I've looked at it a bit within the context of YARN. YARN containers are where this would be ideal, as then you'd be able to request IO capacity as well as CPU and RAM. For that to work, the throttling would have to be outside the App, as you are trying to limit code whether or not it wants to be, and because you probably (*) want to give it more bandwidth if the system is otherwise idle. Self-throttling doesn't pick up spare IO
1. you can use cgroups in YARN to throttle local disk IO through the file:// URLs or the java filesystem APIs -such as for MR temp data 2. you can't c-group throttle HDFS per YARN container, which would be the ideal use case for it. The IO is taking place in the DN, and cgroups only limits IO in the throttled process group. 3. implementing it in the DN would require a lot more complex code there to prioritise work based on block ID (sole identifier that goes around everywhere) or input source (local sockets for HBase IO vs TCP stack) 4. One you go to a heterogenous filesystem you need to think about IO load per storage layer as well as/alongside per-volume 5. There's also generic RPC request throttle to prevent DoS against the NN and other HDFS services. That would need to be server side, but once implemented in the RPC code be universal. You also need to define what is the load you are trying to throttle, pure RPCs/second, read bandwidth, write bandwidth, seeks or IOPs. Once a file is lined up for sequential reading, you'd almost want it to stream through the next blocks until a high priority request came through, but operations like a seek which would involve a disk head movement backwards would be something to throttle (hence you need to be storage type aware as SSD seeks costs less). You also need to consider that although the cost of writes is high, it's usually being done with the goal of preserving data -and you don't want to impact durability. (*) probably, because that's one of the issues that causes debates in other datacentre platforms, such as Google Omega: do you want max cluster utilisation vs max determinism of workload. If someone were to do IOP throttling in the 3.x+ timeline, 1. It needs clear use cases, YARN containers being #1 for me 2. We'd have to look at all the research done on this in the past to see what works, doesn't Andrew, what citations of relevance do you have? -steve On 12 November 2013 04:24, lohit <lohit.vijayar...@gmail.com> wrote: > 2013/11/11 Andrew Wang <andrew.w...@cloudera.com> > > > Hey Lohit, > > > > This is an interesting topic, and something I actually worked on in grad > > school before coming to Cloudera. It'd help if you could outline some of > > your usecases and how per-FileSystem throttling would help. For what I > was > > doing, it made more sense to throttle on the DN side since you have a > > better view over all the I/O happening on the system, and you have > > knowledge of different volumes so you can set limits per-disk. This still > > isn't 100% reliable though since normally a portion of each disk is used > > for MR scratch space, which the DN doesn't have control over. I tried > > playing with thread I/O priorities here, but didn't see much improvement. > > Maybe the newer cgroups stuff can help out. > > > > Thanks. Yes, we also thought about having something on DataNode. This would > also mean one could easily throttle client who access from outside the > cluster, for example distcp or hftp copies. Clients need not worry about > throttle configs and each cluster can control how much much throughput can > be achieved. We do want to have something like this. > > > > > I'm sure per-FileSystem throttling will have some benefits (and probably > be > > easier than some DN-side implementation) but again, it'd help to better > > understand the problem you are trying to solve. > > > > One idea was flexibility for client to override and have value they can > set. For on trusted cluster we could allow clients to go beyond default > value for some usecases. Alternatively we also thought about having default > value and max value where clients could change default, but not go beyond > default. Another problem with DN side config is having different values for > different clients and easily changing those for selective clients. > > As, Haosong also suggested we could wrap FSDataOutputStream/FSDataInput > stream with ThrottleInputStream. But we might have to be careful of any > code which uses FileSystem APIs and accidentally throttling itself. (like > reducer copy, distributed cache and such...) > > > > > Best, > > Andrew > > > > > > On Mon, Nov 11, 2013 at 6:16 PM, Haosong Huang <haosd...@gmail.com> > wrote: > > > > > 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. 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