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From Ascot Moss <ascot.m...@gmail.com>
Subject Re: HDFS2 vs MaprFS
Date Mon, 06 Jun 2016 16:02:08 GMT
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 <aeng@maprtech.com> 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 <ascot.moss@gmail.com> 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 <ascot.moss@gmail.com> 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 <mohajeri@gmail.com> 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 <mtustin@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
>>>>> 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.moss@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
>>>>>> to an unfair comparison (or even misleading comparison)?  (HDFS was
>>>>>> Hadoop 1.x, the old generation) HDFS2 is available since 2013-10-15,
>>>>>> 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
>>>>>> how can they mange well the issue of  "Limit to 50-200 million files"?
>>>>>> instances,  the Facebook's "Like" implementation runs on HBase at
>>>>>> Scale, I can image HBase generates huge number of files in Facbook's
>>>>>> 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,
>>>>>> big data application running on MaprFS might gain some file system
>>>>>> performance but it would totally lose the true gain of performance
>>>>>> 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
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