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MapReduce >> mail # user >> Re: Hadoop noob question


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Re: Hadoop noob question
IMHO,I think the statement about NN with regard to block metadata is more
like a general statement. Even if you put lots of small files of combined
size 10 TB , you need to have a capable NN.

can disct cp be used to copy local - to - hdfs ?

Thanks,
Rahul
On Sat, May 11, 2013 at 9:35 PM, Nitin Pawar <[EMAIL PROTECTED]>wrote:

> absolutely rite Mohammad
>
>
> On Sat, May 11, 2013 at 9:33 PM, Mohammad Tariq <[EMAIL PROTECTED]>wrote:
>
>> Sorry for barging in guys. I think Nitin is talking about this :
>>
>> Every file and block in HDFS is treated as an object and for each object
>> around 200B of metadata get created. So the NN should be powerful enough to
>> handle that much metadata, since it is going to be in-memory. Actually
>> memory is the most important metric when it comes to NN.
>>
>> Am I correct @Nitin?
>>
>> @Thoihen : As Nitin has said, when you talk about that much data you
>> don't actually just do a "put". You could use something like "distcp" for
>> parallel copying. A better approach would be to use a data aggregation tool
>> like Flume or Chukwa, as Nitin has already pointed. Facebook uses their own
>> data aggregation tool, called Scribe for this purpose.
>>
>> Warm Regards,
>> Tariq
>> cloudfront.blogspot.com
>>
>>
>> On Sat, May 11, 2013 at 9:20 PM, Nitin Pawar <[EMAIL PROTECTED]>wrote:
>>
>>> NN would still be in picture because it will be writing a lot of meta
>>> data for each individual file. so you will need a NN capable enough which
>>> can store the metadata for your entire dataset. Data will never go to NN
>>> but lot of metadata about data will be on NN so its always good idea to
>>> have a strong NN.
>>>
>>>
>>> On Sat, May 11, 2013 at 9:11 PM, Rahul Bhattacharjee <
>>> [EMAIL PROTECTED]> wrote:
>>>
>>>> @Nitin , parallel dfs to write to hdfs is great , but could not
>>>> understand the meaning of capable NN. As I know , the NN would not be a
>>>> part of the actual data write pipeline , means that the data would not
>>>> travel through the NN , the dfs would contact the NN from time to time to
>>>> get locations of DN as where to store the data blocks.
>>>>
>>>> Thanks,
>>>> Rahul
>>>>
>>>>
>>>>
>>>> On Sat, May 11, 2013 at 4:54 PM, Nitin Pawar <[EMAIL PROTECTED]>wrote:
>>>>
>>>>> is it safe? .. there is no direct answer yes or no
>>>>>
>>>>> when you say , you have files worth 10TB files and you want to upload
>>>>>  to HDFS, several factors come into picture
>>>>>
>>>>> 1) Is the machine in the same network as your hadoop cluster?
>>>>> 2) If there guarantee that network will not go down?
>>>>>
>>>>> and Most importantly I assume that you have a capable hadoop cluster.
>>>>> By that I mean you have a capable namenode.
>>>>>
>>>>> I would definitely not write files sequentially in HDFS. I would
>>>>> prefer to write files in parallel to hdfs to utilize the DFS write features
>>>>> to speed up the process.
>>>>> you can hdfs put command in parallel manner and in my experience it
>>>>> has not failed when we write a lot of data.
>>>>>
>>>>>
>>>>> On Sat, May 11, 2013 at 4:38 PM, maisnam ns <[EMAIL PROTECTED]>wrote:
>>>>>
>>>>>> @Nitin Pawar , thanks for clearing my doubts .
>>>>>>
>>>>>> But I have one more question , say I have 10 TB data in the pipeline .
>>>>>>
>>>>>> Is it perfectly OK to use hadopo fs put command to upload these files
>>>>>> of size 10 TB and is there any limit to the file size  using hadoop command
>>>>>> line . Can hadoop put command line work with huge data.
>>>>>>
>>>>>> Thanks in advance
>>>>>>
>>>>>>
>>>>>> On Sat, May 11, 2013 at 4:24 PM, Nitin Pawar <[EMAIL PROTECTED]
>>>>>> > wrote:
>>>>>>
>>>>>>> first of all .. most of the companies do not get 100 PB of data in
>>>>>>> one go. Its an accumulating process and most of the companies do have a
>>>>>>> data pipeline in place where the data is written to hdfs on a frequency
>>>>>>> basis and  then its retained on hdfs for some duration as per needed and
>>>>>>> from there its sent to archivers or deleted.
+
Thoihen Maibam 2013-05-11, 10:49
+
Nitin Pawar 2013-05-11, 10:54
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maisnam ns 2013-05-11, 11:08
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Nitin Pawar 2013-05-11, 11:24
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Mohammad Tariq 2013-05-12, 13:42
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Rahul Bhattacharjee 2013-05-12, 11:53
+
Nitin Pawar 2013-05-12, 12:06
+
Mohammad Tariq 2013-05-12, 12:37
+
Rahul Bhattacharjee 2013-05-12, 12:45
+
Mohammad Tariq 2013-05-12, 12:55
+
Chris Mawata 2013-05-12, 14:21
+
Rahul Bhattacharjee 2013-05-16, 14:18
NEW: Monitor These Apps!
elasticsearch, apache solr, apache hbase, hadoop, redis, casssandra, amazon cloudwatch, mysql, memcached, apache kafka, apache zookeeper, apache storm, ubuntu, centOS, red hat, debian, puppet labs, java, senseiDB