Job creation by technology

Owned by Victor Leroux (Unlicensed)
Last updated: Mar 09, 2018 by Cédric Dué (Unlicensed)

Create a Sqoop job

1. Name your job, add description and release note

2. Type your command using the ready-to-use template provided. Add environment variables as $VARIABLE or access your variable library by clicking the link

3. Set your CPU, memory and disk settings

4. Enter one or more e-mail addresses to be alerted on the status of the job

5. Run your job manually or set up a schedule


Create a Talend job

1. Name your job, add description and release note

2. Add a package by uploading a zip of by entering a URL

3. Type your command. {file} is a parameter (don't change it). Customize arg1, arg2, etc. Add environmnent variables as $VARIABLE or access your variable library by clicking the link

4. Set your CPU, memory and disk settings

5. Enter one or more e-mail addresses to be alerted on the status of the job

6. Run your job manually or set up a schedule


Create a Java/Scala job

1. Name your job, add description and release note

2. Add a package by uploading a jar of by entering a URL

3. Type your command. {file} is a parameter (don't change it). Customize arg1, arg2, etc. Add environmnent variables as $VARIABLE or access your variable library by clicking the link

4. Choose the language version: JAVA 8 (recommended) or JAVA 7

5. Set your CPU, memory and disk settings

6. Enter one or more e-mail addresses to be alerted on the status of the job

7. Run your job manually or set up a schedule

Create a R job

1. Name your job, add description and release note

2. Add a package by uploading a R file of by entering a URL

3. Type your command. {file} is a parameter (don't change it). Customize arg1, arg2, etc. Add environmnent variables as $VARIABLE or access your variable library by clicking the link

4. Set your CPU, memory and disk settings

5. Enter one or more e-mail addresses to be alerted on the status of the job

6. Run your job manually or set up a schedule



Create a Python job

1. Name your job, add description and release note

2. Add a package by uploading a file of by entering a URL. Files may be a .py or a zip archive with at least a file named __main__.py inside. In zip archives, you can provide a requirements.txt if you need external packages

3. Type your command. {file} is a parameter (don't change it). Customize arg1, arg2, etc. Add environmnent variables as $VARIABLE or access your variable library by clicking the link

4.Select Python version (2.7 or 3.x)

5. Set your CPU, memory and disk settings

6. Enter one or more e-mail addresses to be alerted on the status of the job

7. Run your job manually or set up a schedule



Create a Spark job

1. Name your job, add description and release note

2. Add a package by uploading a jar of by entering a URL

3. Type your command. {file} and {driver_options} are parameters (don't change it). Customize arg1, arg2, etc. Add environmnent variables as $VARIABLE or access your variable library by clicking the link

4. Choose the language type and version between Java/Scala (8.131 recommended or 8.121) and Python (2.5.2 recommended or 2.7.13)

5. Choose the Spark version: 1.6.1 is recommended but 1.5.2 , 2.0.2 and  2.1.0 are also available

6. Set your CPU, memory and disk settings

7. Enter one or more e-mail addresses to be alerted on the status of the job

8. Enable the streaming option in case of streaming process

9. Run your job manually or set up a schedule


Create a Datascience Notebook

  1. Name your job, add description and release note
  2. Choose the notebook:
    1. Jupyter notebook: Python 2 & 3, Python / Spark 2.1.0 ,  R, Scala / Spark 1.6.1, Scala / Spark 1.5.2, R, Ruby, Haskell, Julia
    2. Zeppelin notebook (Spark 2.1.0)
    3. RStudio
  3. Set your CPU, memory and disk settings


Access a Datascience Notebook

1. Click on the "Open in new window" icon next to a notebook