Hi all,
I'm working on an ETL task with Spark. As part of this work, I'd like to
mark records with some info such as:
1. Whether the record is good or bad (e.g, Either)
2. Originating file and lines
Part of my motivation is to prevent errors with individual records from
stopping the entire
at 12:36 PM, Reynold Xin r...@databricks.com wrote:
How about just using two fields, one boolean field to mark good/bad, and
another to get the source file?
On Wed, Jul 15, 2015 at 10:31 AM, RJ Nowling rnowl...@gmail.com wrote:
Hi all,
I'm working on an ETL task with Spark. As part
at 12:21 PM, RJ Nowling rnowl...@gmail.com wrote:
That's an interesting idea! I hadn't considered that. However, looking
at the Partitioner interface, I would need to know from looking at a single
key which doesn't fit my case, unfortunately. For my case, I need to
compare successive pairs
prematurely.)
On Tue, Jun 30, 2015 at 2:07 PM, Abhishek R. Singh
abhis...@tetrationanalytics.com wrote:
could you use a custom partitioner to preserve boundaries such that all
related tuples end up on the same partition?
On Jun 30, 2015, at 12:00 PM, RJ Nowling rnowl...@gmail.com wrote
by others?
On Tue, Jun 30, 2015 at 1:03 PM, Reynold Xin r...@databricks.com wrote:
Try mapPartitions, which gives you an iterator, and you can produce an
iterator back.
On Tue, Jun 30, 2015 at 11:01 AM, RJ Nowling rnowl...@gmail.com wrote:
Hi all,
I have a problem where I have a RDD of elements
How do these proposals affect PySpark? I think compatibility with PySpark
through Py4J should be considered.
On Mon, Mar 9, 2015 at 8:39 PM, Patrick Wendell pwend...@gmail.com wrote:
Does this matter for our own internal types in Spark? I don't think
any of these types are designed to be used
-6382f8428b13fa6082fa688178f3dbcc
On Wed, Jan 14, 2015 at 2:59 PM, RJ Nowling rnowl...@gmail.com wrote:
Thanks, Sean.
Yes, Spark is incorrectly copying the spark assembly jar to
com/google/guava in the maven repository. This is for the 1.2.0 release,
just to clarify.
I reverted the patches that shade Guava
,
instead of pom.
On Wed, Jan 14, 2015 at 1:08 PM, RJ Nowling rnowl...@gmail.com wrote:
Hi Sean,
I confirmed that if I take the Spark 1.2.0 release (a428c446), undo the
guava PR [1], and use -Dmaven.install.skip=false with the workflow above,
the problem is fixed.
RJ
[1
is in com/google/guava?
You can un-skip the install plugin with -Dmaven.install.skip=false
On Wed, Jan 14, 2015 at 7:26 PM, RJ Nowling rnowl...@gmail.com wrote:
Hi all,
I'm trying to upgrade some Spark RPMs from 1.1.0 to 1.2.0. As part of
the
RPM process, we build Spark with Maven
Congratulations, Chris!
I created a JIRA for dimensional RDDs that might be relevant:
https://issues.apache.org/jira/browse/SPARK-4727
Jeremy Freeman pointed me to his lab's work on for neuroscience that have
some related functionality :
http://thefreemanlab.com/thunder/
On Wed, Jan 14, 2015 at
Hi Andrew,
Patrick Wendell and Andrew Or have committed previous patches related to
Mesos. Maybe they would be good committers to look at it?
RJ
On Mon, Jan 5, 2015 at 6:40 PM, Andrew Ash and...@andrewash.com wrote:
Hi Spark devs,
I'm interested in having a committer look at a PR [1] for
that MLlib supports some operations for time series in 1.2.0-rc1, but
I think that specialized RDDs could optimize the partitioning and
algorithms better than a regular RDD. Or, for example, spatial data could
be partitioned into a grid.
Any feedback would be great!
