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From Drake민영근 <drake....@nexr.com>
Subject Re: How to partition a file to smaller size for performing KNN in hadoop mapreduce
Date Wed, 21 Jan 2015 05:45:40 GMT
Yes, almost same. I assume the most time spending part was copying model
data from datanode which has model data to actual process node(tasktracker
or nodemanager).

How about the model data's replication factor? How many nodes do you have?
If you have 4 or more nodes, you can increase replication with following
command. I suggest the number equal to your datanodes, but first you should
confirm the enough space in HDFS.


   - hdfs dfs -setrep -w 6 /user/model/data




Drake 민영근 Ph.D

On Wed, Jan 21, 2015 at 2:12 PM, unmesha sreeveni <unmeshabiju@gmail.com>
wrote:

> Yes I tried the same Drake.
>
> I dont know if I understood your answer.
>
>  Instead of loading them into setup() through cache I read them directly
> from HDFS in map section. and for each incoming record .I found the
> distance between all the records in HDFS.
> ie if R ans S are my dataset, R is the model data stored in HDFs
> and when S taken for processing
> S1-R(finding distance with whole R set)
> S2-R
>
> But it is taking a long time as it needs to compute the distance.
>
> On Wed, Jan 21, 2015 at 10:31 AM, Drake민영근 <drake.min@nexr.com> wrote:
>
>> In my suggestion, map or reduce tasks do not use distributed cache. They
>> use file directly from HDFS with short circuit local read. Like a shared
>> storage method, but almost every node has the data with high-replication
>> factor.
>>
>> Drake 민영근 Ph.D
>>
>> On Wed, Jan 21, 2015 at 1:49 PM, unmesha sreeveni <unmeshabiju@gmail.com>
>> wrote:
>>
>>> But stil if the model is very large enough, how can we load them inti
>>> Distributed cache or some thing like that.
>>> Here is one source :
>>> http://www.cs.utah.edu/~lifeifei/papers/knnslides.pdf
>>> But it is confusing me
>>>
>>> On Wed, Jan 21, 2015 at 7:30 AM, Drake민영근 <drake.min@nexr.com> wrote:
>>>
>>>> Hi,
>>>>
>>>> How about this ? The large model data stay in HDFS but with many
>>>> replications and MapReduce program read the model from HDFS. In theory, the
>>>> replication factor of model data equals with number of data nodes and with
>>>> the Short Circuit Local Reads function of HDFS datanode, the map or reduce
>>>> tasks read the model data in their own disks.
>>>>
>>>> In this way, maybe use too many usage of HDFS, but the annoying
>>>> partition problem will be gone.
>>>>
>>>> Thanks
>>>>
>>>> Drake 민영근 Ph.D
>>>>
>>>> On Thu, Jan 15, 2015 at 6:05 PM, unmesha sreeveni <
>>>> unmeshabiju@gmail.com> wrote:
>>>>
>>>>> Is there any way..
>>>>> Waiting for a reply.I have posted the question every where..but none
>>>>> is responding back.
>>>>> I feel like this is the right place to ask doubts. As some of u may
>>>>> came across the same issue and get stuck.
>>>>>
>>>>> On Thu, Jan 15, 2015 at 12:34 PM, unmesha sreeveni <
>>>>> unmeshabiju@gmail.com> wrote:
>>>>>
>>>>>> Yes, One of my friend is implemeting the same. I know global sharing
>>>>>> of Data is not possible across Hadoop MapReduce. But I need to check
if
>>>>>> that can be done somehow in hadoop Mapreduce also. Because I found
some
>>>>>> papers in KNN hadoop also.
>>>>>> And I trying to compare the performance too.
>>>>>>
>>>>>> Hope some pointers can help me.
>>>>>>
>>>>>>
>>>>>> On Thu, Jan 15, 2015 at 12:17 PM, Ted Dunning <ted.dunning@gmail.com>
>>>>>> wrote:
>>>>>>
>>>>>>>
>>>>>>> have you considered implementing using something like spark?
 That
>>>>>>> could be much easier than raw map-reduce
>>>>>>>
>>>>>>> On Wed, Jan 14, 2015 at 10:06 PM, unmesha sreeveni <
>>>>>>> unmeshabiju@gmail.com> wrote:
>>>>>>>
>>>>>>>> In KNN like algorithm we need to load model Data into cache
for
>>>>>>>> predicting the records.
>>>>>>>>
>>>>>>>> Here is the example for KNN.
>>>>>>>>
>>>>>>>>
>>>>>>>> [image: Inline image 1]
>>>>>>>>
>>>>>>>> So if the model will be a large file say1 or 2 GB we will
be able
>>>>>>>> to load them into Distributed cache.
>>>>>>>>
>>>>>>>> The one way is to split/partition the model Result into some
files
>>>>>>>> and perform the distance calculation for all records in that
file and then
>>>>>>>> find the min ditance and max occurance of classlabel and
predict the
>>>>>>>> outcome.
>>>>>>>>
>>>>>>>> How can we parttion the file and perform the operation on
these
>>>>>>>> partition ?
>>>>>>>>
>>>>>>>> ie  1 record <Distance> parttition1,partition2,....
>>>>>>>>      2nd record <Distance> parttition1,partition2,...
>>>>>>>>
>>>>>>>> This is what came to my thought.
>>>>>>>>
>>>>>>>> Is there any further way.
>>>>>>>>
>>>>>>>> Any pointers would help me.
>>>>>>>>
>>>>>>>> --
>>>>>>>> *Thanks & Regards *
>>>>>>>>
>>>>>>>>
>>>>>>>> *Unmesha Sreeveni U.B*
>>>>>>>> *Hadoop, Bigdata Developer*
>>>>>>>> *Centre for Cyber Security | Amrita Vishwa Vidyapeetham*
>>>>>>>> http://www.unmeshasreeveni.blogspot.in/
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>
>>>>>>
>>>>>>
>>>>>> --
>>>>>> *Thanks & Regards *
>>>>>>
>>>>>>
>>>>>> *Unmesha Sreeveni U.B*
>>>>>> *Hadoop, Bigdata Developer*
>>>>>> *Centre for Cyber Security | Amrita Vishwa Vidyapeetham*
>>>>>> http://www.unmeshasreeveni.blogspot.in/
>>>>>>
>>>>>>
>>>>>>
>>>>>
>>>>>
>>>>> --
>>>>> *Thanks & Regards *
>>>>>
>>>>>
>>>>> *Unmesha Sreeveni U.B*
>>>>> *Hadoop, Bigdata Developer*
>>>>> *Centre for Cyber Security | Amrita Vishwa Vidyapeetham*
>>>>> http://www.unmeshasreeveni.blogspot.in/
>>>>>
>>>>>
>>>>>
>>>>
>>>
>>>
>>> --
>>> *Thanks & Regards *
>>>
>>>
>>> *Unmesha Sreeveni U.B*
>>> *Hadoop, Bigdata Developer*
>>> *Centre for Cyber Security | Amrita Vishwa Vidyapeetham*
>>> http://www.unmeshasreeveni.blogspot.in/
>>>
>>>
>>>
>>
>
>
> --
> *Thanks & Regards *
>
>
> *Unmesha Sreeveni U.B*
> *Hadoop, Bigdata Developer*
> *Centre for Cyber Security | Amrita Vishwa Vidyapeetham*
> http://www.unmeshasreeveni.blogspot.in/
>
>
>

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