mongodb - 将 dockerized kafka 接收器连接器实现到 mongo

标签 mongodb docker apache-kafka apache-kafka-connect

我正在尝试使用 docker 实现与 mongodb 和 mysql 的 kafka 连接。

我要的是下图:

Kafka connect as sink to MongoDB and MySQL

Kafka 连接 MongoDB:

我看过official mongodb repository的docker-compose .它有两个问题:

  1. 它对于我的目的来说太复杂了。因为跑了多个mongodb的容器，也用了很多镜像，消耗了这么多资源。

  2. 它有一些 Unresolved 问题，最终导致 kafka 与 mongodb 的连接出现故障。 Here你可以看到我的问题。

我在 docker-compose.yml 中使用 debezium 进行连接的实现如下:

version: '3.2'
services:
  kafka:
    image: wurstmeister/kafka:latest
    ports:
      - target: 9094
        published: 9094
        protocol: tcp
        mode: host
    environment:
      KAFKA_ZOOKEEPER_CONNECT: zookeeper:2181
      KAFKA_LISTENER_SECURITY_PROTOCOL_MAP: INSIDE:PLAINTEXT,OUTSIDE:PLAINTEXT
      KAFKA_ADVERTISED_LISTENERS: INSIDE://:9092
      KAFKA_LISTENERS: INSIDE://:9092,OUTSIDE://:9094
      KAFKA_INTER_BROKER_LISTENER_NAME: INSIDE
      KAFKA_LOG_DIRS: /kafka/logs
    volumes:
      - /var/run/docker.sock:/var/run/docker.sock
      - kafka:/kafka

  zookeeper:
    image: wurstmeister/zookeeper
    ports:
      - "2181:2181"
    volumes:
      - zookeeper:/opt/zookeeper-3.4.13

  mongo:
    image: mongo
    container_name: mongo
    ports:
      - 27017:27017

  connect:
    image: debezium/connect
    container_name: connect
    ports:
      - 8083:8083
    environment:
      - BOOTSTRAP_SERVERS=kafka:9092
      - GROUP_ID=1
      - CONFIG_STORAGE_TOPIC=my_connect_configs
      - OFFSET_STORAGE_TOPIC=my_connect_offsets

volumes:
  kafka:
  zookeeper:

正如@cricket_007 所说，我不应该将 debezium 用于我的目的。所以我使用了 confluentinc/kafka-connect-datagen 图像。在这里，我将以下内容添加到 docker-compose.yml 文件中，而不是 debezium:

connect:
    image: confluentinc/kafka-connect-datagen
    build:
      context: .
      dockerfile: Dockerfile
    hostname: connect
    container_name: connect
    depends_on: 
      - zookeeper
    ports: 
      - 8083:8083
    environment: 
      CONNECT_BOOTSTRAP_SERVERS: 'kafka:9092'
      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: io.confluent.connect.avro.AvroConverter
      CONNECT_VALUE_CONVERTER: io.confluent.connect.avro.AvroConverter
      CONNECT_INTERNAL_KEY_CONVERTER: "org.apache.kafka.connect.json.JsonConverter"
      CONNECT_INTERNAL_VALUE_CONVERTER: "org.apache.kafka.connect.json.JsonConverter"
      CONNECT_LOG4J_ROOT_LOGLEVEL: "INFO"
      CONNECT_PLUGIN_PATH: /usr/share/confluent-hub-components
      CONNECT_ZOOKEEPER_CONNECT: 'zookeeper:2181'
      # Assumes image is based on confluentinc/kafka-connect-datagen:latest which is pulling 5.2.2 Connect image
      CLASSPATH: /usr/share/java/monitoring-interceptors/monitoring-interceptors-5.2.2.jar
      CONNECT_PRODUCER_INTERCEPTOR_CLASSES: "io.confluent.monitoring.clients.interceptor.MonitoringProducerInterceptor"
      CONNECT_CONSUMER_INTERCEPTOR_CLASSES: "io.confluent.monitoring.clients.interceptor.MonitoringConsumerInterceptor"
    command: "bash -c 'if [ ! -d /usr/share/confluent-hub-components/confluentinc-kafka-connect-datagen ]; then echo \"WARNING: Did not find directory for kafka-connect-datagen (did you remember to run: docker-compose up -d --build ?)\"; fi ; /etc/confluent/docker/run'"
    volumes:
      - ../build/confluent/kafka-connect-mongodb:/usr/share/confluent-hub-components/kafka-connect-mongodb

docker 文件:

FROM confluentinc/cp-kafka-connect
ENV CONNECT_PLUGIN_PATH="/usr/share/java,/usr/share/confluent-hub-components"
RUN  confluent-hub install --no-prompt confluentinc/kafka-connect-datagen

问题:

  1. Kafka-connect-datagen 图像生成假数据，正如它在 the repository 中提到的那样，它不适合生产。我想要的只是将 Kafka 连接到 mongodb，不多于它。明确地说，我如何使用 curl 从 kafka 发送数据并将它们保存在 mongodb 集合中？

  2. 我遇到了 CONNECT_KEY_CONVERTER_SCHEMA_REGISTRY_URL is required. 错误。正如@cricket_007 所说，schema-registry 是可选的。那么我怎样才能摆脱那个形象呢？

  3. 在最后一步，我尝试按照 README.md 中的说明运行存储库的 docker-compose 文件，不幸的是我遇到了另一个错误:

    WARNING: Could not reach configured kafka system on http://localhost:8083 Note: This script requires curl.

