I have created pyspark code in pycharm and publish it to GitHub repository , i need to run this Pyspark code on AWS . i want to integrated this GitHub code to push to cloud via Jenkins can you please provide the step and reference where specific pyspark code build and deployment step mentioned and can you please provide step by step to follow to run pyspark code on EMR in AWS
Thanks in advance
Related
I am trying to deploy an AWS Glue job through terraform. However, having gone through the documentation over the below, I am unable to find a way to configure "Dependent jars path" in Terraform as I am referencing a jar file in my AWS Glue code
https://registry.terraform.io/providers/hashicorp/aws/latest/docs/resources/glue_job
Is there a way to get around this please?
Click here for a screen grab of the Dependent jars path
Put the --extra-jars path (as per https://docs.aws.amazon.com/glue/latest/dg/aws-glue-programming-etl-glue-arguments.html) into the default_arguments, as per https://registry.terraform.io/providers/hashicorp/aws/latest/docs/resources/glue_job
I'd like to make the CodePipeline Build# (CODEBUILD_BUILD_NUMBER) available to my node code that is being deployed. Currently there are only two steps in the pipeline: pull from bitbucket, then deploy to Elastic Beanstalk, so I don't know how this would work.
Alternatively, if I could get the most recent commit number available to my node.js code, that would be ok.
This demonstrate how to specify an artifact name that is created at build time.example
Is it possible to setup continuous delivery for a simple html page in under 1 hour?
Suppose I have a hello world index.html page being hosted by npm serve, a Dockerfile to build the image and a image.sh script using docker build. This is in a github repo.
I want to be able to check-in a change to the index.html file and see it on my website immediately.
Can this be done in under 1 hour. Either AWS or Google Cloud. What are the steps?
To answer your question. 1 hour. Is it possible? Yes.
Using only AWS,
Services to be used:
AWS CodePipeline - To trigger Github webhooks and send the source files to AWS CodeBuild
AWS CodeBuild - Takes the source files from the CodePipeline and build your application, serve the build to S3, Heroku, Elastic Beanstalk, or any alternate service you desire
The Steps
Create an AWS CodePipeline
Attach your source(Github) in your Pipeline (Each commit will trigger your pipeline to take the new commit and use it as a source and build it in CodeBuild)
Using your custom Docker build environment, CodeBuild uses a yml file to specify the steps to take in your build process. Use it to build the newly committed source files, and deploy your app(s) using the AWS CLI.
Good Luck.
I think I would start with creating a web-enabled script which would be a Github commit hook. Probably in Node on a AWS instance which would then trigger the whole process of cleaning up (deleting) the old AWS instance and reinstalling a new AWS instance with the contents of your repository.
The exact method will be largely dependant on how your whole stack is setup.
We are successfully using code deploy for deployment , however we have a request from client to separate deployment script repository and code repository , right now code repository contains the appspec.yml and other script which need to be run and available to coders too.
I tried searching google and stackoverflow but found nothing :( .
Do we need to make use of other tool like chef,puppet etc ? however client want to be solution using aws only.
Kindly help.
I've accomplished this by adding extra step to my build process.
During the build, my CI tool checks out second repository which contains deployment related scripts and appspec.yml file. After that we zip up the code + scripts and ship it to CodeDeploy.
Don't forget that appspec.yml has to be in root directory.
I hope it helps.
Hope you are doing well.
I am new to Spark as well as Microsoft Azure. As per our project requirement we have developed a pyspark script though the jupyter notebook installed in our HDInsight cluster. Till date we ran the code from the jupyter itself but now we need to automate the script. I tried to use Azure Datafactory but could not find a way to run the pyspark script from there. Also tried to use oozie but could not figure out how to use it.
May you people please help me how I can automate/ schedule a pyspark script in azure.
Thanks,
Shamik.
Azure Data Factory today doesn't have first class support for Spark. We are working to add that integration in future. Till that time, we have published a sample on Github that uses ADF Map Reduce Activity to submit a jar that invokes spark submit.
Please take a look here:
https://github.com/Azure/Azure-DataFactory/tree/master/Samples/Spark