Package: airflow-livy-operators
Airflow Livy OperatorsLets Airflow DAGs run Spark jobs via Livy:Sessions,Batches. This mode supports additional verification via Spark/YARN REST API.Seethis blog postfor more information and detailed comparison of ways to run Spark jobs from Airflow.Directories and files of interestairflow_home/plugins: Airflow Livy operators' code.airflow_home/dags: example DAGs for Airflow.batches: Spark jobs code, to be used in Livy batches.sessions: Spark code for Livy sessions. You can add templates
to files' contents in order to pass parameters into it.helper.sh: helper shell script. Can be used to run sample DAGs,
prep development environment and more.
Run it to find out what other commands are available.How do I......run the examples?Prerequisites:Python 3. Make sure it's installed and in$PATHSpark cluster with Livy. I heavily recommend you "mock" one on your machine withmy Spark cluster on Docker Compose.Now,Optional - this step can be skipped if you're mocking a cluster on your
machine. Openhelper.sh. Insideinit_airflow()function you'll see Airflow
Connections for Livy, Spark and YARN. Redefine as appropriate.Define the way the sample batch files from this repo are delivered to a cluster:if you're using a docker-compose cluster: redefine the BATCH_DIR variable
as appropriate.if you're using your own cluster: modify thecopy_batches()function so that it
delivers the files to a place accessible by your cluster (could beaws s3 cpetc.)run./helper.sh upto bring up the whole infrastructure.
Airflow UI will be available atlocalhost:8888.
The credentials areadmin/admin.Ctrl+C to stop Airflow. Then./helper.sh downto dispose of
remaining Airflow processes (shouldn't be required if everything goes well.
Run this if you can't start Airflow again due to some non-informative errors) .... use it in my project?pipinstallairflow-livy-operatorsThis is how you import them:fromairflow_livy.sessionimportLivySessionOperatorfromairflow_livy.batchimportLivyBatchOperatorSee sample DAGs underairflow_home/dagsto learn how to use the operators.... set up the development environment?Alright, you want to contribute and need to be able to run the stuff on your machine,
as well as the usual niceness that comes with IDEs (debugging, syntax highlighting)../helper.sh updevruns Airflow with local operators' code (as opposed to
pulling them from PyPi). Useful for development../helper.sh full- run tests (pytest) with coverage report
(will be saved tohtmlcov/), highlight code style errors (flake8),
reformat all code (black+isort)./helper.sh ci- same as above, but only check the code formatting. This
same command is ran by CI.(Pycharm-specific) point PyCharm to your newly-created virtual environment: go to"Preferences" -> "Project: airflow-livy-operators" -> "Project interpreter", select "Existing environment"and pickpython3executable fromvenvfolder
(venv/bin/python3)... debug?(Pycharm-specific) Step-by-step debugging withairflow testand running PySpark batch jobs locally (with debugging as well)
is supported via run configurations under.idea/runConfigurations.
You shouldn't have to do anything to use them - just open the folder
in PyCharm as a project.An example of how a batch can be ran on local Spark:python./batches/join_2_files.py\"file:////Users/vpanov/data/vpanov/bigdata-docker-compose/data/grades.csv"\"file:///Users/vpanov/data/vpanov/bigdata-docker-compose/data/ssn-address.tsv"\-file1_sep=,-file1_header=true\-file1_schema="\`Last name\` STRING, \`First name\` STRING, SSN STRING, Test1 INT, Test2 INT, Test3 INT, Test4 INT, Final INT, Grade STRING"\-file1_join_column=SSN-file2_header=false\-file2_schema="\`Last name\` STRING, \`First name\` STRING, SSN STRING, Address1 STRING, Address2 STRING"\-file2_join_column=SSN-output_header=true\-output_columns="file1.\`Last name\` AS LastName, file1.\`First name\` AS FirstName, file1.SSN, file2.Address1, file2.Address2"# Optionally append to save result to file#-output_path="file:///Users/vpanov/livy_batch_example"TODOhelper.sh - replace with modern tools (e.g. pipenv + Docker image)Disable some of flake8 flags for cleaner code