There is nothing special that you need to do if you are already running secure Map Reduce jobs. The client needs to run in a Kerberized authenticated context. After that if you are using the built-in library of inputs/outputs etc then they should be taking care of all the access credentials for you when using the 0.5 API. I
If you are using 0.4 API to write your job then you may need to use additional APIs for passing credentials to the application. Look for credentials in https://github.com/apache/tez/blob/branch-0.4.0-incubating/tez-mapreduce-examples/src/main/java/org/apache/tez/mapreduce/examples/FilterLinesByWord.java and also *public* *synchronized* DAG *addURIsForCredentials(*Collection*<* URI*>* uris*)* The second method is a shortcut if you are using HDFS files for input. It obtains credentials for you from a collection of HDFS input URIs. Bikas *From:* Subroto Sanyal [mailto:[email protected]] *Sent:* Tuesday, August 19, 2014 3:30 AM *To:* [email protected] *Subject:* Tez with secured hadoop hi Tez works on secure hadoop cluster since tez-0.3. Is there any documentation available about configuring TezClient to make it work? -- Cheers, *Subroto Sanyal* -- CONFIDENTIALITY NOTICE NOTICE: This message is intended for the use of the individual or entity to which it is addressed and may contain information that is confidential, privileged and exempt from disclosure under applicable law. If the reader of this message is not the intended recipient, you are hereby notified that any printing, copying, dissemination, distribution, disclosure or forwarding of this communication is strictly prohibited. If you have received this communication in error, please contact the sender immediately and delete it from your system. Thank You.
