Hi all,
Apache Spark 2.1.0 is the second release of Spark 2.x line. This release
makes significant strides in the production readiness of Structured
Streaming, with added support for event time watermarks
2016-12-28 20:17 GMT+01:00 Chawla,Sumit :
> Would this work for you?
>
> def processRDD(rdd):
> analyzer = ShortTextAnalyzer(root_dir)
> rdd.foreach(lambda record: analyzer.analyze_short_text_
> event(record[1]))
>
> ssc.union(*streams).filter(lambda x: x[1] !=
Hello,
We spent sometime preparing artifacts and changes to the website (including
the release notes). I just sent out the the announcement. 2.1.0 is
officially released.
Thanks,
Yin
On Wed, Dec 28, 2016 at 12:42 PM, Justin Miller <
justin.mil...@protectwise.com> wrote:
> Interesting, because
Hi Marco,
Thanks for your response.
Yes I tested it before & am able to load from linux filesystem and it also
sometimes have similar issue.
However in both cases (either from hadoop or linux file system), this error
comes in some specific scenario as per my observations:
1. When two parallel
Hi all,
Thanks a lot for your contributions to bring us new technologies.
I don't want to waste your time, so before I write to you, I googled, checked
stackoverflow and mailing list archive with keywords "streaming" and "jdbc".
But I was not able to get any solution to my use case. I hope I
Have you found any solution to this? I am having a similar issue where my
db2jcc.jar license file is not being found. I was hoping the addjar()
method would work, but it does not seem to help.
I cannot even get the addjar syntax correct it seems...
Can I just call it inline?:
Hi all,
Can somebody solve the below problem using spark?
There are two dataset of numbers
Set1= {4,6,11,14} and Set2= {5,11,12,3}
I have to subtract each element of Set 1 by elements of Set2. But if the
element in Set2 is bigger, then the residue left after subtraction is used
for the
Hi
Pls try to read a CSV from filesystem instead of hadoop. If you can read
it successfully then your hadoop file is the issue and you can start
debugging from there.
Hth
On 29 Dec 2016 6:26 am, "Palash Gupta"
wrote:
> Hi Apache Spark User team,
>
>
>
>
Dear Spark users,
I am trying to setup SparkR on RStudio to perform some basic data
manipulations and ML modeling. However, I am a strange error while
creating SparkR session or DataFrame that says:
java.lang.IllegalArgumentException
Error while instantiating
Alternatively, using the broadcast functionality can also help with this.
On Thu, Dec 29, 2016 at 3:05 AM Eike von Seggern
wrote:
> 2016-12-28 20:17 GMT+01:00 Chawla,Sumit :
>
> Would this work for you?
>
> def processRDD(rdd):
> analyzer =
Hi Yan,
I've been surprised the first time when I noticed rxin stepped back and a
new release manager stepped in. Congrats on your first ANNOUNCE!
I can only expect even more great stuff coming in to Spark from the dev
team after Reynold spared some time
Can't wait to read the changes...
Hello
no sorry i dont have any further insight into that i have seen similar
errors but for completely different issues, and in most of hte cases it had
to do with my data or my processing rather than Spark itself.
What does your program do? you say it runs for 2-3 hours, what is the
logic?
If you are using spark 2.0 (as listed in the stackoverflow post) why are
you using the external CSV module from Databricks? Spark 2.0 includes the
functionality from this external module natively, and its possible you are
mixing an older library with a newer spark which could explain a crash.
Hello Jacek,
Actually, Reynold is still the release manager and I am just sending this
message for him :) Sorry. I should have made it clear in my original email.
Thanks,
Yin
On Thu, Dec 29, 2016 at 10:58 AM, Jacek Laskowski wrote:
> Hi Yan,
>
> I've been surprised the first
Any reason you are setting HADOOP_HOME?
>From the error it seems you are running into issue with Hive config likely
>with trying to load hive-site.xml. Could you try not setting HADOOP_HOME
From: Md. Rezaul Karim
Sent:
Hi,
I have a routine in Spark that iterates through Hbase rows and tries to
read columns.
My question is how can I read the correct ordering of columns?
example
val hBaseRDD = sc.newAPIHadoopRDD(conf, classOf[TableInputFormat],
classOf[org.apache.hadoop.hbase.io.ImmutableBytesWritable],
I think the best advice is: don't do that. If you're trying to solve a
linear system, solve the linear system without explicitly constructing a
matrix inverse. Is that what you mean?
On Thu, Dec 29, 2016 at 2:22 AM Yanwei Wayne Zhang <
actuary_zh...@hotmail.com> wrote:
> Hi all,
>
>
> I have a
Hi all,
I'm writing an ETL process with Spark 1.5, and I was wondering the best way to
do something.
A lot of the fields I am processing require an algorithm similar to this:
Join input dataframe to a lookup table.
if (that lookup fails (the joined fields are null)) {
Lookup into some
I used a word2vec algorithm of spark to compute documents vector of a text.
