Hi Li-Ming,
This binary logistic regression using SGD is in
https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/mllib/classification/LogisticRegression.scala
We're working on multinomial logistic regression using Newton and L-BFGS
optimizer now. Will be released
Thanks.
What will be equivalent code in Hadoop where Spark published the 110s/0.9s
comparison?
On 1 Apr, 2014, at 2:44 pm, DB Tsai dbt...@alpinenow.com wrote:
Hi Li-Ming,
This binary logistic regression using SGD is in
I think with addJar() there is no 'caching', in the sense files will be
copied everytime per job.
Whereas in hadoop distributed cache, files will be copied only once, and a
symlink will be created to the cache file for subsequent runs:
Spark now shades its own protobuf dependency so protobuf 2.4.1 should't be
getting pulled in unless you are directly using akka yourself. Are you?
No i'm not. Although I see that protobuf libraries are directly pulled into the
0.9.0 assembly jar - I do see the shaded version as well.
e.g.
Hi All,
I have a five node spark cluster, Master, s1,s2,s3,s4.
I have passwordless ssh to all slaves from master and vice-versa.
But only one machine, s2, what happens is after 2-3 minutes of my
connection from master to slave, the write-pipe is broken. So if try to
connect again from master i
Hello, I would like to have a kind of sub windows. The idea is to have 3
windows in the following way:
future - --
past
w1 w2 w3
So I can do some processing with the
hello..
i am on my second day with spark.. and im having trouble getting the foreach
function to work with the network wordcount example.. i can see the the
flatMap and map methods are being invoked.. but i dont seem to be getting
into the foreach method... not sure if what i am doing even
How do you remove the validation blocker from the compilation?
Thank you
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View this message in context:
http://apache-spark-user-list.1001560.n3.nabble.com/Unable-to-submit-an-application-to-standalone-cluster-which-on-hdfs-tp1730p3574.html
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i would like to write a custom receiver to receive data from a Tibco RV subject
i found this scala example..
http://spark.incubator.apache.org/docs/0.8.0/streaming-custom-receivers.html
but i cant seem to find a java example
does anybody know of a good java example for creating a custom receiver
Hi all;
Can someone give me some tips to compute mean of RDD by key , maybe with
combineByKey and StatCount.
Cheers,
Jaonary
Some related discussion: https://github.com/apache/spark/pull/246
On Tue, Apr 1, 2014 at 8:43 AM, Philip Ogren philip.og...@oracle.comwrote:
Hi DB,
Just wondering if you ever got an answer to your question about monitoring
progress - either offline or through your own investigation. Any
You could probably port it back, but it required some changes on the Java side
as well (a new PythonMLUtils class). It might be easier to fix the Mesos issues
with 0.9.
Matei
On Apr 1, 2014, at 8:53 AM, Ian Ferreira ianferre...@hotmail.com wrote:
Hi there,
For some reason the
Yes I'm using akka as well. But if that is the problem then I should have
been facing this issue in my local setup as well. I'm only running into this
error on using the spark standalone cluster.
But will try out your suggestion and let you know.
Thanks
Kanwal
--
View this message in context:
The discussion there hits on the distinction of jobs and stages.
When looking at one application, there are hundreds of stages,
sometimes thousands. Depends on the data and the task. And the UI
seems to track stages. And one could independently track them for
such a job.
I've removed the dependency on akka in a separate project but still running
into the same error. In the POM Dependency Hierarchy I do see 2.4.1 - shaded
and 2.5.0 being included. If there is a conflict with project dependency I
would think I should be getting the same error in my local setup as
SPARK_HADOOP_VERSION=2.0.0-cdh4.2.1 sbt/sbt assembly
That's all I do.
On Apr 1, 2014, at 11:41 AM, Patrick Wendell pwend...@gmail.com wrote:
Vidal - could you show exactly what flags/commands you are using when you
build spark to produce this assembly?
On Tue, Apr 1, 2014 at 12:53 AM,
Alright, so I've upped the minSplits parameter on my call to textFile, but
the resulting RDD still has only 1 partition, which I assume means it was
read in on a single process. I am checking the number of partitions in
pyspark by using the rdd._jrdd.splits().size() trick I picked up on this
list.
When my tuple type includes a generic type parameter, the pair RDD
functions aren't available. Take for example the following (a join on two
RDDs, taking the sum of the values):
def joinTest(rddA: RDD[(String, Int)], rddB: RDD[(String, Int)]) :
RDD[(String, Int)] = {
rddA.join(rddB).map {
Looks like you're right that gzip files are not easily splittable [1], and
also about everything else you said.
