I ran into this issue as well. The workaround by copying jar and ivy
manually suggested by Shivaram works for me.
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On Fri, Aug 1, 2014 at 3:31
, and sparse data is supported.
It will be interesting to see new benchmark result.
Anyone familiar with BIDMach? Are they as fast as they claim?
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Are you using 1.0 or current master? A bug related to this is fixed in
master.
On Jul 12, 2014 8:50 AM, Srikrishna S srikrishna...@gmail.com wrote:
I am run logistic regression with SGD on a problem with about 19M
parameters (the kdda dataset from the libsvm library)
I consistently see that
https://issues.apache.org/jira/browse/SPARK-2156
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On Sat, Jul 12, 2014 at 5:23 PM, Srikrishna S srikrishna...@gmail.com wrote:
I am using
It means pulling the code from latest development branch from git
repository.
On Jul 9, 2014 9:45 AM, AlexanderRiggers alexander.rigg...@gmail.com
wrote:
By latest branch you mean Apache Spark 1.0.0 ? and what do you mean by
master? Because I am using v 1.0.0 - Alex
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not be
straightforward by just changing the version in spark build script.
Jetty 9.x required Java 7 since the servlet api (servlet 3.1) requires
Java 7.
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Actually, the one needed to install the jar to each individual node is
standalone mode which works for both MR1 and MR2. Cloudera and
Hortonworks currently support spark in this way as far as I know.
For both yarn-cluster or yarn-client, Spark will distribute the jars
through distributed cache
spark-clinet mode runs driver in your application's JVM while
spark-cluster mode runs driver in yarn cluster.
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On Mon, Jul 7, 2014 at 5:44 PM
You may try LBFGS to have more stable convergence. In spark 1.1, we will be
able to use LBFGS instead of GD in training process.
On Jul 4, 2014 1:23 PM, Thomas Robert tho...@creativedata.fr wrote:
Hi all,
I too am having some issues with *RegressionWithSGD algorithms.
Concerning your issue
There is no python binding for LBFGS. Feel free to submit a PR.
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On Wed, Jun 25, 2014 at 1:41 PM, Mohit Jaggi mohitja...@gmail.com wrote
))
}
System.setProperty(SPARK_YARN_MODE, true)
val sparkConf = new SparkConf
val args = getArgsFromConf(conf)
new Client(new ClientArguments(args, sparkConf), hadoopConfig,
sparkConf).run
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, etc.
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On Thu, Jun 19, 2014 at 12:08 PM, Koert Kuipers ko...@tresata.com wrote:
db tsai,
if in yarn-cluster mode the driver runs inside yarn, how
Hi Xiangrui,
What's different between treeAggregate and aggregate? Why
treeAggregate scales better? What if we just use mapPartition, will it
be as fast as treeAggregate?
Thanks.
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Hi Xiangrui,
Does it mean that mapPartition and then reduce shares the same
behavior as aggregate operation which is O(n)?
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On Tue, Jun 17
Is your data normalized? Sometimes, GD doesn't work well if the data
has wide range. If you are willing to write scala code, you can try
LBFGS optimizer which converges better than GD.
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Hi Congrui,
We're working on weighted regularization, so for intercept, you can
just set it as 0. It's also useful when the data is normalized but
want to solve the regularization with original data.
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Hi Congrui,
I mean create your own TrainMLOR.scala with all the code provided in
the example, and have it under package org.apache.spark.mllib
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Hi Congrui,
Since it's private in mllib package, one workaround will be write your
code in scala file with mllib package in order to use the constructor
of LogisticRegressionModel.
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at 11:13 AM, Aslan Bekirov aslanbeki...@gmail.com
wrote:
Thanks a lot DB.
I will try to do Znorm normalization using map transformation.
BR,
Aslan
On Thu, Jun 12, 2014 at 12:16 AM, DB Tsai dbt...@stanford.edu wrote:
Hi Aslan,
Currently, we don't have the utility function to do so
Hi Aslan,
Currently, we don't have the utility function to do so. However, you
can easily implement this by another map transformation. I'm working
on this feature now, and there will be couple different available
normalization option users can chose.
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DB Tsai
Hi Nick,
How does reduce work? I thought after reducing in the executor, it
will reduce in parallel between multiple executors instead of pulling
everything to driver and reducing there.
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tracker
for each operation will be very expensive. Is there a way to disable
this behavior?
Thanks.
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What if there are multiple threads using the same spark context, will
each of thread have it own UI? In this case, it will quickly run out
of the ports.
Thanks.
