Hi All,
I have some questions about the map output.
As far as I know, the map output is written to the local disk then
shipped to reducer via network. Is this correct? Does it read from and
written to the disk multiple times or only once when the map task
ends? Which parts of the Hadoop code
Moving to mapreduce-user@, bcc common-u...@. Please use the appropriate project
list.
The map output is saved to disk at the end of the map. However, if there is
insufficient memory, we do intermediate spills. The config knob io.sort.mb
controls the memory available to keep map outputs
Hi,
>>As far as I know, the map output is written to the local disk then shipped to
>>reducer via network. Is this correct?
Yes. Each reducer picks up its own partition from the map output, once the map
task completes.
However, its little more complicated (and very interesting) on
strings
and add the doubles. We could have doubles as strings too and we can cast
them back to doubles but I think it would be computationally easy if they
are doubles after the map job to start with.
Any clues?
Thanks
--
View this message in context:
http://www.nabble.com/Multiple-map-output
All
I am encountering the following out-of-memory error during the reduce phase of
a large job.
Map output copy failure : java.lang.OutOfMemoryError: Java heap space
at
org.apache.hadoop.mapred.ReduceTask$ReduceCopier$MapOutputCopier.shuffleInMemory(ReduceTask.java:1669)
at
Is there a way to get the value of "Map output records" from within the
Reducer ?
I want to know the total number of the "Map output records" while the
Reducer is running and I've noticed this value in the web interface shown
for each Map.
Or is there a way to read in Red
ich version of hadoop using?
Devaraj K
-Original Message-
From: Niranjan Balasubramanian [mailto:niran...@cs.washington.edu]
Sent: Thursday, December 08, 2011 12:21 AM
To: common-user@hadoop.apache.org
Subject: OOM Error Map output copy.
All
I am encountering the following out-of-mem
Balasubramanian [mailto:niran...@cs.washington.edu]
> Sent: Thursday, December 08, 2011 12:21 AM
> To: common-user@hadoop.apache.org
> Subject: OOM Error Map output copy.
>
> All
>
> I am encountering the following out-of-memory error during the reduce phase
> of a larg
:+UseSerialGC
>>
>>
>> and also can you tell me which version of hadoop using?
>>
>>
>> Devaraj K
>>
>> -Original Message-
>> From: Niranjan Balasubramanian [mailto:niran...@cs.washington.edu]
>> Sent: Thursday, December 08,
mx1536M -XX:+UseSerialGC
>>
>>
>> and also can you tell me which version of hadoop using?
>>
>>
>> Devaraj K
>>
>> -Original Message-
>> From: Niranjan Balasubramanian [mailto:niran...@cs.washington.edu]
>> Sent: Thursday,
our
job to a queue with a small capacity and max-capacity to restrict your job to
10 or 20 concurrent reduces at a given point.
Arun
On Dec 7, 2011, at 10:51 AM, Niranjan Balasubramanian wrote:
> All
>
> I am encountering the following out-of-memory error during the reduce phase
>
,
int compressedLength)
throws IOException, InterruptedException {
// Reserve ram for the map-output
.
.
.
.
// Copy map-output into an in-memory buffer
byte[] shuffleData = new byte[mapOutputLength];
-Prahant Kommireddi
On Fri, Dec 9, 2011 at 10:29 AM
throws IOException, InterruptedException {
>// Reserve ram for the map-output
> .
> .
> .
> .
>
>// Copy map-output into an in-memory buffer
>byte[] shuffleData = new byte[mapOutputLength];
>
>
> -Prahant Kommireddi
>
> On Fri, Dec
InputStream input,
>> int mapOutputLength,
>> int compressedLength)
>> throws IOException, InterruptedException {
>> // Reserve ram for the map-output
>> .
>> .
>> .
>> .
Hi all,
after finish one mapreduce job, the statistics shows that the number of records
map generated is not equal to the number of records that reduce input. It says:
Map output records=15
Reduce input records=93282
I think it is abnormal. Please give me some ideas how this happen and how
I'm seeing this error when a job runs:
Shuffling 35338524 bytes (35338524 raw bytes) into RAM from
attempt_201001051549_0036_m_03_0
Map output copy failure: java.lang.OutOfMemoryError: Java heap space
at
org.apache.hadoop.mapred.ReduceTask$ReduceCopier$MapOutputCopier.shuffleInM
Hi,
I have a sort job consisting of only the Mapper (no Reducer) task. I want my
results to contain only the top n records. Is there any way of restricting
the number of records that are emitted by the Mappers?
