STEP-1 : Dockerコンテナ環境での Confluent Platform の追加構築
概要
Confluent Platform の「cp-all-in-one」 をベースにローカルのDockerコンテナ環境を構築し、IoTデータ生成Pythonプログラムから送信されるデータを Confluent でストリーミング処理し、InfluxDB+Grafanaでリアルタイム可視化できることを確認しました。該当する Sink Connector を使用しています。
以下の絵(の記事) の環境をベースに、
以下の3つのステップで上記内容を順次説明します。今回は STEP-1 について説明します。
STEP-1.Dockerコンテナ環境での Confluent Platform の追加構築
STEP-2.InfluxDBでのBrokerからのデータ受信確認
STEP-3.InfluxDB経由のGrafanaでのリアルタイムデータ可視化確認
ローカル環境
macOS Big Sur 11.3
python 3.8.3
Docker version 20.10.7, build f0df350 (CPUs:8, Memory:10GB, Swap:1GB)
作業ディレクトリへの移動
- ここ の環境をそのまま使用します。
- confluentinc/cp-all-in-one をクローンしたディレクトリ配下にある作業ディレクトリに移動します。
$ cd cp-all-in-one
$ cd cp-all-in-one
InfluxDB Sink Connector のインストール
- ConfluentのConnectorに「InfluxDB Sink Connector」をインストールするために DockerFileを編集します。
FROM confluentinc/cp-server-connect-base:6.0.0
RUN confluent-hub install --no-prompt confluentinc/kafka-connect-rabbitmq:latest
RUN confluent-hub install --no-prompt confluentinc/kafka-connect-influxdb:latest
2. ConnectorのDockerイメージをビルドします。
$ docker build -t cp-connect-base .
docker-compose.yml の再定義
- 作業ディレクトリにある「docker-compose.yml」を以下のように編集します。
サービス名 | 変更有無 | 内容 |
---|---|---|
zookeeper | 無 | |
broker | 無 | |
schema-registry | 無 | |
connect | 有 | 使用イメージ変更 |
control-center | 無 | |
ksqldb-server | 無 | |
ksqldb-cli | 無 | |
rabbitmq | 無 | |
influxdb | 有 | 新規追加 |
grafana | 有 | 新規追加 |
version: '2'
services:
zookeeper:
image: confluentinc/cp-zookeeper:6.0.0
hostname: zookeeper
container_name: zookeeper
ports:
- "2181:2181"
environment:
ZOOKEEPER_CLIENT_PORT: 2181
ZOOKEEPER_TICK_TIME: 2000
broker:
image: confluentinc/cp-server:6.0.0
hostname: broker
container_name: broker
depends_on:
- zookeeper
ports:
- "9092:9092"
- "9101:9101"
environment:
KAFKA_BROKER_ID: 1
KAFKA_ZOOKEEPER_CONNECT: 'zookeeper:2181'
KAFKA_LISTENER_SECURITY_PROTOCOL_MAP: PLAINTEXT:PLAINTEXT,PLAINTEXT_HOST:PLAINTEXT
KAFKA_ADVERTISED_LISTENERS: PLAINTEXT://broker:29092,PLAINTEXT_HOST://localhost:9092
KAFKA_METRIC_REPORTERS: io.confluent.metrics.reporter.ConfluentMetricsReporter
KAFKA_OFFSETS_TOPIC_REPLICATION_FACTOR: 1
KAFKA_GROUP_INITIAL_REBALANCE_DELAY_MS: 0
KAFKA_CONFLUENT_LICENSE_TOPIC_REPLICATION_FACTOR: 1
KAFKA_CONFLUENT_BALANCER_TOPIC_REPLICATION_FACTOR: 1
KAFKA_TRANSACTION_STATE_LOG_MIN_ISR: 1
KAFKA_TRANSACTION_STATE_LOG_REPLICATION_FACTOR: 1
KAFKA_JMX_PORT: 9101
KAFKA_JMX_HOSTNAME: localhost
KAFKA_CONFLUENT_SCHEMA_REGISTRY_URL: http://schema-registry:8081
CONFLUENT_METRICS_REPORTER_BOOTSTRAP_SERVERS: broker:29092
CONFLUENT_METRICS_REPORTER_TOPIC_REPLICAS: 1
CONFLUENT_METRICS_ENABLE: 'true'
CONFLUENT_SUPPORT_CUSTOMER_ID: 'anonymous'
schema-registry:
image: confluentinc/cp-schema-registry:6.0.0
hostname: schema-registry
container_name: schema-registry
depends_on:
- broker
ports:
- "8081:8081"
environment:
SCHEMA_REGISTRY_HOST_NAME: schema-registry
SCHEMA_REGISTRY_KAFKASTORE_BOOTSTRAP_SERVERS: 'broker:29092'
SCHEMA_REGISTRY_LISTENERS: http://0.0.0.0:8081
SCHEMA_REGISTRY_ACCESS_CONTROL_ALLOW_ORIGIN: '*'
SCHEMA_REGISTRY_ACCESS_CONTROL_ALLOW_METHODS: 'GET,POST,PUT,OPTIONS'
connect:
image: cp-connect-base:latest
hostname: connect
container_name: connect
depends_on:
- broker
- schema-registry
ports:
