![]() The volumes parameter contains the mapping between the host (“/home/airflow/simple-app”) and the Docker container (“/simple-app”) in order to have an access of the cloned repository and so the SimpleApp.py script. The variable PYSPARK_PYTHON is defined to use Python3 as the default interpreter of PySpark and the variable SPARK_HOME contains the path where the script SimpleApp.py must go to fetch the file README.md. In this example, the environment variables set are gonna be used by Spark inside the Docker container. Depending on your OS, you may need to configure Docker to use at least 4.00 GB of memory for the Airflow containers to run properly. Worker: Airflow worker using the apache/airflow:2.0.2 docker image. Experience as team leader and solution architect with a particular focus on design of big data architectures for supporting the development and the delivery of. Lots of pre-defined Airflow operators for running standard tasks, e.g., Bash operator, Python operator, SSH operator. Notice the environmentand the volumes parameters in the DockerOperator. Software engineer with experience in design, development and deployment of machine learning and big data solutions. DevOps-minded by nature and comfortable with working at any level of the technical stack of the product. docs class DockerSwarmOperator(DockerOperator): ''' Execute a command as an ephemeral docker swarm service. The second one is where the DockerOperator is used in order to start a Docker container with Spark and kick off a Spark job using the SimpleApp.py file.īy the way, I’m not gonna explain here what does the BranchPythonOperator and why there is a dummy task, but if you are interested by learning more about Airflow, feel free to check my course right there. The first one is where the BranchPythonOperator is used in order to select one branch or another according to whether or not the repository exists. - 1 Build a solid knowledge of the Architecture of Apache Airflow and How to run it locally via Docker.1234567891011121314151617181920212223242526272829303132333435363738įrom airflow import DAG from _operator import BashOperator from datetime import datetime, timedelta from _operator import DockerOperator default_args =, volumes=, command= '/spark/bin/spark-submit -master local /simple-app/SimpleApp.py', docker_url= 'unix://var/run/docker.sock', network_mode= 'bridge' ) t_git_pull > t_docker ''' Implements Docker operator ''' import ast import six from docker import APIClient, tls from import DockerHook from airflow.exceptions import AirflowException from airflow.models import BaseOperator from import applydefaults from import. To install this package run one of the following: conda install -c conda-forge apache-airflow-providers-docker.
0 Comments
Leave a Reply. |
Details
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |