Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
Large scale graph processing with apache giraph
Search
André Kelpe
May 23, 2012
Programming
2
5.4k
Large scale graph processing with apache giraph
André Kelpe
May 23, 2012
Tweet
Share
More Decks by André Kelpe
See All by André Kelpe
Cascading 3 and beyond
fs111
0
160
The Cascading (big) data application framework
fs111
1
230
SELECT ALL THE THINGS - Cascading Lingual, ANSI SQL for Apache Hadoop
fs111
0
200
A whirlwind tour through Lingual: ANSI SQL for Apache Hadoop
fs111
1
190
Tor for everyone!
fs111
0
170
Other Decks in Programming
See All in Programming
Monixと常駐プログラムの勘どころ / Scalaわいわい勉強会 #4
stoneream
0
270
命名をリントする
chiroruxx
1
390
14 Years of iOS: Lessons and Key Points
seyfoyun
1
770
Асинхронность неизбежна: как мы проектировали сервис уведомлений
lamodatech
0
700
CQRS+ES の力を使って効果を感じる / Feel the effects of using the power of CQRS+ES
seike460
PRO
0
120
Security_for_introducing_eBPF
kentatada
0
110
PHPとAPI Platformで作る本格的なWeb APIアプリケーション(入門編) / phpcon 2024 Intro to API Platform
ttskch
0
150
Beyond ORM
77web
2
330
Scalaから始めるOpenFeature入門 / Scalaわいわい勉強会 #4
arthur1
1
300
【re:Growth 2024】 Aurora DSQL をちゃんと話します!
maroon1st
0
770
talk-with-local-llm-with-web-streams-api
kbaba1001
0
180
ドメインイベント増えすぎ問題
h0r15h0
1
220
Featured
See All Featured
Optimising Largest Contentful Paint
csswizardry
33
3k
Easily Structure & Communicate Ideas using Wireframe
afnizarnur
191
16k
Being A Developer After 40
akosma
87
590k
Building Adaptive Systems
keathley
38
2.3k
How STYLIGHT went responsive
nonsquared
95
5.2k
The Psychology of Web Performance [Beyond Tellerrand 2023]
tammyeverts
45
2.2k
Improving Core Web Vitals using Speculation Rules API
sergeychernyshev
0
97
BBQ
matthewcrist
85
9.4k
Sharpening the Axe: The Primacy of Toolmaking
bcantrill
38
1.9k
For a Future-Friendly Web
brad_frost
175
9.4k
Rails Girls Zürich Keynote
gr2m
94
13k
Design and Strategy: How to Deal with People Who Don’t "Get" Design
morganepeng
127
18k
Transcript
Large scale graph processing with apache giraph André Kelpe @fs111
http://kel.pe
graphs 101
vertices and edges
v2 v5 v4 v7 v3 v8 v6 v1 v9 v8
v10 simple graph
graphs are everywhere road network, the www, social graphs etc.
graphs can be huge
google knows!
Pregel
Pregel by google Describes graph processing approach based on BSP
(Bulk Synchronous Parallel)
pro-tip: search for „pregel_paper.pdf“ on github ;-)
Properties of Pregel batch-oriented, scalable, fault tolerant processing of graphs
It is not a graph database It is a processing
framework
BSP vertex centric processing in so called supersteps
BSP vertices send messages to each other
BSP synchronization points between supersteps
execution of superstep S Each vertex processes messages generated in
S-1 and send messages to be processed in S+1 and determines to halt.
None
apache giraph
giraph Loose implementation of Pregel ideas on top of Hadoop
M/R coming from yahoo
apache giraph http://incubator.apache.org/giraph/
giraph avoid overhead of classic M/R process but reuse existing
infrastructure
giraph simple map jobs in master worker setup. coordination via
zookeeper. messaging via own RPC protocol. in memory processing. custom input and output formats.
current status version 0.1 released compatible with a multitude of
hadoop versions (we use CDH3 at work) still lots of things to do, join the fun!
the APIs the APIs
Vertex-API /** *@param <I> vertex id * @param <V> vertex
data * @param <E> edge data * @param <M> message data */ class BasicVertex<I extends WritableComparable, V extends Writable, E extends Writable, M extends Writable> void compute(Iterator<M> msgIterator); void sendMsg(I id, M msg); void voteToHalt();
Shortest path example https://cwiki.apache.org/confl uence/display/GIRAPH/Shorte st+Paths+Example
v2 v5 v4 v7 v3 v8 v6 v1 v9 v8
v10 simple graph
private boolean isSource() { return (getVertexId().get() == getContext().getConfiguration().getLong(SOURCE_ID, SOURCE_ID_DEFAULT)); }
@Override public void compute(Iterator<DoubleWritable> msgIterator) { if (getSuperstep() == 0) { setVertexValue(new DoubleWritable(Double.MAX_VALUE)); } double minDist = isSource() ? 0d : Double.MAX_VALUE; while (msgIterator.hasNext()) { minDist = Math.min(minDist, msgIterator.next().get()); } if (minDist < getVertexValue().get()) { setVertexValue(new DoubleWritable(minDist)); for (Edge<LongWritable, FloatWritable> edge : getOutEdgeMap().values()) { sendMsg(edge.getDestVertexId(), new DoubleWritable(minDist + edge.getEdgeValue().get())); } } voteToHalt(); }
GiraphJob job = new GiraphJob(getConf(), getClass().getName()); job.setVertexClass(SimpleShortestPathVertex.class); job.setVertexInputFormatClass(SimpleShortestPathsVertexInputFormat.class); job.setVertexOutputFormatClass( SimpleShortestPathsVertexOutputFormat.class);
FileInputFormat.addInputPath(job, new Path(„/foo/bar/baz“)); FileOutputFormat.setOutputPath(job, new Path(„/foo/bar/quux“)); job.getConfiguration().setLong(SimpleShortestPathsVertex.SOURCE_ID, Long.parseLong(argArray[2])); job.setWorkerConfiguration(minWorkers, maxWorkers), 100.0f); GiraphJob
see also http://incubator.apache.org/giraph/ https://cwiki.apache.org/confluence/displ ay/GIRAPH/Shortest+Paths+Example http://googleresearch.blogspot.com/2009/ 06/large-scale-graph-computing-at- google.html
Thanks! Questions?