t seem to have ever worked?
> https://github.com/apache/spark-website/pull/207
>
> On Tue, Jun 18, 2019 at 4:07 AM Olivier Girardot
> wrote:
> >
> > Hi everyone,
> > FYI the spark source download link on spark.apache.org is dead :
> >
> https://archive.apac
Hi everyone,
FYI the spark source download link on spark.apache.org is dead :
https://archive.apache.org/dist/spark/spark-2.4.3/spark-2.4.3-bin-sources.tgz
Regards,
--
*Olivier Girardot*
I am also facing the same issue on my kubernetes
> cluster(v1.11.5) on AWS with spark version 2.3.3, any luck in figuring out
> the root cause?
>
> On Fri, May 3, 2019 at 5:37 AM Olivier Girardot <
> o.girar...@lateral-thoughts.com> wrote:
>
>> Hi,
>> I did not try on
r vendors ? Also on
> the kubelet nodes did you notice any pressure on the DNS side?
>
> Li
>
>
> On Mon, Apr 29, 2019, 5:43 AM Olivier Girardot <
> o.girar...@lateral-thoughts.com> wrote:
>
>> Hi everyone,
>> I have ~300 spark job on Kubernetes (GKE) using the
sed in the kubernetes packing)
- We can add a simple step to the init container trying to do the DNS
resolution and failing after 60s if it did not work
But these steps won't change the fact that the driver will stay stuck
thinking we're still in the case of the Initial allocation d
Hi everyone,
Is there any known way to go from a Spark SQL Logical Plan (optimised ?)
Back to a SQL query ?
Regards,
Olivier.
JIRA or is there a workaround ?
Regards,
--
*Olivier Girardot* | Associé
o.girar...@lateral-thoughts.com
ve the column pruning / filter pushdown issues with complex
> datatypes?
>
> Thanks!
>
> -
> To unsubscribe e-mail: dev-unsubscr...@spark.apache.org
>
>
--
*Olivier Girardot* | Associé
o.girar...@lateral-thoughts.com
+33 6 24 09 17 94
den has been a long time Spark contributor and evangelist. She has written a
few books on Spark, as well as frequent contributions to the Python API to
improve its usability and performance.
Please join me in welcoming the two!
Olivier Girardot| Associé
o.girar...@lateral-thoughts.com
+33 6 24 09 17 94
utations, but that's bound to be inefficient
* or to generate bytecode using the schema
to do the nested "getRow,getSeq…" and re-create the rows once transformation
is applied
I'd like to open an issue regarding that use case because it's not the first or
last time it comes up and I still don'
that are used are all the same across these
versions. That would be the thing that makes you need multiple versions of the
artifact under multiple classifiers.
On Wed, Sep 28, 2016 at 1:16 PM, Olivier Girardot <
o.girar...@lateral-thoughts.com> wrote:
ok, don't you think it could be pub
chance publications of Spark 2.0.0 with different classifier according to
different versions of Hadoop available ?
Thanks for your time !
Olivier Girardot
Olivier Girardot| Associé
o.girar...@lateral-thoughts.com
+33 6 24 09 17 94
to find a way to apply a transformation on complex nested
datatypes (arrays and struct) on a Dataframe updating the value itself.
Regards,
Olivier Girardot
=>
strToExpr(pairExpr._2)(df(pairExpr._1).expr) }.toSeq) }
regards --
Ing. Ivaldi Andres
Olivier Girardot | Associé
o.girar...@lateral-thoughts.com
+33 6 24 09 17 94
t; wrote:
Hi Olivier,
I don't know either, but am curious what you've tried already.
Jacek
On 3 Aug 2016 10:50 a.m., "Olivier Girardot" < o.girardot@lateral-thoughts. com
> wrote:
Hi everyone, I'm currently to use Spark 2.0.0 and making Dataframes work with
kryo. registrationRequi
Hi everyone, I'm currently to use Spark 2.0.0 and making Dataframes work with
kryo.registrationRequired=true Is it even possible at all considering the
codegen ?
