HDFS stands for Hadoop Distributed File System and stores data across multiple cluster nodes.
Incorrect! Try again.
15Which Hadoop component manages cluster resources and schedules applications?
Components of Hadoop
Easy
A.YARN
B.HDFS
C.MapReduce
D.Hadoop Common
Correct Answer: YARN
Explanation:
YARN manages computing resources and coordinates the execution of applications in a Hadoop cluster.
Incorrect! Try again.
16Which Hadoop component processes data using map and reduce tasks?
Components of Hadoop
Easy
A.Hadoop Common
B.HDFS
C.MapReduce
D.YARN
Correct Answer: MapReduce
Explanation:
MapReduce is Hadoop's distributed programming model for processing data with map and reduce tasks.
Incorrect! Try again.
17What does the NameNode manage in HDFS?
Components of Hadoop
Easy
A.User account passwords
B.Application source code
C.File-system metadata
D.Network browser history
Correct Answer: File-system metadata
Explanation:
The NameNode maintains HDFS metadata, including file names, directories, and block locations.
Incorrect! Try again.
18Which software platform must be installed before running Apache Hadoop?
Installation of Apache Hadoop
Easy
A.PHP
B.Java
C.Ruby
D.Swift
Correct Answer: Java
Explanation:
Hadoop is primarily written in Java and requires a compatible Java installation to run.
Incorrect! Try again.
19Which environment variable commonly identifies the Java installation directory during Hadoop setup?
Installation of Apache Hadoop
Easy
A.DATA_PATH
B.CLUSTER_NAME
C.JAVA_HOME
D.HADOOP_PORT
Correct Answer: JAVA_HOME
Explanation:
The JAVA_HOME environment variable points Hadoop to the installed Java directory.
Incorrect! Try again.
20Which Hadoop command is commonly used to verify that Hadoop is installed and display its version?
Installation of Apache Hadoop
Easy
A.hadoop install
B.hadoop verify
C.hadoop status
D.hadoop version
Correct Answer: hadoop version
Explanation:
The hadoop version command displays the installed Hadoop version and related build information.
Incorrect! Try again.
21An 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.Distributed storage with parallel processing
B.Vertical storage with sequential processing
C.Local caching with transactional processing
D.Manual sampling with spreadsheet processing
Correct Answer: Distributed storage with parallel processing
Explanation:
Big Data platforms distribute large datasets and process partitions in parallel, reducing dependence on a single server.
Incorrect! Try again.
22A 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 handles diverse data at large scale
B.It guarantees real-time results for every query
C.It converts every file into relational tables
D.It eliminates the need for data validation
Correct Answer: It handles diverse data at large scale
Explanation:
Big Data systems are designed to store and process large collections containing structured, semi-structured, and unstructured data.
Incorrect! Try again.
23A 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.Updating one account balance immediately
C.Authorizing one card payment atomically
D.Analyzing five years of transaction history
Correct Answer: Analyzing five years of transaction history
Explanation:
Large-scale historical analysis benefits from distributed storage and parallel processing, while individual transactions usually require an OLTP system.
Incorrect! Try again.
24A data pipeline receives fixed-schema sales tables, JSON application events, and product photographs. How should these sources be classified, respectively?
Tables have a predefined schema, JSON contains flexible tags or keys, and photographs do not have a tabular data model.
Incorrect! Try again.
25A 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.Structured data
C.Reference data
D.Unstructured data
Correct Answer: Semi-structured data
Explanation:
JSON has recognizable keys and structure, but its fields can vary between records, making it semi-structured.
Incorrect! Try again.
26A 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 must be stored on separate networks
B.The sources require different processing methods
C.Both sources are completely unstructured
D.Both sources follow the same fixed schema
Correct Answer: The sources require different processing methods
Explanation:
Relational records are structured, while physician notes are unstructured text and commonly require text-processing techniques.
Incorrect! Try again.
27A 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.Variety
B.Volume
C.Veracity
D.Velocity
Correct Answer: Velocity
Explanation:
Velocity concerns how quickly data is generated, received, and processed.
Incorrect! Try again.
28Weather 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.Veracity
B.Value
C.Volume
D.Velocity
Correct Answer: Veracity
Explanation:
Veracity refers to data accuracy, reliability, uncertainty, and overall quality.
Incorrect! Try again.
29An 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.Velocity
B.Volume
C.Variety
D.Value
Correct Answer: Variety
Explanation:
Variety describes the presence of multiple data formats and structures.
Incorrect! Try again.
30A 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.Volume
B.Value
C.Variety
D.Velocity
Correct Answer: Value
Explanation:
Value is realized when data produces useful insights, improved decisions, or measurable business benefits.