- "8083:8083"
environment:
CONNECT_BOOTSTRAP_SERVERS: 'broker:29092'
CONNECT_REST_ADVERTISED_HOST_NAME: connect
CONNECT_REST_PORT: 8083
CONNECT_GROUP_ID: compose-connect-group
CONNECT_CONFIG_STORAGE_TOPIC: docker-connect-configs
CONNECT_CONFIG_STORAGE_REPLICATION_FACTOR: 1
CONNECT_OFFSET_FLUSH_INTERVAL_MS: 10000
CONNECT_OFFSET_STORAGE_TOPIC: docker-connect-offsets
CONNECT_OFFSET_STORAGE_REPLICATION_FACTOR: 1
CONNECT_STATUS_STORAGE_TOPIC: docker-connect-status
CONNECT_STATUS_STORAGE_REPLICATION_FACTOR: 1
CONNECT_KEY_CONVERTER: org.apache.kafka.connect.storage.StringConverter
CONNECT_VALUE_CONVERTER: io.confluent.connect.avro.AvroConverter
CONNECT_VALUE_CONVERTER_SCHEMA_REGISTRY_URL: http://schema-registry:8081
CONNECT_INTERNAL_KEY_CONVERTER: "org.apache.kafka.connect.json.JsonConverter"
CONNECT_INTERNAL_VALUE_CONVERTER: "org.apache.kafka.connect.json.JsonConverter"
CLASSPATH: /usr/share/java/monitoring-interceptors/monitoring-interceptors-6.0.0.jar
CONNECT_PRODUCER_INTERCEPTOR_CLASSES: "io.confluent.monitoring.clients.interceptor.MonitoringProducerInterceptor"
CONNECT_CONSUMER_INTERCEPTOR_CLASSES: "io.confluent.monitoring.clients.interceptor.MonitoringConsumerInterceptor"
CONNECT_PLUGIN_PATH: "/usr/share/java,/usr/share/confluent-hub-components"
CONNECT_LOG4J_ROOT_LOGLEVEL: "INFO"
CONNECT_LOG4J_LOGGERS: org.apache.zookeeper=ERROR,org.I0Itec.zkclient=ERROR,org.org.apache.kafka.connect.runtime.rest=WARN,reflections=ERROR
CONNECT_HOST: connect
control-center:
image: confluentinc/cp-enterprise-control-center:6.0.0
hostname: control-center
container_name: control-center
depends_on:
- broker
- schema-registry
- connect
- ksqldb-server
ports:
- "9021:9021"
environment:
CONTROL_CENTER_BOOTSTRAP_SERVERS: 'broker:29092'
CONTROL_CENTER_CONNECT_CLUSTER: 'connect:8083'
CONTROL_CENTER_KSQL_KSQLDB1_URL: "http://ksqldb-server:8088"
CONTROL_CENTER_KSQL_KSQLDB1_ADVERTISED_URL: "http://localhost:8088"
CONTROL_CENTER_SCHEMA_REGISTRY_URL: "http://schema-registry:8081"
CONTROL_CENTER_REPLICATION_FACTOR: 1
CONTROL_CENTER_INTERNAL_TOPICS_PARTITIONS: 1
CONTROL_CENTER_MONITORING_INTERCEPTOR_TOPIC_PARTITIONS: 1
CONFLUENT_METRICS_TOPIC_REPLICATION: 1
PORT: 9021
ksqldb-server:
image: confluentinc/cp-ksqldb-server:6.0.0
hostname: ksqldb-server
container_name: ksqldb-server
depends_on:
- broker
- connect
ports:
- "8088:8088"
environment:
KSQL_CONFIG_DIR: "/etc/ksql"
KSQL_BOOTSTRAP_SERVERS: "broker:29092"
KSQL_HOST_NAME: ksqldb-server
KSQL_LISTENERS: "http://0.0.0.0:8088"
KSQL_CACHE_MAX_BYTES_BUFFERING: 0
KSQL_KSQL_SCHEMA_REGISTRY_URL: "http://schema-registry:8081"
KSQL_PRODUCER_INTERCEPTOR_CLASSES: "io.confluent.monitoring.clients.interceptor.MonitoringProducerInterceptor"
KSQL_CONSUMER_INTERCEPTOR_CLASSES: "io.confluent.monitoring.clients.interceptor.MonitoringConsumerInterceptor"
KSQL_KSQL_CONNECT_URL: "http://connect:8083"
KSQL_KSQL_LOGGING_PROCESSING_TOPIC_REPLICATION_FACTOR: 1
KSQL_KSQL_LOGGING_PROCESSING_TOPIC_AUTO_CREATE: 'true'
KSQL_KSQL_LOGGING_PROCESSING_STREAM_AUTO_CREATE: 'true'
KSQL_AUTO_OFFSET_RESET: "latest"
ksqldb-cli:
image: confluentinc/cp-ksqldb-cli:6.0.0
container_name: ksqldb-cli
depends_on:
- broker
- connect
- ksqldb-server
entrypoint: /bin/sh