[1]
http://mail-archives.apache.org/mod_mbox/spark-user/201310.mbox/%3CCANDWdjY2hN-=jXTSNZ8JHZ=G-S+ZKLNze=rgkjacjaw3tto...@mail.gmail.com%3E
On Tue, Apr 1, 2014 at 1:51 PM, Nicholas
import org.apache.spark.SparkContext._
import org.apache.spark.rdd.RDD
import scala.reflect.ClassTag
def joinTest[K: ClassTag](rddA: RDD[(K, Int)], rddB: RDD[(K, Int)]) :
RDD[(K, Int)] = {
rddA.join(rddB).map { case (k, (a, b)) = (k, a+b) }
}
On Tue, Apr 1, 2014 at 4:55 PM, Daniel
Koert's answer is very likely correct. This implicit definition which
converts an RDD[(K, V)] to provide PairRDDFunctions requires a ClassTag is
available for K:
https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/SparkContext.scala#L1124
To fully understand what's
Just an FYI, it's not obvious from the
docshttp://spark.incubator.apache.org/docs/latest/api/pyspark/pyspark.rdd.RDD-class.html#partitionBythat
the following code should fail:
a = sc.parallelize([1,2,3,4,5,6,7,8,9,10], 2)
a._jrdd.splits().size()
a.count()
b = a.partitionBy(5)
http://spark.incubator.apache.org/docs/latest/spark-standalone.html#monitoring-and-logging
As the above shows:
Monitoring and Logging
Spark’s standalone mode offers a web-based user interface to monitor the
cluster. The master and each worker has its own web UI that shows cluster
and job
Are you trying to access the UI from another machine? If so, first confirm
that you don't have a network issue by opening the UI from the master node
itself.
For example:
yum -y install lynx
lynx ip_address:8080
If this succeeds, then you likely have something blocking you from
accessing the
Do you get the same problem if you build with maven?
On Tue, Apr 1, 2014 at 12:23 PM, Vipul Pandey vipan...@gmail.com wrote:
SPARK_HADOOP_VERSION=2.0.0-cdh4.2.1 sbt/sbt assembly
That's all I do.
On Apr 1, 2014, at 11:41 AM, Patrick Wendell pwend...@gmail.com wrote:
Vidal - could you show
Hm, yeah, the docs are not clear on this one. The function you're looking
for to change the number of partitions on any ol' RDD is repartition(),
which is available in master but for some reason doesn't seem to show up in
the latest docs. Sorry about that, I also didn't realize partitionBy() had
Alright!
Thanks for that link. I did little research based on it and it looks like
Snappy or LZO + some container would be better alternatives to gzip.
I confirmed that gzip was cramping my style by trying sc.textFile() on an
uncompressed version of the text file. With the uncompressed file,
Hmm, doing help(rdd) in PySpark doesn't show a method called repartition().
Trying rdd.repartition() or rdd.repartition(10) also fail. I'm on 0.9.0.
The approach I'm going with to partition my MappedRDD is to key it by a
random int, and then partition it.
So something like:
rdd =
Dell - Internal Use - Confidential
I got an exception can't zip RDDs with unusual numbers of Partitions when I
apply any action (reduce, collect) of dataset created by zipping two dataset of
10 million entries each. The problem occurs independently of the number of
partitions or when I let
You can get detailed information through Spark listener interface regarding
each stage. Multiple jobs may be compressed into a single stage so jobwise
information would be same as Spark.
Regards
Mayur
Mayur Rustagi
Ph: +1 (760) 203 3257
http://www.sigmoidanalytics.com
@mayur_rustagi
mllib has been part of Spark distribution (under mllib directory), also check
http://spark.apache.org/docs/latest/mllib-guide.html
and for JIRA, because of the recent migration to apache JIRA, I think all
mllib-related issues should be under the Spark umbrella,
Hi Nan,
I was actually referring to MLI/MLBase (http://www.mlbase.org); is this
being actively developed?
I'm familiar with mllib and have been looking at its documentation.
Thanks!
On Tue, Apr 1, 2014 at 10:44 PM, Nan Zhu [via Apache Spark User List]
ml-node+s1001560n3611...@n3.nabble.com
Ah, I see, I’m sorry, I didn’t read your email carefully
then I have no idea about the progress on MLBase
Best,
--
Nan Zhu
On Tuesday, April 1, 2014 at 11:05 PM, Krakna H wrote:
Hi Nan,
I was actually referring to MLI/MLBase (http://www.mlbase.org); is this being
actively
Hi there,
MLlib is the first component of MLbase - MLI and the higher levels of the
stack are still being developed. Look for updates in terms of our progress
on the hyperparameter tuning/model selection problem in the next month or
so!
- Evan
On Tue, Apr 1, 2014 at 8:05 PM, Krakna H
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