Train job stuck executing

I’ve followed the quick start guide: https://actionml.com/docs/h_ur_quickstart

My config.json is as follows:

{
    "engineId": "2",
    "engineFactory": "com.actionml.engines.ur.UREngine",
    "sparkConf": {
        "spark.serializer": "org.apache.spark.serializer.KryoSerializer",
        "spark.kryo.registrator": "org.apache.mahout.sparkbindings.io.MahoutKryoRegistrator",
        "spark.kryo.referenceTracking": "false",
        "spark.kryoserializer.buffer": "300m",
        "spark.executor.memory": "3g",
        "spark.driver.memory": "3g",
        "spark.es.index.auto.create": "true",
        "spark.es.nodes": "harness-docker-compose_elasticsearch_1",
        "spark.es.nodes.wan.only": "true"
    },
    "algorithm":{
        "indicators": [
            {
                "name": "buy"
            },{
                "name": "view"
            }
        ]
    }
}

I run harness-cli train 2 and when I check harness-cli status engines 2 I see:

/harness-cli/harness-cli/harness-status: line 10: /harness-cli/harness-cli/RELEASE: No such file or directory
Harness CLI v settings
==================================================================
HARNESS_CLI_HOME ........................ /harness-cli/harness-cli
HARNESS_CLI_SSL_ENABLED .................................... false
HARNESS_CLI_AUTH_ENABLED ................................... false
HARNESS_SERVER_ADDRESS ................................... harness
HARNESS_SERVER_PORT ......................................... 9090
==================================================================
Harness Server status: OK
Status for engine-id: 2
{
    "engineParams": {
        "algorithm": {
            "indicators": [
                {
                    "name": "buy"
                },
                {
                    "name": "view"
                }
            ]
        },
        "engineFactory": "com.actionml.engines.ur.UREngine",
        "engineId": "2",
        "sparkConf": {
            "spark.driver.memory": "3g",
            "spark.es.index.auto.create": "true",
            "spark.es.nodes": "harness-docker-compose_elasticsearch_1",
            "spark.es.nodes.wan.only": "true",
            "spark.executor.memory": "3g",
            "spark.kryo.referenceTracking": "false",
            "spark.kryo.registrator": "org.apache.mahout.sparkbindings.io.MahoutKryoRegistrator",
            "spark.kryoserializer.buffer": "300m",
            "spark.serializer": "org.apache.spark.serializer.KryoSerializer"
        }
    },
    "jobStatuses": {
        "ed0becbf-ce7d-4e62-822d-2e3f2138e235": {
            "comment": "Spark job",
            "jobId": "ed0becbf-ce7d-4e62-822d-2e3f2138e235",
            "status": {
                "name": "executing"
            }
        }
    }
}

The job never moves from executing, is there anyway I can debug why this is happening?

I’ve set harness up by following https://actionml.com/docs/harness_container_guide

[dataedgehungary]

The

org.apache.spark.SparkException: A master URL must be set in your configuration

ERROR is solved by adding “master”: “local” according to the documentation:

https://actionml.com/docs/h_ur_config#spark-parameters-codesparkconfcode

{
   "engineId": "ecom_ur",
   "engineFactory": "com.actionml.engines.ur.UREngine",
   "sparkConf": {
       "master": "local",
       "spark.serializer": "org.apache.spark.serializer.KryoSerializer",
       "spark.kryo.registrator": "org.apache.mahout.sparkbindings.io.MahoutKryoRegistrator",
       "spark.kryo.referenceTracking": "false",
       "spark.kryoserializer.buffer": "300m",
       "spark.executor.memory": "20g",
       "spark.driver.memory": "10g",
       "spark.es.index.auto.create": "true",
       "spark.es.nodes": "localhost",
       "spark.es.nodes.wan.only": "true"
   },
   "algorithm":{
       "indicators": [ 
           {
               "name": "buy"
           }
       ]
   }
}

[mick912]

Thank you!