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Diffstat (limited to 'chapter/4')
| -rw-r--r-- | chapter/4/dist-langs.md | 62 |
1 files changed, 31 insertions, 31 deletions
diff --git a/chapter/4/dist-langs.md b/chapter/4/dist-langs.md index c12ea82..a26c42f 100644 --- a/chapter/4/dist-langs.md +++ b/chapter/4/dist-langs.md @@ -395,28 +395,24 @@ In other graph-processing frameworks, results from a graph query would have to b With GraphX, if you can structure your application logic as a series of graph operations, an implementation may be created on top of RDD's. Because many real-world applications, like social media "connections," are naturally expressed as graphs, GraphX can be used to create a highly scalable, fault-tolerant implementation. -### Which is best? Why? - -MR vs Actors: depends on problem, solution - -How fine grain is your data and logic? (MR job can be built from actor model) -Does your algorithm map to a batch processing job? - -MR: - -* MR is DSL for distribution? (wouldn't use it to develop single-machine app (probably)) -* Dataflow / MapReduce fundamentally changed the programming style for distributed systems -* Other models (Actor, DSM) tried to mask distribution -* By changing the style, programs need necessarily consider communication patterns (disk, network) -* Although, system may still handle fault tolerance - -Actors: - -* Message-passing chapter +## Comparing Design + +* level of implementation + * OS + * compiler (language) + * library +* granularity + * logic, state + * course (batch) + * fine (actors) +* abstractions + * location + * scalability + * fault tolerance ## Thoughts on System Design -### Intro +### Domain-Specific Languages The definition of a domain-specific language is a hot topic and there have been several attempts to concretely define what exactly *it* is. @@ -443,22 +439,26 @@ A language may be qualified if it has its own compiler. An orthogonal definition qualifies a language by its style, as in the case of sets of macros. This confusion is why I adopt the even more vague term *system* in my own definition. -### Where is it in the stack? +### Distribution as a Domain + +Given the examples of models and systems, I think it is reasonable to qualify distribution as a domain. +Distributed computing has a unique set of problems, such as fault-tolerance, nondeterminism, network partitioning, and consistency that make it unique from parallel computing on a single machine. +The languages, systems, and models presented here all are built to assist the developer in dealing with these problems. -* Libraries: -* Compiler Extension -* Compiler / Runtime: -* Hardware +### DSL's as Libraries -### Why DSL's as Libraries? +The examples given above demonstrate a trend. +At first, systems designed to tackle the distribution domain were implemented as stand-alone languages. +Later, these systems appear as libraries built on top of existing general-purpose languages. +For many reasons, this style of system development is superior. -Reasons for moving to GPL's as base for DSL's -* problem of domain-composition -* problem of abstraction -* problem of ecosystem -* problem of tumultuous architecture -* "any gpl + library can act as a dsl" - mernik" +#### problem of domain-composition + * domains may be orthogonal -> can be composed +#### problem of abstraction +#### problem of ecosystem +#### problem of tumultuous architecture +#### "any gpl + library can act as a dsl" - mernik" ## References |