a pull request for this? We'd be happy to
accept the change.
- Patrick
Currently, an executor is always run in it's own JVM, so it should be
possible to just use some static initialization to e.g. launch a
sub-process and set up a bridge with which to communicate.
This is would be a fairly advanced use case, however.
- Patrick
On Thu, May 29, 2014 at 8:
.
- Patrick
On Thu, May 29, 2014 at 2:13 AM, innowireless TaeYun Kim
wrote:
> Hi,
>
>
>
> How can I dispose an Accumulator?
>
> It has no method like 'unpersist()' which Broadcast provides.
>
>
>
> Thanks.
>
>
Can you look at the logs from the executor or in the UI? They should
give an exception with the reason for the task failure. Also in the
future, for this type of e-mail please only e-mail the "user@" list
and not both lists.
- Patrick
On Sat, May 31, 2014 at 3:22 AM, prabeesh k w
I've removed my docs from my site to avoid confusion... somehow that
link propogated all over the place!
On Sat, May 31, 2014 at 1:58 AM, Xiangrui Meng wrote:
> The documentation you looked at is not official, though it is from
> @pwendell's website. It was for the Spark SQL release. Please find
lob/master/core/src/main/scala/org/apache/spark/scheduler/SparkListener.scala
- Patrick
On Fri, May 30, 2014 at 7:09 AM, Daniel Siegmann
wrote:
> The Spark 1.0.0 release notes state "Internal instrumentation has been added
> to allow applications to monitor and instrument Spark jobs."
ard way to make them
compatible with 2.6 we should do that.
For r3.large, we can add that to the script. It's a newer type. Any
interest in contributing this?
- Patrick
On May 30, 2014 5:08 AM, "Jeremy Lee"
wrote:
>
> Hi there! I'm relatively new to the list, so s
;>
>>> --
>>> Christopher T. Nguyen
>>> Co-founder & CEO, Adatao <http://adatao.com>
>>> linkedin.com/in/ctnguyen <http://linkedin.com/in/ctnguyen>
>>>
>>>
>>>
>>>
>>> On Fri, May 30, 2014 at 3:12 AM, Patrick
he.org/releases/spark-release-1-0-0.html
Note that since release artifacts were posted recently, certain
mirrors may not have working downloads for a few hours.
- Patrick
Hi Tathagata,
Thanks for your response, just the advice I was looking for. I will try
this out with Spark 1.0 when it comes out.
Best regards,
Patrick
On 5 May 2014 22:42, Tathagata Das wrote:
> A few high-level suggestions.
>
> 1. I recommend using the new Receiver API in almost
ew SparkContext(conf)
- Patrick
On Wed, May 14, 2014 at 9:09 AM, Koert Kuipers wrote:
> i have some settings that i think are relevant for my application. they are
> spark.akka settings so i assume they are relevant for both executors and my
> driver program.
>
&
Hello,
I'm trying to write a python function that does something like:
def foo(line):
try:
return stuff(line)
except Exception:
raise MoreInformativeException(line)
and then use it in a map like so:
rdd.map(foo)
and have my MoreInformativeException make it back if/when
kely to be almost identical to the final release.
- Patrick
On Tue, May 13, 2014 at 9:40 AM, bhusted wrote:
> Can anyone comment on the anticipated date or worse case timeframe for when
> Spark 1.0.0 will be released?
>
>
>
> --
> View this message in context:
> http:/
Hey Adrian,
If you are including log4j-over-slf4j.jar in your application, you'll
still need to manually exclude slf4j-log4j12.jar from Spark. However,
it should work once you do that. Before 0.9.1 you couldn't make it
work, even if you added an exclude.
- Patrick
On Thu, May 8, 2014
c.registerInputStream(tascQueue)
Is this the best way to go?
Best regards,
Patrick
PM, Patrick Wendell wrote:
> Hey Jeremy,
>
> This is actually a big problem - thanks for reporting it, I'm going to
> revert this change until we can make sure it is backwards compatible.
>
> - Patrick
>
> On Sun, May 4, 2014 at 2:00 PM, Jeremy Freeman
> wrote
Hey Jeremy,
This is actually a big problem - thanks for reporting it, I'm going to
revert this change until we can make sure it is backwards compatible.
