. Automatically scales with network load
    d. Always scales out automatically
    Answer: b. Scalability depends on available local disk sizeweka+1​
27. For ephemeral ML jobs, which type of storage is tied to the job’s lifecycle?
    a. Local ephemeral storage
    b. Cloud archive storage
    c. NAS storage
    d. Tape backup storage
    Answer: a. Local ephemeral storagecloud.google​
28. What is the effect of network bottlenecks on ML jobs without local storage?
    a. Slower data loading and reduced performance
    b. Increased accuracy
    c. Faster disk operations
    d. Automated feature selection
    Answer: a. Slower data loading and reduced performanceweka+1​
29. A hash of files stored in local cache for ML helps to:
    a. Identify duplicates
    b. Improve deep learning performance
    c. Encrypt data automatically
    d. Split datasets
    Answer: a. Identify duplicatestdcommons​
30. Which machine learning scenario least benefits from local storage?
    a. High-frequency access and computation
    b. Distributed inference with global datasets
    c. Offline batch training
    d. Accelerated feature extraction
    Answer: b. Distributed inference with global datasetsweka​
31. Local storage on compute nodes is cleared:
    a. After each ML job execution
    b. Once per week
    c. Only during system upgrades
    d. Never cleared automatically
    Answer: a. After each ML job executioncsc​
32. In ML pipelines, local storage for hot data gives:
    a. Rapid access to frequently used datasets
    b. Lower disk utilization
    c. Slower training time
    d. Minimized memory consumption
    Answer: a. Rapid access to frequently used datasetstdcommons​
33. Which storage approach minimizes latency in model training?
    a. Local SSD/NVMe use
    b. Cloud-only storage
    c. USB flash drives
    d. FTP archives
    Answer: a. Local SSD/NVMe usecloud.google+1​
34. What is a common method to provision local block storage in Kubernetes ML jobs?
    a. Using the local PersistentVolume API
    b. Enabling remote mounting
    c. Writing custom drivers
    d. Manual database migration
    Answer: a. Using the local PersistentVolume APIcloud.google​
35. When would you disable local storage in ML workflows?
    a. Job requires durability and backup
    b. CPU-intensive tasks only
    c. GPU memory is always sufficient
    d. Model training needs cloud service latency
    Answer: a. Job requires durability and backupweka+1​
36. ML data access patterns influence local storage allocation by:
    a. Adjusting storage dynamically for hot/cold data
    b. Fixing disk space before job start
    c. Requiring daily cloud sync
    d. Predicting user errors
    Answer: a. Adjusting storage dynamically for hot/cold datatdcommons​
37. Cloud object storage may replace local storage in ML when:
    a. Data is static and rarely accessed
    b. Frequent real-time updates are required
    c. Low-latency local compute is needed
    d. GPU exclusively processes text data
    Answer: a. Data is static and rarely accessedweka​
38. Datasets stored locally on ML nodes are:
    a. Temporary unless specifically migrated
    b. Always archived in cloud
    c. Never accessed by jobs
    d. Replicated between clusters
    Answer: a. Temporary unless specifically migratedcsc+1​
39. The main reason for copying datasets to local SSD for ML jobs is:
    a. Achieve fast access and minimize network delays
    b. Lower cost of storage
    c. Simplify feature engineering
    d. Store final results
    Answer: a. Achieve fast access and minimize network delayscloud.google+1​
40. Local storage mechanisms for ML on cloud platforms typically use:
    a. NVMe SSD volumes
    b. Floppy disks
    c. Remote tapes
    d. Email file attachments
    Answer: a. NVMe SSD volumescloud.google+1​
41. Cache/client usage of local storage in ML is recommended when:
    a. Multiple jobs access the same subset of data
    b. Only single-job training occurs
    c. Data always resides in cloud buckets
    d. Jobs have no IOPS requirement
    Answer: a. Multiple jobs access the same subset of datatdcommons​
