To make it more general, it's better to separate them. Since there might be
multiple batches of training (or to-be-label), and you only need to train
the model once (if your data is stable).
Ok , I will go for the second one.
So if we are going for separate.They will not have any connection with
b
Actually the training and testing (or prediction) are not necessary to be
done in one shot. If you need to do them consecutively in your particular
scenario, you can do it as what you said.
To make it more general, it's better to separate them. Since there might be
multiple batches of training (or
1. I jst thought of building a model using a project named say DT and wen a
huge input comes do another mr job test.java with in DT.
If not chaining jobs we need to create seperate project right DT_build and
DT_test projects
NO need for seperate project file?
2. M1_train - dataset for training.
M1
I am trying to configure hadoop 2.2.0 from source code and I found the
instructions really crappy and incomplete. It is like they were written to
avoid someone can do the job himself and must contract someone else to do
it or buy a packaged version.
It is about three days I am struggling with this
What is your motivation of using chaining jobs?
2013/12/1 unmesha sreeveni
> Thanks Yexi...A very nice explanation...Thanks a lot..
> Explained in a very simple way which is really understandable for
> beginners..Thanks a lot.
> I can go for chaining jobs right?
>
>
>
>
>
> On Sun, Dec 1, 2013
Thanks Yexi...A very nice explanation...Thanks a lot..
Explained in a very simple way which is really understandable for
beginners..Thanks a lot.
I can go for chaining jobs right?
On Sun, Dec 1, 2013 at 8:55 PM, Yexi Jiang wrote:
> In my opinion.
>
> 1. Build the decision tree model with the
I implemented jt ha on cdh4.4.2 . Jobtracker keeps on failing over to each
other, job keeps restarting, also namenode goes down at times and I can see
logs for few datanodes mentioning all data nodes are bad. aborting.
I installed jt ha manually like this :-
After configuring jt ha i started j
Hello,
I'm currently writing code to run my application using Yarn (Hadoop 2.2.0).
I used this code as a skeleton:
https://github.com/hortonworks/simple-yarn-app
Everything works fine on my local machine or on a cluster with the shared
directories, but when I want to access resources outside of c
In my opinion.
1. Build the decision tree model with the training data.
2. Store it somewhere.
3. When the unlabeled data is available:
3.1 if the unlabeled data is huge, write another mrjob to process them,
load the model at the setup stage, use the model to label the data one by
one in map st
Thanks Yexi ,
But how it can be accomplished.
The input to Desicion Tree MR will be a set of data. But while
predicting a data it will be a one line data without classlabel right?
So what changes will be there in mrjob.Should we design like this.
1. When a set of data is coming draw Desicion tree
Hi,
I found the page (
http://hadoop.apache.org/docs/stable/hadoop-yarn/hadoop-yarn-site/WritingYarnApplications.html)
and know how to write an ApplicationMaster.
However, is there a complete example showing how to run this
ApplicationMaster with a real Hadoop Program (e.g. WordCount) on YARN?
T
11 matches
Mail list logo
