Towards Language Support for Distributed Programming

Transcript

1. Towards Language Support
   for Distributed Systems
   Heather Miller
   

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2. But it doesn’t always look that way from the outside…
   One thing I love about research
   is that research is very animated.
   

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6. This talk is
   about context
   Whirlwind tour of research
   on language support for
   distributed programming
   

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7. Language Support for
   Distributed Systems
   =
   ways that the programming language/
   compiler can aid in the development of
   a distributed application
   

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8. Distributed Programming
   Research Today
   If I could visually depict all
   of the various research
   projects in the space of
   distributed programming…
   it’d look something
   like this!
   Context
   

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9. Distributed Programming
   Research Today
   Session Types
   Consistency &
   Programming Models
   Context
   Static Analysis &
   Verification
   

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10. Distributed Programming
    Research Today
    Context
    Session Types
    Consistency &
    Programming Models
    Static Analysis &
    Verification
    Other research
    

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11. Distributed Programming
    Research Today
    Context
    Session Types
    Consistency &
    Programming Models
    Static Analysis &
    Verification
    Other research
    I’ll give a high-level
    overview of these
    

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12. Consistency
    

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13. Consistency?
    Specifically I mean programming models that
    provide some kind of consistency guarantee.
    

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14. Consistency?
    If I have a replica of an object/datum that can be
    updated by another node… What guarantees do I
    have about what all other nodes see?
    Specifically I mean programming models that
    provide some kind of consistency guarantee.
    Example scenario:
    

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15. Consistency?
    Example scenario:
    If I have a replica of an object/datum that can be
    updated by another node… What guarantees do I
    have about what all other nodes see?
    Specifically I mean programming models that
    provide some kind of consistency guarantee.
    Often a developer assumes that they want strong
    consistency (everyone can see the same state). But
    sometimes weak consistency is good enough (not every
    node needs to be in sync before computation can resume)
    

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16. the CAP theorem.
    Consistency?
    Specifically I mean programming models that
    provide some kind of consistency guarantee.
    In the past decade or so, thinking about controlling
    consistency by way of a programming model has
    come out of a famous impossibility result:
    

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17. the CAP theorem.
    A
    Consistency
    Availability
    C P
    Partition Tolerance
    (Linearizability)
    Quickly must state
    

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18. the CAP theorem.
    A
    Consistency
    Availability
    C P
    Partition Tolerance
    (Linearizability)
    Quickly must state
    This has
    been broadly
    interpreted
    as:
    Pick two.
    

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19. Models that can enforce or
    tolerate weaker consistency
    Models like CRDTs choose sides.
    CRDTs
    (Conflict-free replicated data types.)
    

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20. Models that can enforce or
    tolerate weaker consistency
    Models like CRDTs choose sides.
    Such models sacrifice consistency in favor of
    availability.
    CRDTs
    (Conflict-free replicated data types.)
    (People like to call these AP)
    Think:
    Data structures that can be replicated over many nodes.
    When one node updates its replica, a CRDT guarantees
    that eventually all replicas will be eventually consistent.
    

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21. Models that can enforce or
    tolerate weaker consistency
    There has been effort to provide CRDTs as data types
    in functional languages that allow for composition.
    On the CRDTs+ programming model
    front…
    

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22. Models that choose other
    points in the design space
    There is also work experimenting with other edges
    of that triangle.
    

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23. Models that choose other
    points in the design space
    There is also work experimenting with other edges
    of that triangle.
    Meiklejohn’s work on Spry explores whether there’s
    other design points in the space, e.g., CA.
    “Spry is a programming model for building applications
    that want to tradeoff availability and consistency at
    varying points in application code to support application
    requirements.”
    

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24. Models that choose other
    points in the design space
    There is also work experimenting with other edges
    of that triangle.
    Meiklejohn’s work on Spry explores whether there’s
    other design points in the space, e.g., CA.
    “Spry is a programming model for building applications
    that want to tradeoff availability and consistency at
    varying points in application code to support application
    requirements.”
    Can add bounded staleness and freshness
    requirements via annotations!
    