42. What describes ‘data temperature’ in ML local storage?
    a. Frequency and likelihood of dataset use
    b. Amount of noise in data
    c. Model loss accuracy
    d. Hardware efficiency
    Answer: a. Frequency and likelihood of dataset usetdcommons​
43. In ML, local storage as ‘hot storage’ is typically:
    a. Rapid, expensive, limited-volume space
    b. Slow, network-shared space
    c. Long-term archival space
    d. Low-cost, large storage
    Answer: a. Rapid, expensive, limited-volume spacetdcommons​
44. Storage optimization in ML via local storage is enabled by:
    a. Dynamically resizing volumes based on use
    b. Fixed disk allocation per job
    c. Static directory assignment
    d. Disabling fast disk
    Answer: a. Dynamically resizing volumes based on usetdcommons​
45. Choosing local storage over networked storage in ML is driven by:
    a. Speed requirements for job execution
    b. Documentation standards
    c. Loss functions choice
    d. Number of parameters
    Answer: a. Speed requirements for job executionweka+1​
46. What’s a disadvantage of local storage for ML on clusters?
    a. Data loss after job completion unless copied
    b. Inability to use GPUs
    c. Increased computational complexity
    d. Only usable for cloud models
    Answer: a. Data loss after job completion unless copiedcsc​
47. Using local storage in ML increases risk of:
    a. Dataset fragmentation and isolation
    b. Data centralization errors
    c. Over-optimization of model weights
    d. Automatic dataset labeling
    Answer: a. Dataset fragmentation and isolationcsc+1​
48. How does local storage affect ML job scheduling?
    a. Nodes are autoscaled for storage needs
    b. Scheduling becomes random
    c. Always uses cloud provisioning
    d. Model training speeds decrease
    Answer: a. Nodes are autoscaled for storage needscloud.google​
49. In ML batch jobs, local storage usage is:
    a. Ephemeral, tied to job duration
    b. Persistent for life of system
    c. Only for session storage
    d. Irrelevant for large datasets
    Answer: a. Ephemeral, tied to job durationcloud.google+1​
50. The role of local storage in ML is best summarized as:
    a. Providing high-speed, local access for data-intensive jobs
    b. Ensuring permanent data backup
    c. Automating cloud migration
    d. Synchronizing model features
    Answer: a. Providing high-speed, local access for data-intensive jobsweka+2​

1. https://cloud.google.com/blog/products/containers-kubernetes/high-performance-aiml-storage-through-local-ssd-support-on-gke
2. https://www.weka.io/learn/glossary/cloud-storage/cloud-storage-vs-local-storage/
3. https://www.tdcommons.org/cgi/viewcontent.cgi?article=8360&context=dpubs_series
4. https://docs.csc.fi/support/tutorials/ml-data/
5. https://www.sanfoundry.com/1000-machine-learning-questions-answers/
6. https://testbook.com/objective-questions/mcq-on-storage-allocation–5eea6a1139140f30f369eb5b
7. https://www.sanfoundry.com/javascript-mcqs-client-side-storage/
8. https://interviewkickstart.com/blogs/articles/data-science-mcq-answers
9. https://www.scribd.com/document/513570416/ACFrOgCJFUigNteKuu50LJxpBGcbPjZqsROcKBB5PyM5KE-Q-oAs-YZJ3IADaoXffYVg95KJOlVhH3Y7i3EhDpSdahDSH67nvSoQ0jRcRPfnxznydI9KqW1NG5BlF4MYakTohHZdry6b99-9xv5H
10. https://www.includehelp.com/mcq/how-many-methods-does-localstorage-object-provides.aspx
11. https://dev.to/dboatengx/javascript-local-storage-explained-1di6
12. https://examradar.com/fundamentals-of-data-storage-technologies-magnetic-solid-state-optical-etc-mcqs/
13. https://www.geeksforgeeks.org/javascript/difference-between-local-storage-session-storage-and-cookies/
14. https://www.examveda.com/what-is-the-lifetime-of-the-data-stored-through-localstorage-41241/
15. https://www.geeksforgeeks.org/javascript/javascript-localstorage/
16. https://www.digitalocean.com/community/tutorials/js-introduction-localstorage-sessionstorage
17. https://www.igmguru.com/blog/machine-learning-mcqs
18. https://www.w3schools.com/jsref/prop_win_localstorage.asp
19. https://rxdb.info/articles/localstorage.html
20. https://aticleworld.com/c-mcq-on-storage-classes/