Incorrect! Try again.
31In 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.The NameNode recomputes the original records
B.Every block is stored only in memory
C.Block replicas exist on other machines
D.The mapper downloads blocks from the internet
Correct Answer: Block replicas exist on other machines
Explanation:
HDFS stores replicas of data blocks on multiple DataNodes, allowing data to remain available after a worker failure.
Incorrect! Try again.
32A Hadoop cluster is running out of storage and processing capacity. Which action best follows Hadoop's typical scaling model?
Introduction to Hadoop
Medium
A.Replace HDFS with a spreadsheet system
B.Move all data to the NameNode machine
C.Add more worker nodes to the cluster
D.Run every task on one faster processor
Correct Answer: Add more worker nodes to the cluster
Explanation:
Hadoop primarily uses horizontal scaling, which increases capacity by adding worker machines.
Incorrect! Try again.
33Which workload is most suitable for a standard Hadoop batch-processing environment?
Introduction to Hadoop
Medium
A.Processing each ATM withdrawal as one transaction
B.Controlling an aircraft using immediate sensor feedback
C.Rendering interactive game frames in milliseconds
D.Computing nightly summaries from terabytes of logs
Correct Answer: Computing nightly summaries from terabytes of logs
Explanation:
Hadoop is well suited to high-throughput batch analysis of large datasets rather than strict low-latency processing.
Incorrect! Try again.
34A 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.Map task
C.NameNode
D.NodeManager
Correct Answer: NameNode
Explanation:
The NameNode manages the HDFS namespace and metadata that maps files to blocks and DataNodes.
Incorrect! Try again.
35A YARN application requests cluster resources, but the central service responsible for allocating containers is unavailable. Which component has failed?
Components of Hadoop
Medium
A.HDFS client
B.ResourceManager
C.DataNode
D.SecondaryNameNode
Correct Answer: ResourceManager
Explanation:
The ResourceManager performs cluster-wide resource allocation and scheduling in YARN.
Incorrect! Try again.
36In 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 copied directly into the NameNode
B.Pairs are converted into HDFS metadata blocks
C.Pairs are scheduled only by the DataNodes
D.Pairs are shuffled and grouped by customerID
Correct Answer: Pairs are shuffled and grouped by customerID
Explanation:
The shuffle and sort phase groups intermediate values by key so each reducer can process a customer's values together.
Incorrect! Try again.
37An 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 creates checkpoints of NameNode metadata
C.It only executes mapper and reducer tasks
D.It only allocates YARN containers to applications
Correct Answer: It only creates checkpoints of NameNode metadata
Explanation:
The SecondaryNameNode periodically merges namespace images and edit logs; it is not a basic automatic hot standby.
Incorrect! Try again.
38After 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.fs.defaultFS in core-site.xml
B.JAVA_HOME in hadoop-env.sh
C.yarn.nodemanager.local-dirs in yarn-site.xml
D.dfs.replication in hdfs-site.xml
Correct Answer: JAVA_HOME in hadoop-env.sh
Explanation:
Hadoop needs a valid JAVA_HOME value so its scripts can locate the Java runtime.
Incorrect! Try again.
39An 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.hdfs namenode -format
C.start-yarn.sh -format
D.yarn nodemanager -format
Correct Answer: hdfs namenode -format
Explanation:
The hdfs namenode -format command initializes the NameNode storage directories and creates a new HDFS namespace.
Incorrect! Try again.
40When 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.Move the NameNode metadata into YARN
B.Disable Java in the Hadoop environment file
C.Configure passwordless SSH access to localhost
D.Increase the HDFS block replication factor
Correct Answer: Configure passwordless SSH access to localhost
Explanation:
Hadoop's management scripts use SSH to launch daemons, so pseudo-distributed mode commonly requires passwordless SSH to localhost.
Incorrect! Try again.
41A 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 daily data generation is below one terabyte
B.The workload is not Big Data because a larger centralized server can theoretically store it
C.The workload qualifies as Big Data only if every record is completely unstructured
D.The workload qualifies as Big Data because it exceeds the current system's scalable processing capabilities
Correct Answer: The workload qualifies as Big Data because it exceeds the current system's scalable processing capabilities
Explanation:
Big Data is defined relative to the ability of conventional systems to ingest, store, and process data within required cost and time constraints, not by a universal size threshold.
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42An 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 JSON syntax guarantees identical fields and types across all documents
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 every document can be represented internally as key-value pairs
Correct Answer: Semi-structured because it has self-describing organization without a rigid shared schema
Explanation:
JSON provides structural markers such as keys and nesting, but documents need not conform to one fixed tabular schema. This makes it semi-structured.
