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Re: Hadoop noob question
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,
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 <
>> @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.
>>>>> For data management products, you can look at falcon which is open
>>>>> sourced by inmobi along with hortonworks.
>>>>> In any case, if you want to write files to hdfs there are few options
>>>>> available to you
>>>>> 1) Write your dfs client which writes to dfs
>>>>> 2) use hdfs proxy
>>>>> 3) there is webhdfs
>>>>> 4) command line hdfs
>>>>> 5) data collection tools come with support to write to hdfs like flume
>>>>> etc
>>>>> On Sat, May 11, 2013 at 4:19 PM, Thoihen Maibam <[EMAIL PROTECTED]>wrote:
>>>>>> Hi All,
>>>>>> Can anyone help me know how does companies like Facebook ,Yahoo etc