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25. Mixed
    Consistency
    Answers the question of what if we want to choose from
    multiple consistency options in one application?
    Work from the distributed systems
    community takes a step:
    Correctables
    

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26. Mixed
    Consistency
    Answers the question of what if we want to choose from
    multiple consistency options in one application?
    • invokeWeak(operation)
    • invokeStrong(operation)
    • invoke(operation[, levels])
    Give the user different APIs depending on
    the sort of consistency they’re after!
    Correctables
    They provide incremental consistency guarantees by capturing successive
    changes to the value of a replicated object. Applications can opt to receive a fast
    but possibly inconsistent result if eventual consistency is acceptable, or to wait
    for a strongly consistent result.
    

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27. Mixed
    Consistency
    Answers the question of what if we want to choose from
    multiple consistency options in one application?
    Work from the programming languages
    community takes a step:
    MixT
    

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28. Session Types
    

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29. What are they?
    Can be thought of as types for communication protocols
    

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30. What are they?
    Can be thought of as types for communication protocols
    That is, if a program type checks, then it’s guaranteed
    to follow the defined communication protocol.
    

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31. What are they?
    No hanging systems due to an accidental
    message send to the wrong service!
    Can be thought of as types for communication protocols
    That is, if a program type checks, then it’s guaranteed
    to follow the defined communication protocol.
    More concretely:
    

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32. What are they?
    No hanging systems due to an accidental
    message send to the wrong service!
    Can be thought of as types for communication protocols
    Binary & Multiparty Static & Dynamic
    That is, if a program type checks, then it’s guaranteed
    to follow the defined communication protocol.
    More concretely:
    Many variants of session types:
    

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33. What are they?
    Tiny example of implementing SMTP:
    SMTPClient = ⊕ {
    EHLO: !Domain.!FromAddress.!ToAddress.!Message.SMTPClient
    QUIT: end
    }
    great introduction to session types by Simon Fowler:
    http:/
    /simonjf.com/2016/05/28/session-type-implementations.html
    Client side:
    

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34. What are they?
    Tiny example of implementing SMTP:
    SMTPClient = ⊕ {
    EHLO: !Domain.!FromAddress.!ToAddress.!Message.SMTPClient
    QUIT: end
    }
    great introduction to session types by Simon Fowler:
    http:/
    /simonjf.com/2016/05/28/session-type-implementations.html
    Client side:
    means: select between the
    following two branches
    

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35. What are they?
    Tiny example of implementing SMTP:
    SMTPClient = ⊕ {
    EHLO: !Domain.!FromAddress.!ToAddress.!Message.SMTPClient
    QUIT: end
    }
    great introduction to session types by Simon Fowler:
    http:/
    /simonjf.com/2016/05/28/session-type-implementations.html
    Client side:
    EHLO: send (!) domain, from
    address, to address, and the
    message. Repeat.
    means: select between the
    following two branches
    

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36. What are they?
    Tiny example of implementing SMTP:
    SMTPClient = ⊕ {
    EHLO: !Domain.!FromAddress.!ToAddress.!Message.SMTPClient
    QUIT: end
    }
    great introduction to session types by Simon Fowler:
    http:/
    /simonjf.com/2016/05/28/session-type-implementations.html
    Client side:
    EHLO: send (!) domain, from
    address, to address, and the
    message. Repeat.
    QUIT: protocol is over.
    means: select between the
    following two branches
    

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37. What are they?
    SMTPClient = ⊕ {
    EHLO: !Domain.!FromAddress.!ToAddress.!Message.SMTPClient
    QUIT: end
    }
    SMTPServer = & {
    EHLO: ?Domain.?FromAddress.?ToAddress.?Message.SMTPServer
    QUIT: end
    }
    great introduction to session types by Simon Fowler:
    http:/
    /simonjf.com/2016/05/28/session-type-implementations.html
    Tiny example of implementing SMTP:
    Client side:
    Server side:
    

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38. What are they?
    SMTPClient = ⊕ {
    EHLO: !Domain.!FromAddress.!ToAddress.!Message.SMTPClient
    QUIT: end
    }
    SMTPServer = & {
    EHLO: ?Domain.?FromAddress.?ToAddress.?Message.SMTPServer
    QUIT: end
    }
    great introduction to session types by Simon Fowler:
    http:/
    /simonjf.com/2016/05/28/session-type-implementations.html
    Tiny example of implementing SMTP:
    Client side:
    Server side:
    means: offering a choice between
    the following two branches
    

