Incorrect IP Address in the batch pipeline


I have many events in Redshift with IP Addresses as 2, 2001, 2003, 2401, 2402, 2405, 2406, 2407, 2409, 2600, 2601, 2604, 2620, and 2804.

Sharing the EmrEtlRunner config file

  # Credentials can be hardcoded or set in environment variables
  access_key_id: ###
  secret_access_key: ###
    region: us-east-1
      assets: s3://snowplow-hosted-assets # DO NOT CHANGE unless you are hosting the jarfiles etc yourself in your own bucket
      jsonpath_assets: s3://snowplow-iglu-repository-replica/jsonpaths
      log: s3://snowplow-emretl-enricher/logs
        in:                  # This is a YAML array of one or more in buckets - you MUST use hyphens before each entry in the array, as below
          - s3://snowplow-tracking-unenriched        # e.g. s3://my-old-collector-bucket
        processing: s3://snowplow-emretl-enricher/raw/processing-new
        #processing: s3://snowplow-emretl-enricher/raw/archive/run=2018-01-20-12-00-19
        archive: s3://snowplow-emretl-enricher/raw/archive
        good: s3://snowplow-emretl-enricher/enriched/good       # e.g. s3://my-out-bucket/enriched/good
        bad: s3://snowplow-emretl-enricher/enriched/bad        # e.g. s3://my-out-bucket/enriched/bad
        errors: s3://snowplow-emretl-enricher/enriched/errors     # Leave blank unless :continue_on_unexpected_error: set to true below
        archive: s3://snowplow-emretl-enricher/enriched/archive    # Where to archive enriched events to, e.g. s3://my-archive-bucket/enriched
        good: s3://snowplow-emretl-enricher/shredded/good       # e.g. s3://my-out-bucket/shredded/good
        bad: s3://snowplow-emretl-enricher/shredded/bad        # e.g. s3://my-out-bucket/shredded/bad
        errors: s3://snowplow-emretl-enricher/shredded/errors     # Leave blank unless :continue_on_unexpected_error: set to true below
        archive: s3://snowplow-emretl-enricher/shredded/archive    # Where to archive enriched events to, e.g. s3://my-archive-bucket/enriched
    ami_version: 5.5.0
    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-e0edddec # Set this if running in VPC. Leave blank otherwise
    ec2_key_name: snowplow-emr
    bootstrap: []           # Set this to specify custom boostrap actions. Leave empty otherwise
      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
      job_name: Snowplow EMR ETL # Give your job a name
      master_instance_type: m4.xlarge
      core_instance_count: 4
      core_instance_type: m4.xlarge
      core_instance_ebs:    # Optional. Attach an EBS volume to each core instance.
        volume_size: 200    # Gigabytes
        volume_type: "gp2"
        volume_iops: 800    # 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: m4.xlarge
      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
      yarn-site: "1"
          maximizeResourceAllocation: "true"
      additional_info:        # Optional JSON string for selecting additional features
    format: thrift # For example: 'clj-tomcat' for the Clojure Collector, 'thrift' for Thrift records, 'tsv/' for Cloudfront access logs or 'ndjson/urbanairship.connect/v1' for UrbanAirship Connect events
      spark_enrich: 1.9.0 # Version of the Spark Enrichment process
    continue_on_unexpected_error: true # 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
      rdb_loader: 0.12.0
      rdb_shredder: 0.12.0        # Version of the Spark Shredding process
      hadoop_elasticsearch: 0.1.0 # Version of the Hadoop to Elasticsearch copying process
    tags: {} # Name-value pairs describing this job
      level: DEBUG # You can optionally switch to INFO for production
      method: get
      app_id: snowplow-emr-etl # e.g. snowplow
      collector: # e.g.

The same events are saved correctly in the real-time pipeline.