Emretlrunner executionerror data files not archived


hi all,
i tried to run EmrEtlrunner using bellow command
i am using EmrEtlrunner version "snowplow_emr_r91_stonehenge_rc9

./snowplow-emr-etl-runner run --config snowplow/4-storage/config/emretlrunner.yml --resolver snowplow/3-enrich/config/iglu_resolver.json --enrichments snowplow/3-enrich/config/enrichments/ --skip staging

when i ran this command many times got same issue even though using --skip staging and --skip,emr in my command

bellow is the error in command line

		 F, [2017-09-26T11:52:41.929000 #10462] FATAL -- :slight_smile: nowplow::EmrEtlRunner::EmrExecutionError (EMR jobflow j-1RGHAMRBK321 failed, check Amazon EMR console and Hadoop logs for details (help: https://github.com/snowplow/snowplow/wiki/Troubleshooting-jobs-on-Elastic-MapReduce). Data files not archived.
	Snowplow ETL: TERMINATING [STEP_FAILURE] ~ elapsed time n/a [2017-09-26 11:41:12 +0000 - ]
	 - 1. Elasticity S3DistCp Step: Raw S3 -> Raw HDFS: COMPLETED ~ 00:07:17 [2017-09-26 11:41:14 +0000 - 2017-09-26 11:48:31 +0000]
	 - 2. Elasticity Spark Step: Enrich Raw Events: COMPLETED ~ 00:01:58 [2017-09-26 11:48:33 +0000 - 2017-09-26 11:50:32 +0000]
	 - 3. Elasticity S3DistCp Step: Enriched HDFS -> S3: FAILED ~ 00:00:31 [2017-09-26 11:50:34 +0000 - 2017-09-26 11:51:05 +0000]
	 - 4. Elasticity S3DistCp Step: Shredded S3 -> Shredded Archive S3: CANCELLED ~ elapsed time n/a [ - ]
	 - 5. Elasticity S3DistCp Step: Enriched S3 -> Enriched Archive S3: CANCELLED ~ elapsed time n/a [ - ]
	 - 6. Elasticity S3DistCp Step: Raw Staging S3 -> Raw Archive S3: CANCELLED ~ elapsed time n/a [ - ]
	 - 7. Elasticity S3DistCp Step: Shredded HDFS _SUCCESS -> S3: CANCELLED ~ elapsed time n/a [ - ]
	 - 8. Elasticity S3DistCp Step: Shredded HDFS -> S3: CANCELLED ~ elapsed time n/a [ - ]
	 - 9. Elasticity Spark Step: Shred Enriched Events: CANCELLED ~ elapsed time n/a [ - ]
	 - 10. Elasticity Custom Jar Step: Empty Raw HDFS: CANCELLED ~ elapsed time n/a [ - ]
	 - 11. Elasticity S3DistCp Step: Enriched HDFS _SUCCESS -> S3: CANCELLED ~ elapsed time n/a [ - ]):
		uri:classloader:/emr-etl-runner/lib/snowplow-emr-etl-runner/emr_job.rb:586:in `run'
		uri:classloader:/gems/contracts-0.11.0/lib/contracts/method_reference.rb:43:in `send_to'
		uri:classloader:/gems/contracts-0.11.0/lib/contracts/call_with.rb:76:in `call_with'
		uri:classloader:/gems/contracts-0.11.0/lib/contracts/method_handler.rb:138:in `block in redefine_method'
		uri:classloader:/emr-etl-runner/lib/snowplow-emr-etl-runner/runner.rb:103:in `run'
		uri:classloader:/gems/contracts-0.11.0/lib/contracts/method_reference.rb:43:in `send_to'
		uri:classloader:/gems/contracts-0.11.0/lib/contracts/call_with.rb:76:in `call_with'
		uri:classloader:/gems/contracts-0.11.0/lib/contracts/method_handler.rb:138:in `block in redefine_method'
		uri:classloader:/emr-etl-runner/bin/snowplow-emr-etl-runner:41:in `<main>'
		org/jruby/RubyKernel.java:979:in `load'
		uri:classloader:/META-INF/main.rb:1:in `<main>'
		org/jruby/RubyKernel.java:961:in `require'
		uri:classloader:/META-INF/main.rb:1:in `(root)'
		uri:classloader:/META-INF/jruby.home/lib/ruby/stdlib/rubygems/core_ext/kernel_require.rb:1:in `<main>'

