Version: 0.13.0

Run Stateful Functions

To run Java or Python stateful functions in Function Mesh, you need to package the function and then submit the package to a Pulsar cluster.

Prerequisites

Apache Pulsar v2.8.0 or higher
Function Mesh v0.2.0 or higher

Package Stateful Functions

This section describes how to package Java and Python Stateful functions.

Java Stateful Functions

For details, see package Java Functions.

Python Stateful Functions

For details, see package Python Functions.

Submit Stateful Functions

After packaging a stateful function, you can submit it to a Pulsar cluster. This section describes how to submit Java and Python Stateful functions.

Enable BookKeeper table service

Before submitting a stateful function, you need to enable the Apache BookKeeper table service. This section describes how to enable the BookKeeper table service.

Currently, the BookKeeper table service uses the NAR package, so you need to set the configuration in the bookkeeper.conf configuration file.

##################################################################
##################################################################
# stream/table service settings
##################################################################
##################################################################

### gRPC Server ###

# The gRPC server port to listen on. The default is 4181.
storageserver.grpc.port=4181

### Dlog settings for the BookKeeper table service ###

#### Replication Settings
dlog.bkcEnsembleSize=3
dlog.bkcWriteQuorumSize=2
dlog.bkcAckQuorumSize=2

### Storage ###

# The local storage directories for storing table range data (For example, the RocksDB Sorted String Table (SST)  files).
storage.range.store.dirs=data/bookkeeper/ranges

# Specify whether the storage server supports serving read-only tables. The default is false.
storage.serve.readonly.tables=false

# The cluster controller schedule interval, in milliseconds. The default is 30 seconds.
storage.cluster.controller.schedule.interval.ms=30000

You can apply the above configurations to your Kubernetes environment as follows.

Update the BookKeeper configuration file.

In the namespace (${PULSAR_NAMESPACE}) where the Pulsar cluster is installed, find and edit the ConfigMap resource that is named ${PULSAR_RELEASE_NAME}-pulsar-bookie. ${PULSAR_RELEASE_NAME} is the release name when the Pulsar cluster is installed using the Helm chart).

kubectl edit -n ${PULSAR_NAMESPACE} ${PULSAR_RELEASE_NAME}-pulsar-bookie

Insert the configurations in the following location.

apiVersion: v1
data:
  # <Place your configurations here>
  BOOKIE_MEM: |
    -Xms128m -Xmx256m -XX:MaxDirectMemorySize=256m
  PULSAR_GC: |
    -XX:+UseG1GC -XX:MaxGCPauseMillis=10 -XX:+ParallelRefProcEnabled -XX:+UnlockExperimentalVMOptions -XX:+AggressiveOpts -XX:+DoEscapeAnalysis -XX:ParallelGCThreads=4 -XX:ConcGCThreads=4 -XX:G1NewSizePercent=50 -XX:+DisableExplicitGC -XX:-ResizePLAB -XX:+ExitOnOutOfMemoryError -XX:+PerfDisableSharedMem
  PULSAR_MEM: |
    -Xms128m -Xmx256m -XX:MaxDirectMemorySize=256m
  PULSAR_PREFIX_autoRecoveryDaemonEnabled: "false"
  extraServerComponents: org.apache.bookkeeper.stream.server.StreamStorageLifecycleComponent
  httpServerEnabled: "true"
  httpServerPort: "8000"
  journalDirectories: /pulsar/data/bookkeeper/journal
  journalMaxBackups: "0"
  ledgerDirectories: /pulsar/data/bookkeeper/ledgers
  ...

It will be like this in the end.

Note
You need to add the PULSAR_PREFIX_ prefix to each added parameter.
dlog.bkcEnsembleSize should be the same as the number of replicas of the BookKeeper table service.
The value of dlog.bkcAckQuorumSize and dlog.bkcWriteQuorumSize cannot be greater than the value of dlog.bkcEnsembleSize.
By default you can ignore the storageserver.grpc.port, storage.range.store.dirs, storage.serve.readonly.tables, and storage.cluster.controller.schedule.interval.ms configurations.

apiVersion: v1
data:
  PULSAR_PREFIX_storage.cluster.controller.schedule.interval.ms: "30000"
  PULSAR_PREFIX_storage.serve.readonly.tables: "false"
  PULSAR_PREFIX_storage.range.store.dirs: /pulsar/data/bookkeeper/ranges
  PULSAR_PREFIX_storageserver.grpc.port: "4181"
  PULSAR_PREFIX_dlog.bkcAckQuorumSize: "2"
  PULSAR_PREFIX_dlog.bkcEnsembleSize: "3"
  PULSAR_PREFIX_dlog.bkcWriteQuorumSize: "2"
  BOOKIE_MEM: |
    -Xms128m -Xmx256m -XX:MaxDirectMemorySize=256m
  PULSAR_GC: |
    -XX:+UseG1GC -XX:MaxGCPauseMillis=10 -XX:+ParallelRefProcEnabled -XX:+UnlockExperimentalVMOptions -XX:+AggressiveOpts -XX:+DoEscapeAnalysis -XX:ParallelGCThreads=4 -XX:ConcGCThreads=4 -XX:G1NewSizePercent=50 -XX:+DisableExplicitGC -XX:-ResizePLAB -XX:+ExitOnOutOfMemoryError -XX:+PerfDisableSharedMem
  PULSAR_MEM: |
    -Xms128m -Xmx256m -XX:MaxDirectMemorySize=256m
  PULSAR_PREFIX_autoRecoveryDaemonEnabled: "false"
  extraServerComponents: org.apache.bookkeeper.stream.server.StreamStorageLifecycleComponent
  httpServerEnabled: "true"
  httpServerPort: "8000"
  journalDirectories: /pulsar/data/bookkeeper/journal
  journalMaxBackups: "0"
  ledgerDirectories: /pulsar/data/bookkeeper/ledgers
  ...

