pyflink on yarn

PyFlink is a Python API for Apache Flink, which is a distributed processing framework that can handle large scale data processing. YARN (Yet Another Resource Negotiator) is a component of Apache Hadoop that manages resources for distributed applications. PyFlink can be run on YARN by setting up a Flink cluster on YARN.

Here are the steps to run PyFlink on YARN:

1. Install Apache Flink and Apache Hadoop on your system.
2. Configure the Hadoop and Flink configuration files to set up a Flink cluster on YARN.
3. Configure PyFlink to use the Flink cluster on YARN.
4. Submit a PyFlink job to the Flink cluster on YARN using the ‘yarn’ execution mode.

Here is an example of submitting a PyFlink job in yarn mode:

from pyflink.dataset import ExecutionEnvironment
from pyflink.table import TableConfig, BatchTableEnvironment

env = ExecutionEnvironment.get_execution_environment()
t_config = TableConfig()
t_env = BatchTableEnvironment.create(env, t_config)

# define your PyFlink job here

t_env.execute("my_job", "yarn")

In this example, we create a Flink execution environment, table configuration, and table environment. We then define our PyFlink job and execute it using the ‘yarn’ execution mode. This will submit the job to the Flink cluster running on YARN.

Overall, running PyFlink on YARN allows you to leverage the scalability and resource management capabilities of YARN for your PyFlink jobs.