Unit 1: Introduction to Hadoop - Practice Quiz

INT312 — Big Data Fundamentals 60 Questions
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1 What does the term Big Data generally describe?

Introduction to Big Data Easy
A. Datasets stored only in spreadsheets
B. Datasets containing only numeric values
C. Datasets that are large and complex
D. Datasets processed by one application

2 Which activity commonly generates large volumes of data?

Introduction to Big Data Easy
A. Renaming one folder
B. Printing one document
C. Social media interactions
D. Editing one text file

3 Why are traditional data-processing tools sometimes unsuitable for Big Data?

Introduction to Big Data Easy
A. They may not scale efficiently
B. They require no computer memory
C. They cannot store text values
D. They support only online access

4 Which type of data follows a fixed schema with rows and columns?

Types of Data Easy
A. Multimedia data
B. Structured data
C. Streaming data
D. Unstructured data

5 Which is an example of unstructured data?

Types of Data Easy
A. A payroll spreadsheet
B. A customer table
C. A digital video
D. A product database

6 Which is an example of semi-structured data?

Types of Data Easy
A. A JSON document
B. A printed photograph
C. A raw audio recording
D. A relational table

7 Which V of Big Data refers to the amount of data generated and stored?

V's of Big Data Easy
A. Veracity
B. Variety
C. Volume
D. Velocity

8 Which V of Big Data describes the speed at which data is generated and processed?

V's of Big Data Easy
A. Value
B. Veracity
C. Velocity
D. Variety

9 Which V of Big Data refers to the different formats and sources of data?

V's of Big Data Easy
A. Velocity
B. Volume
C. Value
D. Variety

10 Which V of Big Data is concerned with data accuracy and trustworthiness?

V's of Big Data Easy
A. Volume
B. Velocity
C. Variety
D. Veracity

11 What is Apache Hadoop primarily designed to do?

Introduction to Hadoop Easy
A. Edit documents through web browsers
B. Process large datasets across clusters
C. Manage emails on mobile devices
D. Create graphics on desktop computers

12 Apache Hadoop is best described as which type of software?

Introduction to Hadoop Easy
A. An open-source framework
B. A relational query language
C. A desktop operating system
D. A commercial web browser

13 Which feature allows Hadoop to increase capacity by adding more computers to a cluster?

Introduction to Hadoop Easy
A. Horizontal scalability
B. Vertical alignment
C. Local compression
D. Manual formatting

14 Which Hadoop component provides distributed storage?

Components of Hadoop Easy
A. YARN
B. HDFS
C. MapReduce
D. Hadoop Common

15 Which Hadoop component manages cluster resources and schedules applications?

Components of Hadoop Easy
A. MapReduce
B. Hadoop Common
C. YARN
D. HDFS

16 Which Hadoop component processes data using map and reduce tasks?

Components of Hadoop Easy
A. MapReduce
B. Hadoop Common
C. HDFS
D. YARN

17 What does the NameNode manage in HDFS?

Components of Hadoop Easy
A. Application source code
B. Network browser history
C. User account passwords
D. File-system metadata

18 Which software platform must be installed before running Apache Hadoop?

Installation of Apache Hadoop Easy
A. PHP
B. Java
C. Ruby
D. Swift

19 Which environment variable commonly identifies the Java installation directory during Hadoop setup?

Installation of Apache Hadoop Easy
A. JAVA_HOME
B. CLUSTER_NAME
C. HADOOP_PORT
D. DATA_PATH

20 Which Hadoop command is commonly used to verify that Hadoop is installed and display its version?

Installation of Apache Hadoop Easy
A. hadoop status
B. hadoop install
C. hadoop verify
D. hadoop version

21 An online marketplace generates several terabytes of clickstream data each day. A single database server cannot process the data within the required time. Which capability is most appropriate for this problem?

Introduction to Big Data Medium
A. Manual sampling with spreadsheet processing
B. Local caching with transactional processing
C. Distributed storage with parallel processing
D. Vertical storage with sequential processing

22 A company stores customer transactions efficiently in a relational database, but its recommendation system must also analyze images, reviews, and browsing events. Why is a Big Data approach appropriate?

Introduction to Big Data Medium
A. It converts every file into relational tables
B. It handles diverse data at large scale
C. It guarantees real-time results for every query
D. It eliminates the need for data validation

23 A bank must choose which workload to move from its transaction system to a Big Data platform. Which workload is the best candidate?

