all right, thanks~
在 2012年7月5日星期四，Marcos Ortiz 写道：
> Jason,
> Ramon is right.
> The best way to debug a MapReduce job is mounting a local cluster, and
> then, when you have tested enough your code, then, you can
> deploy it in a real distributed cluster.
> On 07/04/2012 10
using iptables :(
在 2012年7月4日星期三， 写道：
> Jason,
>
>
>the easiest way to debug a MapRedupe program with eclipse is working
> on hadoop local.
> http://hadoop.apache.org/common/docs/r0.20.2/quickstart.html#Local In
> this mode all the components run locally on the same
Hi, all
I have a hadoop cluster with 3 nodes, the network topology is like this:
1. For each DataNode, its IP address is like :192.168.0.XXX;
2. For the NameNode, it has two network cards: one is connect with the
DataNodes as a local LAN with IP address 192.168.0.110, while the other one
is connec
.dll into the PATH.
> And everything works.
>
> Zhu, Guojun
> Modeling Sr Graduate
> 571-3824370
> guojun_...@freddiemac.com
> Financial Engineering
> Freddie Mac
>
>
> *jason Yang *
>
>05/23/2012 05:37 AM
> Please respond to
> mapreduce-user@had
Hi, All~
Currently, I'm trying to rewrite an algorithm to MapReduce form. Since the
algorithm depends on some third-party DLLs which are written in C++, I was
wondering would I call a DLL in the Map() / Reduce() by using JNI?
Thanks.
--
YANG, Lin
You can extend/customize MultipleOutputs and pass schema related settings via
properties prefixed with MO name, just like it is done with format classes
there.
Also to send a dummy key or value why not just to use NullWritable? It's
efficient as it does not consume any space.
Sent from my iPho
everal times until the mapper
> had generated all sets of the form
>
>
> On Wed, Jun 22, 2011 at 5:13 PM, Jason wrote:
> I remember I had a similar problem.
> The way I approached it was by partitioning one of the data sets. At high
> level these are the steps:
>
I remember I had a similar problem.
The way I approached it was by partitioning one of the data sets. At high level
these are the steps:
Suppose you decide to partition set A.
Each partition represents a subset/range of the A keys and must be small enough
to fit records in memory.
Each partit
Look at NLineInputFormat
Sent from my iPhone
On May 23, 2011, at 2:09 AM, Vincent Xue wrote:
> Hello Hadoop Users,
>
> I would like to know if anyone has ever tried splitting an input
> sequence file by key instead of by size. I know that this is unusual
> for the map reduce paradigm but I am
M/R job with a single reducer would do the job. This way you can
utilize distributed sort and merge/combine/dedupe key/values as you
wish.
On 5/11/11, 丛林 wrote:
> Hi all,
>
> There is lots of SequenceFile in HDFS, how can I merge them into one
> SequenceFile?
>
> Thanks for you suggestion.
>
> -L
It is actually trivial to do using MultipleOutputs. You just need to emit your
key-values to both MO and standard output context/collector in your mapper.
Two things you should know about MO:
1. Early implementation has a serious (couple of order of magnitude)
performance bug
2. Output files not
I think this kind of partitioner is a little hackish. More straight forward
approach is to emit the extra data N times under special keys and write a
partitioner that would recognize these keys and dispatch them accordingly
between partitions 0..N-1
Also if this data needs to be shipped to reduc
I am afraid that by reading an hdfs file manually in your mapper, you are
loosing data locality.
You can try putting smaller vectors into distributed cache and preload them all
in memory in the mapper setup. This implies that they can fit in memory and
also that you can change your m/r to run ov
t from my iPhone 4
On Dec 18, 2010, at 3:19 PM, Martin Becker <_martinbec...@web.de> wrote:
> Hello Jason,
>
> real time values are not required. Some lagging is tolerable. The
> value/threshold communication is only needed to keep other reducers
> from doing unnecessary work.
> Reducers would retrieve that increased value when accessing the same
> Counter?
I do not think counters reflect real time value. Even if they get updated the
values will lag.
If you require uptodate value I am afraid you will have to run a single reducer.
Sent from my iPhone 4
On Dec 18, 201
Take a look at NLineInputFormat. You might want to use it in combination with
DistributedCache.
Sent from my iPhone
On Dec 9, 2010, at 5:02 AM, Narinder Kumar wrote:
> Hi All,
>
> We have a problem in hand which we would like to solve using Distributed and
> Parallel Processing.
>
> Probl
When most of the work is done by reducer at cleanup ( takes 90% of the job
time) how can I report a proper progress of the overall job?
