Big Data Storage Concepts
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What defines 'Big Data' as a problem?

  • The inability to store data effectively
  • The sheer volume of data becoming a part of the problem (correct)
  • The slow transfer speed of old storage devices
  • The high cost of data storage solutions

    • Which storage size is equivalent to a large dataset typically used by data centers?

  • Gigabyte
  • Petabyte
  • Terabyte
  • Exabyte (correct)

    • What is the approximate increase in disk capacity from 1990 to 2020?

  • 100000 times
  • 1000 times
  • 10000 times (correct)
  • 100 times

    • Distributing multiple HDDs across several computers improves what aspect of data processing?

    <p>I/O speed</p> Signup and view all the answers

    Which of the following best describes the impact of increased storage capacity on the perception of data size?

    <p>Today's big data is considered small in the future</p> Signup and view all the answers

    What is a disadvantage of using only one CPU with multiple HDDs?

    <p>Bottlenecking during data processing</p> Signup and view all the answers

    What is the storage capacity range of a typical hard drive installed in a server?

    <p>2 TB to 6 TB</p> Signup and view all the answers

    What problem is also associated with Big Data beyond its sheer volume?

    <p>I/O speed limitations</p> Signup and view all the answers

    What happens when a master node fails in a master-slave replication system?

    <p>Reads can occur via slave nodes while writes are disabled.</p> Signup and view all the answers

    Which strategy is employed to prevent multiple updates to the same record in peer-to-peer replication?

    <p>Pessimistic concurrency</p> Signup and view all the answers

    What issue can arise during read operations in a master-slave replication system?

    <p>Inconsistent reads if updates happen before replication.</p> Signup and view all the answers

    Which statement about the CAP theorem is true?

    <p>A system can choose to guarantee consistency and availability without partition tolerance.</p> Signup and view all the answers

    In the context of sharding and master-slave replication, which role does a node take with respect to different shards?

    <p>Each node serves as both a master and a slave for different shards.</p> Signup and view all the answers

    What does Atomicity in ACID ensure?

    <p>All transactions must complete successfully or rollback.</p> Signup and view all the answers

    When read/write requests occur in a distributed database, what must it accommodate according to the CAP theorem?

    <p>It must maintain at least one form of consistency, availability, or partition tolerance.</p> Signup and view all the answers

    What does the term 'consistency' refer to in the context of ACID properties?

    <p>Data must conform to the constraints defined by the database schema.</p> Signup and view all the answers

    What is a key concern with peer-to-peer replication regarding read consistency?

    <p>A peer may return stale data before updates complete.</p> Signup and view all the answers

    In optimistic concurrency control, what happens if simultaneous updates occur?

    <p>Updates may lead to temporary inconsistencies, which will later be resolved.</p> Signup and view all the answers

    Which ACID property is responsible for ensuring the visibility of transaction results?

    <p>Isolation</p> Signup and view all the answers

    What is the primary focus of the BASE model compared to ACID?

    <p>Favors availability over strong consistency.</p> Signup and view all the answers

    What does Durability in the ACID model promise?

    <p>Once a transaction is committed, it will persist despite failures.</p> Signup and view all the answers

    Which of the following best represents an advantage of horizontal scaling in master-slave systems?

    <p>Manages growing read demands efficiently through additional slave nodes.</p> Signup and view all the answers

    In a BASE system, what does 'soft state' imply?

    <p>Data may vary based on when it is read due to replication delays.</p> Signup and view all the answers

    Which statement correctly describes a scenario highlighting the ACID property of durability?

    <p>Database state is preserved despite a power failure occurring post-update.</p> Signup and view all the answers

    Which of the following choices accurately summarizes how master-slave replication handles writes?

    <p>Writes are aggregated at the master node only.</p> Signup and view all the answers

    Why might a distributed database prioritize availability over consistency?

    <p>To allow permanent read and write access during outages.</p> Signup and view all the answers

    Which of the following scenarios would likely result from employing a strict ACID compliance?

    <p>Users may experience delays when accessing records being updated.</p> Signup and view all the answers

    What aspect of BASE allows it to better handle network partitions?

    <p>Eventual consistency framework.</p> Signup and view all the answers

    Which feature allows ACID databases to favor consistency over availability according to the CAP theorem?

    <p>The use of strict locking to manage data integrity.</p> Signup and view all the answers

    If a distributed database system is in a soft state, what can happen when two users access the same data?

    <p>One user may receive stale or outdated data.</p> Signup and view all the answers

    What is a significant drawback of BASE compliant databases for transactional systems?

    <p>They can lead to stale data being served to clients.</p> Signup and view all the answers

    What is the main advantage of matching the speed of drives with the processing power of a server?

    <p>To prevent the CPU from becoming a bottleneck</p> Signup and view all the answers

    Which technology is essential for analyzing large volumes of data in Big Data analytics?

    <p>Highly scalable distributed technologies</p> Signup and view all the answers

    What is sharding in the context of Big Data storage?

    <p>Partitioning a dataset into smaller parts</p> Signup and view all the answers

    What does a relational database management system (RDBMS) use to interact with the database?

    <p>Structured Query Language (SQL)</p> Signup and view all the answers

    Which statement accurately describes a distributed file system (DFS)?

    <p>It can spread large files across multiple nodes</p> Signup and view all the answers

    What is a significant potential drawback of sharding?

