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This page explains how to setup and use the Simudyne SDK to distribute a single simulation using Spark and Akka.\nSpark is used as a cluster management tool while Akka manages all the communication logic.

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Distributed Graph Backend

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The distributed graph backend allows you to run large graphs on a cluster of machines.\nRunning a distributed graph simulation depends on the core-graph-distributed package which needs to be imported in your project:

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pom.xml

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<dependency>\n    <groupId>simudyne</groupId>\n    <artifactId>simudyne-core-graph-distributed_2.11</artifactId>\n    <version>${simudyne.version}</version>\n</dependency>
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Simudyne has two implementations of the distributed graph. One runs locally using subprocesses and can be used for testing purposes. This implementation does NOT require Spark.\nThe other implementation distributes the load using Spark and thus needs to be provided with a working Spark cluster.

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Testing model in distributed environment

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Aimed towards model developers, we have included a way of running distributed graph using subprocesses,\nwithout need for spark, in order to establish model's compatibility and distributed-graph readiness.

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Properties

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Both implementations share the same main properties.

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You need to configure the properties related to core-graph-distributed.\nYou have two possibilities to configure them:

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Some properties are already listed with default values in simudyneSDK.properties:

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### CORE ABM distributed (experimental)\n# core.graph.experimental.timeouts.base=240\ncore.graph.experimental.clusterSize=3
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Limitations

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The Distributed graph comes with limitations, most notable being:
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  • no support for Immutable Schema, please set feature.immutable-schema=false
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  • no support for dynamic agent creation/stopping
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  • no support for SystemMessages
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    You also might want to disable the health check for models by setting nexus-server.health-check to false in order to avoid their distribution.

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    Local Implementation

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    To test your model running on Distributed Graph, add the following lines to your properties file:

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    simudyneSDK.properties

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    core-abm.backend-implementation=simudyne.core.graph.experimental.dig.treelike.backend.SubprocessBackend\nfeature.immutable-schema=false
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    You can then start the server and control the simulation through the Console or the REST API without further configuration.

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    Cluster Implementation

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    To let Spark manage nodes of the Distributed Graph implementation, add the following:

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    simudyneSDK.properties

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    core-abm.backend-implementation=simudyne.core.graph.experimental.dig.treelike.backend.spark.ClusterBackend\ncore.graph.experimental.distributed.master-url=local[*]\ncore.graph.experimental.distributed.log-level=WARN\nfeature.immutable-schema=false
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    Please be aware that properties set in simudyneSDK.properties file takes precedence over options passed to spark-submit.

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    You can then submit your job using spark-submit. Here is an example:

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    spark-submit --class Main --master yarn  --deploy-mode client --files simudyneSDK.properties,licenseKey hdfs://path/name-of-the-fat-jar.jar
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    This command will run the main function of the class Main and distribute it on Spark. You can then access the console through the config parameters nexus-server.hostname and nexus-server.port.\nThey default to localhost and 8080. You can also interact with the server through the REST API

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    spark-submit allows you to configure Spark. You need to choose a configuration that best suits your cluster.\nTo learn more about Spark configuration, refer to the official documentation.

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    Some useful resources can be found on Cloudera's website.

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