log status

	Exception in thread "main" java.lang.RuntimeException: Error running job
	at com.amazon.elasticmapreduce.s3distcp.S3DistCp.run(S3DistCp.java:927)
	at com.amazon.elasticmapreduce.s3distcp.S3DistCp.run(S3DistCp.java:705)
	at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:70)
	at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:84)
	at com.amazon.elasticmapreduce.s3distcp.Main.main(Main.java:22)
	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
	at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
	at java.lang.reflect.Method.invoke(Method.java:498)
	at org.apache.hadoop.util.RunJar.run(RunJar.java:221)
	at org.apache.hadoop.util.RunJar.main(RunJar.java:136)
	 Caused by: org.apache.hadoop.mapreduce.lib.input.InvalidInputException: Input path does not exist: hdfs://ip-172-31-4-251.ec2.internal:8020/tmp/1b3cec1f-c859-4d4b-b320-63b90e51b52c/files
	at org.apache.hadoop.mapreduce.lib.input.FileInputFormat.singleThreadedListStatus(FileInputFormat.java:317)
	at org.apache.hadoop.mapreduce.lib.input.FileInputFormat.listStatus(FileInputFormat.java:265)
	at org.apache.hadoop.mapreduce.lib.input.SequenceFileInputFormat.listStatus(SequenceFileInputFormat.java:59)
	at org.apache.hadoop.mapreduce.lib.input.FileInputFormat.getSplits(FileInputFormat.java:352)
	at org.apache.hadoop.mapreduce.JobSubmitter.writeNewSplits(JobSubmitter.java:301)
	at org.apache.hadoop.mapreduce.JobSubmitter.writeSplits(JobSubmitter.java:318)
	at org.apache.hadoop.mapreduce.JobSubmitter.submitJobInternal(JobSubmitter.java:196)
	at org.apache.hadoop.mapreduce.Job$10.run(Job.java:1290)
	at org.apache.hadoop.mapreduce.Job$10.run(Job.java:1287)
	at java.security.AccessController.doPrivileged(Native Method)
	at javax.security.auth.Subject.doAs(Subject.java:422)
	at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1698)
	at org.apache.hadoop.mapreduce.Job.submit(Job.java:1287)
	at com.amazon.elasticmapreduce.s3distcp.S3DistCp.run(S3DistCp.java:901)
	... 10 more


  # Credentials can be hardcoded or set in environment variables
  access_key_id: xxxxxx
  secret_access_key: xxxxxx
  #keypair: Snowplowkeypair
  #key-pair-file: /home/ubuntu/snowplow/4-storage/config/Snowplowkeypair.pem
  region: us-east-1
    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: # If you have defined your own JSON Schemas, add the s3:// path to your own JSON Path files in your own bucket here
      log: s3://unilogregion1/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://unilogregion1         # e.g. s3://my-old-collector-bucket
        processing: s3://unilogregion1/raw/processing
        archive: s3://unilogregion1/raw/archive   # e.g. s3://my-archive-bucket/raw
        good: s3://unilogregion1/enriched/good        # e.g. s3://my-out-bucket/enriched/good
        bad: s3://unilogregion1/enriched/bad       # e.g. s3://my-out-bucket/enriched/bad
        errors: s3://unilogregion1/enriched/errors     # Leave blank unless :continue_on_unexpected_error: set to true below
        archive: s3://unilogregion1/enriched/archive    # Where to archive enriched events to, e.g. s3://my-archive-bucket/enriched
        good: s3://unilogregion1/shredded/good        # e.g. s3://my-out-bucket/shredded/good
        bad: s3://unilogregion1/shredded/bad        # e.g. s3://my-out-bucket/shredded/bad
        errors: s3://unilogregion1/shredded/errors     # Leave blank unless :continue_on_unexpected_error: set to true below
        archive: s3://unilogregion1/shredded/archive     # Where to archive shredded events to, e.g. s3://my-archive-bucket/shredded
    ami_version: 4.5.0
    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: us-east-1a      # Set this if not running in VPC. Leave blank otherwise
    ec2_subnet_id:  # Set this if running in VPC. Leave blank otherwise
    ec2_key_name: Snowplowkeypair
    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 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: 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
        yarn.resourcemanager.am.max-attempts: "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/com.amazon.aws.cloudfront/wd_access_log' 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: 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
    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: unilog # e.g. snowplow
    #collector: # e.g. d3rkrsqld9gmqf.cloudfront.net

please help me how to solve this issue.


@shashi Could you avoid using release candidates? They have been produced for testing only and should not be used otherwise.


hi @BenFradet thanks for the response.

But their are 10 versions in “snowplow_emr_r91_stonehenge” in release candidates
please suggest which one should i select.


@shashi You should always pick the one not labelled rc (rc means release candidate), so that would be snowplow_emr_r91_stonehenge.

Even better would be to use the latest version snowplow_emr_r92_maiden_castle.