- Patrick
On Sun, May 4, 2014 at 2:00 PM, Jeremy Freeman wrote:
> Hi all,
>
> A heads up in case others hit this and are con
Broadcast variables need to fit entirely in memory - so that's a
pretty good litmus test for whether or not to broadcast a smaller
dataset or turn it into an RDD.
On Fri, May 2, 2014 at 7:50 AM, Prashant Sharma wrote:
> I had like to be corrected on this but I am just trying to say small enough
>
your spark-ec2.py script to checkout spark-ec2 from forked version.
- Patrick
On Thu, May 1, 2014 at 2:14 PM, Ian Ferreira wrote:
> Is this possible, it is very annoying to have such a great script, but still
> have to manually update stuff afterwards.
e datasets with many
partitions, since often there are bottlenecks at the granularity of a
file.
Is there a reason you need this to be exactly one file?
- Patrick
On Sat, May 3, 2014 at 4:14 PM, Chris Fregly wrote:
> not sure if this directly addresses your issue, peter, but it's worth
>
This is a consequence of the way the Hadoop files API works. However,
you can (fairly easily) add code to just rename the file because it
will always produce the same filename.
(heavy use of pseudo code)
dir = "/some/dir"
rdd.coalesce(1).saveAsTextFile(dir)
f = new File(dir + "part-0")
f.move
could be like this, it
wouldn't violate the contract of union
AFIAK the only guarentee is the resulting RDD will contain all elements.
- Patrick
On Tue, Apr 29, 2014 at 11:26 PM, Mingyu Kim wrote:
> Yes, that’s what I meant. Sure, the numbers might not be actually sorted,
> but t
ions returned by RDD.getPartitions()
> and the row orders within the partitions determine the row order, I’m not
> sure why union doesn’t respect the order because union operation simply
> concatenates the two lists of partitions from the two RDDs.
>
> Mingyu
>
>
>
>
> On 4/
You are right, once you sort() the RDD, then yes it has a well defined ordering.
But that ordering is lost as soon as you transform the RDD, including
if you union it with another RDD.
On Tue, Apr 29, 2014 at 10:22 PM, Mingyu Kim wrote:
> Hi Patrick,
>
> I¹m a little confused about you
This class was made to be "java friendly" so that we wouldn't have to
use two versions. The class itself is simple. But I agree adding java
setters would be nice.
On Tue, Apr 29, 2014 at 8:32 PM, Soren Macbeth wrote:
> There is a JavaSparkContext, but no JavaSparkConf object. I know SparkConf
> i
ut I'm no
expert.
On Tue, Apr 29, 2014 at 10:14 PM, Liu, Raymond wrote:
> For all the tasks, say 32 task on total
>
> Best Regards,
> Raymond Liu
>
>
> -Original Message-
> From: Patrick Wendell [mailto:pwend...@gmail.com]
>
> Is this the serialization throug
The signature of this function was changed in spark 1.0... is there
any chance that somehow you are actually running against a newer
version of Spark?
On Tue, Apr 29, 2014 at 8:58 PM, wxhsdp wrote:
> i met with the same question when update to spark 0.9.1
> (svn checkout https://github.com/apache
Is this the serialization throughput per task or the serialization
throughput for all the tasks?
On Tue, Apr 29, 2014 at 9:34 PM, Liu, Raymond wrote:
> Hi
>
> I am running a WordCount program which count words from HDFS, and I
> noticed that the serializer part of code takes a lot of CPU
Could you explain more what your job is doing and what data types you are
using? These numbers alone don't necessarily indicate something is wrong.
The relationship between the in-memory and on-disk shuffle amount is
definitely a bit strange, the data gets compressed when written to disk,
but unles
erver
You can also accomplish this by just having a separate service that submits
multiple jobs to a cluster where those jobs e.g. use different jars.
- Patrick
On Mon, Apr 28, 2014 at 4:44 PM, Andrew Ash wrote:
> For the second question, you can submit multiple jobs through the same
> S
This was fixed in master. I think this happens if you don't set
HADOOP_CONF_DIR to the location where your hadoop configs are (e.g.
yarn-site.xml).
