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Flashcards

Distributed Systems

Lenio Vogt Informatik Alemão 5,0Avaliação média 5,0 de 5 (3 avaliações) 48 flashcards

Distributed Systems

Flashcards do conjunto (48)

  1. 1What is a Distributed System?Is a collection of autonomous computing elements that appears to its users as a single coherent system
  2. 2Autonomous computing elements- consits of all kinds of nodes
    - nodes can act independently
  3. 3Single coherent system- where data is stored should be of no concern
    - infrastructure in the background is not visible for the user
  4. 4Centralized/Decentralized/DistributedCentralized/Decentralized/Distributed
  5. 5Middleware- assist the development of distributed applications
    - separate layer of software that is logically placed on top of the respective operating system
    - data exchange between different OS
  6. 6RPCRemote Procedure Call
    - Communication Service
    - Allows application to invoke a function on a remote computer
  7. 7Transactions- applications make use of multiple services that are distributed among several computers
    - makes sure that every service is invoked, or none at all
  8. 8Goals for Distributed Systems- make resources easily accessible
    - hide the fact that resources are distributed across a network
    - open (components can be easily integrated)
    - be scalable
  9. 9Types of Distributed Systems- computing systems
    - information systems
    - pervasive systems
  10. 10Computing Systems- Cluster computing
    - Grid computing
    - Cloud computing
  11. 11Cluster Computing- Group of connected computers
    - Act like single entity
    --> High redundancy and distributed workload
  12. 12Grid Computing- Loosely coupled (decentralized)
    - Sharing tasks over multiple computers
  13. 13Cloud computing- Storing and accessing applications and data over the internet
    - Coupled (distributed)
    - Single system image
  14. 14Information Systems- Server running application and making it available to remote programmes (clients)
    - Clients send request --> Server sends response
    - Requests to different servers --> called distributed transaction
  15. 15Pervasive Systems- System is often equipped with many sensors that pick up various aspects
    - Small, battery-powered, mobile and having a wireless connection
    --> IoT
  16. 16Internet of Things (IoT)- Connecting all kinds of electronic devices to the internet
    - Benefits: Pick up data
    - Downsides: Data safety, rely too much on technology
  17. 17Reasons for distributed data- Scalability
    - Fault tolerance
    - High availability
    - Latency
  18. 18Replication- keeping a copy of the same data on serveral different nodes in different locations
  19. 19Leader-based replicationLeader-based replication
  20. 20Leader-based replication- one leader and followers, every write request goes to the leader, any read request by leader or any follower
  21. 21Syncrhonous vs. Asynchronous ReplicationSyncrhonous vs. Asynchronous Replication
  22. 22Handling node outages- Follower: each follower keeps log data, after recovery he resynchronise with the leader
    - Leader: timeout -> leader failed, follower with most up-to-date data becomes new leader
  23. 23Data lossData loss
  24. 24Split BrainSplit Brain
  25. 25TimeoutTimeout
  26. 26Read your own writesRead your own writes
  27. 27Monotonic readsMonotonic reads
  28. 28Multi-Leader ReplicationMulti-Leader Replication
  29. 29Single vs MultileaderPerformance
    Tolerance of outages
    Tolerances of network problems
  30. 30PerformanceSingle: every write must go over internet to the leader
    Multi: every write can be processed by local datacenter
  31. 31Tolerance of outagesSingle: if leader fails, failover can promote a follower to be leader
    Multi: if leader fails, other leaders continue operating independetly
  32. 32Tolerance of network problemsSingle: very sensitive, because writes are made synchronously
    Multi: can tolerate temporary network problems
  33. 33Leaderless ReplicationLeaderless Replication
  34. 34PartitioningSplitting data into smaller subsets called partitions so that different partitions can be assigned to different nodes
  35. 35HotspotPartition with disproportionately high load
  36. 36Partitioning by Hash Key- Takes skewed data and makes it uniformly distributed (Timestamp)
    Disadvantages:
    - losing property of key-range partitioning -> ability to do efficient range queries
    - keys that were once adjacent --> sort order is loss
  37. 37RebalancingRebalancing
  38. 38Request routingRequest routing
  39. 39Zoo KeeperZoo Keeper
  40. 40Models of Data Flow- via Databases
    - via service calls
    - asynchronous message passing
  41. 41via Database- data outlives the code
    process writes encoded data, another process reads it again sometime in the future
    - Migrating data is possible, but expensive on a large dataset
  42. 42via Service Callsvia Service Calls
  43. 43Service Calls - Web services- when http is used as the underlying protocol for talking to the service -> web service
  44. 44Service Calls - REST REpresentational State Transfer- not a protocol
    - design philosophy
    - builds upon the principles of http
    - Using URL´s for identifying resources
  45. 45Service Calls - SOAP Simple Object Access Protocol- XML based for making network API requests
  46. 46via Asynchronous Message Passing- sender doesn´t wait for the message to be delivered
    - simply sends it and then forgets about it
  47. 47SOAService oriented architecture:
    Decomposing large applications into smaller services by functionality
  48. 48Message broker- stores the messages temporarily
    - act as a buffer if recipient is unavailable
    - redeliver messages if crashes
    - allows sending message to different recipient

Informações

Descrição
Informatik FlashCards sobre Distributed Systems, criado por Lenio Vogt em 11-09-2019.
Criado por
Lenio Vogt
Visualizações
107
Avaliação
Avaliação média 5,0 de 5 (3 avaliações)

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