Restart the BookKeeper table service to make the configurations work.

kubectl rollout restart statefulset -n ${PULSAR_NAMESPACE} ${PULSAR_RELEASE_NAME}-pulsar-bookie 

Verify whether the BookKeeper table service is enabled successfully.

After starting the bookie, execute the following command.

kubectl exec -it -n ${PULSAR_NAMESPACE} ${PULSAR_RELEASE_NAME}-pulsar-bookie-0 -- nc -zv 127.0.0.1 4181

The output is something like this:

Connection to 127.0.0.1 4181 port [tcp/*] succeeded!

Submit Java Stateful Functions

This section describes how to submit a Java stateful function through a function CRD.

Define a Java stateful function and specify the statefulConfig.pulsar.serviceUrl option in a YAML file.

This example shows how to publish a java-function-stateful-sample stateful function to a Pulsar cluster by using a Docker image. You can use the spec.image field to specify the runner image for creating the Java stateful function.

apiVersion: compute.functionmesh.io/v1alpha1
kind: Function
metadata:
  name: java-function-stateful-sample
  namespace: default
spec:
  className: org.apache.pulsar.functions.api.examples.WordCountFunction
  forwardSourceMessageProperty: true
  maxPendingAsyncRequests: 1000
  replicas: 1
  maxReplicas: 5
  logTopic: persistent://public/default/logging-function-logs
  input:
    topics:
    - persistent://public/default/java-function-stateful-input-topic
    typeClassName: java.lang.String
  output:
    topic: persistent://public/default/java-function-stateful-output-topic
    typeClassName: java.lang.String
  resources:
    requests:
      cpu: "0.1"
      memory: 1G
    limits:
      cpu: "0.2"
      memory: 1.1G
  pulsar:
    pulsarConfig: "test-pulsar"
  java:
    jar: pulsar-functions-api-examples.jar
    jarLocation: public/default/nlu-test-java-function
    extraDependenciesDir: random-dir/
  clusterName: test-pulsar
  autoAck: true
  statefulConfig:
    pulsar:
      serviceUrl: "bk://test-pulsar-bookie.default.svc.cluster.local:4181"
---
apiVersion: v1
kind: ConfigMap
metadata:
  name: test-pulsar
data:
  webServiceURL: http://test-pulsar-broker.default.svc.cluster.local:8080
  brokerServiceURL: pulsar://test-pulsar-broker.default.svc.cluster.local:6650

Apply the YAML file to create the Java stateful function.
```
kubectl apply -f /path/to/YAML/file
```
Check whether the Java stateful function is created successfully.
```
kubectl get all
```

Submit Python Stateful Functions

This section describes how to submit a Python stateful function through a function CRD.

Define a Python stateful function and specify the statefulConfig.pulsar.serviceUrl option in a YAML file.

This example shows how to publish a python-function-stateful-sample stateful function to a Pulsar cluster by using a Docker image. You can use the spec.image field to specify the runner image for creating the Python stateful function.

apiVersion: compute.functionmesh.io/v1alpha1
kind: Function
metadata:
  name: python-function-stateful-sample
  namespace: default
spec:
  className: wordcount_function.WordCountFunction
  forwardSourceMessageProperty: true
  maxPendingAsyncRequests: 1000
  replicas: 1
  maxReplicas: 5
  logTopic: persistent://public/default/logging-function-logs
  input:
    topics:
    - persistent://public/default/python-function-stateful-input-topic
    typeClassName: java.lang.String
  output:
    topic: persistent://public/default/python-function-stateful-output-topic
    typeClassName: java.lang.String
  resources:
    requests:
      cpu: "0.1"
      memory: 1G
    limits:
      cpu: "0.2"
      memory: 1.1G
  pulsar:
    pulsarConfig: "test-pulsar"
  java:
    py: wordcount_function.py
    pyLocation: public/default/test-python-function
    extraDependenciesDir: random-dir/
  clusterName: test-pulsar
  autoAck: true
  statefulConfig:
    pulsar:
      serviceUrl: "bk://test-pulsar-bookie.default.svc.cluster.local:4181"
---
apiVersion: v1
kind: ConfigMap
metadata:
  name: test-pulsar
data:
  webServiceURL: http://test-pulsar-broker.default.svc.cluster.local:8080
  brokerServiceURL: pulsar://test-pulsar-broker.default.svc.cluster.local:6650

Apply the YAML file to create the Python stateful function.
```
kubectl apply -f /path/to/YAML/file
```
Check whether the Python stateful function is created successfully.
```
kubectl get all
```

Prerequisites​

Package Stateful Functions​

Java Stateful Functions​

Python Stateful Functions​

Submit Stateful Functions​

Enable BookKeeper table service​

Submit Java Stateful Functions​

Submit Python Stateful Functions​