On Sun, Apr 27, 2014 at 7:40 PM, martin.ou wrote:
> 1.my hadoop 2.3.0
> 2.SPARK_HADOOP_VERSION=2.3.0 SPARK_YARN=true sbt/sbt assembly
> 3.SPARK_YARN
This can only be a local filesystem though, it can't refer to an HDFS
location. This is because it gets passed directly to the JVM.
On Mon, Apr 28, 2014 at 9:55 PM, Patrick Wendell wrote:
> Yes, you can set SPARK_LIBRARY_PATH in 0.9.X and in 1.0 you can set
> spark.executor.extra
Yes, you can set SPARK_LIBRARY_PATH in 0.9.X and in 1.0 you can set
spark.executor.extraLibraryPath.
On Mon, Apr 28, 2014 at 9:16 AM, Shubham Chopra wrote:
> I am trying to use Spark/MLLib on Yarn and do not have libgfortran
> installed on my cluster. Is there any way I can set LD_LIBRARY_PATH s
What about if you run ./bin/spark-shell
--driver-class-path=/path/to/your/jar.jar
I think either this or the --jars flag should work, but it's possible there
is a bug with the --jars flag when calling the Repl.
On Mon, Apr 28, 2014 at 4:30 PM, Roger Hoover wrote:
> A couple of issues:
> 1) the
sees the error first before the reader knows what is
going on.
Anyways maybe if you have a simpler solution you could sketch it out in the
JIRA and we could talk over there. The current proposal in the JIRA is
somewhat complicated...
- Patrick
On Mon, Apr 28, 2014 at 1:01 PM, Jim Blomo
what you do inside of the function. But I'd be careful using this
approach...
- Patrick
On Sat, Apr 26, 2014 at 5:59 AM, Lisonbee, Todd wrote:
> For example,
>
> val originalRDD: RDD[SomeCaseClass] = ...
>
> // Option 1: objects are copied, setting prop1 in the process
> val tra
Try running sbt/sbt clean and re-compiling. Any luck?
On Thu, Apr 24, 2014 at 5:33 PM, martin.ou wrote:
>
>
> occure exception when compile spark 0.9.1 using sbt,env: hadoop 2.3
>
> 1. SPARK_HADOOP_VERSION=2.3.0 SPARK_YARN=true sbt/sbt assembly
>
>
>
> 2.found Exception:
>
> found : org.apache
For a HadoopRDD, first the spark scheduler calculates the number of tasks
based on input splits. Usually people use this with HDFS data so in that
case it's based on HDFS blocks. If the HDFS datanodes are co-located with
the Spark cluster then it will try to run the tasks on the data node that
cont
I put some notes in this doc:
https://cwiki.apache.org/confluence/display/SPARK/Useful+Developer+Tools
On Sun, Apr 20, 2014 at 8:58 PM, Arun Ramakrishnan <
sinchronized.a...@gmail.com> wrote:
> I would like to run some of the tests selectively. I am in branch-1.0
>
> Tried the following two comm
Unfortunately - I think a lot of this is due to generally increased latency
on ec2 itself. I've noticed that it's way more common than it used to be
for instances to come online past the "wait" timeout in the ec2 script.
On Fri, Apr 18, 2014 at 9:11 PM, FRANK AUSTIN NOTHAFT wrote:
> Aureliano,
To reiterate what Tom was saying - the code that runs inside of Spark on
YARN is exactly the same code that runs in any deployment mode. There
shouldn't be any performance difference once your application starts
(assuming you are comparing apples-to-apples in terms of hardware).
The differences ar
I've actually done it using PySpark and python libraries which call cuda code,
though I've never done it from scala directly. The only major challenge I've
hit is assigning tasks to gpus on multiple gpu machines.
Sent from my iPhone
> On Apr 11, 2014, at 8:38 AM, Jaonary Rabarisoa wrote:
>
>
Pierre - I'm not sure that would work. I just opened a Spark shell and did
this:
scala> classOf[SparkContext].getClass.getPackage.getImplementationVersion
res4: String = 1.7.0_25
It looks like this is the JVM version.
- Patrick
On Thu, Apr 10, 2014 at 2:08 PM, Pierre Borckmans <
pi
I think this was solved in a recent merge:
https://github.com/apache/spark/pull/204/files#diff-364713d7776956cb8b0a771e9b62f82dR779
Is that what you are looking for? If so, mind marking the JIRA as resolved?