Regards,
Olivier Girardot | Associé
o.girar...@lateral-thoughts.com
+33 6 24 09 17 94
List$SerializationProxy to field
org.apache.spark.rdd.RDD.org $apache$spark$rdd$RDD$$dependencies_ of type
scala.collection.Seq in instance
of org.apache.spark.rdd.MapPartitionsRDD
Olivier Girardot | Associé
o.girar...@lateral-thoughts.com
+33 6 24 09 17 94
sorry for the delay, yes still.
I'm still trying to figure out if it comes from bad data and trying to
isolate the bug itself...
2015-09-11 0:28 GMT+02:00 Reynold Xin <r...@databricks.com>:
> Does this still happen on 1.5.0 release?
>
>
> On Mon, Aug 31, 2015 at 9:31 AM, Oliv
n$8$$anon$1.next(Window.scala:252)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
2015-08-26 11:47 GMT+02:00 Olivier Girardot <ssab...@gmail.com>:
> Hi everyone,
> I know this "post title" doesn't seem very logical and I agree,
> we have a very com
...@spark.apache.org
--
*Olivier Girardot* | Associé
o.girar...@lateral-thoughts.com
+33 6 24 09 17 94
://burakisikli.wordpress.com*
--
*Olivier Girardot* | Associé
o.girar...@lateral-thoughts.com
+33 6 24 09 17 94
, Ted Malaska ted.mala...@cloudera.com
wrote:
100% I would love to do it. Who a good person to review the design
with. All I need is a quick chat about the design and approach and I'll
create the jira and push a patch.
Ted Malaska
On Tue, Jul 21, 2015 at 10:19 AM, Olivier Girardot
o.girar
, Olivier Girardot
o.girar...@lateral-thoughts.com wrote:
Hi,
Is there any plan to add the countByValue function to Spark SQL Dataframe
?
Even
https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/ml/feature/StringIndexer.scala#L78
is using the RDD part right now
would love to add it
to dataframes.
Let me know
Ted Malaska
On Tue, Jul 21, 2015 at 7:24 AM, Olivier Girardot
o.girar...@lateral-thoughts.com wrote:
Yop,
actually the generic part does not work, the countByValue on one column
gives you the count for each value seen in the column.
I would
categorical value on multiple columns would be very useful.
Regards,
--
*Olivier Girardot* | Associé
o.girar...@lateral-thoughts.com
+33 6 24 09 17 94
Hi everyone,
Using spark-ml there seems to be only BinaryClassificationEvaluator and
RegressionEvaluator, is there any way or plan to provide a ROC-based or
PR-based or F-Measure based for multi-class, I would be interested
especially in evaluating and doing a grid search for a RandomForest model.
/jira/browse/SPARK-7690 is tracking work on
this if you are interested in following the development.
On Mon, Jul 13, 2015 at 2:16 AM, Olivier Girardot
o.girar...@lateral-thoughts.com wrote:
Hi everyone,
Using spark-ml there seems to be only BinaryClassificationEvaluator
and Java halves of
PySpark than just requiring SPARK_HOME to be set; if we did this, I bet
we'd run into tons of issues when users try to run a newer version of the
Python half of PySpark against an older set of Java components or
vice-versa.
On Thu, Jun 4, 2015 at 10:45 PM, Olivier Girardot
Hi everyone,
Considering the python API as just a front needing the SPARK_HOME defined
anyway, I think it would be interesting to deploy the Python part of Spark
on PyPi in order to handle the dependencies in a Python project needing
PySpark via pip.
For now I just symlink the python/pyspark in
Hi everyone,
I think there's a blocker on PySpark the when functions in python seems
to be broken but the Scala API seems fine.
Here's a snippet demonstrating that with Spark 1.4.0 RC3 :
In [*1*]: df = sqlCtx.createDataFrame([(1, 1), (2, 2), (1, 2), (1,
2)], [key, value])
In [*2*]: from
, May 29, 2015 at 2:45 AM, Olivier Girardot
o.girar...@lateral-thoughts.com wrote:
Actually, the Scala API too is only based on column name
Le ven. 29 mai 2015 à 11:23, Olivier Girardot
o.girar...@lateral-thoughts.com a écrit :
Hi,
Testing a bit more 1.4, it seems that the .drop() method
,
Olivier.
Le sam. 30 mai 2015 à 09:54, Reynold Xin r...@databricks.com a écrit :
Yea would be great to support a Column. Can you create a JIRA, and
possibly a pull request?