Incorrect! Try again.
43A 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
Correct Answer: Images are unstructured, JSON annotations are semi-structured, and relational labels are structured
Explanation:
Binary images lack an explicit analytical schema, JSON has self-describing organization, and relational records follow a predefined table schema.
Incorrect! Try again.
44A 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.Volume, because the total number of stored historical events determines their arrival order
B.Value, because late arrivals always have less business usefulness than immediate arrivals
C.Velocity, because rapid and time-sensitive event flow requires processing of delayed arrivals
D.Variety, because delayed events necessarily use schemas different from on-time events
Correct Answer: Velocity, because rapid and time-sensitive event flow requires processing of delayed arrivals
Explanation:
Velocity covers the rate and time-sensitive nature of data generation and processing. Event-time windows and lateness policies address the temporal challenges of fast streams.
Incorrect! Try again.
45Two 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.Velocity, because conflicting measurements imply that the data arrived too quickly
C.Volume, because duplicate patient records necessarily exceed centralized storage capacity
D.Veracity, because the reliability and uncertainty of the reported values are in question
Correct Answer: Veracity, because the reliability and uncertainty of the reported values are in question
Explanation:
Veracity concerns data accuracy, trustworthiness, inconsistency, noise, and uncertainty, including conflicts between otherwise credible sources.
Incorrect! Try again.
46An 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.Value, because the data processing has not produced a useful organizational outcome
B.Veracity, because data without immediate profit must be assumed to be inaccurate
C.Velocity, because reliable processing implies that the logs were ingested too slowly
D.Volume, because petabyte-scale storage cannot be considered sufficiently large
Correct Answer: Value, because the data processing has not produced a useful organizational outcome
Explanation:
Value measures whether data and analytics produce useful outcomes. Successfully storing and processing large datasets does not by itself create value.
Incorrect! Try again.
47Which workload is least aligned with Hadoop's traditional design strengths?
Introduction to Hadoop
Hard
A.Transforming large immutable files through several parallel batch-processing stages
B.Serving millisecond-latency random updates to individual records under heavy concurrency
C.Analyzing a historical dataset whose partitions can be processed independently
D.Scanning multi-terabyte log archives to calculate aggregate usage statistics overnight
Correct Answer: Serving millisecond-latency random updates to individual records under heavy concurrency
Explanation:
Traditional Hadoop emphasizes high-throughput distributed storage and batch computation. It is not designed as a low-latency transactional system for frequent random record updates.
Incorrect! Try again.
48A 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 the least utilized node regardless of the block's replica locations
B.Run the task on the ResourceManager node to centralize all scheduling decisions
C.Run the task on a node that already stores a replica of the required block
D.Run the task on a remote rack so that local disks remain available for HDFS writes
Correct Answer: Run the task on a node that already stores a replica of the required block
Explanation:
Hadoop exploits data locality by moving computation near the data. Node-local execution generally avoids transferring the input block across the network.
Incorrect! Try again.
49A 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 NameNode still has namespace metadata, but the DataNodes holding the block contents are unavailable
D.The ResourceManager retains file metadata, but NodeManagers have lost the corresponding namespace entries
Correct Answer: The NameNode still has namespace metadata, but the DataNodes holding the block contents are unavailable
Explanation:
The NameNode manages namespace and block-location metadata, while DataNodes store the actual blocks. Metadata operations may succeed even when file contents cannot be retrieved.
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50An 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 becomes unreadable because HDFS requires all three replicas for every read
B.The file remains readable but is under-replicated until replacement replicas are created
C.The file is deleted because rack failure invalidates every block belonging to that file
D.The file remains fully replicated because replicas on failed nodes still count as available
Correct Answer: The file remains readable but is under-replicated until replacement replicas are created
Explanation:
A block can be read from any available replica. Losing replicas below the configured factor makes the block under-replicated, prompting HDFS to create replacements.
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51Ignoring 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.32 physical block replicas
B.16 physical block replicas
C.24 physical block replicas
D.8 physical block replicas
Correct Answer: 24 physical block replicas
Explanation:
The file has logical blocks. With three replicas per block, HDFS stores physical block replicas.
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52In YARN, which component pairing correctly separates cluster-wide resource arbitration from per-application task coordination?
Components of Hadoop
Hard
A.NameNode performs cluster-wide arbitration, while DataNode coordinates one application
B.ApplicationMaster performs cluster-wide arbitration, while ResourceManager manages one worker node
C.NodeManager performs cluster-wide arbitration, while NameNode coordinates one application
D.ResourceManager performs cluster-wide arbitration, while ApplicationMaster coordinates one application
Correct Answer: ResourceManager performs cluster-wide arbitration, while ApplicationMaster coordinates one application
Explanation:
The ResourceManager allocates cluster resources across applications. Each application's ApplicationMaster negotiates resources and coordinates that application's execution.