    <p>It may impose performance penalties for queries across shards</p> Signup and view all the answers

    What does the CAP theorem state about distributed data systems?

    <p>They cannot guarantee all three—consistency, availability, and partition tolerance—at once</p> Signup and view all the answers

    In a master-slave replication setup, where are all write requests processed?

    <p>On the master node</p> Signup and view all the answers

    What type of database is specifically designed to manage semi-structured and unstructured data?

    <p>NoSQL databases</p> Signup and view all the answers

    Which of the following is NOT a benefit of sharding?

    <p>Reduction of overall storage space requirements</p> Signup and view all the answers

    How can commonly accessed data be managed in a sharded database to avoid performance issues?

    <p>By keeping commonly accessed data co-located on one shard</p> Signup and view all the answers

    What is the primary function of a cluster in Big Data storage?

    <p>To connect multiple nodes to work together as a unit</p> Signup and view all the answers

    Which of the following best describes replication in the context of Big Data storage?

    <p>Creating multiple copies of a dataset across nodes</p> Signup and view all the answers

    Which characteristic is associated with NoSQL databases?

    <p>Highly scalable and fault-tolerant</p> Signup and view all the answers

    Study Notes

    Big Data Storage Concepts

    • Big Data is not new, but as storage expands, the size of the data itself becomes a problem
    • Key issues include storage cost, hardware/software management, and compute power provision
    • Input/Output (I/O) speed is also a significant concern, with disk capacity and transfer speeds vastly outpacing read/write times

    Storage Sizes

    • Storage sizes increase exponentially: kilobytes, megabytes, gigabytes, terabytes, petabytes, exabytes, zettabytes, brontobytes, geopbytes
    • Specific examples of data sizes are given for each measurement, helping to visualize the magnitude of the scale
    • Real-world examples are given: the Library of Congress, the volume of internet data

    Solving Big Data Problems

    • Distributing storage across multiple servers (sharding) improves read/write speeds compared to a single server with a large number of drives
    • Matching drive speed to server processing power is crucial to prevent CPU bottlenecks
    • Effectively reading/writing data simultaneously from multiple drives across multiple servers is a challenge
    • Determining the location of file fragments on multiple servers is another key difficulty

    Big Data Storage Concepts

    • Big Data analytics relies on scalable distributed technologies
    • Innovative storage strategies/technologies are necessary for cost-effective and highly scalable storage solutions

    Clusters

    • A cluster is a group of tightly coupled servers (nodes)
    • Nodes have similar hardware and are networked for unified operation
    • Nodes possess dedicated resources (memory, processor, drive)
    • A cluster distributes tasks to different nodes for execution

    Distributed File Systems

    • A file system organizes files on a storage device
    • A distributed file system (DFS) stores files across cluster nodes
    • Examples include Google File System (GFS) and Hadoop Distributed File System (HDFS)

    Relational Database Management Systems (RDBMS)

    • RDBMS represent data as rows and columns
    • SQL (Structured Query Language) is used for database queries/maintenance
    • A transaction is a work unit in a database, treating operations cohesively

    NoSQL

    • NoSQL (Not-Only SQL) databases are scalable, fault-tolerant, and accommodate semi-structured/unstructured data
    • NoSQL database types: key-value, document, wide-column, graph

    Sharding

    • Sharding horizontally partitions large datasets into smaller units (shards)
    • Each shard resides on a separate node, managing only its data
    • All shards use a similar schema and together represent the full dataset
    • Data locality helps keep frequently accessed data on the same shard
    • Queries affecting multiple shards face performance issues, which can be alleviated by data localization

    Replication

    • Replication stores multiple copies (replicas) of data on different nodes
    • Replication methods include master-slave and peer-to-peer

    Master-Slave Replication

    • Data is written to a master node
    • Replication copies updates to slave nodes
    • Read requests can be processed by any slave
    • Master-slave replication is suitable for high read volumes
    • Single point of failure issue (master node failure halts writes)

    Peer-to-Peer Replication

    • All nodes (peers) are equal, capable of handling reads/writes
    • Data is replicated to all peers on write
    • Issues include potential inconsistency in read/write operations
    • Different concurrent strategies (pessimistic/optimistic) can be used to mitigate these issues

    Sharding vs. Replication

    • Sharding and replication can be used together in different configurations
    • Combination of sharding and master-slave replication (Master/Slave per shard)
    • Combination of sharding and peer-to-peer replication

    CAP Theorem

    • A choice must be made between consistency, availability, and partition tolerance
    • Selecting two of three characteristics is required for distributed database design
    • Partition tolerance is important; consistency and availability can be mutually exclusive

    ACID

    • ACID properties (Atomicity, Consistency, Isolation, Durability) define a standard for transaction management
    • Traditional databases prioritize ACID

    BASE

    • BASE (Basically Available, Soft State, Eventual Consistency) is a trade-off between consistency and availability for distributed systems
    • BASE systems prioritize availability over strict consistency, allowing for temporary inconsistencies before eventual consistency

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    Description

    Explore the fundamental concepts of Big Data storage, including challenges related to size, cost, and I/O speed. This quiz will delve into different storage sizes and real-world examples, as well as solutions for optimizing storage across servers. Test your knowledge on how to effectively manage and harness the power of Big Data storage.

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