On Fri, May 29, 2015 at 2:45 AM, Olivier Girardot
o.girar...@lateral-thoughts.com wrote:
Actually, the Scala API too
Actually, the Scala API too is only based on column name
Le ven. 29 mai 2015 à 11:23, Olivier Girardot
o.girar...@lateral-thoughts.com a écrit :
Hi,
Testing a bit more 1.4, it seems that the .drop() method in PySpark
doesn't seem to accept a Column as input datatype :
*.join
Hi,
Testing a bit more 1.4, it seems that the .drop() method in PySpark doesn't
seem to accept a Column as input datatype :
*.join(only_the_best, only_the_best.pol_no == df.pol_no,
inner).drop(only_the_best.pol_no)\* File
/usr/local/lib/python2.7/site-packages/pyspark/sql/dataframe.py, line
I've just tested the new window functions using PySpark in the Spark 1.4.0
rc2 distribution for hadoop 2.4 with and without hive support.
It works well with the hive support enabled distribution and fails as
expected on the other one (with an explicit error : Could not resolve
window function
You're trying to launch using sbt run some provided dependency,
the goal of the provided scope is exactly to exclude this dependency from
runtime, considering it as provided by the environment.
You configuration is correct to create an assembly jar - but not to use sbt
run to test your project.
that show better
performance for both the fits in memory case and the too big for memory
case.
On Thu, May 7, 2015 at 2:23 AM, Olivier Girardot
o.girar...@lateral-thoughts.com wrote:
Ok, but for the moment, this seems to be killing performances on some
computations...
I'll try to give you
Hi everyone,
there seems to be different implementations of the distinct feature in
DataFrames and RDD and some performance issue with the DataFrame distinct
API.
In RDD.scala :
def distinct(numPartitions: Int)(implicit ord: Ordering[T] = null): RDD[T] =
withScope { map(x = (x,
to either use the
Aggregate operator which will benefit from all the Tungsten optimizations,
or have a Tungsten version of distinct for SQL/DataFrame.
On Thu, May 7, 2015 at 1:32 AM, Olivier Girardot
o.girar...@lateral-thoughts.com wrote:
Hi everyone,
there seems to be different
, Olivier Girardot
o.girar...@lateral-thoughts.com wrote:
Hi everyone,
Is there any way in Spark SQL to load multi-line JSON data
efficiently, I
think there was in the mailing list a reference to
http://pivotal-field-engineering.github.io/pmr-common/ for its
JSONInputFormat
/json-mapreduce
--
Emre Sevinç
On Sun, May 3, 2015 at 10:04 PM, Olivier Girardot
o.girar...@lateral-thoughts.com wrote:
Hi everyone,
Is there any way in Spark SQL to load multi-line JSON data
efficiently, I
think there was in the mailing list a reference to
http://pivotal
this is to scan from the beginning and parse the json properly, which
makes it not possible with large files (doable for whole input with a lot
of small files though). If there is a better way, we should do it.
On Sun, May 3, 2015 at 1:04 PM, Olivier Girardot
o.girar...@lateral-thoughts.com wrote
languages).
On Sat, May 2, 2015 at 11:05 AM, Olivier Girardot
o.girar...@lateral-thoughts.com wrote:
Hi everyone,
SQLContext.createDataFrame has different behaviour in Scala or Python :
l = [('Alice', 1)]
sqlContext.createDataFrame(l).collect()
[Row(_1=u'Alice', _2=1
Hi everyone,
Is there any way in Spark SQL to load multi-line JSON data efficiently, I
think there was in the mailing list a reference to
http://pivotal-field-engineering.github.io/pmr-common/ for its
JSONInputFormat
But it's rather inaccessible considering the dependency is not available in
any
Hi everyone,
SQLContext.createDataFrame has different behaviour in Scala or Python :
l = [('Alice', 1)]
sqlContext.createDataFrame(l).collect()
[Row(_1=u'Alice', _2=1)]
sqlContext.createDataFrame(l, ['name', 'age']).collect()
[Row(name=u'Alice', age=1)]
and in Scala :
scala val data =
To close this thread rxin created a broader Jira to handle window functions
in Dataframes : https://issues.apache.org/jira/browse/SPARK-7322
Thanks everyone.