Basically I am looking to see if there is an equivalent of achieving
the behavior simi
Hi,
How can memory usage be calculated in case of BZip2Codec for map output?
Cheers,
Attila
Hello forumers,
Before spill the data in kvbuffer to local disk in map task, k/v are
sorted using quick sort. The complexity of quick sort is O(nlogn) and
worst case is O(n^2).
Why using quick sort?
Regards
Do you have any combiner implemented in your job ?
On 12/10/2009 09:11 PM, Gang Luo wrote:
Hi all,
after finish one mapreduce job, the statistics shows that the number of records
map generated is not equal to the number of records that reduce input. It says:
Map output records=15
Reduce
Reduce shuffle bytes=10266764
Reduce output records=43282
Spilled Records=30
Map output bytes=9966746
Map input bytes=18711537
Combine input records=0
Map output records=15
Reduce input records=93282
-Gang
- 原始邮件
发件人: Huy Phan
收件人: common-user@hadoop.apache.org
发送日期: 2009/12/10
Hi,
Can you please let us know your system configuration running hadoop?
The error you see is when the reducer is copying its respective map output into
memory. The parameter mapred.job.shuffle.input.buffer.percent can be
manipulated for this ( a bunch of others will also help you optimize sort
Amogh Vasekar wrote:
Hi,
Can you please let us know your system configuration running hadoop?
The error you see is when the reducer is copying its respective map output into
memory. The parameter mapred.job.shuffle.input.buffer.percent can be
manipulated for this ( a bunch of others will also
New to Hadoop (now using 0.20.1), I want to know how to choose and set up
compression methods for Map output, especially how to configure and use LZO
compression?
Specifically, please share your experience for the following 2 scenarios.
Thanks!
(1) Is there a global setting in some
Hi hadoop Gurus, here's a question about intermediate compression.
As I understand, the point to compress Map output is to reduce network traffic
that occur when feeding sequence files from Map to Reduce tasks which do not
reside on the same boxes as Map tasks. So, depending on various fa
Either use an instance variable or a Combiner. The latter is correct
if you want the top-n per key from the mapper.
On Wed, Jan 12, 2011 at 10:03 AM, Rakesh Davanum wrote:
> Hi,
>
> I have a sort job consisting of only the Mapper (no Reducer) task. I want my
> results to contain only the top n r
Ideally, mappers should be independent of other mappers. Still, you can use
counters and start skipping records when counter>some value to achieve
similar behavior. It will not be very reliable if you want very exact
results though.
On Thu, Jan 13, 2011 at 12:43 AM, Anthony Urso wrote:
> Either
Hi Rakesh, What do you mean by the top N? The first ones or you need to
sort them in memory? You can always output records in the cleanup() method
at the end of the mapper run.
On Fri, Jan 14, 2011 at 7:05 AM, Hari Sreekumar wrote:
> Ideally, mappers should be independent of other mappers. Stil
Hi,
> I have a sort job consisting of only the Mapper (no Reducer) task. I want my
> results to contain only the top n records. Is there any way of restricting
> the number of records that are emitted by the Mappers?
>
> Basically I am looking to see if there is an equivalent of achieving
> the be
Sorting out of the map phase is core to how hadoop works. Are you asking why
sort at all? or why did someone use quick sort as opposed to _sort?
Cheers
James
On 2011-02-28, at 3:30 AM, elton sky wrote:
> Hello forumers,
>
> Before spill the data in kvbuffer to local disk in map task, k/
one of the major reasons of using quicksort would be that quicksort
can easily be parallalized...due to its divide and conquer nature
On Mon, Feb 28, 2011 at 6:06 PM, James Seigel wrote:
> Sorting out of the map phase is core to how hadoop works. Are you asking why
> sort at all? or why did so
>From this week,My Hadoop caught his problem with information as following:
Lost task tracker: tracker_rsync.host01:localhost/127.0.0.1:40759
Map output lost, rescheduling:
getMapOutput(attempt_201108021855_6734_m_97_1,2002) failed :
org.apache.hadoop.util.DiskChecker$DiskErrorExcept
10266764
> Reduce output records=43282
> Spilled Records=30
> Map output bytes=9966746
> Map input bytes=18711537
> Combine input records=0
> Map output records=15
> Reduce input records=93282
>
> -Gang
al Message
From: jiang licht
To: common-user@hadoop.apache.org
Sent: Wed, February 17, 2010 12:26:48 AM
Subject: LZO compression for Map output in Hadoop 0.20+?
