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https://issues.apache.org/jira/browse/HAMA-642?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13478892#comment-13478892
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Thomas Jungblut commented on HAMA-642:
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Okay new requirements:
- linked structure on disk for iterating sequentially
- updates for vertices without requiring a certain alignment
If you assume that vertices always change if they are active, maybe it is
better to write the complete vertices in every superstep with their values etc.
The problem obviously is that this is like mapreduce without sorting.
However I think we can use a prefetch cache to preread vertices before the
compute function, so we can speedup the slow reads a bit.
> Make GraphRunner disk based
> ---------------------------
>
> Key: HAMA-642
> URL: https://issues.apache.org/jira/browse/HAMA-642
> Project: Hama
> Issue Type: Improvement
> Components: graph
> Affects Versions: 0.5.0
> Reporter: Thomas Jungblut
> Assignee: Thomas Jungblut
> Attachments: HAMA-642_unix_1.patch, HAMA-642_unix_2.patch,
> HAMA-642_unix_3.patch, HAMA-scale_1.patch, HAMA-scale_2.patch,
> HAMA-scale_3.patch, HAMA-scale_4.patch
>
>
> To improve scalability we can improve the graph runner to be disk based.
> Which basically means:
> - We have just a single Vertex instance that get's refilled.
> - We directly write vertices to disk after partitioning
> - In every superstep we iterate over the vertices on disk, fill the vertex
> instance and call the users compute functions
> Problems:
> - State other than vertex value can't be stored easy
> - How do we deal with random access after messages have arrived?
> So I think we should make the graph runner more hybrid, like using the queues
> we have implemented in the messaging. So the graphrunner can be configured to
> run completely on disk, in cached mode or in in-memory mode.
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