ArgumentError running EmrEtlRunner: wrong number of arguments (2 for 1)

I’m trying to run my first Snowplow EMR job, but the executable is giving me a difficult to debug error.

$ ./snowplow-emr-etl-runner run -c snowplow-emr-config.yml -r iglu-resolver.json

[2019-06-27T00:26:36.571309 #15957] DEBUG -- : Initializing EMR jobflow
ArgumentError: wrong number of arguments (2 for 1)
          failure_callback at uri:classloader:/emr-etl-runner/lib/snowplow-emr-etl-runner/contracts.rb:501
  block in redefine_method at uri:classloader:/gems/contracts-0.11.0/lib/contracts/method_handler.rb:143
                initialize at uri:classloader:/emr-etl-runner/lib/snowplow-emr-etl-runner/emr_job.rb:501
                   send_to at uri:classloader:/gems/contracts-0.11.0/lib/contracts/method_reference.rb:43
                 call_with at uri:classloader:/gems/contracts-0.11.0/lib/contracts/call_with.rb:76
  block in redefine_method at uri:classloader:/gems/contracts-0.11.0/lib/contracts/method_handler.rb:138
                       run at uri:classloader:/emr-etl-runner/lib/snowplow-emr-etl-runner/runner.rb:135
                   send_to at uri:classloader:/gems/contracts-0.11.0/lib/contracts/method_reference.rb:43
                 call_with at uri:classloader:/gems/contracts-0.11.0/lib/contracts/call_with.rb:76
  block in redefine_method at uri:classloader:/gems/contracts-0.11.0/lib/contracts/method_handler.rb:138
                    <main> at uri:classloader:/emr-etl-runner/bin/snowplow-emr-etl-runner:41
                      load at org/jruby/RubyKernel.java:994
                    <main> at uri:classloader:/META-INF/main.rb:1
                   require at org/jruby/RubyKernel.java:970
                    (root) at uri:classloader:/META-INF/main.rb:1
                    <main> at uri:classloader:/META-INF/jruby.home/lib/ruby/stdlib/rubygems/core_ext/kernel_require.rb:1
ERROR: org.jruby.embed.EvalFailedException: (ArgumentError) wrong number of arguments (2 for 1)

Here’s my EMR config.

aws:
  # Credentials can be hardcoded or set in environment variables
  access_key_id: xx
  secret_access_key: xx
  s3:
    region: us-west-1
    buckets:
      assets: s3://snowplow-hosted-assets
      jsonpath_assets:
      log: s3://tjw-snowplow/log
      encrypted: false
      raw:
        in:
          - s3://elasticbeanstalk-us-west-1-002031781174/resources/environments/logs/publish/e-jwqyebkbwz/ 
        processing: s3://tjw-snowplow/raw/processing
        archive: s3://tjw-snowplow/raw/processing
      enriched:
        good: s3://tjw-snowplow/enriched/good
        bad: s3://tjw-snowplow/enriched/bad
        errors: s3://tjw-snowplow/enriched/errors     
        archive: s3://tjw-snowplow/enriched/archive    
      shredded:
        good: s3://tjw-snowplow/shredded/good
        bad: s3://tjw-snowplow/shredded/bad
        errors: s3://tjw-snowplow/shredded/errors     # Leave blank unless :continue_on_unexpected_error: set to true below
        archive: s3://tjw-snowplow/shredded/archive    # Where to archive shredded events to, e.g. s3://my-archive-bucket/shredded
    consolidate_shredded_output: false # Whether to combine files when copying from hdfs to s3
  emr:
    ami_version: 5.9.0
    region: us-west-1        # Always set this
    jobflow_role: EMR_EC2_DefaultRole # Created using $ aws emr create-default-roles
    service_role: EMR_DefaultRole     # Created using $ aws emr create-default-roles
    placement:      # Set this if not running in VPC. Leave blank otherwise
    ec2_subnet_id: subnet-8d7567ea # Set this if running in VPC. Leave blank otherwise
    ec2_key_name: tjw_rsa_id
    security_configuration:  # Specify your EMR security configuration if needed. Leave blank otherwise
    bootstrap: []           # Set this to specify custom boostrap actions. Leave empty otherwise
    software:
      hbase:                # Optional. To launch on cluster, provide version, "0.92.0", keep quotes. Leave empty otherwise.
      lingual:              # Optional. To launch on cluster, provide version, "1.1", keep quotes. Leave empty otherwise.
    # Adjust your Hadoop cluster below
    jobflow:
      job_name: Snowplow_test_ETL # Give your job a name
      master_instance_type: m1.medium
      core_instance_count: 2
      core_instance_type: m1.medium
      core_instance_ebs:    # Optional. Attach an EBS volume to each core instance.
        volume_size: 10    # Gigabytes
        volume_type: "gp2"
        volume_iops: 400    # Optional. Will only be used if volume_type is "io1"
        ebs_optimized: false # Optional. Will default to true
      task_instance_count: 0 # Increase to use spot instances
      task_instance_type: m1.medium
      task_instance_bid: 0.015 # In USD. Adjust bid, or leave blank for non-spot-priced (i.e. on-demand) task instances
    bootstrap_failure_tries: 3 # Number of times to attempt the job in the event of bootstrap failures
    configuration:
      yarn-site:
        yarn.resourcemanager.am.max-attempts: "1"
      spark:
        maximizeResourceAllocation: "true"
    additional_info:        # Optional JSON string for selecting additional features
collectors:
  format: clj-tomcat # For example: 'clj-tomcat' for the Clojure Collector, 'thrift' for Thrift records, 'tsv/com.amazon.aws.cloudfront/wd_access_log' for Cloudfront access logs or 'ndjson/urbanairship.connect/v1' for UrbanAirship Connect events
enrich:
  versions:
    spark_enrich: 1.17.0 # Version of the Spark Enrichment process
  continue_on_unexpected_error: false # Set to 'true' (and set :out_errors: above) if you don't want any exceptions thrown from ETL
  output_compression: NONE # Compression only supported with Redshift, set to NONE if you have Postgres targets. Allowed formats: NONE, GZIP
storage:
  versions:
    rdb_loader: 0.14.0
    rdb_shredder: 0.13.1        # Version of the Spark Shredding process
    hadoop_elasticsearch: 0.1.0 # Version of the Hadoop to Elasticsearch copying process
monitoring:
  tags: {} # Name-value pairs describing this job
  logging:
    level: DEBUG # You can optionally switch to INFO for production
  # snowplow:
  #   method: get
  #   protocol: http
  #   port: 80
  #   app_id: ADD HERE # e.g. snowplow
  #   collector: ADD HERE # e.g. d3rkrsqld9gmqf.cloudfront.net

It is this line on the current version that’s throwing the error.

Has anyone else had a similar issue? Is my config somehow broken?

I was able to resolve this by using a different version of the EmrEtlRunner [snowplow_emr_r109_lambaesis instead of snowplow_emr_r116_madara_rider_rc2].

So can see the clusters are at least starting now.

@tjwaterman99, if you were running R114 when you got ArgumentError then yes, downgrading/upgrading should have resolved this. There appears to be a bug in R114 that occasionally could produce that error.

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