[04/Sarda/01]
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What is the current exception in the Flow.BI architecture?

  • Distributed Data Vault 2.0 architecture
  • Massively parallel processing (MPP)
  • Multiple reader instances
  • Repository based on PostgreSQL (correct)

    • Which component of Flow.BI runs in the cloud or on premise?

  • Metadata and results
  • Writer instance
  • Repository (correct)
  • Multiple reader instances

    • What type of architecture is used in Flow.BI for its components?

  • Cloud-based architecture
  • Distributed Data Vault 2.0 architecture (correct)
  • Load balancing based architecture
  • MPP (Massively parallel processing)

    • Flow.BI's repository is not based on PostgreSQL.

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

    Flow.BI's repository is used to store metadata and results.

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

    Flow.BI's distributed Data Vault 2.0 architecture is not based on Massively Parallel Processing (MPP).

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

    Match the following components of Flow.BI with their descriptions:

    <p>MPP (Massively Parallel Processing) = Basis for every component except the repository PostgreSQL = Used for the repository with one writer instance and multiple reader instances Repository = Stores metadata and results, runs in the cloud or on premise Distributed Data Vault 2.0 architecture = Architecture used for Flow.BI's components</p> Signup and view all the answers

    Match the following characteristics with their description in Flow.BI architecture:

    <p>One writer instance, multiple reader instances = Characteristic of PostgreSQL usage in Flow.BI Configurability of host name = Applies to testing and load balancing in Flow.BI Cloud or on premise deployment = Applies to the repository in Flow.BI MPP (Massively Parallel Processing) = Basis for every component except the repository in Flow.BI</p> Signup and view all the answers

    Match the following terms with their association in Flow.BI architecture:

    <p>Flow.BI components = Based on MPP (Massively Parallel Processing) except the repository PostgreSQL = Used for the repository and supports one writer instance and multiple reader instances Distributed Data Vault 2.0 architecture = The architecture used in Flow.BI's components Repository = Stores metadata and results, and can run in the cloud or on premise</p> Signup and view all the answers

    What is the main characteristic of an MPP cluster?

    <p>Each node has its own CPU, memory, and storage</p> Signup and view all the answers

    Why are MPP clusters well-suited for applications that require a high degree of parallelism?

    <p>They can distribute the workload across multiple nodes</p> Signup and view all the answers

    What benefit makes MPP clusters a good choice for applications that require a lot of processing power?

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

    What makes MPP clusters more cost-effective than traditional mainframes and supercomputers?

    <p>They can be built using commodity hardware</p> Signup and view all the answers

    Which application is often associated with the use of MPP clusters?

    <p>Data warehousing</p> Signup and view all the answers

    What is the primary function of MPP clusters in data warehousing?

    <p>Storing and analyzing large amounts of data</p> Signup and view all the answers

    What does each node in an MPP cluster have?

    <p>CPU, memory, and storage</p> Signup and view all the answers

    How do nodes in an MPP cluster communicate with each other?

    <p>Using a high-speed network</p> Signup and view all the answers

    What makes MPP clusters suitable for scientific computing?

    <p>High degree of parallelism</p> Signup and view all the answers

    What characteristic allows MPP clusters to provide very high levels of performance?

    <p>Distributing the workload across multiple nodes</p> Signup and view all the answers

    Why are MPP clusters often more cost-effective than traditional mainframes and supercomputers?

    <p>They can be built using commodity hardware</p> Signup and view all the answers

    True or false: MPP clusters consist of interconnected nodes that work together to process data in series, not in parallel?

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

    True or false: Each node in an MPP cluster has its own CPU, memory, and storage?

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

    True or false: MPP clusters are not suitable for applications that require a high degree of parallelism?

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

    True or false: MPP clusters can be easily scaled by adding more nodes, making them a good choice for applications that require a lot of processing power?

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

    True or false: MPP clusters are often more cost-effective than traditional mainframes and supercomputers because they require specialized and expensive hardware?

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

    True or false: MPP clusters are well-suited for scientific computing due to their ability to distribute the workload across multiple nodes?

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

    True or false: MPP clusters are not commonly used for data warehousing applications?

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

    True or false: MPP clusters can provide very high levels of performance due to their ability to distribute the workload across multiple nodes?

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

    True or false: MPP clusters can communicate with each other using a low-speed network?

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

    True or false: MPP clusters are often used to store and analyze large amounts of data in data warehousing applications?

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

    True or false: MPP clusters are not cost-effective because they can be built using commodity hardware?

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

    True or false: MPP clusters are not suitable for big data analytics applications?

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

    Match the following benefits with their descriptions of MPP clusters:

    <p>Scalability = MPP clusters can be easily scaled by adding more nodes Performance = MPP clusters can provide very high levels of performance Cost-effectiveness = MPP clusters are often more cost-effective than traditional mainframes and supercomputers Reliability = MPP clusters can distribute the workload across multiple nodes, improving performance</p> Signup and view all the answers

    Match the following applications with their usage of MPP clusters:

    <p>Data warehousing = MPP clusters are often used to store and analyze large amounts of data Big data analytics = MPP clusters are well-suited for applications that require a high degree of parallelism Scientific computing = MPP clusters are suitable for scientific computing applications Web development = MPP clusters are not commonly used for web development purposes</p> Signup and view all the answers

    Match the following components with their description in an MPP cluster:

    <p>CPU, memory, and storage = Each node in an MPP cluster has its own CPU, memory, and storage High-speed network = Nodes in an MPP cluster communicate with each other using a high-speed network Interconnected nodes = MPP clusters consist of interconnected nodes that work together to process data in parallel Commodity hardware = MPP clusters can be built using commodity hardware, which is relatively inexpensive</p> Signup and view all the answers

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