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From Ascot Moss <ascot.m...@gmail.com>
Subject Re: HDFS2 vs MaprFS
Date Sun, 05 Jun 2016 13:58:42 GMT
HDFS2 "Limit to 50-200 million files", is it really true like what MapR

On Sun, Jun 5, 2016 at 7:55 PM, Hayati Gonultas <hayati.gonultas@gmail.com>

> I forgot to mention about file system limit.
> Yes HDFS has limit, because for the performance considirations HDFS
> filesystem is read from disk to RAM and rest of the work is done with RAM.
> So RAM should be big enough to fit the filesystem image. But HDFS has
> configuration options like har files (Hadoop Archive) to defeat these
> limitations.
> On Sun, Jun 5, 2016 at 11:14 AM, Ascot Moss <ascot.moss@gmail.com> wrote:
>> Will the the common pool of datanodes and namenode federation be a more
>> effective alternative in HDFS2  than multiple clusters?
>> On Sun, Jun 5, 2016 at 12:19 PM, daemeon reiydelle <daemeonr@gmail.com>
>> wrote:
>>> There are indeed many tuning points here. If the name nodes and journal
>>> nodes can be larger, perhaps even bonding multiple 10gbyte nics, one can
>>> easily scale. I did have one client where the file counts forced multiple
>>> clusters. But we were able to differentiate by airframe types ... eg fixed
>>> wing in one, rotary subsonic in another, etc.
>>> sent from my mobile
>>> Daemeon C.M. Reiydelle
>>> USA 415.501.0198
>>> London +
>>> On Jun 4, 2016 2:23 PM, "Gavin Yue" <yue.yuanyuan@gmail.com> wrote:
>>>> Here is what I found on Horton website.
>>>> *Namespace scalability*
>>>> While HDFS cluster storage scales horizontally with the addition of
>>>> datanodes, the namespace does not. Currently the namespace can only be
>>>> vertically scaled on a single namenode.  The namenode stores the entire
>>>> file system metadata in memory. This limits the number of blocks, files,
>>>> and directories supported on the file system to what can be accommodated
>>>> the memory of a single namenode. A typical large deployment at Yahoo!
>>>> includes an HDFS cluster with 2700-4200 datanodes with 180 million
>>>> files and blocks, and address ~25 PB of storage.  At Facebook, HDFS has
>>>> around 2600 nodes, 300 million files and blocks, addressing up to 60PB of
>>>> storage. While these are very large systems and good enough for majority
>>>> Hadoop users, a few deployments that might want to grow even larger could
>>>> find the namespace scalability limiting.
>>>> On Jun 4, 2016, at 04:43, 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 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
> --
> Hayati Gonultas

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