Dear Spark developers,
I am exploring how to make linear algebra operations faster within Spark. One
way of doing this is to use Scala Breeze library that is bundled with Spark.
For matrix operations, it employs Netlib-java that has a Java wrapper for BLAS
(basic linear algebra subprograms)
Dear Spark developers,
I am trying to measure the Spark reduce performance for big vectors. My
motivation is related to machine learning gradient. Gradient is a vector that
is computed on each worker and then all results need to be summed up and
broadcasted back to workers. For example,
aggregation? If that is the problem, then
how to force it to do aggregation after receiving each portion of data from
Workers?
Best regards, Alexander
-Original Message-
From: DB Tsai [mailto:dbt...@dbtsai.com]
Sent: Friday, January 23, 2015 11:53 AM
To: Ulanov, Alexander
Cc: dev
,
changes to memory between different threads is bad.
There's actually a potential bug in the KMeans code where it uses
+= instead of +.
On Wed, Sep 3, 2014 at 1:26 PM, Ulanov, Alexander
alexander.ula...@hp.com
wrote:
Hi,
Is breeze library called thread safe from Spark mllib code
Hi,
Is breeze library called thread safe from Spark mllib code in case when native
libs for blas and lapack are used? Might it be an issue when running Spark
locally?
Best regards, Alexander
-
To unsubscribe, e-mail:
, 2014 at 1:26 PM, Ulanov, Alexander
alexander.ula...@hp.com
wrote:
Hi,
Is breeze library called thread safe from Spark mllib code in case
when
native libs for blas and lapack are used? Might it be an issue when
running
Spark locally?
Best regards, Alexander
at 8:15 AM, Ulanov, Alexander
alexander.ula...@hp.commailto:alexander.ula...@hp.com wrote:
Hi, RJ
https://github.com/avulanov/spark/blob/neuralnetwork/mllib/src/main/scala/org/apache/spark/mllib/classification/NeuralNetwork.scala
Unit tests are in the same branch.
Alexander
From: RJ Nowling
Hi,
I'm trying to create a maven project that references the latest build of Spark.
1)downloaded sources and compiled the latest version of Spark.
2)added new spark-core jar to the a new local maven repo
3)created Scala maven project with net.alchim31.maven (scala-archetype-simple v
1.5)
4)added
FYI This is my first take on feature selection, filtering and chi-squared:
https://github.com/apache/spark/pull/1484
-Original Message-
From: Ulanov, Alexander
Sent: Thursday, July 10, 2014 9:39 PM
To: dev@spark.apache.org
Subject: Feature selection interface
Hi,
I've implemented
Hi,
I've implemented a class that does Chi-squared feature selection for
RDD[LabeledPoint]. It also computes basic class/feature occurrence statistics
and other methods like mutual information or information gain can be easily
implemented. I would like to make a pull request. However, MLlib
Hi,
I wonder how I can pass parameters to RDD functions with closures. If I do it
in a following way, Spark crashes with NotSerializableException:
class TextToWordVector(csvData:RDD[Array[String]]) {
val n = 1
lazy val x = csvData.map{ stringArr = stringArr(n)}.collect()
}
Exception:
Job
, Ulanov, Alexander alexander.ula...@hp.com
wrote:
Hi,
I wonder how I can pass parameters to RDD functions with closures. If I do it
in a following way, Spark crashes with NotSerializableException:
class TextToWordVector(csvData:RDD[Array[String]]) {
val n = 1
lazy val x = csvData.map
a project there which used
autoencoder functions...It's not updated for a long time now !
On Thu, Jun 26, 2014 at 10:51 PM, Ulanov, Alexander
alexander.ula...@hp.com
wrote:
Hi Bert,
It would be extremely interesting. Do you plan to implement
autoencoder as
well? It would be great
Hi Ron Hu,
The Idea project generated with update gen-idea didn't work properly for me
as well. My workaround is to open corresponding Maven project in Idea
(File-Open look for .bom file). To compile the opened project I use Maven
window in Idea (View-show Maven ). However, tests fail to
Hi Bert,
It would be extremely interesting. Do you plan to implement autoencoder as
well? It would be great to have deep learning in Spark.
Best regards, Alexander
27.06.2014, в 4:47, Bert Greevenbosch bert.greevenbo...@huawei.com
написал(а):
Hello all,
I was wondering whether
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