By default the job tracker shows 100% right after all records are passed
through the reduce(). I would rather like to see 10% after all reduce() calls
and the
Great! mapred.map.tasks and mapred.task.partition work perfectly for me, even
for the local job runner.
Thanks
On Dec 3, 2010, at 5:59 PM, Harsh J wrote:
> Hi,
>
> (Answers may be 0.20 specific)
>
> On Sat, Dec 4, 2010 at 6:41 AM, Jason wrote:
>> In my mapper code I n
> BTW, why not take task attempt id context.getTaskAttemptID() as the
> prefix of unique id ? The task attempt id for each task should be
> different
The reason is that I would prefer to not have big gaps in my int id sequence,
so i'd rather store mapper task ID in the low bits (suffix instead of
In my mapper code I need to know the total number of mappers which is the same
as number of input splits.
(I need it for unique int Id generation)
Basically Im looking for an analog of context.getNumReduceTasks() but can't
find it.
Thanks
>
t and guarantee your seat to this year's event!
--
Jason Dixon
OmniTI Computer Consulting, Inc.
jdi...@omniti.com
443.325.1357 x.241
your seat to this year's event!
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Thanks,
--
Jason Dixon
OmniTI Computer Consulting, Inc.
jdi...@omniti.com
443.325.1357 x.241
your business sponsor/exhibit at Surge 2010, please contact us at
su...@omniti.com.
Thanks!
--
Jason Dixon
OmniTI Computer Consulting, Inc.
jdi...@omniti.com
443.325.1357 x.241
icipating as an exhibitor, please
visit the Surge website or contact us at su...@omniti.com.
Thanks,
--
Jason Dixon
OmniTI Computer Consulting, Inc.
jdi...@omniti.com
443.325.1357 x.241
n
Surge is just what you've been waiting for. For more information,
including CFP, sponsorship of the event, or participating as an
exhibitor, please contact us at su...@omniti.com.
Thanks,
--
Jason Dixon
OmniTI Computer Consulting, Inc.
jdi...@omniti.com
443.325.1357 x.241
There is a very clear picture in chapter 8 of pro hadoop, on all of the
separators for streaming jobs.
On Tue, Nov 10, 2009 at 6:53 AM, wd wrote:
> You mean the ^A ?
> I tried \u0001 and \x01, the streaming job recognise it as a string, not
> ^A..
>
> :(
>
> 2009/11/10 Amogh Vasekar
>
> Hi,
>
The dfs client code waits until the all of the datanodes that are going to
hold a replica of your output's blocks have ack'd.
If you are pausing there, most likely something is wrong in your hdfs
cluster.
On Thu, Nov 12, 2009 at 7:06 AM, Ted Xu wrote:
> hi all,
>
> We are using hadoop-0.19.1 on
All of your data has to be converted back and forth to strings, and passed
through pipes from the jvm to your task and back from the task to the jvm.
On Thu, Nov 12, 2009 at 10:06 PM, Alexey Tigarev
wrote:
> Hi All!
>
> How much overhead using Hadoop Streming vs. native Java steps does add?
>
>
Your log messages to stdout,stderr and syslog will end up in the
logs/userlogs directory of your task tracker.
If the job is still visible via the web ui for the job tracker host (usually
port 50030), you can select the individual tasks that were run for your job,
and if you click through enough s
Your eclipse instance doesn't have the jar files in the lib directory of
your hadoop installation in the class path.
On Sat, Nov 14, 2009 at 7:51 PM, felix gao wrote:
> I wrote a simple code in my eclipse as
>
> Text t = new Text("hadoop");
> System.out.println((char)t.charAt(2));
>
> when I tr
The failure appear or occur in code in the system dynamic linker, which
implies a shared library compatibility problem, or a heap shortfall
On Mon, Oct 26, 2009 at 2:25 PM, Ed Mazur wrote:
> Err, disregard that.
>
> $ cat /proc/version
> Linux version 2.6.9-89.0.9.plus.c4smp (mockbu...@builder10
This error is very common in applications that run out of file descriptors
or simply open vast numbers of files on an and HDFS with a very high block
density per datanode.
It is quite easy to open hundreds of thousands of files with the
Multi*OutputFormat classes.
If you can collect your output in
Are you perhaps creating large numbers of files, and running out of file
descriptors in your tasks.
On Wed, Oct 7, 2009 at 1:52 PM, Geoffry Roberts
wrote:
> All,
>
> I have a MapRed job that ceases to produce output about halfway through.
> The obvious question is why?
>
> This job reads a file a
I have seen this happen when there are inconsistent hostname to ip address
lookups across the cluster and a node running a reducer is not connecting to
the host that actually has the map output due to getting a different ip
address for the node name.
On Mon, Jul 27, 2009 at 9:46 AM, Geoffry Robert
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