This is the best coverage I've seen from a source that would know: http://developer.yahoo.com/blogs/hadoop/posts/2010/05/scalability_of_the_hadoop_dist/
One relevant quote: To store 100 million files (referencing 200 million blocks), a name-node should have at least 60 GB of RAM. But, honestly, if you're just building out your cluster, you'll probably run into a lot of other limits first: hard drive space, regionserver memory, the infamous ulimit/xciever :), etc... Take care, -stu --- On Wed, 2/2/11, Dhruba Borthakur <dhr...@gmail.com> wrote: From: Dhruba Borthakur <dhr...@gmail.com> Subject: Re: HDFS without Hadoop: Why? To: hdfs-user@hadoop.apache.org Date: Wednesday, February 2, 2011, 9:00 PM The Namenode uses around 160 bytes/file and 150 bytes/block in HDFS. This is a very rough calculation. dhruba On Wed, Feb 2, 2011 at 5:11 PM, Dhodapkar, Chinmay <chinm...@qualcomm.com> wrote: What you describe is pretty much my use case as well. Since I don’t know how big the number of files could get , I am trying to figure out if there is a theoretical design limitation in hdfs….. From what I have read, the name node will store all metadata of all files in the RAM. Assuming (in my case), that a file is less than the configured block size….there should be a very rough formula that can be used to calculate the max number of files that hdfs can serve based on the configured RAM on the name node? Can any of the implementers comment on this? Am I even thinking on the right track…? Thanks Ian for the haystack link…very informative indeed. -Chinmay From: Stuart Smith [mailto:stu24m...@yahoo.com] Sent: Wednesday, February 02, 2011 4:41 PM To: hdfs-user@hadoop.apache.org Subject: RE: HDFS without Hadoop: Why? Hello, I'm actually using hbase/hadoop/hdfs for lots of small files (with a long tail of larger files). Well, millions of small files - I don't know what you mean by lots :) Facebook probably knows better, But what I do is: - store metadata in hbase - files smaller than 10 MB or so in hbase -larger files in a hdfs directory tree. I started storing 64 MB files and smaller in hbase (chunk size), but that causes issues with regionservers when running M/R jobs. This is related to the fact that I'm running a cobbled together cluster & my region servers don't have that much memory. I would play the size to see what works for you.. Take care, -stu --- On Wed, 2/2/11, Dhodapkar, Chinmay <chinm...@qualcomm.com> wrote: From: Dhodapkar, Chinmay <chinm...@qualcomm.com> Subject: RE: HDFS without Hadoop: Why? To: "hdfs-user@hadoop.apache.org" <hdfs-user@hadoop.apache.org> Date: Wednesday, February 2, 2011, 7:28 PM Hello, I have been following this thread for some time now. I am very comfortable with the advantages of hdfs, but still have lingering questions about the usage of hdfs for general purpose storage (no mapreduce/hbase etc). Can somebody shed light on what the limitations are on the number of files that can be stored. Is it limited in anyway by the namenode? The use case I am interested in is to store a very large number of relatively small files (1MB to 25MB). Interestingly, I saw a facebook presentation on how they use hbase/hdfs internally. Them seem to store all metadata in hbase and the actual images/files/etc in something called “haystack” (why not use hdfs since they already have it?). Anybody know what “haystack” is? Thanks! Chinmay From: Jeff Hammerbacher [mailto:ham...@cloudera.com] Sent: Wednesday, February 02, 2011 3:31 PM To: hdfs-user@hadoop.apache.org Subject: Re: HDFS without Hadoop: Why? Large block size wastes space for small file. The minimum file size is 1 block. That's incorrect. If a file is smaller than the block size, it will only consume as much space as there is data in the file. There are no hardlinks, softlinks, or quotas. That's incorrect; there are quotas and softlinks. -- Connect to me at http://www.facebook.com/dhruba