I then used the findSynonyms function of the model object to get synonyms
of few words.
I see something like this:
I do not understand why the cosine similarity is being calculated as more
than 1. Cosine similarity
Sean,
Thanks for answer. I am using Spark 1.6 so are you saying the output I am
getting is cos(A,B)=dot(A,B)/norm(A) ?
My point with respect to normalization was that if you normalise or don't
normalize both vectors A,B, the output would be same. Since if I normalize
A and B, then
Cos(A,B)=
Thanks for the advice. I figured out a way to solve this problem by avoiding
the matrix representation.
Wayne
From: Sean Owen
Sent: Thursday, December 29, 2016 1:52 PM
To: Yanwei Wayne Zhang; user
Subject: Re: Invert large matrix
I think
Yes you're just dividing by the norm of the vector you passed in. You can
look at the change on that JIRA and probably see how this was added into
the method itself.
On Thu, Dec 29, 2016 at 10:34 PM Manish Tripathi
wrote:
> ok got that. I understand that the ordering won't
It should be the cosine similarity, yes. I think this is what was fixed in
https://issues.apache.org/jira/browse/SPARK-7617 ; previously it was really
just outputting the 'unnormalized' similarity (dot / norm(a) only) but the
docs said cosine similarity. Now it's cosine similarity in Spark 2. The
Yes, the vectors are not otherwise normalized.
You are basically getting the cosine similarity, but times the norm of the
word vector you supplied, because it's not divided through. You could just
divide the results yourself.
I don't think it will be back-ported because the the behavior was
ok got that. I understand that the ordering won't change. I just wanted to
make sure I am getting the right thing or I understand what I am getting
since it didn't make sense going by the cosine calculation.
One last confirmation and I appreciate all the time you are spending to
reply:
In the
We don't support this yet, but I've opened this JIRA as it sounds generally
useful: https://issues.apache.org/jira/browse/SPARK-19031
In the mean time you could try implementing your own Source, but that is
pretty low level and is not yet a stable API.
On Thu, Dec 29, 2016 at 4:05 AM, "Yuanzhe
Say I have following data in file:{"id":1234,"ln":"Doe","fn":"John","age":25}
{"id":1235,"ln":"Doe","fn":"Jane","age":22}
java code snippet: final SparkConf sparkConf = new
SparkConf().setMaster("local[2]").setAppName("json_test");
JavaSparkContext ctx = new
Richard,
Below documentation will show you how to create a sparkSession and how to
programmatically load data:
Spark SQL and DataFrames - Spark 2.1.0 Documentation
|
| |
Spark SQL and DataFrames - Spark 2.1.0 Documentation
| |
|
On Thursday, December 29, 2016 5:16 PM,
thanks, I have seen this, but this doesn't cover my question.
What I need is read json and include raw json as part of my dataframe.
On Friday, December 30, 2016 10:23 AM, Annabel Melongo
wrote:
Richard,
Below documentation will show you how to create
Dear all,
Is there any way to change the host location for a certain partition of RDD?
"protected def getPreferredLocations(split: Partition)" can be used to
initialize the location, but how to change it after the initialization?
Thanks,
Fei
Richard,
In the provided documentation, under the paragraph "Schema Merging", you can
actually perform what you want this way:
1. Create a schema that read the raw json, line by line
2. Create another schema that read the json file and structure it in ("id",
"ln", "fn")
3. Merge the two
Maybe you can create your own subclass of RDD and override the
getPreferredLocations() to implement the logic of dynamic changing of the
locations.
> On Dec 30, 2016, at 12:06, Fei Hu wrote:
>
> Dear all,
>
> Is there any way to change the host location for a certain
I am running spark streaming with Yarn -
*spark-submit --master yarn --deploy-mode cluster --num-executors 2
> --executor-memory 8g --driver-memory 2g --executor-cores 8 ..*
>
I am consuming Kafka through DireactStream approach (No receiver). I have 2
topics (each with 3 partitions).
I
why not sync binlog of mysql(hopefully the data is immutable and the table
is append-only), send the log through kafka and then consume it by spark
streaming?
On Fri, Dec 30, 2016 at 9:01 AM, Michael Armbrust
wrote:
> We don't support this yet, but I've opened this JIRA
"If data ingestion speed is faster than data production speed, then
eventually the entire database will be harvested and those workers will
start to "tail" the database for new data streams and the processing
becomes real time."
This part is really database dependent. So it will be hard to
How about this -
select a.*, nvl(b.col,nvl(c.col,'some default'))
from driving_table a
left outer join lookup1 b on a.id=b.id
left outer join lookup2 c on a.id=c,id
?
On Fri, Dec 30, 2016 at 9:55 AM, Sesterhenn, Mike
wrote:
> Hi all,
>
>
> I'm writing an ETL process with
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