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
109
110
111
112
113
114
115
116
117
118
|
---
layout: global
type: "page singular"
title: GraphX
description: GraphX is Apache Spark's API for graphs and graph-parallel computation, with a built-in library of common algorithms.
subproject: GraphX
---
<div class="jumbotron">
<b>GraphX</b> is Apache Spark's API for graphs and graph-parallel computation.
</div>
<div class="row row-padded">
<div class="col-md-7 col-sm-7">
<h2>Flexibility</h2>
<p class="lead">
Seamlessly work with both graphs and collections.
</p>
<p>
GraphX unifies ETL, exploratory analysis, and iterative graph computation within a single system. You can <a href="{{site.baseurl}}/docs/latest/graphx-programming-guide.html#the-property-graph">view</a> the same data as both graphs and collections, <a href="{{site.baseurl}}/docs/latest/graphx-programming-guide.html#property-operators">transform</a> and <a href="{{site.baseurl}}/docs/latest/graphx-programming-guide.html#join-operators">join</a> graphs with RDDs efficiently, and write custom iterative graph algorithms using the <a href="{{site.baseurl}}/docs/latest/graphx-programming-guide.html#pregel-api">Pregel API</a>.
</p>
</div>
<div class="col-md-5 col-sm-5 col-padded-top col-center">
<div style="margin-top: 15px; text-align: left; display: inline-block;">
<div class="code">
graph = <span class="sparkop">Graph</span>(vertices, edges)<br/>
messages = spark.textFile(<span class="string">"hdfs://..."</span>)<br/>
graph2 = graph.<span class="sparkop">joinVertices</span>(messages) {<br/>
<span class="closure">(id, vertex, msg) => ...</span><br/>
}
</div>
<div class="caption">Using GraphX in Scala</div>
</div>
</div>
</div>
<div class="row row-padded">
<div class="col-md-7 col-sm-7">
<h2>Speed</h2>
<p class="lead">
Comparable performance to the fastest specialized graph processing systems.
</p>
<p>
GraphX competes on performance with the fastest graph systems while retaining Spark's flexibility, fault tolerance, and ease of use.
</p>
</div>
<div class="col-md-5 col-sm-5 col-padded-top col-center">
<div style="width: 100%; max-width: 272px; display: inline-block; text-align: center; padding:0;">
<img src="{{site.baseurl}}/images/graphx-perf-comparison.png" style="width: 60%; max-width: 250px;">
<div class="caption" style="min-width: 272px;">End-to-end PageRank performance (20 iterations, 3.7B edges)</div>
</div>
</div>
</div>
<div class="row row-padded">
<div class="col-md-7 col-sm-7">
<h2>Algorithms</h2>
<p class="lead">
Choose from a growing library of graph algorithms.
</p>
<p>In addition to a <a href="{{site.baseurl}}/docs/latest/graphx-programming-guide.html#graph-operators">highly flexible API</a>, GraphX comes with a variety of graph algorithms, many of which were contributed by our users.</p>
</div>
<div class="col-md-5 col-sm-5 col-padded-top">
<ul class="list-narrow">
<li>PageRank</li>
<li>Connected components</li>
<li>Label propagation</li>
<li>SVD++</li>
<li>Strongly connected components</li>
<li>Triangle count</li>
</ul>
</div>
</div>
<div class="row">
<div class="col-md-6 col-padded">
<h3>Community</h3>
<p>
GraphX is developed as part of the Apache Spark project. It thus gets
tested and updated with each Spark release.
</p>
<p>
If you have questions about the library, ask on the
<a href="{{site.baseurl}}/community.html#mailing-lists">Spark mailing lists</a>.
</p>
<p>
GraphX is in the alpha stage and welcomes contributions. If you'd like to submit a change to GraphX,
read <a href="{{site.baseurl}}/contributing.html">how to
contribute to Spark</a> and send us a patch!
</p>
</div>
<div class="col-md-6 col-padded">
<h3>Getting Started</h3>
<p>
To get started with GraphX:
</p>
<ul class="list-narrow">
<li><a href="{{site.baseurl}}/downloads.html">Download Spark</a>. GraphX is included as a module.</li>
<li>Read the <a href="{{site.baseurl}}/docs/latest/graphx-programming-guide.html">GraphX guide</a>, which includes
usage examples.</li>
<li>Learn how to <a href="{{site.baseurl}}/docs/latest/#launching-on-a-cluster">deploy</a> Spark on a cluster
if you'd like to run in distributed mode. You can also run locally on a multicore machine
without any setup.
</li>
</ul>
</div>
</div>
<div class="row">
<div class="col-sm-12 col-center">
<a href="{{site.baseurl}}/downloads.html" class="btn btn-success btn-lg btn-multiline">
Download Apache Spark<br/><span class="small">Includes GraphX</span>
</a>
</div>
</div>
|
