Does anybody know how to run Beam Python pipelines with Flink when Flink is running as pods in Kubernetes?
I have successfully managed to run a Beam Python pipeline using the Portable runner and the job service pointing to a local Flink server running in Docker containers.
I was able to achieve that mounting the Docker socket in my Flink containers, and running Flink as root process, so the class DockerEnvironmentFactory can create the Python harness container.
Unfortunately, I can't use the same solution when Flink is running in Kubernetes. Moreover, I don't want to create the Python harness container using the Docker command from my pods.
It seems that Bean runner automatically selects Docker for executing Python pipelines. However, I noticed there is an implementation called ExternalEnvironmentFactory, but I am not sure how to use it.
Is there a way to deploy a side container and use a different factory to run the Python harness process? What is the correct approach?
This is the patch for DockerEnvironmentFactory:
diff -pr beam-release-2.15.0/runners/java-fn-execution/src/main/java/org/apache/beam/runners/fnexecution/environment/DockerEnvironmentFactory.java beam-release-2.15.0-1/runners/java-fn-execution/src/main/java/org/apache/beam/runners/fnexecution/environment/DockerEnvironmentFactory.java
*** beam-release-2.15.0/runners/java-fn-execution/src/main/java/org/apache/beam/runners/fnexecution/environment/DockerEnvironmentFactory.java 2019-08-14 22:33:41.000000000 +0100
--- beam-release-2.15.0-1/runners/java-fn-execution/src/main/java/org/apache/beam/runners/fnexecution/environment/DockerEnvironmentFactory.java 2019-09-09 16:02:07.000000000 +0100
*************** package org.apache.beam.runners.fnexecut
*** 19,24 ****
--- 19,26 ----
import static org.apache.beam.vendor.guava.v26_0_jre.com.google.common.base.MoreObjects.firstNonNull;
+ import java.net.InetAddress;
+ import java.net.UnknownHostException;
import java.nio.file.Files;
import java.nio.file.Paths;
import java.time.Duration;
*************** public class DockerEnvironmentFactory im
*** 127,133 ****
ImmutableList.<String>builder()
.addAll(gcsCredentialArgs())
// NOTE: Host networking does not work on Mac, but the command line flag is accepted.
! .add("--network=host")
// We need to pass on the information about Docker-on-Mac environment (due to missing
// host networking on Mac)
.add("--env=DOCKER_MAC_CONTAINER=" + System.getenv("DOCKER_MAC_CONTAINER"));
--- 129,135 ----
ImmutableList.<String>builder()
.addAll(gcsCredentialArgs())
// NOTE: Host networking does not work on Mac, but the command line flag is accepted.
! .add("--network=flink")
// We need to pass on the information about Docker-on-Mac environment (due to missing
// host networking on Mac)
.add("--env=DOCKER_MAC_CONTAINER=" + System.getenv("DOCKER_MAC_CONTAINER"));
*************** public class DockerEnvironmentFactory im
*** 222,228 ****
private static ServerFactory getServerFactory() {
ServerFactory.UrlFactory dockerUrlFactory =
! (host, port) -> HostAndPort.fromParts(DOCKER_FOR_MAC_HOST, port).toString();
if (RUNNING_INSIDE_DOCKER_ON_MAC) {
// If we're already running in a container, we need to use a fixed port range due to
// non-existing host networking in Docker-for-Mac. The port range needs to be published
--- 224,230 ----
private static ServerFactory getServerFactory() {
ServerFactory.UrlFactory dockerUrlFactory =
! (host, port) -> HostAndPort.fromParts(getCanonicalHostName(), port).toString();
if (RUNNING_INSIDE_DOCKER_ON_MAC) {
// If we're already running in a container, we need to use a fixed port range due to
// non-existing host networking in Docker-for-Mac. The port range needs to be published
*************** public class DockerEnvironmentFactory im
*** 237,242 ****
--- 239,252 ----
}
}
+ private static String getCanonicalHostName() throws RuntimeException {
+ try {
+ return InetAddress.getLocalHost().getCanonicalHostName();
+ } catch (UnknownHostException e) {
+ throw new RuntimeException(e);
+ }
+ }
+
/** Provider for DockerEnvironmentFactory. */
public static class Provider implements EnvironmentFactory.Provider {
private final boolean retainDockerContainer;
*************** public class DockerEnvironmentFactory im
*** 269,275 ****
public ServerFactory getServerFactory() {
switch (getPlatform()) {
case LINUX:
! return ServerFactory.createDefault();
case MAC:
return DockerOnMac.getServerFactory();
default:
--- 279,286 ----
public ServerFactory getServerFactory() {
switch (getPlatform()) {
case LINUX:
! return DockerOnMac.getServerFactory();
! // return ServerFactory.createDefault();
case MAC:
return DockerOnMac.getServerFactory();
default:
This is the Docker compose file I use to run Flink:
version: '3.4'
services:
jobmanager:
image: tenx/flink:1.8.1
command: 'jobmanager'
environment:
JOB_MANAGER_RPC_ADDRESS: 'jobmanager'
DOCKER_MAC_CONTAINER: 1
FLINK_JM_HEAP: 128
volumes:
- jobmanager-data:/data
- /var/run/docker.sock:/var/run/docker.sock
ports:
- target: 8081
published: 8081
protocol: tcp
mode: ingress
networks:
- flink
taskmanager:
image: tenx/flink:1.8.1
command: 'taskmanager'
environment:
JOB_MANAGER_RPC_ADDRESS: 'jobmanager'
DOCKER_MAC_CONTAINER: 1
FLINK_TM_HEAP: 1024
TASK_MANAGER_NUMBER_OF_TASK_SLOTS: 2
networks:
- flink
volumes:
- taskmanager-data:/data
- /var/run/docker.sock:/var/run/docker.sock
- /var/folders:/var/folders
volumes:
jobmanager-data:
taskmanager-data:
networks:
flink:
external: true
This is my Python pipeline:
import apache_beam as beam
import logging
class LogElements(beam.PTransform):
class _LoggingFn(beam.DoFn):
def __init__(self, prefix=''):
super(LogElements._LoggingFn, self).__init__()
self.prefix = prefix
def process(self, element, **kwargs):
logging.info(self.prefix + str(element))
yield element
def __init__(self, label=None, prefix=''):
super(LogElements, self).__init__(label)
self.prefix = prefix
def expand(self, input):
input | beam.ParDo(self._LoggingFn(self.prefix))
from apache_beam.options.pipeline_options import PipelineOptions
options = PipelineOptions(["--runner=PortableRunner", "--job_endpoint=localhost:8099"])
p = beam.Pipeline(options=options)
(p | beam.Create([1, 2, 3, 4, 5]) | LogElements())
p.run()
This is how I run the job service:
gradle :runners:flink:1.8:job-server:runShadow -PflinkMasterUrl=localhost:8081
Docker is automatically selected for executing the Python harness.
I can change the image used to run the Python container:
options = PipelineOptions(["--runner=PortableRunner", "--job_endpoint=localhost:8099", "--environment_type=DOCKER", "--environment_config=beam/python:latest"])
I can disable Docker and enable the ExternalEnvironmentFactory:
options = PipelineOptions(["--runner=PortableRunner", "--job_endpoint=localhost:8099", "--environment_type=EXTERNAL", "--environment_config=server"])
but I have to implement some callback answering on http://server:80.
Is there an implementation available?
I found the solution. The new version of Apache Beam 2.16.0 provides an implementation to use in combination with environment type EXTERNAL. The implementation is based on worker_pool_main which has been created to support Kubernetes.