Le mer. 29 avr. 2015 à 22:51, Olivier Girardot
o.girar...@lateral-thoughts.com a écrit :
To give you a broader idea of the current use
for
Reynold or Michael I guess), but I just wanted to point out that the
JIRA
would be the recommended way to create a central place for discussing a
feature add like that.
Nick
On Wed, Apr 29, 2015 at 3:43 PM Olivier Girardot
o.girar...@lateral-thoughts.com wrote:
Hi Nicholas
I guess you can use cast(id as String) instead of just id in your where
clause ?
Le mer. 29 avr. 2015 à 12:13, lonely Feb lonely8...@gmail.com a écrit :
Hi all, we are transfer our HIVE job into SparkSQL, but we found a litter
difference between HIVE and Spark SQL that our sql has a statement
done : https://github.com/apache/spark/pull/5683 and
https://issues.apache.org/jira/browse/SPARK-7118
thx
Le ven. 24 avr. 2015 à 07:34, Olivier Girardot
o.girar...@lateral-thoughts.com a écrit :
I'll try thanks
Le ven. 24 avr. 2015 à 00:09, Reynold Xin r...@databricks.com a écrit :
You can
yep :) I'll open the jira when I've got the time.
Thanks
Le jeu. 23 avr. 2015 à 19:31, Reynold Xin r...@databricks.com a écrit :
Ah damn. We need to add it to the Python list. Would you like to give it a
shot?
On Thu, Apr 23, 2015 at 4:31 AM, Olivier Girardot
o.girar...@lateral
What is the way of testing/building the pyspark part of Spark ?
Le jeu. 23 avr. 2015 à 22:06, Olivier Girardot
o.girar...@lateral-thoughts.com a écrit :
yep :) I'll open the jira when I've got the time.
Thanks
Le jeu. 23 avr. 2015 à 19:31, Reynold Xin r...@databricks.com a écrit :
Ah damn
)
But this seems very specific and very prone to future mistakes.
Is there any way in Py4j to know before calling it the signature of a
method ?
Le jeu. 23 avr. 2015 à 22:17, Olivier Girardot
o.girar...@lateral-thoughts.com a écrit :
What is the way of testing/building the pyspark part
I'll try thanks
Le ven. 24 avr. 2015 à 00:09, Reynold Xin r...@databricks.com a écrit :
You can do it similar to the way countDistinct is done, can't you?
https://github.com/apache/spark/blob/master/python/pyspark/sql/functions.py#L78
On Thu, Apr 23, 2015 at 1:59 PM, Olivier Girardot
, Olivier Girardot
o.girar...@lateral-thoughts.com wrote:
From PySpark it seems to me that the fillna is relying on Java/Scala
code, that's why I was wondering.
Thank you for answering :)
Le lun. 20 avr. 2015 à 22:22, Reynold Xin r...@databricks.com a écrit :
You can just create fillna function
I think I found the Coalesce you were talking about, but this is a catalyst
class that I think is not available from pyspark
Regards,
Olivier.
Le mer. 22 avr. 2015 à 11:56, Olivier Girardot
o.girar...@lateral-thoughts.com a écrit :
Where should this *coalesce* come from ? Is it related
a écrit :
It runs tons of integration tests. I think most developers just let
Jenkins run the full suite of them.
On Tue, Apr 21, 2015 at 12:54 PM, Olivier Girardot ssab...@gmail.com
wrote:
Hi everyone,
I was just wandering about the Spark full build time (including tests),
1h48 seems to me
Hi everyone,
It seems the some of the Spark 1.2.2 prebuilt versions (I tested mainly for
Hadoop 2.4 and later) didn't get deploy on all the mirrors and cloudfront.
Both the direct download and apache mirrors fails with dead links, for
example :
, 2015 at 6:06 AM, Olivier Girardot
o.girar...@lateral-thoughts.com wrote:
Hi everyone,
It seems the some of the Spark 1.2.2 prebuilt versions (I tested mainly
for
Hadoop 2.4 and later) didn't get deploy on all the mirrors and
cloudfront.
Both the direct download and apache mirrors fails
Hi Sourav,
Can you post your updateFunc as well please ?
