[jira] [Commented] (TOREE-457) spark context seen corrupted after load KAfka libraries

2017-12-26 Thread fxoSa (JIRA)

[ 
https://issues.apache.org/jira/browse/TOREE-457?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16303850#comment-16303850
 ] 

fxoSa commented on TOREE-457:
-

It's work now.
I have installed the suggested version on GCP  :
https://dist.apache.org/repos/dist/dev/incubator/toree/0.2.0-incubating-rc2/toree-pip/toree-0.2.0.tar.gz
 
Also I use the updated vesion of kafka clients on jpyter notebook.
%AddDeps org.apache.spark spark-streaming-kafka-0-10_2.11 2.2.1

 Thanks Luciano. 

> spark context seen corrupted after load KAfka libraries
> ---
>
> Key: TOREE-457
> URL: https://issues.apache.org/jira/browse/TOREE-457
> Project: TOREE
>  Issue Type: Bug
>  Components: Kernel
>Reporter: fxoSa
>Priority: Minor
>
> I am trying to set up a jupyter notebook (apache-toree Scala) to access kafka 
> logs from spark a streaming.
> First I add dependencies using AddDeps:
>  
> {code:java}
> %AddDeps org.apache.spark spark-streaming-kafka-0-10_2.11 2.2.0. 
> Marking org.apache.spark:spark-streaming-kafka-0-10_2.11:2.2.0 for download 
> Preparing to fetch from:
> -> file:/tmp/toree_add_deps8235567186565695423/
> -> https://repo1.maven.org/maven2
> -> New file at 
> /tmp/toree_add_deps8235567186565695423/https/repo1.maven.org/maven2/org/apache/spark/spark-streaming-kafka-0-10_2.11/2.2.0/spark-streaming-kafka-0-10_2.11-2.2.0.jar
> {code}
> After that I am able to import successfully part of necesary libraries:
> {code:java}
> import org.apache.spark.SparkConf
> import org.apache.spark.streaming._
> import org.apache.spark.streaming.kafka010._
> {code}
> However code fails when I try to create streaming context:
> {code:java}
> val ssc = new StreamingContext(sc, Seconds(2))
> Name: Compile Error
> Message: :38: error: overloaded method constructor StreamingContext 
> with alternatives:
>   (path: String,sparkContext: 
> org.apache.spark.org.apache.spark.org.apache.spark.org.apache.spark.org.apache.spark.SparkContext)org.apache.spark.streaming.StreamingContext
>  
>   (path: String,hadoopConf: 
> org.apache.hadoop.conf.Configuration)org.apache.spark.streaming.StreamingContext
>  
>   (conf: org.apache.spark.SparkConf,batchDuration: 
> org.apache.spark.streaming.Duration)org.apache.spark.streaming.StreamingContext
>  
>   (sparkContext: 
> org.apache.spark.org.apache.spark.org.apache.spark.org.apache.spark.org.apache.spark.SparkContext,batchDuration:
>  
> org.apache.spark.streaming.Duration)org.apache.spark.streaming.StreamingContext
>  cannot be applied to 
> (org.apache.spark.org.apache.spark.org.apache.spark.org.apache.spark.org.apache.spark.SparkContext,
>  org.apache.spark.streaming.Duration)
>val ssc = new StreamingContext(sc, Seconds(2))
>  ^
> StackTrace: 
> {code}
> I have try it, in a jupyter docker 
> https://github.com/jupyter/docker-stacks/tree/master/all-spark-notebook
> and in spark cluster set up in Google cloud platform with the same results
> Thanks



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[jira] [Commented] (TOREE-457) spark context seen corrupted after load KAfka libraries

2017-12-14 Thread Luciano Resende (JIRA)

[ 
https://issues.apache.org/jira/browse/TOREE-457?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16291730#comment-16291730
 ] 

Luciano Resende commented on TOREE-457:
---

This is a very old version of Toree and most likely was not built with Spark 
2.2.0, I would recommend you building your own toree distribution like :

APACHE_SPARK_VERSION=2.2.0 BASE_VERSION=0.2.0  IS_SNAPSHOT=False make clean 
release

And then installing from pip package created in the dist folder.

Or try installing from the Toree 0.2 RC

https://dist.apache.org/repos/dist/dev/incubator/toree/0.2.0-incubating-rc2/toree-pip/toree-0.2.0.tar.gz

> spark context seen corrupted after load KAfka libraries
> ---
>
> Key: TOREE-457
> URL: https://issues.apache.org/jira/browse/TOREE-457
> Project: TOREE
>  Issue Type: Bug
>  Components: Kernel
>Reporter: fxoSa
>Priority: Minor
>
> I am trying to set up a jupyter notebook (apache-toree Scala) to access kafka 
> logs from spark a streaming.
> First I add dependencies using AddDeps:
>  
> {code:java}
> %AddDeps org.apache.spark spark-streaming-kafka-0-10_2.11 2.2.0. 
> Marking org.apache.spark:spark-streaming-kafka-0-10_2.11:2.2.0 for download 
> Preparing to fetch from:
> -> file:/tmp/toree_add_deps8235567186565695423/
> -> https://repo1.maven.org/maven2
> -> New file at 
> /tmp/toree_add_deps8235567186565695423/https/repo1.maven.org/maven2/org/apache/spark/spark-streaming-kafka-0-10_2.11/2.2.0/spark-streaming-kafka-0-10_2.11-2.2.0.jar
> {code}
> After that I am able to import successfully part of necesary libraries:
> {code:java}
> import org.apache.spark.SparkConf
> import org.apache.spark.streaming._
> import org.apache.spark.streaming.kafka010._
> {code}
> However code fails when I try to create streaming context:
> {code:java}
> val ssc = new StreamingContext(sc, Seconds(2))
> Name: Compile Error
> Message: :38: error: overloaded method constructor StreamingContext 
> with alternatives:
>   (path: String,sparkContext: 
> org.apache.spark.org.apache.spark.org.apache.spark.org.apache.spark.org.apache.spark.SparkContext)org.apache.spark.streaming.StreamingContext
>  
>   (path: String,hadoopConf: 
> org.apache.hadoop.conf.Configuration)org.apache.spark.streaming.StreamingContext
>  
>   (conf: org.apache.spark.SparkConf,batchDuration: 
> org.apache.spark.streaming.Duration)org.apache.spark.streaming.StreamingContext
>  
>   (sparkContext: 
> org.apache.spark.org.apache.spark.org.apache.spark.org.apache.spark.org.apache.spark.SparkContext,batchDuration:
>  
> org.apache.spark.streaming.Duration)org.apache.spark.streaming.StreamingContext
>  cannot be applied to 
> (org.apache.spark.org.apache.spark.org.apache.spark.org.apache.spark.org.apache.spark.SparkContext,
>  org.apache.spark.streaming.Duration)
>val ssc = new StreamingContext(sc, Seconds(2))
>  ^
> StackTrace: 
> {code}
> I have try it, in a jupyter docker 
> https://github.com/jupyter/docker-stacks/tree/master/all-spark-notebook
> and in spark cluster set up in Google cloud platform with the same results
> Thanks



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