On Wed, Apr 9, 2014 at 3:30 PM, Nicholas Chammas wrote:
> Hey Patrick,
>
This job might still be faster... in MapReduce there will be other
overheads in addition to the fact that doing sequential reads from HBase is
slow. But it's possible the bottleneck is the HBase scan performance.
- Patrick
On Wed, Apr 9, 2014 at 10:10 AM, Jerry Lam wrote:
> Hi Dave,
Okay so I think the issue here is just a conflict between your application
code and the Hadoop code.
Hadoop 2.0.0 depends on protobuf 2.4.0a:
https://svn.apache.org/repos/asf/hadoop/common/tags/release-2.0.0-alpha/hadoop-project/pom.xml
Your code is depending on protobuf 2.5.X
The protobuf libra
On Mon, Apr 7, 2014 at 7:37 PM, Brad Miller wrote:
> I am running the latest version of PySpark branch-0.9 and having some
> trouble with join.
>
> One RDD is about 100G (25GB compressed and serialized in memory) with
> 130K records, the other RDD is about 10G (2.5G compressed and
> serialized in
If you look in the Spark UI, do you see any garbage collection happening?
My best guess is that some of the executors are going into GC and they are
timing out. You can manually increase the timeout by setting the Spark conf:
spark.storage.blockManagerSlaveTimeoutMs
to a higher value. In your cas
in
the community has feedback from trying this.
- Patrick
On Fri, Apr 4, 2014 at 12:43 PM, Rahul Singhal wrote:
> Hi Christophe,
>
> Thanks for your reply and the spec file. I have solved my issue for now.
> I didn't want to rely building spark using the spec file (%buil
and on jobs that crunch hundreds of
terabytes (uncompressed) of data.
- Patrick
On Fri, Apr 4, 2014 at 12:05 PM, Parviz Deyhim wrote:
> Spark community,
>
>
> What's the size of the largest Spark cluster ever deployed? I've heard
> Yahoo is running Spark on several hun
Btw - after that initial thread I proposed a slightly more detailed set of
dates:
https://cwiki.apache.org/confluence/display/SPARK/Wiki+Homepage
- Patrick
On Thu, Apr 3, 2014 at 11:28 AM, Matei Zaharia wrote:
> Hey Bhaskar, this is still the plan, though QAing might take longer than
> 1
l piece of functionality and something we might, e.g.
want to change the API of over time.
- Patrick
On Wed, Apr 2, 2014 at 3:39 PM, Philip Ogren wrote:
> What I'd like is a way to capture the information provided on the stages
> page (i.e. cluster:4040/stages via IndexPage). Look
The driver stores the meta-data associated with the partition, but the
re-computation will occur on an executor. So if several partitions are
lost, e.g. due to a few machines failing, the re-computation can be striped
across the cluster making it fast.
On Wed, Apr 2, 2014 at 11:27 AM, David Thoma
For textFile I believe we overload it and let you set a codec directly:
https://github.com/apache/spark/blob/master/core/src/test/scala/org/apache/spark/FileSuite.scala#L59
For saveAsSequenceFile yep, I think Mark is right, you need an option.
On Wed, Apr 2, 2014 at 12:36 PM, Mark Hamstra wrote
(default-cli) on project spark-0.9.0-incubating: Error reading assemblies:
> No assembly descriptors found. -> [Help 1]
> upon runnning
> mvn -Dhadoop.version=2.0.0-cdh4.2.1 -DskipTests clean assembly:assembly
>
>
> On Apr 1, 2014, at 4:13 PM, Patrick Wendell wrote:
>
> D
Do you get the same problem if you build with maven?
On Tue, Apr 1, 2014 at 12:23 PM, Vipul Pandey 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 wrote:
>
> Vidal - could you show e
dependency but it still failed whenever I use the
> jar with ScalaBuf dependency.
> Spark version is 0.9.0
>
>
> ~Vipul
>
> On Mar 31, 2014, at 4:51 PM, Patrick Wendell wrote:
>
> Spark now shades its own protobuf dependency so protobuf 2.4.1 should't be
> getting pull
Ya this is a good way to do it.
On Sun, Mar 30, 2014 at 10:11 PM, Vipul Pandey wrote:
> Hi,
>
> I need to batch the values in my final RDD before writing out to hdfs. The
> idea is to batch multiple "rows" in a protobuf and write those batches out
> - mostly to save some space as a lot of metad
your
dependencies including the exact Spark version and other libraries.
