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https://issues.apache.org/jira/browse/GIRAPH-256?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Eli Reisman updated GIRAPH-256:
-------------------------------

    Attachment: GIRAPH-256-5.patch

Went stale after vertex redesign, recent patches to BspServiceWorker. Passes 
'mvn verify' etc., ready for review.


                
> Partitioning outgoing graph data during INPUT_SUPERSTEP by # of vertices 
> results in wide variance in RPC message sizes
> ----------------------------------------------------------------------------------------------------------------------
>
>                 Key: GIRAPH-256
>                 URL: https://issues.apache.org/jira/browse/GIRAPH-256
>             Project: Giraph
>          Issue Type: Improvement
>          Components: bsp, graph
>    Affects Versions: 0.2.0
>            Reporter: Eli Reisman
>            Assignee: Eli Reisman
>              Labels: patch
>             Fix For: 0.2.0
>
>         Attachments: GIRAPH-256-1.patch, GIRAPH-256-2.patch, 
> GIRAPH-256-3.patch, GIRAPH-256-4.patch, GIRAPH-256-5.patch
>
>
> This relates to GIRAPH-247. The unfortunately named 
> "MAX_VERTICES_PER_PARTITION" fooled me into thinking this value was 
> regulating the size of initial Partition objects as they were composed during 
> INPUT_SUPERSTEP from InputSplits each worker reads.
> In fact this configuration option only regulates the size of the outgoing RPC 
> messages, stored locally in Partition objects but decomposed into Collections 
> of BasicVertex for transfer to their eventual homes on another (or this) 
> worker. There they are combined into the actual Partitions they will exist in 
> for the job run.
> By partitioning these outgoing messages by # of vertices, metrics load tests 
> have shown the size of the average message is not well regulated and can 
> create overloads on either side of these transfers. This is important because:
> 1. Throughput and memory are at a premium during INPUT_SUPERSTEP.
> 2. Only one crashed worker in a Giraph job causes cascading job failure, even 
> in an otherwise healthy workflow.
> This JIRA renames the offending variables/config options and further 
> regulates outgoing graph data in INPUT_SUPERSTEP by the # of edges and THEN 
> the # of vertices in a candidate for transfer. This much more effectively 
> regulates message size for typical social graph data and has been show in 
> testing to greatly improve the amount of load-in data Giraph can handle 
> without failure given fixed memory and worker limits.

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