New to Hadoop (now using 0.20.1), I want to know how to choose and set up
compression methods for Map output, especially how to configu
Thanks Himanshu. Is there a part 2?
--
Michael
--- On Tue, 2/16/10, himanshu chandola wrote:
From: himanshu chandola
Subject: Re: LZO compression for Map output in Hadoop 0.20+?
To: common-user@hadoop.apache.org
Date: Tuesday, February 16, 2010, 11:35 PM
You might want to check out this
: Wed, February 17, 2010 3:26:26 AM
Subject: Re: LZO compression for Map output in Hadoop 0.20+?
Thanks Himanshu. Is there a part 2?
--
Michael
--- On Tue, 2/16/10, himanshu chandola wrote:
From: himanshu chandola
Subject: Re: LZO compression for Map output in Hadoop 0.20+?
To: common-user@ha
http://code.google.com/p/hadoop-gpl-compression/
Arun
On Feb 16, 2010, at 9:26 PM, jiang licht wrote:
New to Hadoop (now using 0.20.1), I want to know how to choose
and set up compression methods for Map output, especially how to
configure and use LZO compression?
Specifically, please
Hi Todd,
I didn't change the partitioner, just use the default one. Will the default
partitioner cause the lost of the records?
-Gang
- 原始邮件
发件人: Todd Lipcon
收件人: common-user@hadoop.apache.org
发送日期: 2009/12/10 (周四) 3:37:18 下午
主 题: Re: Re: map output not euqal to reduce inpu
On Thu, Dec 10, 2009 at 1:15 PM, Gang Luo wrote:
> Hi Todd,
> I didn't change the partitioner, just use the default one. Will the default
> partitioner cause the lost of the records?
>
> -Gang
>
Do the maps output data nondeterministically? Did you experience any
task failures in the run of the
In the mapper of this job, I get something I am interested in for each
line and then output all of them. So the number of map input records is
equal to the map output records. Actually, I am doing semi join in this
job. There is no failure during execution.
-Gang
- 原始邮件
发件人: Todd
I have a pig script. If I don't set any codec for Map output for hadoop
cluster, no problem. Now I made the following compression settings, the job
failed and the error message is shown below. I guess there are some other
settings that should be correctly set together with using the compre
Hi, everyone
I'm a beginner of hadoop.
I notice it from the web console after I've tried to run serveral jobs.
Every one of the jobs has the number of Spilled Records equal to Map output
records, even if there are only 5 map output records
In the reduce phase, there are also spill
Thanks, Amogn.
I am not sure whether all the records mepper generate are consumed by reducer.
But how do you define 'consumed by reducer'? I can set a counter to see how
many lines go to my map function, but this is likely the same as reduce input #
which is less than map output #.
ript. If I don't set any codec for Map output for hadoop
cluster, no problem. Now I made the following compression settings, the job
failed and the error message is shown below. I guess there are some other
settings that should be correctly set together with using the compression. Im
using 0.20.
in hadoop wiki :) )
Amogh
On 2/23/10 8:16 AM, "jiang licht" wrote:
I have a pig script. If I don't set any codec for Map output for hadoop
cluster, no problem. Now I made the following compression settings, the job
failed and the error message is shown below. I guess there are some
hael
--- On Mon, 2/22/10, Amogh Vasekar wrote:
From: Amogh Vasekar
Subject: Re: java.io.IOException: Spill failed when using w/ GzipCodec for Map
output
To: "common-user@hadoop.apache.org"
Date: Monday, February 22, 2010, 11:27 PM
Hi,
Can you please let us know what platform you are ru
Thanks, Amogh. Good to know :)
Michael
--- On Tue, 2/23/10, Amogh Vasekar wrote:
From: Amogh Vasekar
Subject: Re: java.io.IOException: Spill failed when using w/ GzipCodec for Map
output
To: "common-user@hadoop.apache.org"
Date: Tuesday, February 23, 2010, 1:45 AM
Hi,
Certainly
On Jul 12, 2009, at 3:55 AM, Mu Qiao wrote:
I notice it from the web console after I've tried to run serveral
jobs.