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Hi Aslan,
You can check out the unittest code of GradientDescent.runMiniBatchSGD
https://github.com/apache/spark/blob/master/mllib/src/test/scala/org/apache/spark/mllib/optimization/GradientDescentSuite.scala
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/latest/mllib-optimization.html
for detail.
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On Wed, Jun 4, 2014 at 7:56 PM, Xiangrui Meng men...@gmail.com wrote:
Hi Krishna,
Specifying executor
Hi Krishna,
It should work, and we use it in production with great success.
However, the constructor of LogisticRegressionModel is private[mllib],
so you have to write your code, and have the package name under
org.apache.spark.mllib instead of using scala console.
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DB Tsai
not serializable, it will raise exception.
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On Sun, May 18, 2014 at 12:58 PM, Robert James srobertja...@gmail.comwrote:
I see - I didn't realize that scope
will not be seen.
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in
JVM. Users can use the classes directly.
https://github.com/dbtsai/classloader-experiement/blob/master/calling/src/main/java/Calling3.java
I'm now porting example 3) to Spark, and will let you know if it works.
Thanks.
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DB Tsai
The jars are actually there (and in classpath), but you need to load
through reflection. I've another thread giving the workaround.
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On Fri
classNotFound exception.
Thanks.
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On Wed, May 14, 2014 at 6:04 PM, Xiangrui Meng men...@gmail.com wrote:
In SparkContext#addJar, for yarn
honor
it. I'm trying to figure out the problem now.
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On Wed, May 14, 2014 at 5:46 AM, wxhsdp wxh...@gmail.com wrote:
Hi, DB
i've add breeze
tomorrow.
Thanks.
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On Tue, May 13, 2014 at 11:41 PM, Xiangrui Meng men...@gmail.com wrote:
I don't know whether this would fix the problem
the loop have to be serializable. Since the for-loop is serializable
in scala, I guess you have something non-serializable inside the for-loop.
The while-loop in scala is native, so you won't have this issue if you use
while-loop.
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Hi wxhsdp,
See https://github.com/scalanlp/breeze/issues/142 and
https://github.com/fommil/netlib-java/issues/60 for details.
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On Tue, May 13
It seems that the code isn't managed in github. Can be downloaded from
http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/distributed-liblinear/spark/spark-liblinear-1.94.zip
It will be easier to track the changes in github.
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DB Tsai
jar api like Yadid said.
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On Sun, May 4, 2014 at 10:24 PM, wxhsdp wxh...@gmail.com wrote:
Hi, DB, i think it's something related to sbt
breeze jar in the spark flat
assembly jar, so you don't need to add breeze dependency yourself.
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On Sun, May 4, 2014 at 4:07 AM, wxhsdp wxh
You can drop header in csv by
rddData.mapPartitionsWithIndex((partitionIdx: Int, lines: Iterator[String])
= {
if (partitionIdx == 0) {
lines.drop(1)
}
lines
}
On May 2, 2014 6:02 PM, SK skrishna...@gmail.com wrote:
1) I have a csv file where one of the field has integer data but it
Our customer asked us to implement Naive Bayes which should be able to at
least train news20 one year ago, and we implemented for them in Hadoop
using distributed cache to store the model.
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Your code is unformatted. Can u paste the whole file in gist and i can take
a look for u.
On Apr 28, 2014 10:42 PM, Earthson earthson...@gmail.com wrote:
I've moved SparkContext and RDD as parameter of train. And now it tells me
that SparkContext need to serialize!
I think the the problem is
tolerance and data splitting
to disk.
It will be nice to have an API that we can do this type of book-keeping
with native support.
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On Sat, Apr
Which version of mllib are you using? For Spark 1.0, mllib will
support sparse feature vector which will improve performance a lot
when computing the distance between points and centroid.
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What I suggested will not work if # of records you want to drop is more
than the data in first partition. In my use-case, I only drop the first
couple lines, so I don't have this issue.
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with
Spark in SF Machine Learning Meetup, please let me know.
Thanks.
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Hi Dong,
This is pretty much what I did. I run into the same issue you have.
Since I'm not developing yarn related stuff, I just excluded those two
yarn related project from intellji, and it works. PS, you may need to
exclude java8 project as well now.
Sincerely,
DB Tsai
soon.
Sincerely,
DB Tsai
Machine Learning Engineer
Alpine Data Labs
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On Mon, Mar 31, 2014 at 11:38 PM, Tsai Li Ming mailingl...@ltsai.comwrote:
Hi,
Is the code available for Hadoop to calculate the Logistic Regression
hyperplane
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