I have written PySpark code locally. Now I want to push the code into the EC2 and run it in a Standalone mode. But if i run the code with spark-submit program was occupying terminal. But I have to use the terminal to work with other things.
I thought Running PySpark in background or as daemon was solution but i don't know how to do it.
There are several ways.
Nohup
Cron
nohup command(spark-submit coommand) &
this will execute your spark job in background.
you have to write your spark code in python file (.py file) and submit that using spark-submit in nohup.
Related
I am very new to spark.
I have created the spark code in pyspark but it is repl shell, how can I run this as a script.
I tried python script.py but it fails as it cannot access spark libraries.
spark-submit script.py is the way to submit a pyspark code.
Before using this please make sure pyspark and spark is properly set up in your environment.
If not done yet, do follow the below link
I want to place my python machine learning code in AWS. Can someone please help me with the procedure. Thank you.
Python script is in .py format.
You have many options available:
You can start your script using EC2's User Data feature
You can use rsync your script to the EC2 instance and run it over SSH
You can build a Docker container in which you would include your script and run a task in ECS
If your script takes less than 15 minutes to execute, you can run it in a Lambda function
I have a running instance of docker with zeppelin/spark environment configured. I would like to know if there is a possibility to run spark-shell process for example with
docker exec -it CONTAINTER spark-shell
and then connect to created spark context with zeppelin notebook. I've seen that there is a "Connect to existing process" checkbox in the Zeppelin interpreters page, however I'm not sure how to use it.
For example, in Jupyter notebook there is a possibility to connect ipython console to an existing Jupyter kernel such that I have access to the notebook variables from ipython console. I'm wondering if there is a similar functionality in case of Zeppeling and spark-shell or maybe for some reasons this is not possible.
Thank you in advance.
KK
I'm trying to run a script in the pyspark environment but so far I haven't been able to.
How can I run a script like python script.py but in pyspark?
You can do: ./bin/spark-submit mypythonfile.py
Running python applications through pyspark is not supported as of Spark 2.0.
pyspark 2.0 and later execute script file in environment variable PYTHONSTARTUP, so you can run:
PYTHONSTARTUP=code.py pyspark
Compared to spark-submit answer this is useful for running initialization code before using the interactive pyspark shell.
Just spark-submit mypythonfile.py should be enough.
You can execute "script.py" as follows
pyspark < script.py
or
# if you want to run pyspark in yarn cluster
pyspark --master yarn < script.py
Existing answers are right (that is use spark-submit), but some of us might want to just get started with a sparkSession object like in pyspark.
So in the pySpark script to be run first add:
from pyspark.sql import SparkSession
spark = SparkSession.builder \
.master('yarn') \
.appName('pythonSpark') \
.enableHiveSupport()
.getOrCreate()
Then use spark.conf.set('conf_name', 'conf_value') to set any configuration like executor cores, memory, etc.
Spark environment provides a command to execute the application file, be it in Scala or Java(need a Jar format), Python and R programming file.
The command is,
$ spark-submit --master <url> <SCRIPTNAME>.py.
I'm running spark in windows 64bit architecture system with JDK 1.8 version.
P.S find a screenshot of my terminal window.
Code snippet
I have a “myprogram.py” and my “myprogram.scala” that I need to run on my spark machine. How Can I upload and launch them?
I have been using shell to do my transformation and calling actions, but now I want to launch a complete program on spark machine instead of entering single commands every time. Also I believe that will make it easy for me to make changes to my program instead of starting to enter commands in shell.
I did standalone installation in Ubuntu 14.04, on single machine, not a cluster, used spark 1.4.1.
I went through spark docs online, but I only find instruction on how to do that on cluster. Please help me on that.
Thank you.
The documentation to do this (as commented above) is available here: http://spark.apache.org/docs/latest/submitting-applications.html
However, the code you need is here:
# Run application locally on 8 cores
./bin/spark-submit \
--class org.apache.spark.examples.SparkPi \
--master local[8] \
/path/to/examples.jar \
100
You'll need to compile the scala file using sbt (documentation here: http://www.scala-sbt.org/0.13/tutorial/index.html)
Here's some information on the build.sbt file you'll need in order to grab the right dependencies: http://spark.apache.org/docs/latest/quick-start.html
Once the scala file is compiled, you'll send the resulting jar using the above submit command.
Put it simply:
In Linux terminal, cd to the directory that spark is unpacked/installed
Note, this folder normally contains subfolders like “bin”, “conf”, “lib”, “logs” and so on.
To run the Python program locally with simple/default settings, type command
./bin/spark-submit --master local[*] myprogram.py
More complete descriptions are here like zero323 and ApolloFortyNine described.