- Patrick
On Sun, Mar 30, 2014 at 10:03 PM, Vipul Pandey wrote:
> I'm using ScalaBuff (which depends on protobuf2.5) and facing the same
> issue. any word on this one?
> On Mar 27, 2014, at 6:41 PM, Kanwaldeep
Also in NYC, definitely interested in a spark meetup!
Sent from my iPhone
> On Mar 31, 2014, at 3:07 PM, Jeremy Freeman wrote:
>
> Happy to help with an NYC meet up (just emailed Andy). I recently moved to
> VA, but am back in NYC quite often, and have been turning several
> computational peo
This will be a feature in Spark 1.0 but is not yet released. In 1.0 Spark
applications can persist their state so that the UI can be reloaded after
they have completed.
- Patrick
On Sun, Mar 30, 2014 at 10:30 AM, David Thomas wrote:
> Is there a way to see 'Application Detail UI&#
If you call repartition() on the original stream you can set the level of
parallelism after it's ingested from Kafka. I'm not sure how it maps kafka
topic partitions to tasks for the ingest thought.
On Thu, Mar 27, 2014 at 11:09 AM, Scott Clasen wrote:
> I have a simple streaming job that create
f fields to
the respective cassandra columns. I think all of this would be fairly easy
to implement on SchemaRDD and likely will make it into Spark 1.1
- Patrick
On Wed, Mar 26, 2014 at 10:59 PM, Rohit Rai wrote:
> Great work guys! Have been looking forward to this . . .
>
> In the blog it ment
I'm not sure exactly how your cluster is configured. But as far as I can
tell Cloudera's MR1 CDH5 dependencies are against Hadoop 2.3. I'd just find
the exact CDH version you have and link against the `mr1` version of their
published dependencies in that version.
So I think you wan't "2.3.0-mr1-cd
Starting with Spark 0.9 the protobuf dependency we use is shaded and
cannot interfere with other protobuf libaries including those in
Hadoop. Not sure what's going on in this case. Would someone who is
having this problem post exactly how they are building spark?
- Patrick
On Fri, Mar 21,
Ah we should just add this directly in pyspark - it's as simple as the
code Shivaram just wrote.
- Patrick
On Mon, Mar 24, 2014 at 1:25 PM, Shivaram Venkataraman
wrote:
> There is no direct way to get this in pyspark, but you can get it from the
> underlying java rdd. For ex
Ognen - just so I understand. The issue is that there weren't enough
inodes and this was causing a "No space left on device" error? Is that
correct? If so, that's good to know because it's definitely counter
intuitive.
On Sun, Mar 23, 2014 at 8:36 PM, Ognen Duzlevski
wrote:
> I would love to work
le if you do a highly selective filter on an
RDD. For instance, you filter out one day of data from a dataset of a
year.
- Patrick
On Sun, Mar 23, 2014 at 9:53 PM, Mark Hamstra wrote:
> It's much simpler: rdd.partitions.size
>
>
> On Sun, Mar 23, 2014 at 9:24 PM, Nicholas Chamm
ngle pass automatically... but that's not quite
released yet :)
- Patrick
On Sun, Mar 23, 2014 at 1:31 PM, Koert Kuipers wrote:
> i currently typically do something like this:
>
> scala> val rdd = sc.parallelize(1 to 10)
> scala> import com.twitter.algebird.Operators._
&g
Hey Roman,
Ya definitely checkout pull request 42 - one cool thing is this patch
now includes information about in-memory storage in the listener
interface, so you can see directly which blocks are cached/on-disk
etc.
- Patrick
On Mon, Mar 17, 2014 at 5:34 PM, Matei Zaharia wrote:
> Tak
This is not released yet but we're planning to cut a 0.9.1 release
very soon (e.g. most likely this week). In the mean time you'll have
checkout branch-0.9 of Spark and publish it locally then depend on the
snapshot version. Or just wait it out...
On Fri, Mar 14, 2014 at 2:01 PM, Adrian Mocanu
wr
Sean - was this merged into the 0.9 branch as well (it seems so based
on the message from rxin). If so it might make sense to try out the
head of branch-0.9 as well. Unless there are *also* other changes
relevant to this in master.
