Providing Serializability for Pregel-like Graph Processing ...
Pregel : A System for Large-Scale Graph Processing
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Transcript of Pregel : A System for Large-Scale Graph Processing
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Pregel: A System for Large-Scale Graph
ProcessingPresented by Dylan Davis
Authors: Grzegorz Malewicz, Matthew H. Austern, Aart J.C. Bik, James C. Dehnert, Ilan Horn, Naty Leiser, Grzegorz Czajkowski
(GOOGLE, INC.)
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Overview•What is a graph?•Graph Problems• The Purpose of Pregel•Model of Computation•C++ API• Implementation•Applications• Experiments
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What is a graph?G = (V, E)
Binary Tree
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Graph Problems
Network Routing Social Network Connections
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The Purpose of Pregel•Google was interested in applications that could perform internet-related graph algorithms, such as PageRank, so they designed Pregel to perform these tasks efficiently.• It is a scalable, general-purpose system for implementing graph algorithms in a distributed environment.•Focus on “Thinking Like a Vertex” and parallelism
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Model of Computation
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Model of Computation (Vertex)
Vertex ID
Vertex Value
Edge ValueVertex
ID
Vertex ID
Edge Value
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Model of Computation (Superstep)Superstep 0 Superstep 1 Superstep 2
Execution Time
Compute()
Compute()
Compute() Compute()
Compute()
Compute() Compute()
Compute()
Compute()
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Model of Computation (Vertex Actions)
A vertex can:
Vertex ID
Vertex Value
• Modify its values• Receive messages from
previous superstep• Send messages• Request topology changes
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Model of Computation (State Machine)
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C++ API
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C++ API (Message Passing)Destination
Vertex IDMessage
Value
2 571 2
Message Buffer
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C++ API (Combiners & Aggregators)
Combiner Aggregator
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C++ API (Topology Mutations)V
Superstep
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C++ API (Input and Output)0 1 2 3 4
0 0 0 1 1 01 0 0 0 1 12 1 1 0 1 13 0 1 1 0 14 1 1 1 0 0
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Implementation
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Implementation (Basic Architecture)
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Implementation (Program Execution)
Flow:1. Copy user program – Master copy & worker copies2. Master assigns graph partitions3. Master takes user input data, assigns to workers –
load vertex data4. Supersteps (Compute() and send messages)5. Save output
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Implementation (Fault Tolerance)Checkpoint
WorkerSave()
WorkerSave()
WorkerSave()
Recover
WorkerRecompute()
WorkerWorker
Recompute()X
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Implementation (Worker)
Worker Worker
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Implementation (Master)List of
WorkersMaster
Partitions
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Applications
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Applications (Shortest Path)2 1
5
3
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Experiments
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Experiments (Description)• Test the execution times of Pregel running the Single-
Source Shortest Path algorithm. •Use a cluster of 300 multicore commodity PCs.•Run Pregel with Binary Tree graphs, and with a more
realistic, randomly-distributed graph. •Results do not include initialization, graph generation,
and result verification times.• Failure Recovery is not included (reduces overhead)
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Conclusion•Pregel is a model suitable for large-scale graph computing
with a production-quality, scalable and fault tolerant implementation.
•Programs are expressed as a sequence of iterations, in each of which a vertex can receive messages sent in the previous iteration, send messages to other vertices, and modify its own state and that of its outgoing edges.
•This implementation is flexible enough to express a broad set of algorithms.