Introduction to Big Data Medium
A. Recording one customer password change
B. Authorizing one card payment atomically
C. Analyzing five years of transaction history
D. Updating one account balance immediately

24 A data pipeline receives fixed-schema sales tables, JSON application events, and product photographs. How should these sources be classified, respectively?

Types of Data Medium
A. Semi-structured, structured, unstructured
B. Unstructured, semi-structured, structured
C. Structured, unstructured, semi-structured
D. Structured, semi-structured, unstructured

25 A log file contains one JSON object per line, but different events may contain different fields. Which data type best describes the file?

Types of Data Medium
A. Semi-structured data
B. Unstructured data
C. Reference data
D. Structured data

26 A hospital wants to combine relational patient records with free-text physician notes. Which statement best describes the integration challenge?

Types of Data Medium
A. The sources require different processing methods
B. The sources must be stored on separate networks
C. Both sources follow the same fixed schema
D. Both sources are completely unstructured

27 A fraud-detection system must evaluate thousands of card events per second before approving transactions. Which V of Big Data is the primary concern?

V's of Big Data Medium
A. Veracity
B. Volume
C. Variety
D. Velocity

28 Weather sensors occasionally report impossible temperatures because of faulty calibration. Which V should the data engineering team address first?

V's of Big Data Medium
A. Velocity
B. Veracity
C. Value
D. Volume

29 An analytics platform must process database rows, audio recordings, XML documents, and social media images. Which V is most directly illustrated?

V's of Big Data Medium
A. Variety
B. Velocity
C. Value
D. Volume

30 A retailer stores petabytes of customer activity but has not identified any decisions that the data can improve. Which V is currently least realized?

V's of Big Data Medium
A. Variety
B. Value
C. Velocity
D. Volume

31 In an HDFS cluster with replication enabled, one worker machine fails during a batch analysis. Why can the Hadoop job usually continue?

Introduction to Hadoop Medium
A. Every block is stored only in memory
B. The NameNode recomputes the original records
C. The mapper downloads blocks from the internet
D. Block replicas exist on other machines

32 A Hadoop cluster is running out of storage and processing capacity. Which action best follows Hadoop's typical scaling model?

Introduction to Hadoop Medium
A. Run every task on one faster processor
B. Add more worker nodes to the cluster
C. Replace HDFS with a spreadsheet system
D. Move all data to the NameNode machine

33 Which workload is most suitable for a standard Hadoop batch-processing environment?

Introduction to Hadoop Medium
A. Rendering interactive game frames in milliseconds
B. Controlling an aircraft using immediate sensor feedback
C. Processing each ATM withdrawal as one transaction
D. Computing nightly summaries from terabytes of logs

34 A client needs to locate the DataNodes containing the blocks of an HDFS file. Which component provides the required metadata?

Components of Hadoop Medium
A. ResourceManager
B. NodeManager
C. Map task
D. NameNode

35 A YARN application requests cluster resources, but the central service responsible for allocating containers is unavailable. Which component has failed?

Components of Hadoop Medium
A. DataNode
B. HDFS client
C. SecondaryNameNode
D. ResourceManager

36 In a MapReduce job, mappers emit (customerID, purchaseAmount) pairs. What normally happens before reducers calculate totals for each customer?

Components of Hadoop Medium
A. Pairs are scheduled only by the DataNodes
B. Pairs are copied directly into the NameNode
C. Pairs are converted into HDFS metadata blocks
D. Pairs are shuffled and grouped by customerID

37 An administrator expects the SecondaryNameNode to become the active NameNode automatically after a failure. Why is this expectation incorrect in a basic Hadoop setup?

Components of Hadoop Medium
A. It only stores replicas of user data blocks
B. It only executes mapper and reducer tasks
C. It only creates checkpoints of NameNode metadata
D. It only allocates YARN containers to applications

38 After installing Hadoop, running hadoop version reports that Java cannot be found even though Java is installed. Which configuration should be checked first?

Installation of Apache Hadoop Medium
A. JAVA_HOME in hadoop-env.sh
B. yarn.nodemanager.local-dirs in yarn-site.xml
C. fs.defaultFS in core-site.xml
D. dfs.replication in hdfs-site.xml

39 An administrator is initializing a new pseudo-distributed HDFS installation for the first time. Which command prepares the NameNode's storage metadata?

Installation of Apache Hadoop Medium
A. hadoop fs -format /
B. start-yarn.sh -format
C. yarn nodemanager -format
D. hdfs namenode -format

40 When start-dfs.sh is executed in a pseudo-distributed installation, the script repeatedly asks for the local user's password. What is the most appropriate fix?

