Couple of weeks back everything was working fine…
But now it is frequently failing in the 4th step of the storage process…
Below is the architecture i am following.
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-172-31-12-31.ec2.internal:8020/tmp/0f4fda2c-b209-452d-9aa6-261ca887c175/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
Every time the events are ending in bad bucket during the enrichment process…
please help me out to resolve this error.
Let know any changes i need to do?
Below is my config.yml file
aws:
# Credentials can be hardcoded or set in environment variables
access_key_id: xxxxxx
secret_access_key: xxxxxxxx
#keypair: Snowplowkeypair
#key-pair-file: /home/ubuntu/snowplow/4-storage/config/Snowplowkeypair.pem
region: us-east-1
s3:
region: us-east-1
buckets:
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://dataobjecteventsstorage/logs
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
- s3://dataobjecteventsstorage/ # e.g. s3://my-old-collector-bucket
processing: s3://dataobjecteventsstorage/raw/processing
archive: s3://dataobjecteventsstorage/raw/archive # e.g. s3://my-archive-bucket/raw
enriched:
good: s3://dataobjecteventsstorage/enriched/good # e.g. s3://my-out-bucket/enriched/good
bad: s3://dataobjecteventsstorage/enriched/bad # e.g. s3://my-out-bucket/enriched/bad
errors: s3://dataobjecteventsstorage/enriched/errors # Leave blank unless :continue_on_unexpected_error: set to true below
archive: s3://dataobjecteventsstorage/enriched/archive # Where to archive enriched events to, e.g. s3://my-archive-bucket/enriched
shredded:
good: s3://dataobjecteventsstorage/shredded/good # e.g. s3://my-out-bucket/shredded/good
bad: s3://dataobjecteventsstorage/shredded/bad # e.g. s3://my-out-bucket/shredded/bad
errors: s3://dataobjecteventsstorage/shredded/errors # Leave blank unless :continue_on_unexpected_error: set to true below
archive: s3://dataobjecteventsstorage/shredded/archive # Where to archive shredded events to, e.g. s3://my-archive-bucket/shredded
emr:
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: 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
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 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
configuration:
yarn-site:
yarn.resourcemanager.am.max-attempts: "1"
spark:
maximizeResourceAllocation: "true"
additional_info: # Optional JSON string for selecting additional features
collectors:
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
enrich:
versions:
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
storage:
versions:
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
monitoring:
tags: {} # Name-value pairs describing this job
logging:
level: DEBUG # You can optionally switch to INFO for production
#snowplow:
#method: get
#app_id: unilog # e.g. snowplow
#collector: 172.31.38.39:8082 # e.g. d3rkrsqld9gmqf.cloudfront.net
Hey @anton,
I checked in the enriched bad bucket, it has 1 file and 1 folder(inside the folder another file was their)
As show in the screenshot.
I checked both the file ,but it was empty.
I’m not sure I’m following @sandesh. You said that events ending up in bad bucket, but at the same time it’s empty, so it means there’s no events at all.
Hey @anton SORRY for the confusion.
Buckets are generating but when i check the bad bucket as well as good bucket both are empty…
In the Enrich bucket under the archive .csv file is generating, below is the data of the event present in the csv file
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-172-31-2-208.ec2.internal:8020/tmp/029fefc3-5b34-4f1d-87ec-84d2fd7798d9/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
Why the buckets are getting empty.
Do i need to do any changes in configuration?
Do i need to rebuild the server please let me know…
Below is my config.yml file
aws:
# Credentials can be hardcoded or set in environment variables
access_key_id: xxxxxxxxx
secret_access_key: xxxxxxxxx
#keypair: Snowplowkeypair
#key-pair-file: /home/ubuntu/snowplow/4-storage/config/Snowplowkeypair.pem
region: us-east-1
s3:
region: us-east-1
buckets:
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://dataobjecteventsstorage/logs
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
- s3://dataobjecteventsstorage/ # e.g. s3://my-old-collector-bucket
processing: s3://dataobjecteventsstorage/raw/processing
archive: s3://dataobjecteventsstorage/raw/archive # e.g. s3://my-archive-bucket/raw
enriched:
good: s3://dataobjecteventsstorage/enriched/good # e.g. s3://my-out-bucket/enriched/good
bad: s3://dataobjecteventsstorage/enriched/bad # e.g. s3://my-out-bucket/enriched/bad
errors: s3://dataobjecteventsstorage/enriched/errors # Leave blank unless :continue_on_unexpected_error: set to true below
archive: s3://dataobjecteventsstorage/enriched/archive # Where to archive enriched events to, e.g. s3://my-archive-bucket/enriched
shredded:
good: s3://dataobjecteventsstorage/shredded/good # e.g. s3://my-out-bucket/shredded/good
bad: s3://dataobjecteventsstorage/shredded/bad # e.g. s3://my-out-bucket/shredded/bad
errors: s3://dataobjecteventsstorage/shredded/errors # Leave blank unless :continue_on_unexpected_error: set to true below
archive: s3://dataobjecteventsstorage/shredded/archive # Where to archive shredded events to, e.g. s3://my-archive-bucket/shredded
emr:
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: 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
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 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
configuration:
yarn-site:
yarn.resourcemanager.am.max-attempts: "1"
spark:
maximizeResourceAllocation: "true"
additional_info: # Optional JSON string for selecting additional features
collectors:
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
enrich:
versions:
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
storage:
versions:
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
monitoring:
tags: {} # Name-value pairs describing this job
logging:
level: DEBUG # You can optionally switch to INFO for production
#snowplow:
#method: get
#app_id: unilog # e.g. snowplow
#collector: 172.31.38.39:8082 # e.g. d3rkrsqld9gmqf.cloudfront.net