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53A 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 only the partial average and average all received partial averages equally
B.Emit a partial pair (average, count) and add the average fields without weighting
C.Emit a partial pair (sum, count) and merge pairs by adding both fields
D.Emit the largest transaction and divide it by the final number of transactions
Correct Answer: Emit a partial pair (sum, count) and merge pairs by adding both fields
Explanation:
Combiner logic must remain correct under repeated or omitted execution. Sums and counts merge associatively, and the final average is computed as total sum divided by total count.
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54A 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.All reducer output files collectively form one globally sorted sequence without further merging
D.Equal values reach one reducer even when they belong to different map-output keys
Correct Answer: All values for a given key reach one reducer, and that reducer processes keys in sorted order
Explanation:
Hash partitioning sends identical keys to the same reducer, and sorting orders keys within each reducer partition. It does not guarantee global ordering across reducer outputs.
Incorrect! Try again.
55Which design supports automatic HDFS NameNode failover while keeping the standby NameNode's namespace state synchronized?
Components of Hadoop
Hard
A.Active and standby NameNodes share edits through JournalNodes, with ZKFC coordinating failover
B.Two active NameNodes independently edit the same local namespace, with DataNodes merging conflicts
C.A Secondary NameNode continuously replaces the active NameNode whenever a heartbeat is missed
D.The ResourceManager replicates namespace edits to NodeManagers and elects a new NameNode
Correct Answer: Active and standby NameNodes share edits through JournalNodes, with ZKFC coordinating failover
Explanation:
HDFS high availability commonly uses quorum JournalNodes for shared edits and ZooKeeper Failover Controllers for health monitoring and automatic failover.
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56A 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.Each file requires a separate ResourceManager process to maintain its replication state
B.Every small file is automatically expanded on disk to the full configured HDFS block size
C.Every unused byte in a partial block is stored as NameNode heap-resident file content
D.Each file and block consumes namespace metadata even when the block contains little data
Correct Answer: Each file and block consumes namespace metadata even when the block contains little data
Explanation:
HDFS does not physically pad small files to the block size, but each file and block creates metadata entries. Very large numbers of small files therefore pressure NameNode memory.
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57One 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.Standalone local mode
C.Pseudo-distributed mode
D.Fully distributed mode
Correct Answer: Pseudo-distributed mode
Explanation:
Pseudo-distributed mode runs Hadoop daemons as separate processes on one machine, allowing distributed behavior to be tested without a multi-host cluster.
Incorrect! Try again.
58A 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 cannot register because workers is the authoritative HDFS membership database
B.It automatically becomes a NameNode because unlisted hosts cannot assume worker roles
C.It can register only as a NodeManager because DataNodes must be created by the NameNode
D.It can register with the NameNode because workers mainly guides administrative start and stop scripts
Correct Answer: It can register with the NameNode because workers mainly guides administrative start and stop scripts
Explanation:
The workers file identifies hosts targeted by helper scripts. A manually started DataNode can register if it can reach the NameNode and is not blocked by other configuration controls.
Incorrect! Try again.
59Hadoop 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.Add the Java executable to core-site.xml so that HDFS distributes it to every worker
B.Set a valid JAVA_HOME in Hadoop's environment configuration on every daemon host
C.Set JAVA_HOME only in the administrator's current shell before formatting the NameNode
D.Set the Java path in the workers file beside each host name used by the scripts
Correct Answer: Set a valid JAVA_HOME in Hadoop's environment configuration on every daemon host
Explanation:
Remote non-interactive sessions may not load a user's shell profile. Hadoop's environment configuration, such as hadoop-env.sh, should provide JAVA_HOME consistently on each host.
Incorrect! Try again.
60After 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.Format the active NameNode so it forgets all existing block locations and namespace information
B.Assign every cloned worker the same hostname so the NameNode treats them as one larger node
C.Increase the HDFS replication factor so duplicate DataNode identities are accepted as replicas
D.Clear and reinitialize each cloned DataNode data directory so every worker receives a unique identity
Correct Answer: Clear and reinitialize each cloned DataNode data directory so every worker receives a unique identity
Explanation:
A cloned DataNode directory may contain the same persistent DataNode UUID on multiple hosts. Reinitializing each new worker's DataNode storage creates unique identities without destroying the NameNode namespace.
Incorrect! Try again.
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