With Contract: Maybe, String, Bool => Maybe At: uri:classloader:/emr-etl-runner/lib/snowplow-emr-etl-runner/cli.rb:211

For engineers Enrichment
1

Getting error while running emrEtlRunner

Value guarded in: Snowplow::EmrEtlRunner::Cli::load_config
        With Contract: Maybe, String, Bool => Maybe
        At: uri:classloader:/emr-etl-runner/lib/snowplow-emr-etl-runner/cli.rb:211

my config is

aws:
  # Credentials can be hardcoded or set in environment variables
  access_key_id: abc
  secret_access_key:def
  s3:
    region: us-east-1
    buckets:
      assets: s3://snowplow-assets
      log: s3n://snowplow-etl/logs/
      raw:
        in: 
          - "s3n://snowplow-events/"
        processing: s3n://snowplow-etl/processing/
        archive: s3://snowplow-archive/raw
      enriched:
        good: s3://snowplow-data/enriched/good
        bad: s3://snowplow-data/enriched/bad
        errors: s3://snowplow-data/enriched/errors
        archive: s3://snowplow-data/enriched/archive
      shredded:
        good: s3://snowplow-data/shredded/good
        bad: s3://snowplow-data/shredded/bad
        errors: s3://snowplow-data/shredded/errors
  emr:
    job_name: Snowplow ETL # Give your job a name
    ami_version: 5.9.0      # Don't change this
    region: us-east-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-082251e665ce25c17  # Set this if running in VPC. Leave blank otherwise
    ec2_key_name: nmj
    bootstrap: []           # Set this to specify custom boostrap actions. Leave empty otherwise
    software:
      hbase: "0.92.0"                # Optional. To launch on cluster, provide version, "0.92.0", keep quotes. Leave empty otherwise.
      lingual: "1.1"             # Optional. To launch on cluster, provide version, "1.1", keep quotes. Leave empty otherwise.
    # Adjust your Spark cluster below
    jobflow:
      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: 100    # 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
    additional_info:        # Optional JSON string for selecting additional features
collectors:
  format: cloudfront # Or 'clj-tomcat' for the Clojure Collector, or 'thrift' for Thrift records, or 'tsv/com.amazon.aws.cloudfront/wd_access_log' for Cloudfront access logs
enrich:
  versions:
    spark_enrich: 1.10.0 # 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_shredder: 0.13.0        # Version of the Relational Database Shredding process
    rdb_loader: 0.14.0          # Version of the Relational Database Loader app
    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
    app_id: ID-ap001
    collector: klk.cloudfront.net # e.g. d3rkrsqld9gmqf.cloudfront.net
2

@Haseeb717, could you provide the formatted config, please, (in between the triple ticks). Indentation is very important when it comes to troubleshooting loading/parsing the configuration file. Also, what version of EmrEtlRunner do you use? Configuration files have different structures from version to version.

3

Question Updated with formatted config
I am using this version

http://dl.bintray.com/snowplow/snowplow-generic/snowplow_emr_r117_biskupin.zip
4

Might not be the exact issue here but ‘cloudfront’ isn’t a valid value for format (see the comment).

5

@Haseeb717, it does appear you are using configuration format for older EmrEtlRunner. Could you, please, check your config against this version. You will find a few discrepancies. Once corrected, the configuration should be accepted.

As a hint, job_name is in the wrong place as well as some properties are missing like encrypted, consolidate_shredded_output, etc.

6

Hi @ihor
Thank you for your reply .
Yeah I update my config exactly with the link you send

aws:
  # Credentials can be hardcoded or set in environment variables
  access_key_id: ID
  secret_access_key: Key
  s3:
region: us-east-1
buckets:
  assets: s3://snowplow-assets # DO NOT CHANGE unless you are hosting the jarfiles etc yourself in your own bucket
  jsonpath_assets: # If you have defined your own JSON Schemas, add the s3:// path to your own JSON Path files in your own bucket here
  log: s3n://snowplow-etl/logs/
  encrypted: false # Whether the buckets below are enrcrypted using server side encryption (SSE-S3)
  raw:
    in:                  # This is a YAML array of one or more in buckets - you MUST use hyphens before each entry in the array, as below
      - "s3n://snowplow-events/"       # e.g. s3://my-old-collector-bucket
    processing: s3n://snowplow-etl/processing/
    archive: s3://snowplow-archive/raw
  enriched:
    good: s3://snowplow-data/enriched/good
    bad: s3://snowplow-data/enriched/bad
    errors: s3://snowplow-data/enriched/errors
    archive: s3://snowplow-data/enriched/archive
  shredded:
    good: s3://snowplow-data/shredded/good
    bad: s3://snowplow-data/shredded/bad
    errors: s3://snowplow-data/shredded/errors
    archive: s3://snowplow-data/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      # Don't change this
region: us-east-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-082251e665ce25c17"  # Set this if running in VPC. Leave blank otherwise
ec2_key_name: "tolga"
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: "0.92.0"                # Optional. To launch on cluster, provide version, "0.92.0", keep quotes. Leave empty otherwise.
  lingual: "1.1"             # Optional. To launch on cluster, provide version, "1.1", keep quotes. Leave empty otherwise.
# Adjust your Spark cluster below
jobflow:
  job_name: Snowplow ETL # Give your job a name
  master_instance_type: m1.medium
  core_instance_count: 2
  core_instance_type: m1.medium
  core_instance_bid: 0.015
  core_instance_ebs:    # Optional. Attach an EBS volume to each core instance.
    volume_size: 100    # 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: cloudfront # 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: 1.18.0 # 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: ID # e.g. snowplow
collector: d3qhcvxu0vb.cloudfront.net # e.g. d3rkrsqld9gmqf.cloudfront.net

But now I get another error
ERROR: org.jruby.embed.EvalFailedException: (ArgumentError) AWS EMR API Error (AccessDeniedException):

Is it due to config or my IAM Rules?

7

Yes - this sounds like an IAM issue that the user / role doesn’t have permissions to create an EMR cluster.