It is very common practice to backup the metadata in some SAN store. So the idea of complete loss of all the metadata is preventable. You could lose a day worth of data if e.g. you back the metadata once a day but you could do it more frequently. I'm not saying S3 or Azure Blob are bad ideas.
On Sun, Jun 5, 2016 at 8:19 AM, Marcin Tustin <mtus...@handybook.com> wrote: > The namenode architecture is a source of fragility in HDFS. While a high > availability deployment (with two namenodes, and a failover mechanism) > means you're unlikely to see service interruption, it is still possible to > have a complete loss of filesystem metadata with the loss of two machines. > > Secondly, because HDFS identifies datanodes by their hostname/ip, dns > changes can cause havoc with HDFS (see my war story on this here: > https://medium.com/handy-tech/renaming-hdfs-datanodes-considered-terribly-harmful-2bc2f37aabab > ). > > Also, the namenode/datanode architecture probably does contribute to the > small files problem being a problem. That said, there are lot of practical > solutions for the small files problem. > > If you're just setting up a data infrastructure, I would say consider > alternatives before you pick HDFS. If you run in AWS, S3 is a good > alternative. If you run in some other cloud, it's probably worth > considering whatever their equivalent storage system is. > > > On Sat, Jun 4, 2016 at 7:43 AM, Ascot Moss <ascot.m...@gmail.com> wrote: > >> Hi, >> >> I read some (old?) articles from Internet about Mapr-FS vs HDFS. >> >> https://www.mapr.com/products/m5-features/no-namenode-architecture >> >> It states that HDFS Federation has >> >> a) "Multiple Single Points of Failure", is it really true? >> Why MapR uses HDFS but not HDFS2 in its comparison as this would lead to >> an unfair comparison (or even misleading comparison)? (HDFS was from >> Hadoop 1.x, the old generation) HDFS2 is available since 2013-10-15, there >> is no any Single Points of Failure in HDFS2. >> >> b) "Limit to 50-200 million files", is it really true? >> I have seen so many real world Hadoop Clusters with over 10PB data, some >> even with 150PB data. If "Limit to 50 -200 millions files" were true in >> HDFS2, why are there so many production Hadoop clusters in real world? how >> can they mange well the issue of "Limit to 50-200 million files"? For >> instances, the Facebook's "Like" implementation runs on HBase at Web >> Scale, I can image HBase generates huge number of files in Facbook's Hadoop >> cluster, the number of files in Facebook's Hadoop cluster should be much >> much bigger than 50-200 million. >> >> From my point of view, in contrast, MaprFS should have true limitation up >> to 1T files while HDFS2 can handle true unlimited files, please do correct >> me if I am wrong. >> >> c) "Performance Bottleneck", again, is it really true? >> MaprFS does not have namenode in order to gain file system performance. >> If without Namenode, MaprFS would lose Data Locality which is one of the >> beauties of Hadoop If Data Locality is no longer available, any big data >> application running on MaprFS might gain some file system performance but >> it would totally lose the true gain of performance from Data Locality >> provided by Hadoop's namenode (gain small lose big) >> >> d) "Commercial NAS required" >> Is there any wiki/blog/discussion about Commercial NAS on Hadoop >> Federation? >> >> regards >> >> >> >> > > Want to work at Handy? Check out our culture deck and open roles > <http://www.handy.com/careers> > Latest news <http://www.handy.com/press> at Handy > Handy just raised $50m > <http://venturebeat.com/2015/11/02/on-demand-home-service-handy-raises-50m-in-round-led-by-fidelity/> > led > by Fidelity > >