Regards,
Olivier.
Le mar. 21 avr. 2015 à 12:48, Sourav Chandra sourav.chan...@livestream.com
a écrit :
Hi,
We are building a spark streaming application which reads from kafka, does
updateStateBykey based on the received message type
Hi everyone,
I was just wandering about the Spark full build time (including tests),
1h48 seems to me quite... spacious. What's taking most of the time ? Is the
build mainly integration tests ? Is there any roadmap or jiras dedicated to
that we can chip in ?
Regards,
Olivier.
a UDF might be a good idea no ?
Le lun. 20 avr. 2015 à 11:17, Olivier Girardot
o.girar...@lateral-thoughts.com a écrit :
Hi everyone,
let's assume I'm stuck in 1.3.0, how can I benefit from the *fillna* API
in PySpark, is there any efficient alternative to mapping the records
myself
Hi everyone,
let's assume I'm stuck in 1.3.0, how can I benefit from the *fillna* API in
PySpark, is there any efficient alternative to mapping the records myself ?
Regards,
Olivier.
this document needs to be changed '
https://spark.apache.org/docs/latest/sql-programming-guide.html'
return Row.create(fields[0], fields[1].trim());
needs to be replaced with RowFactory.create.
Thanks again for your reponse.
Thanks
Nipun Batra
On Fri, Apr 17, 2015 at 2:50 PM, Olivier
JavaSchemaRDD used to be JavaRDDLike but DataFrame's are not (and are
not callable with JFunctions), I can open a Jira if you want ?
Regards,
--
*Olivier Girardot* | Associé
o.girar...@lateral-thoughts.com
+33 6 24 09 17 94
Yes thanks !
Le ven. 17 avr. 2015 à 16:20, Ted Yu yuzhih...@gmail.com a écrit :
The image didn't go through.
I think you were referring to:
override def map[R: ClassTag](f: Row = R): RDD[R] = rdd.map(f)
Cheers
On Fri, Apr 17, 2015 at 6:07 AM, Olivier Girardot
o.girar...@lateral
Ok, do you want me to open a pull request to fix the dedicated
documentation ?
Le ven. 17 avr. 2015 à 18:14, Reynold Xin r...@databricks.com a écrit :
I think in 1.3 and above, you'd need to do
.sql(...).javaRDD().map(..)
On Fri, Apr 17, 2015 at 9:22 AM, Olivier Girardot
o.girar
Hi Nipun,
I'm sorry but I don't understand exactly what your problem is ?
Regarding the org.apache.spark.sql.Row, it does exists in the Spark SQL
dependency.
Is it a compilation problem ?
Are you trying to run a main method using the pom you've just described ?
or are you trying to spark-submit
more 7 users than 8.
On Fri, Apr 17, 2015 at 3:36 PM, Olivier Girardot
o.girar...@lateral-thoughts.com wrote:
Is there any convention *not* to show java 8 versions in the
documentation ?
Le ven. 17 avr. 2015 à 21:39, Reynold Xin r...@databricks.com a écrit :
Please do! Thanks.
On Fri
.
On Fri, Apr 17, 2015 at 3:36 PM, Olivier Girardot
o.girar...@lateral-thoughts.com wrote:
Is there any convention *not* to show java 8 versions in the
documentation ?
Le ven. 17 avr. 2015 à 21:39, Reynold Xin r...@databricks.com a écrit :
Please do! Thanks.
On Fri, Apr 17, 2015 at 2
Is there any convention *not* to show java 8 versions in the documentation ?
Le ven. 17 avr. 2015 à 21:39, Reynold Xin r...@databricks.com a écrit :
Please do! Thanks.
On Fri, Apr 17, 2015 at 2:36 PM, Olivier Girardot
o.girar...@lateral-thoughts.com wrote:
Ok, do you want me to open
Hi,
this was not reproduced for me, what kind of jdk are you using for the zinc
server ?
Regards,
Olivier.
2015-02-11 5:08 GMT+01:00 Yi Tian tianyi.asiai...@gmail.com:
Hi, all
I got an ERROR when I build spark master branch with maven (commit:
2d1e916730492f5d61b97da6c483d3223ca44315)
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