I am trying to integrate my Scala Eclipse IDE with my Azure Databricks Cluster so that I can directly run my Spark program through Eclipse IDE on my Databricks Cluster.
I followed the official documentation of Databricks Connect(https://docs.databricks.com/dev-tools/databricks-connect.html)
.
I have:
Installed Anaconda.
Installed Python Lib 3.7 and Databricks Connect library 6.0.1.
Did the Databricks Connect Configuration part(CLI part).
Also, added the client libraries in the Eclipse IDE.
Set the SPARK_HOME env. variable to the path which I get from running command in Anaconda, i.e. 'databricks-connect get-jar-dir'
I have not set any other environment variables apart from the one mentioned above.
Need help on finding what else is to be done to accomplish this integration, like how the ENV. variable related to connection works if running through IDE.
If someone has already done this successfully, guide me please.
Related
I'm having some issues getting JProfiler connected to a remote WebSphere 8.5.5 instance that is running on Linux. When I start JProfiler on my Windows 10 machine I select the "Profile an application server, locally or remotely" and select the option to integrate with IBM WebSphere 8.x Application Server.
The part I'm having an issue with is the "Specify the remote address" section of setting up the profile. The setup says I need the profiling agent running on target JVM. I download the tar file from the JProfiler website and extract it on Linux machine and run jpenable as it says I should but I get this message.
"No suitable Java Virtual Machine could be found on your system. The version of the JVM must be at least 1.6 and at most 11. Please define INSTALL4J_JAVA_HOME to point to a suitable JVM."
I have made edits to the arguments file that came with the JProfiler in order to remedy this issue but I just can't seem to get JProfiler to see the IBM Java that WebSphere is using on this machine. I have tried using the INSTALL_JAVA_HOME_OVERRIDE variable in the arguments file by putting the full path to the WebSphere Java install. I have tried using the INSTALL4J_JAVA_PREFIX variable and I have created a INSTALL4J_JAVA_HOME variable in the arguments file and put the full path to the WebSphere Java.
Any help would be appreciated greatly appreciated in getting me around this issue. I have verified that WebSphere is using Java version 1.8.0_171.
but I just can't seem to get JProfiler to see the IBM Java that WebSphere is using on this machine.
That's because IBM JVMs are not supported for attach mode.
The setup says I need the profiling agent running on target JVM.
Generally, this is achieved by adding an -agentpath VM parameter to the profiled VM. The remote address that you are asked for in the wizard will be added as an option to that parameter. The wizard will then modify the server config file and add the complete VM parameter, so you don't have to it manually.
More information is available at
https://www.ej-technologies.com/resources/jprofiler/help/doc/main/profiling.html
currently I'm evaluating, how to setup my web development infrastructure using docker.
I would like to use eclipse with nodeclipse, but I don't want to install nodejs locally. Additionally I don't want to use Eclipse Che.
So my question is, if it is possible to configure eclipse that I use a docker-container including nodejs?
The biggest challange currently is, that without nodejs I get error messages in my typescript code, that my imported packages can't be found.
Thank you for your help :)
I have Installed a single node hadoop 2.8 on AWS free tier nano instance. I have a local windows machine with eclipse on it. What is a good learning workflow. I am not sure of capabilities of AWS orhadoop. Should I write code in local eclipse build a jar, transfer it AWS machine and run it?
If I have to write and create a jar from local machine should I have hadoop installed? how should I do? and What is good learning path from installation to being comfortable with working on hadoop?
I am trying to setup Spark on my Windows 10 PC. After executing the spark-shell command, I got the following error:
java.lang.IllegalArgumentException: Error while instantiating 'org.apache.spark.sql.hive.HiveSessionState':
at rg.apache.spark.sql.SparkSession$.org$apache$spark$sql$SparkSession$$reflect
Spark Installation on windows machine is not much difficult. We need to take care of some permissions and configurations during the installation. Please follow below link for step wise Spark and Scala installation and configuration on windows machine.
Apache Spark Installation on windows10
I am trying to follow the Yahoo hadoop tutorial:
http://developer.yahoo.com/hadoop/tutorial/module3.html#vm
Everything is fine until I try to connect my Eclipse IDE to the hadoop server process according to the "Getting Started With Eclipse" section. The short story is that my "map reduce location", my DFS Location keeps coming back with "Error:null". My VM is running and I can ping it from my PC. Hadoop server is running as I have run the Pi example.
My PC runs WindowsXP and there is no "hadoop.job.ugi" in the Advanced list for the hadoop location....What does "/hadoop/mapred/system" refer too. There is no such directory in the hadoop installation that you install from the tutorial. It seems like a pretty important directory from the name of the field. I have gone into the advanced settings and switched any reference to my WinXP login (Ben) over to "hadoop-user". It is easy to find in the VM the folder locations that it is looking for like "/tmp/hadoop-hadoop-user/mapred/temp".
Am I right in thinking I can run eclipse on the WinXP environment and connect to the VMWare process via its IP address? Isn't that the point of the article? It does not work.
You read it right. The eclipse plugin for hadoop has lot of caveats and there are couple of things that are not well documented. See the second answer by Icn over Installing Hadoop's Eclipse Plugin. Hopefully that would solve the problem.
"/hadoop/mapred/system" refers to the directories inside HDFS, so you don't see it from terminal using ls
I did see the "hadoop.job.ugi" in Advanced list, and succeed to connected to the VM following the instructions there.
are you using the recommended version of eclipse (3.3.1) ?