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Using a Graph Database for JVM Heap Analysis

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Summary

James Richardson, Nat Pryce discuss some of the challenges faced using Neo4J for interactive analysis of large data imports (80K nodes, 150k relationships) and how they overcame them.

Bio

Nat Pryce is a co-author of Growing Object-Oriented Software Guided by Tests. An early adopter of XP, he has written or contributed to several open source libraries and tools that support TDD and was one of the founding organizers of the London XP Day conference. James Richardson

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ACCU is an organisation for anyone interested in developing and improving programming skills. ACCU welcomes everyone who is interested in any programming language. ACCU supports its members by hosting mailing lists, running a yearly conference, publishing journals and organising online study groups.

Recorded at:

Mar 19, 2015

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Community comments

  • 80K nodes is tiny...trying 80 million nodes and doing that in a few seconds

    by William Louth /

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    Creating New Software Memories from Simulated Episodic Memory Recall
    vimeo.com/121273568

    This video demonstrates how during the recollection of a software machine episodic memory new memories can be created of a very different nature. An integration with Neo4j, a graph database, is deployed into a simulated machine (dream sequencing) whereby it intercepts the simulated entering and exiting of method call invocations by individual threads and creates corresponding nodes (threads, frames and names) within a graph database for visualization and ad hoc querying. The original recording was created by deploying the Satoris agent into a JVM running the Apache Cassandra NoSQL database with the stenos metering extension enabled.

    The interception code can be found here: gist.github.com/autoletics/fafbffedfbb13176e4fa

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    by Charles Humble /

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    We're sorry about the sound quality on this video. We couldn't get a feed from the clip mics and had to rely on room audio.

    Charles Humble
    Head of editorial, InfoQ

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