Every one of the jobs has the number of Spilled Records equal to Map
output
records, even if there are only 5 map output records
This is good. The map outputs need
ote:
>
> I notice it from the web console after I've tried to run serveral jobs.
>> Every one of the jobs has the number of Spilled Records equal to Map
>> output
>> records, even if there are only 5 map output records
>>
>
>
> This is good. The map ou
wrote:
> >
> > I notice it from the web console after I've tried to run serveral jobs.
> >> Every one of the jobs has the number of Spilled Records equal to Map
> >> output
> >> records, even if there are only 5 map output records
> >>
> >
&
from the web console after I've tried to run serveral
> jobs.
> > >> Every one of the jobs has the number of Spilled Records equal to Map
> > >> output
> > >> records, even if there are only 5 map output records
> > >>
> > >
> &g
There is no requirement that all of the reduces are running while the map is
running. The dataflow is that the map writes its output to local disk and
that the reduces pull the map outputs when they need them. There are threads
handling sorting and spill of the records to disk, but that doesn't rem
Thanks. But when I refer to "Hadoop: The Definitive Guide" chapter 6, I find
that the map writes its outputs to a memory buffer(not to local disk) whose
size is controlled by io.sort.mb. Only the buffer reaches its threshold, it
will spill the outputs to local disk. If that is true, I can't see any
It is true, map writes its output to a memory buffer. But when the map
process is complete, the contents of this buffer are sorted and spilled to
the disk so that the Task Tracker running on that node can serve these map
outputs to the requesting reducers.
On 7/15/09 7:59 AM, "Mu Qiao" wrote:
>
Thanks. It's clear now. :)
On Wed, Jul 15, 2009 at 11:40 AM, Jothi Padmanabhan
wrote:
> It is true, map writes its output to a memory buffer. But when the map
> process is complete, the contents of this buffer are sorted and spilled to
> the disk so that the Task Tracker running on that node can
ot; wrote:
In the mapper of this job, I get something I am interested in for each
line and then output all of them. So the number of map input records is
equal to the map output records. Actually, I am doing semi join in this
job. There is no failure during execution.
-Gang
- ԭʼ�ʼ�
��
quot;Gang Luo" wrote:
Thanks, Amogn.
I am not sure whether all the records mepper generate are consumed by reducer.
But how do you define 'consumed by reducer'? I can set a counter to see how
many lines go to my map function, but this is likely the same as reduce input #
which is l
-
发件人: Amogh Vasekar
收件人: "common-user@hadoop.apache.org"
发送日期: 2009/12/15 (周二) 1:59:14 上午
主 题: Re: Re: Re: Re: Re: map output not euqal to reduce input
>>how do you define 'consumed by reducer'
Trivially, as long as you have your values iterator go to the end, you shoul
Yes, in terms of 'Java types', they _must_ match. That doesn't mean
you can't set them all to just 'Writable' and have fun, I think ;)
2011/8/3 Daniel,Wu :
> should they matched exactly?
>
--
Harsh J
Hi all,
I'd like to know does the map task push map output to reduce task or reduce
task pull it from map task ? Which way is real in hadoop ?
Thank you very much.
Jeff zhang
bottle neck, but in reality it
seems it isnt .
btw, Wait for some expert to answer, I m a beginner too !
On Mon, Oct 26, 2009 at 9:05 PM, Jeff Zhang wrote:
> Hi all,
>
> I'd like to know does the map task push map output to reduce task or reduce
> task pull it from map task ? Whi
On Oct 26, 2009, at 6:05 PM, Jeff Zhang wrote:
I'd like to know does the map task push map output to reduce task or
reduce
task pull it from map task ? Which way is real in hadoop ?
In 0.19, it appears to be a pull. Look at the run() method in mapred/
org/apache/hadoop/m
O(n) , S&S is O(nlogn),
so if the amount of intermediate data is huge you will see a relative drop in
performance.
Amogh
On 10/27/09 6:35 AM, "Jeff Zhang" wrote:
Hi all,
I'd like to know does the map task push map output to reduce task or reduce
task pull it from map task
Don't
know what the equivalent would be in the mapreduce package
in 0.20.x.
dave bayer
The framework code to do with fetching of map outputs is the same for
both the mapred and mapreduce based reducers.
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