- Patrick
On Sun, Mar 16, 2014 at 12:24 PM, Sean Owen wrote
(Data Science Track)
Recent Developments in Spark MLlib and Beyond
bit.ly/1hgZW5D
(The Future of Apache Hadoop Track)
Cheers,
- Patrick
/core/index.html#org.apache.spark.rdd.JdbcRDD
https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/rdd/JdbcRDD.scala#L73
- Patrick
On Thu, Mar 13, 2014 at 2:05 PM, Nicholas Chammas
wrote:
> My fellow welders,
>
> (Can we make that a thing? Let's mak
ss the RDD itself and override getPreferredLocations.
Keep in mind this is tricky because the set of executors might change
during the lifetime of a Spark job.
- Patrick
On Thu, Mar 13, 2014 at 11:50 AM, David Thomas wrote:
> Is it possible to parition the RDD elements in a round robin fashion?
is:
for slave in `cat "$HOSTLIST"|sed "s/#.*$//;/^$/d"`; do
to this
for slave in `cat "$HOSTLIST"| head -n $NUM_SLAVES | sed
"s/#.*$//;/^$/d"`; do
Then you could just set NUM_SLAVES before you stop/start. Not sure if
this helps much but maybe it'
Dianna I'm forwarding this to the dev list since it might be useful
there as well.
On Wed, Mar 12, 2014 at 11:39 AM, Diana Carroll wrote:
> Hi all. I needed to build the Spark docs. The basic instructions to do
> this are in spark/docs/README.md but it took me quite a bit of playing
> around to
A block is an internal construct that isn't directly exposed to users.
Internally though, each partition of an RDD is mapped to one block.
- Patrick
On Mon, Mar 10, 2014 at 11:06 PM, David Thomas wrote:
> What is the concept of Block and BlockManager in Spark? How is a Block
> r
x27;t change so it won't help the ulimit problem.
This means you'll have to use fewer reducers (e.g. pass reduceByKey a
number of reducers) or use fewer cores on each machine.
- Patrick
On Mon, Mar 10, 2014 at 10:41 AM, Matthew Cheah
wrote:
> Hi everyone,
>
> My team (cc'
Hey Sen,
Suarav is right, and I think all of your print statements are inside of the
driver program rather than inside of a closure. How are you running your
program (i.e. what do you run that starts this job)? Where you run the
driver you should expect to see the output.
- Patrick
On Mon, Mar
hines. If you see stderr but not stdout
that's a bit of a puzzler since they both go through the same
mechanism.
- Patrick
On Sun, Mar 9, 2014 at 2:32 PM, Sen, Ranjan [USA] wrote:
> Hi
> I have some System.out.println in my Java code that is working ok in a local
> environment. But
Hey There,
This is interesting... thanks for sharing this. If you are storing in
MEMORY_ONLY then you are just directly storing Java objects in the
JVM. So they can't be compressed because they aren't really stored in
a known format it's just left up to the JVM.
To answer you other question, it's
The difference between your two jobs is that take() is optimized and
only runs on the machine where you are using the shell, whereas
sortByKey requires using many machines. It seems like maybe python
didn't get upgraded correctly on one of the slaves. I would look in
the /root/spark/work/ folder (f
ssic/1.1.1
- Patrick
On Wed, Mar 5, 2014 at 1:52 PM, Sergey Parhomenko wrote:
> Hi Patrick,
>
> Thanks for the patch. I tried building a patched version of
> spark-core_2.10-0.9.0-incubating.jar but the Maven build fails:
> [ERROR]
> /home/das/Work/thx/incubator-spark/core/src
Spark with this batch and seeing if
it works that would be great.
Thanks,
Patrick
On Wed, Mar 5, 2014 at 10:26 AM, Paul Brown wrote:
>
> Hi, Sergey --
>
> Here's my recipe, implemented via Maven; YMMV if you need to do it via sbt,
> etc., but it should
Yep, currently it only supports running at least 1 slave.
On Sat, Mar 1, 2014 at 4:47 PM, nicholas.chammas
wrote:
> I successfully launched a Spark EC2 "cluster" with 0 slaves using spark-ec2.
> When trying to login to the master node with spark-ec2 login, I get the
> following:
>
> Searching for
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