Thanks,
RJ Nowling
--
em rnowl
Matei,
I saw that you're listed as a maintainer for ~6 different subcomponents,
and on over half of those, you're only the 2nd person. My concern is that
you would be stretched thin and maybe wouldn't be able to work as a back
up on all of those subcomponents. Are you planning on adding more
Two thoughts here:
1. The real flaw with the sort benchmark was that Hadoop wasn't run on the
same hardware. Given the advances in networking (availabIlity of
10GB Ethernet) and disks (SSDs) since the Hadoop benchmarks it was compared
to, it's an apples to oranges comparison. Without that, it
. I will ask other developers to help
review the PR. Thanks for working with Yu and helping the code review!
Best,
Xiangrui
On Thu, Oct 23, 2014 at 2:58 AM, RJ Nowling rnowl...@gmail.com wrote:
Hi all,
A few months ago, I collected feedback on what the community was looking
Hi all,
A few months ago, I collected feedback on what the community was looking
for in clustering methods. A number of the community members requested a
divisive hierarchical clustering method.
Yu Ishikawa has stepped up to implement such a method. I've been working
with him to communicate
On Tue, Oct 7, 2014 at 6:29 AM, RJ Nowling rnowl...@gmail.com wrote:
I was able to reproduce it on a small 4 node cluster (1 mesos master and
3 mesos slaves) with relatively low-end specs. As I said, I just ran the
log query examples with the fine-grained mesos mode.
Spark 1.1.0 and mesos
at 9:20 AM, Timothy Chen tnac...@gmail.com wrote:
Ok I created SPARK-3817 to track this, will try to repro it as well.
Tim
On Mon, Oct 6, 2014 at 6:08 AM, RJ Nowling rnowl...@gmail.com wrote:
I've recently run into this issue as well. I get it from running Spark
examples such as log query
I've recently run into this issue as well. I get it from running Spark
examples such as log query. Maybe that'll help reproduce the issue.
On Monday, October 6, 2014, Gurvinder Singh gurvinder.si...@uninett.no
wrote:
The issue does not occur if the task at hand has small number of map
tasks.
I think it would be interesting to have a variety of matrix operations
(multiplication, addition / subtraction, powers, scalar multiply, etc.)
available in Spark.
Diagonalization may be more difficult but iterative approximation
approaches may be quite amenable.
On Fri, Sep 5, 2014 at 5:26 AM,
to
lapack, so it should be fine. In general concurrent modification isn't
thread safe of course, but things that ought to be thread safe really
should be.
On Wed, Sep 3, 2014 at 10:41 AM, RJ Nowling rnowl...@gmail.com wrote:
No, it's not in all cases. Since Breeze uses lapack under the hood
work arrays for each call to
lapack, so it should be fine. In general concurrent modification isn't
thread safe of course, but things that ought to be thread safe really
should be.
On Wed, Sep 3, 2014 at 10:41 AM, RJ Nowling rnowl...@gmail.com wrote:
No, it's not in all cases. Since Breeze
be safe.
On Wed, Sep 3, 2014 at 11:58 AM, RJ Nowling rnowl...@gmail.com wrote:
David,
Can you confirm that += is not thread safe but + is? I'm assuming +
allocates a new object for the write, while += doesn't.
Thanks!
RJ
On Wed, Sep 3, 2014 at 2:50 PM, David Hall d...@cs.berkeley.edu
Hi Yu,
A standardized API has not been implemented yet. I think it would be
better to implement the other clustering algorithms then extract a common
API. Others may feel differently. :)
Just a note, there was a pre-existing JIRA for hierarchical KMeans
SPARK-2429
On Aug 12, 2014, at 2:20 PM, RJ Nowling rnowl...@gmail.com wrote:
Hi all,
I wanted to follow up.
I have a prototype for an optimized version of hierarchical k-means. I
wanted to get some feedback on my apporach.
Jeremy's implementation splits the largest cluster in each round. Is it
better
Hi all,
PR #720 https://github.com/apache/spark/pull/720 made multiple changes
to GraphGenerator.logNormalGraph including:
- Replacing the call to functions for generating random vertices and
edges with in-line implementations with different equations. Based on
reading the Pregel
Hi Alexander,
Can you post a link to the code?
