Connection Refused Exception while using Teradata Hadoop Connector - hadoop

Question

I am currently using the free version of Teradata Hadoop connector teradata-connector 1.3.4 to load data to Teradata. I am using internal.fastload to load the data.
Database version is 14.10
jdbc driver version is 15.0
Sometimes I face Connection refused exception while running the job but this issue goes off while reseting the load job 2-3 times. Also this has nothing to do with the load on teradata database as the load is pretty normal. The exception which is thrown is below:
15/10/29 22:52:54 INFO mapreduce.Job: Running job: job_1445506804193_290389
com.teradata.connector.common.exception.ConnectorException: Internal fast load socket server time out
at com.teradata.connector.teradata.TeradataInternalFastloadOutputFormat$InternalFastloadCoordinator.beginLoading(TeradataInternalFastloadOutputFormat.java:642)
at com.teradata.connector.teradata.TeradataInternalFastloadOutputFormat$InternalFastloadCoordinator.run(TeradataInternalFastloadOutputFormat.java:503)
at java.lang.Thread.run(Thread.java:745)
15/10/29 23:39:29 INFO mapreduce.Job: Job job_1445506804193_290389 running in uber mode : false
15/10/29 23:39:29 INFO mapreduce.Job: map 0% reduce 0%
15/10/29 23:40:08 INFO mapreduce.Job: Task Id : attempt_1445506804193_290389_m_000001_0, Status : FAILED
Error: com.teradata.connector.common.exception.ConnectorException: java.net.ConnectException: Connection refused
at java.net.PlainSocketImpl.socketConnect(Native Method)
at java.net.AbstractPlainSocketImpl.doConnect(AbstractPlainSocketImpl.java:345)
at java.net.AbstractPlainSocketImpl.connectToAddress(AbstractPlainSocketImpl.java:206)
at java.net.AbstractPlainSocketImpl.connect(AbstractPlainSocketImpl.java:188)
at java.net.SocksSocketImpl.connect(SocksSocketImpl.java:392)
at java.net.Socket.connect(Socket.java:589)
at java.net.Socket.connect(Socket.java:538)
at java.net.Socket.<init>(Socket.java:434)
at java.net.Socket.<init>(Socket.java:211)
at com.teradata.connector.teradata.TeradataInternalFastloadOutputFormat.getRecordWriter(TeradataInternalFastloadOutputFormat.java:301)
at com.teradata.connector.common.ConnectorOutputFormat$ConnectorFileRecordWriter.<init>(ConnectorOutputFormat.java:84)
at com.teradata.connector.common.ConnectorOutputFormat.getRecordWriter(ConnectorOutputFormat.java:33)
at org.apache.hadoop.mapred.MapTask$NewDirectOutputCollector.<init>(MapTask.java:624)
at org.apache.hadoop.mapred.MapTask.runNewMapper(MapTask.java:744)
at org.apache.hadoop.mapred.MapTask.run(MapTask.java:340)
at org.apache.hadoop.mapred.YarnChild$2.run(YarnChild.java:167)
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:1591)
at org.apache.hadoop.mapred.YarnChild.main(YarnChild.java:162)
Any pointers in this regard will definitely help.
Thanks in advance.

Answer 1

Root cause: com.teradata.connector.common.exception.ConnectorException: Internal fast load socket server time out
Internal fast load server socket time out
When running export job using the "internal.fastload" method, the following error may occur: Internal fast load socket server time out
This error occurs because the number of available map tasks currently is less than the number of map tasks specified in the command line by parameter of "-nummappers".
This error can occur in the following conditions:
(1) There are some other map/reduce jobs running concurrently in the Hadoop cluster, so there are not enough resources to allocate specified map tasks for the export job.
(2) The maximum number of map tasks is smaller than existing map tasks added expected map tasks of the export jobs in the Hadoop cluster.
When the above error occurs, please try to increase the maximum number of map tasks of the Hadoop cluster, or decrease the number of map tasks for the export job
There is good trouble shooter PDF available #teradata
If you get any type of errors, have a look at above PDF and get it fixed.
Have a look at other map reduce properties if you have to fine tune them.

Answer 2

ravindra-babu's answer is correct since the answer is buried in the pdf docs. The support.teradata.com kb article KB0023556 also offers more details on the why.
Resolution
All mappers should run simultaneously. If they are not
running simultaneously, try to reduce the number of mappers in TDCH
job through -nummappers argument.
Resubmit the TDCH job after
changing the -nummappers
Honestly it's a very confusing error and could be displayed better.