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39. What are they?
    sig smtpClient : (SMTPClient, FromAddress, ToAddress, Message) ~> ()
    fun smtpClient(c, from, to, msg) {
    var c1 = select EHLO c;
    var c2 = send(getDomain(from), c1);
    var c3 = send(from, c2);
    var c4 = send(to, c3);
    var c5 = send(message, c4)
    var c6 = select QUIT c5;
    close c6
    }
    great introduction to session types by Simon Fowler:
    http:/
    /simonjf.com/2016/05/28/session-type-implementations.html
    Tiny example of implementing SMTP:
    Implementation of the client:
    (Implemented in Links)
    

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40. Is this only theory?
    No! There are prototypes of session types
    implemented for many languages!
    C: Multiparty Session C (https://www.doc.ic.ac.uk/~cn06/sessionc/)
    Rust: session-types (https://github.com/Munksgaard/session-types)
    Erlang: monitored-session-erlang (https://github.com/SimonJF/monitored-session-erlang)
    Java: Scribble (https://www.doc.ic.ac.uk/~rhu/scribble/index.html)
    Scala: Ichannels (http://alcestes.github.io/lchannels/)
    Haskell: effect-sessions (https://www.doc.ic.ac.uk/~dorchard/popl16/)
    Python: SPY (https://www.doc.ic.ac.uk/~rn710/spy/)
    

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41. Still interested?
    If you want a friendly
    introduction, check out
    Simon Fowler’s blog article!
    http:/
    /simonjf.com/
    2016/05/28/session-type-
    implementations.html
    Sam
    Lindley
    Phil
    Wadler
    Frank
    Pfenning
    

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42. Zooming out…
    

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43. Some cool
    projects that
    don’t fit neatly
    into these
    categories
    

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44. Whip
    Lucas Waye, Stephen Chong, Christos Dimoulas
    ICFP 2017
    

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45. Whip
    Lucas Waye, Stephen Chong, Christos Dimoulas
    Whip must…
    • …operate under partial deployment
    • …be transparent (don’t touch communication)
    • …be language agnostic
    • …should accommodate the loose coupling of
    modern services and be extensible with wire
    protocols.
    

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46. Paul Chiusano, Arya Irani, Rúnar Bjarnason
    Unison
    under
    development
    

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47. Paul Chiusano, Arya Irani, Rúnar Bjarnason
    Unison
    move computations around which are received
    and interpreted by the receiving node.
    Key idea:
    Functional Haskell-like language, where you can
    

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48. Syndicate
    Tony Garnock-Jones and collaborators
    PhD 2017
    

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49. ML5
    Tom Murphy VII and collaborators
    PhD 2008
    

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50. Function-passing
    Philipp Haller, Heather Miller, Normen Müller
    JFP 2018
    

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51. A bird’s eye
    view of a couple
    of our projects
    that we hope
    will move the
    needle.
    

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52. Statically
    ensuring that
    microservices
    satisfy invariants
    Adelbert Chang
    Getting going on this
    project together.
    

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53. Christopher
    Meiklejohn
    Zeeshan
    Lakhani
    Peter
    Alvaro
    

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54. Statically
    ensuring that
    functions on
    replicated data
    are monotone.
    Kevin Clancy
    

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55. our projects
    Distributed Programming
    Research Today
    (relatively)
    

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56. Ilya Sergey
    University College
    London
    Damien Zufferey
    Max Planck
    Institute for
    Software Systems
    Marc Shapiro
    Sorbonne-
    Université-LIP6 &
    Inria
    ! " #
    Alexy Gotsman
    IMDEA Software
    Institute$
    Sebastian
    Burckhardt
    Microsoft Research
    %
    Tom Van Cutsem
    Nokia Bell Labs
    &
    Suresh Jagannathan
    Purdue University
    %
    Patrick Eugster
    University of Lugano
    '
    James Cheney
    University of
    Edinburgh !
    Wolfgang De Meuter
    Vrije Universiteit
    Brussel
    Tony Garnock-Jones
    University of
    Glasgow !
    Other
    folks
    active in
    this
    space
    

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57. Lotsa References
    Programming Languages conferences
    

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58. Lotsa References
    Programming Languages conferences
    

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59. Lotsa References
    Programming Languages conferences
    

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60. Lotsa References
    Programming Languages conferences
    

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61. Lotsa References
    Programming Languages conferences
    

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62. Lotsa References
    other conferences
    

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63. Lotsa References
    other conferences
    http://bit.ly/dist-prog-refs
    posted online at:
    

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64. Thank you!
    References available:
    (soon)
    http://bit.ly/dist-prog-refs
    posted online at:
    

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