Installation of Apache Hadoop Medium
A. Configure passwordless SSH access to localhost
B. Disable Java in the Hadoop environment file
C. Increase the HDFS block replication factor
D. Move the NameNode metadata into YARN

41 A company receives only 800 GB of new data per day, but its centralized database cannot ingest the data within the required time window or economically scale to support analysis. Which conclusion is most accurate?

Introduction to Big Data Hard
A. The workload is not Big Data because a larger centralized server can theoretically store it
B. The workload qualifies as Big Data because it exceeds the current system's scalable processing capabilities
C. The workload is not Big Data because daily data generation is below one terabyte
D. The workload qualifies as Big Data only if every record is completely unstructured

42 An application stores events as JSON documents. Different events may contain different optional attributes, but each document uses keys and nested structures. How should this data be classified?

Types of Data Hard
A. Structured because every document can be represented internally as key-value pairs
B. Unstructured because optional attributes prevent the enforcement of a relational schema
C. Semi-structured because it has self-describing organization without a rigid shared schema
D. Structured because JSON syntax guarantees identical fields and types across all documents

43 A machine-learning repository contains JPEG images, JSON annotation documents, and label records in relational tables. Which classification correctly describes the individual components?

Types of Data Hard
A. Images are structured, JSON annotations are unstructured, and relational labels are semi-structured
B. Images are unstructured, JSON annotations are semi-structured, and relational labels are structured
C. Images are unstructured, JSON annotations are unstructured, and relational labels are structured
D. Images are semi-structured, JSON annotations are structured, and relational labels are unstructured

44 A streaming system receives millions of events per second, but network delays cause some events to arrive several minutes after later events. Which Big Data characteristic most directly drives the need for windowing and late-event handling?

V's of Big Data Hard
A. Velocity, because rapid and time-sensitive event flow requires processing of delayed arrivals
B. Variety, because delayed events necessarily use schemas different from on-time events
C. Volume, because the total number of stored historical events determines their arrival order
D. Value, because late arrivals always have less business usefulness than immediate arrivals

45 Two trusted medical data providers report conflicting values for the same patient's test result, and neither value can immediately be validated. Which V is the primary concern?

V's of Big Data Hard
A. Variety, because each provider must be using a fundamentally different data structure
B. Veracity, because the reliability and uncertainty of the reported values are in question
C. Velocity, because conflicting measurements imply that the data arrived too quickly
D. Volume, because duplicate patient records necessarily exceed centralized storage capacity

46 An organization stores petabytes of logs and processes them reliably, but no team can identify a decision, service, or measurable outcome improved by the analysis. Which V remains least satisfied?

V's of Big Data Hard
A. Veracity, because data without immediate profit must be assumed to be inaccurate
B. Velocity, because reliable processing implies that the logs were ingested too slowly
C. Volume, because petabyte-scale storage cannot be considered sufficiently large
D. Value, because the data processing has not produced a useful organizational outcome

47 Which workload is least aligned with Hadoop's traditional design strengths?

Introduction to Hadoop Hard
A. Analyzing a historical dataset whose partitions can be processed independently
B. Transforming large immutable files through several parallel batch-processing stages
C. Scanning multi-terabyte log archives to calculate aggregate usage statistics overnight
D. Serving millisecond-latency random updates to individual records under heavy concurrency

48 A large HDFS file has replicas on several worker nodes. When scheduling a map task for one block, which placement generally minimizes network traffic?

Introduction to Hadoop Hard
A. Run the task on a remote rack so that local disks remain available for HDFS writes
B. Run the task on a node that already stores a replica of the required block
C. Run the task on the least utilized node regardless of the block's replica locations
D. Run the task on the ResourceManager node to centralize all scheduling decisions

49 A client can list HDFS file names and permissions, but attempts to read file contents fail because all DataNodes are unavailable. What best explains this behavior?

Components of Hadoop Hard
A. The Secondary NameNode serves directory metadata, but it cannot execute map tasks without DataNodes
B. The NameNode stores complete file contents, but it delegates directory listings to unavailable DataNodes
C. The ResourceManager retains file metadata, but NodeManagers have lost the corresponding namespace entries
D. The NameNode still has namespace metadata, but the DataNodes holding the block contents are unavailable

50 An HDFS file has replication factor 3, and rack-aware placement has put its replicas across two racks. One entire rack becomes unavailable, while the other retains one replica. What is the immediate file state?