RJ
On Tue, Aug 26, 2014 at 6:53 AM, Ulanov, Alexander alexander.ula...@hp.com
wrote:
Hi,
I've implemented back propagation algorithm using Gradient class and a
simple update using Updater class. Then I run the algorithm with mllib's
/mllib/classification/NeuralNetwork.scala
Unit tests are in the same branch.
Alexander
From: RJ Nowling [mailto:rnowl...@gmail.com]
Sent: Tuesday, August 26, 2014 6:59 PM
To: Ulanov, Alexander
Cc: dev@spark.apache.org
Subject: Re: Gradient descent and runMiniBatchSGD
Hi
Also, another idea: may algorithms that use sampling tend to do so multiple
times. It may be beneficial to allow a transformation to a representation
that is more efficient for multiple rounds of sampling.
On Tue, Aug 26, 2014 at 4:36 PM, RJ Nowling rnowl...@gmail.com wrote:
Xiangrui,
I
?
Are there are any open-source examples that are being widely used in
production?
Thanks!
On Fri, Jul 18, 2014 at 8:05 AM, RJ Nowling rnowl...@gmail.com wrote:
Nice to meet you, Jeremy!
This is great! Hierarchical clustering was next on my list --
currently trying to get my PR for MiniBatch KMeans
.
-Sandy
On Mon, Jul 21, 2014 at 8:36 AM, RJ Nowling rnowl...@gmail.com wrote:
Hi all,
The examples listed here
https://spark.apache.org/examples.html
refer to the spark context as spark but when running Spark Shell
uses sc for the SparkContext.
Am I missing something?
Thanks!
RJ
Nice to meet you, Jeremy!
This is great! Hierarchical clustering was next on my list --
currently trying to get my PR for MiniBatch KMeans accepted.
If it's cool with you, I'll try converting your code to fit in with
the existing MLLib code as you suggest. I also need to review the
Decision
at 2:15 PM, RJ Nowling rnowl...@gmail.com wrote:
Thanks everyone for the input.
So it seems what people want is:
* Implement MiniBatch KMeans and Hierarchical KMeans (Divide and
conquer approach, look at DecisionTree implementation as a reference)
* Restructure 3 Kmeans clustering algorithm
Hi Meethu,
There is no code for a Gaussian Mixture Model clustering algorithm in the
repository, but I don't know if anyone is working on it.
RJ
On Wednesday, July 9, 2014, MEETHU MATHEW meethu2...@yahoo.co.in wrote:
Hi,
I am interested in contributing a clustering algorithm towards MLlib
as you have
to already find the nearest neighbor to an item to begin the process.
On Tue, Jul 8, 2014 at 1:59 PM, RJ Nowling rnowl...@gmail.com wrote:
The scikit-learn implementation may be of interest:
http://scikit-learn.org/stable/modules/generated/sklearn.cluster.Ward.html
Hi all,
MLlib currently has one clustering algorithm implementation, KMeans.
It would benefit from having implementations of other clustering
algorithms such as MiniBatch KMeans, Fuzzy C-Means, Hierarchical
Clustering, and Affinity Propagation.
I recently submitted a PR [1] for a MiniBatch
Thanks, Hector! Your feedback is useful.
On Tuesday, July 8, 2014, Hector Yee hector@gmail.com wrote:
I would say for bigdata applications the most useful would be hierarchical
k-means with back tracking and the ability to support k nearest centroids.
On Tue, Jul 8, 2014 at 10:54 AM, RJ
at 10:54 AM, RJ Nowling rnowl...@gmail.com
wrote:
Hi all,
MLlib currently has one clustering algorithm implementation, KMeans.
It would benefit from having implementations of other clustering
algorithms such as MiniBatch KMeans, Fuzzy C-Means, Hierarchical
Clustering
Hey Alex,
I'm also a new contributor. I created a pull request for the KMeans
MiniBatch implementation here:
https://github.com/apache/spark/pull/1248
I also created a JIRA here:
https://issues.apache.org/jira/browse/SPARK-2308
As part of my work, I started to refactor the common code to
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