Hi, lohit. There is a Class named ThrottledInputStream<http://svn.apache.org/repos/asf/hadoop/common/trunk/hadoop-tools/hadoop-distcp/src/main/java/org/apache/hadoop/tools/util/ThrottledInputStream.java> in hadoop-distcp, you could check it out and find more details.
In addition to this, I am working on this and try to achieve resources control(include CPU, Network, Disk IO) in JVM. But my implementation is depends on cgroup, which only could run in Linux. I would push my library(java-cgroup) to github in the next several months. If you are interested at it, give my any advices and help me improve it please. :-) On Tue, Nov 12, 2013 at 3:47 AM, lohit <lohit.vijayar...@gmail.com> wrote: > Hi Adam, > > Thanks for the reply. The changes I was referring was in FileSystem.java > layer which should not affect HDFS Replication/NameNode operations. > To give better idea this would affect clients something like this > > Configuration conf = new Configuration(); > conf.setInt("read.bandwitdh.mbpersec", 20); // 20MB/s > FileSystem fs = FileSystem.get(conf); > > FSDataInputStream fis = fs.open("/path/to/file.xt"); > fis.read(); // <-- This would be max of 20MB/s > > > > > 2013/11/11 Adam Muise <amu...@hortonworks.com> > > > See https://issues.apache.org/jira/browse/HDFS-3475 > > > > Please note that this has met with many unexpected impacts on workload. > Be > > careful and be mindful of your Datanode memory and network capacity. > > > > > > > > > > On Mon, Nov 11, 2013 at 1:59 PM, lohit <lohit.vijayar...@gmail.com> > wrote: > > > > > Hello Devs, > > > > > > Wanted to reach out and see if anyone has thought about ability to > > throttle > > > data transfer within HDFS. One option we have been thinking is to > > throttle > > > on a per FileSystem basis, similar to Statistics in FileSystem. This > > would > > > mean anyone with handle to HDFS/Hftp will be throttled globally within > > JVM. > > > Right value to come up for this would be based on type of hardware we > use > > > and how many tasks/clients we allow. > > > > > > On the other hand doing something like this at FileSystem layer would > > mean > > > many other tasks such as Job jar copy, DistributedCache copy and any > > hidden > > > data movement would also be throttled. We wanted to know if anyone has > > had > > > such requirement on their clusters in the past and what was the > thinking > > > around it. Appreciate your inputs/comments > > > > > > -- > > > Have a Nice Day! > > > Lohit > > > > > > > > > > > -- > > * Adam Muise * Solutions Engineer > > ------------------------------ > > > > Phone: 416-417-4037 > > Email: amu...@hortonworks.com > > Website: http://www.hortonworks.com/ > > > > * Follow Us: * > > < > > > http://facebook.com/hortonworks/?utm_source=WiseStamp&utm_medium=email&utm_term=&utm_content=&utm_campaign=signature > > > > > < > > > http://twitter.com/hortonworks?utm_source=WiseStamp&utm_medium=email&utm_term=&utm_content=&utm_campaign=signature > > > > > < > > > http://www.linkedin.com/company/hortonworks?utm_source=WiseStamp&utm_medium=email&utm_term=&utm_content=&utm_campaign=signature > > > > > > > [image: photo] > > > > Latest From Our Blog: How to use R and other non-Java languages in > > MapReduce and Hive > > < > > > http://hortonworks.com/blog/using-r-and-other-non-java-languages-in-mapreduce-and-hive/?utm_source=WiseStamp&utm_medium=email&utm_term=&utm_content=&utm_campaign=signature > > > > > > > -- > > 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. > > > > > > -- > Have a Nice Day! > Lohit > -- Best Regards, Haosdent Huang