Components of Hadoop Hard
A. The file remains readable but is under-replicated until replacement replicas are created
B. The file is deleted because rack failure invalidates every block belonging to that file
C. The file remains fully replicated because replicas on failed nodes still count as available
D. The file becomes unreadable because HDFS requires all three replicas for every read

51 Ignoring the final partial-block case, a GiB file is stored in HDFS using a MiB block size and replication factor 3. How many physical block replicas are stored?

Components of Hadoop Hard
A. 24 physical block replicas
B. 16 physical block replicas
C. 8 physical block replicas
D. 32 physical block replicas

52 In YARN, which component pairing correctly separates cluster-wide resource arbitration from per-application task coordination?

Components of Hadoop Hard
A. NodeManager performs cluster-wide arbitration, while NameNode coordinates one application
B. ApplicationMaster performs cluster-wide arbitration, while ResourceManager manages one worker node
C. ResourceManager performs cluster-wide arbitration, while ApplicationMaster coordinates one application
D. NameNode performs cluster-wide arbitration, while DataNode coordinates one application

53 A MapReduce job computes the average transaction value for each customer. Which combiner output design is safe when the combiner may run zero, one, or multiple times?

Components of Hadoop Hard
A. Emit a partial pair (average, count) and add the average fields without weighting
B. Emit a partial pair (sum, count) and merge pairs by adding both fields
C. Emit only the partial average and average all received partial averages equally
D. Emit the largest transaction and divide it by the final number of transactions

54 A MapReduce job uses the default hash partitioner and multiple reducers. Which ordering guarantee is valid after the shuffle and sort phase?

Components of Hadoop Hard
A. Each reducer receives a contiguous key range determined solely by the number of reducers
B. All values for a given key reach one reducer, and that reducer processes keys in sorted order
C. Equal values reach one reducer even when they belong to different map-output keys
D. All reducer output files collectively form one globally sorted sequence without further merging

55 Which design supports automatic HDFS NameNode failover while keeping the standby NameNode's namespace state synchronized?

Components of Hadoop Hard
A. A Secondary NameNode continuously replaces the active NameNode whenever a heartbeat is missed
B. Two active NameNodes independently edit the same local namespace, with DataNodes merging conflicts
C. The ResourceManager replicates namespace edits to NodeManagers and elects a new NameNode
D. Active and standby NameNodes share edits through JournalNodes, with ZKFC coordinating failover

56 A cluster stores ten million files of 2 KB each, far below the configured HDFS block size. Storage capacity remains available, but NameNode memory becomes a bottleneck. What is the main cause?

Components of Hadoop Hard
A. Every small file is automatically expanded on disk to the full configured HDFS block size
B. Each file requires a separate ResourceManager process to maintain its replication state
C. Each file and block consumes namespace metadata even when the block contains little data
D. Every unused byte in a partial block is stored as NameNode heap-resident file content

57 One machine runs the NameNode, DataNode, ResourceManager, and NodeManager as separate Java processes, and HDFS is configured with replication factor 1. Which Hadoop deployment mode is this?

Installation of Apache Hadoop Hard
A. Federated storage mode
B. Fully distributed mode
C. Standalone local mode
D. Pseudo-distributed mode

58 A host is omitted from Hadoop's workers file, but its DataNode is started manually with the correct fs.defaultFS and network configuration. What is the most accurate outcome?

Installation of Apache Hadoop Hard
A. It automatically becomes a NameNode because unlisted hosts cannot assume worker roles
B. It cannot register because workers is the authoritative HDFS membership database
C. It can register with the NameNode because workers mainly guides administrative start and stop scripts
D. It can register only as a NodeManager because DataNodes must be created by the NameNode

59 Hadoop commands work in an administrator's interactive shell, but daemons launched remotely by start-dfs.sh fail with a Java-not-found error. Which correction is most appropriate?

Installation of Apache Hadoop Hard
A. Set a valid JAVA_HOME in Hadoop's environment configuration on every daemon host
B. Set JAVA_HOME only in the administrator's current shell before formatting the NameNode
C. Set the Java path in the workers file beside each host name used by the scripts
D. Add the Java executable to core-site.xml so that HDFS distributes it to every worker

60 After copying a preconfigured DataNode data directory to several new workers, only one worker registers successfully; the others are rejected as duplicate DataNodes. What is the safest corrective action?

Installation of Apache Hadoop Hard
A. Increase the HDFS replication factor so duplicate DataNode identities are accepted as replicas
B. Format the active NameNode so it forgets all existing block locations and namespace information
C. Clear and reinitialize each cloned DataNode data directory so every worker receives a unique identity
D. Assign every cloned worker the same hostname so the NameNode treats them as one larger node