tty: true
rabbitmq:
image: rabbitmq:3.8.17-management
restart: always
ports:
- '5672:5672'
- '15672:15672'
hostname: rabbitmq
container_name: rabbitmq
environment:
RABBITMQ_DEFAULT_USER: guest
RABBITMQ_DEFAULT_PASS: guest
influxdb:
image: influxdb:1.8.6
ports:
- 8086:8086
hostname: influxdb
container_name: influxdb
grafana:
image: grafana/grafana
ports:
- 3000:3000
hostname: grafana
container_name: grafana
environment:
- GF_SERVER_ROOT_URL=http://grafana:3000
- GF_INSTALL_PLUGINS=grafana-polystat-panel,bessler-pictureit-panel,marcuscalidus-svg-panel
- GF_SECURITY_ADMIN_PASSWORD=admin
depends_on:
- influxdb
Confluent Platform の起動
- -d オプションを使用して Confluent Platform を起動し、デタッチモードで実行します。
$ docker-compose up -d
2. サービスが稼働状態であることを確認します。
$ docker-compose ps
Name Command State Ports
------------------------------------------------------------------------------------------------------------------------
broker /etc/confluent/docker/run Up 0.0.0.0:9092->9092/tcp,:::9092->9092/tcp,
0.0.0.0:9101->9101/tcp,:::9101->9101/tcp
connect /etc/confluent/docker/run Up 0.0.0.0:8083->8083/tcp,:::8083->8083/tcp, 9092/tcp
control-center /etc/confluent/docker/run Up 0.0.0.0:9021->9021/tcp,:::9021->9021/tcp
grafana /run.sh Up 0.0.0.0:3000->3000/tcp,:::3000->3000/tcp
influxdb /entrypoint.sh influxd Up 0.0.0.0:8086->8086/tcp,:::8086->8086/tcp
ksqldb-cli /bin/sh Up
ksqldb-server /etc/confluent/docker/run Up 0.0.0.0:8088->8088/tcp,:::8088->8088/tcp
rabbitmq docker-entrypoint.sh rabbi ... Up 15671/tcp, 0.0.0.0:15672->15672/tcp,:::15672->15672/tcp,
15691/tcp, 15692/tcp, 25672/tcp, 4369/tcp, 5671/tcp,
0.0.0.0:5672->5672/tcp,:::5672->5672/tcp
schema-registry /etc/confluent/docker/run Up 0.0.0.0:8081->8081/tcp,:::8081->8081/tcp
zookeeper /etc/confluent/docker/run Up 0.0.0.0:2181->2181/tcp,:::2181->2181/tcp, 2888/tcp, 3888/tcp
3. Connectorも稼働状態であることを確認します。
$ curl http://localhost:8083/connector-plugins | jq
% Total % Received % Xferd Average Speed Time Time Time Current
Dload Upload Total Spent Left Speed
100 793 100 793 0 0 14962 0 --:--:-- --:--:-- --:--:-- 14962
[
{
"class": "io.confluent.connect.rabbitmq.RabbitMQSourceConnector",
"type": "source",
"version": "0.0.0.0"
},
{
"class": "io.confluent.influxdb.InfluxDBSinkConnector",
"type": "sink",
"version": "unknown"
},
{
"class": "io.confluent.influxdb.source.InfluxdbSourceConnector",
"type": "source",
"version": "1.2.1"
},
{
"class": "org.apache.kafka.connect.file.FileStreamSinkConnector",
"type": "sink",
"version": "6.0.0-ce"
},
{
"class": "org.apache.kafka.connect.file.FileStreamSourceConnector",
"type": "source",
"version": "6.0.0-ce"
},
{
"class": "org.apache.kafka.connect.mirror.MirrorCheckpointConnector",
"type": "source",
"version": "1"
},
{
"class": "org.apache.kafka.connect.mirror.MirrorHeartbeatConnector",
"type": "source",
"version": "1"
},
{
"class": "org.apache.kafka.connect.mirror.MirrorSourceConnector",
"type": "source",
"version": "1"
}
]
これで正常にDockerコンテナ環境下で Confluent Platform の稼働が確認できました。
次のステップでは、IoTデータ生成プログラムからデータを送信し、Brokerのトピック経由でInfluxDBでデータ受信できることを確認してみます。
本課題のステップ情報
STEP-1.Dockerコンテナ環境での Confluent Platform の追加構築
STEP-2.InfluxDBでのBrokerからのデータ受信確認
STEP-3.InfluxDB経由のGrafanaでのリアルタイムデータ可視化確認