1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
|
---
layout: page
title: "Distributed Programming Languages"
by: "A Systems Person"
---
## Problems of Distributed Programming
* Partial failure
* Consistency (Concurrency)
* Efficiency (Latency)
* Scallability
For the above points cite "A Note on Distributed Computing," "Fallacies of Distributed Computing Explained"
Languages and systems designed for distribution aim to abstract these problems from the application developer.
## Three major approaches to distributed languages:
### Shared Memory
What is it?
Some examples:
* Linda
* Orca
* RPC ( and why RPC is shared-memory )
Tries to make many machines look like a single machine.
This is hard because of consistency and partitioning.
The logic of the program is simple, but requiring that the system handle shared memory opens up many opportunities for performance bugs.
### Actor / Object model
The actor model has its roots in procedural and object oriented programming.
Communication through RPC or message-passing.
Actors/Objects are location agnostic, because state is not shared.
The system can decide how to most efficiently place actors.
* Erlang
* Cloud Haskell
* Emerald
* Argus
* Orleans
### Dataflow model (static and stream)
The dataflow model has its roots in functional programming.
Some languages that use this model are:
* Multilisp
* MapReduce (Spark, Hadoop, etc.)
* RDD
* Dryad, DryadLinq
### 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
## Support for Distribution
### Intro
* What is a DSL?
> Domain-specific languages are languages tailored to a specific application domain.
Another definition:
> A domain-specific language is a programming language or executable specification language that offers, through appropriate notations and abstractions, expressive power focused on, and usually restricted to, a particular problem domain.
### Where is it in the stack?
* Libraries:
* Compiler Extension
* Compiler / Runtime:
* Hardware
### Why GPL's not DSL's?
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"
## References
{% bibliography --file dist-langs %}
|
