In HDFS2, I can find "dfs.storage.policy", for instances, HDFS2 allows to *Apply the COLD storage policy to a directory,* where are these features in Mapr-FS?
On Mon, Jun 6, 2016 at 11:43 PM, Aaron Eng <[email protected]> wrote: > >Since MapR is proprietary, I find that it has many compatibility issues > in Apache open source projects > > This is faulty logic. And rather than saying it has "many compatibility > issues", perhaps you can describe one. > > Both MapRFS and HDFS are accessible through the same API. The backend > implementations are what differs. > > >Hadoop has a built-in storage policy named COLD, where is it in Mapr-FS? > > Long before HDFS had storage policies, MapRFS had topologies. You can > restrict particular types of storage to a topology and then assign a volume > (subset of data stored in MapRFS) to the topology, and hence the data in > that subset would be served by whatever hardware was mapped into the > topology. > > >no to mention that Mapr-FS loses Data-Locality. > > This statement is false. > > > > On Mon, Jun 6, 2016 at 8:32 AM, Ascot Moss <[email protected]> wrote: > >> Since MapR is proprietary, I find that it has many compatibility issues >> in Apache open source projects, or even worse, lose Hadoop's features. For >> instances, Hadoop has a built-in storage policy named COLD, where is it in >> Mapr-FS? no to mention that Mapr-FS loses Data-Locality. >> >> On Mon, Jun 6, 2016 at 11:26 PM, Ascot Moss <[email protected]> wrote: >> >>> I don't think HDFS2 needs SAN, use the QuorumJournal approach is much >>> better than using Shared edits directory SAN approach. >>> >>> >>> >>> >>> On Monday, June 6, 2016, Peyman Mohajerian <[email protected]> wrote: >>> >>>> 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 <[email protected]> >>>> 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 <[email protected]> >>>>> 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 >>>>> >>>>> >>>> >> >