  4. 每当我没有对配置进行任何更改时，我都会遇到另一个错误:

Kafka Connectors: 

{"error_code":409,"message":"Cannot complete request momentarily due to stale configuration (typically caused by a concurrent config change)"}

请帮助我找到问题的答案。

我的输出:

Building the MongoDB Kafka Connector

> Task :shadowJar
FatJar: /home/mostafa/Documents/Docker/kafka-mongo/build/libs/kafka-mongo-0.3-SNAPSHOT-all.jar (2.108904 MB)

Deprecated Gradle features were used in this build, making it incompatible with Gradle 6.0.
Use '--warning-mode all' to show the individual deprecation warnings.
See https://docs.gradle.org/5.2/userguide/command_line_interface.html#sec:command_line_warnings

BUILD SUCCESSFUL in 4h 26m 25s
7 actionable tasks: 7 executed
Unzipping the confluent archive plugin....

Archive:  ./build/confluent/mongodb-kafka-connect-mongodb-0.3-SNAPSHOT.zip
   creating: ./build/confluent/mongodb-kafka-connect-mongodb-0.3-SNAPSHOT/
   creating: ./build/confluent/mongodb-kafka-connect-mongodb-0.3-SNAPSHOT/etc/
  inflating: ./build/confluent/mongodb-kafka-connect-mongodb-0.3-SNAPSHOT/etc/MongoSinkConnector.properties  
  inflating: ./build/confluent/mongodb-kafka-connect-mongodb-0.3-SNAPSHOT/etc/MongoSourceConnector.properties  
   creating: ./build/confluent/mongodb-kafka-connect-mongodb-0.3-SNAPSHOT/lib/
  inflating: ./build/confluent/mongodb-kafka-connect-mongodb-0.3-SNAPSHOT/lib/kafka-mongo-0.3-SNAPSHOT-all.jar  
  inflating: ./build/confluent/mongodb-kafka-connect-mongodb-0.3-SNAPSHOT/manifest.json  
   creating: ./build/confluent/mongodb-kafka-connect-mongodb-0.3-SNAPSHOT/assets/
  inflating: ./build/confluent/mongodb-kafka-connect-mongodb-0.3-SNAPSHOT/assets/mongodb-leaf.png  
  inflating: ./build/confluent/mongodb-kafka-connect-mongodb-0.3-SNAPSHOT/assets/mongodb-logo.png  
   creating: ./build/confluent/mongodb-kafka-connect-mongodb-0.3-SNAPSHOT/doc/
  inflating: ./build/confluent/mongodb-kafka-connect-mongodb-0.3-SNAPSHOT/doc/README.md  
  inflating: ./build/confluent/mongodb-kafka-connect-mongodb-0.3-SNAPSHOT/doc/LICENSE.txt  
Starting docker .
Creating volume "docker_rs2" with default driver
Creating volume "docker_rs3" with default driver
Building connect
Step 1/3 : FROM confluentinc/cp-kafka-connect:5.2.2
 ---> 32bb41f78617
Step 2/3 : ENV CONNECT_PLUGIN_PATH="/usr/share/confluent-hub-components"
 ---> Using cache
 ---> 9e4fd4f10a38
Step 3/3 : RUN  confluent-hub install --no-prompt confluentinc/kafka-connect-datagen:latest
 ---> Using cache
 ---> 5f879008bb73

Successfully built 5f879008bb73
Successfully tagged confluentinc/kafka-connect-datagen:latest
Recreating mongo1 ... 
Recreating mongo1        ... done
Creating mongo3          ... done
Starting broker   ... done
Creating mongo2          ... done
Starting schema-registry ... done
Starting connect         ... done
Creating rest-proxy      ... done
Creating ksql-server              ... done
Creating docker_kafka-topics-ui_1 ... done
Creating control-center           ... done
Creating ksql-cli                 ... done


Waiting for the systems to be ready.............
WARNING: Could not reach configured kafka system on http://localhost:8082 
Note: This script requires curl.



SHUTTING DOWN


  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
                                 Dload  Upload   Total   Spent    Left  Speed
100    68  100    68    0     0     23      0  0:00:02  0:00:02 --:--:--    23
  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
                                 Dload  Upload   Total   Spent    Left  Speed
100    61  100    61    0     0   4066      0 --:--:-- --:--:-- --:--:--  4066
  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
                                 Dload  Upload   Total   Spent    Left  Speed
100    63  100    63    0     0   9000      0 --:--:-- --:--:-- --:--:--  9000
MongoDB shell version v4.0.12
connecting to: mongodb://127.0.0.1:27017/?gssapiServiceName=mongodb
Implicit session: session { "id" : UUID("80ebb904-f81a-4230-b63b-4e62f65fbeb7") }
MongoDB server version: 4.0.12
{
        "ok" : 1,
        "operationTime" : Timestamp(1567235833, 1),
        "$clusterTime" : {
                "clusterTime" : Timestamp(1567235833, 1),
                "signature" : {
                        "hash" : BinData(0,"AAAAAAAAAAAAAAAAAAAAAAAAAAA="),
                        "keyId" : NumberLong(0)
                }
        }
}
Stopping ksql-cli                 ... done
Stopping control-center           ... done
Stopping docker_kafka-topics-ui_1 ... done
Stopping ksql-server              ... done
Stopping rest-proxy               ... done
Stopping mongo1                   ... done
Stopping mongo2                   ... done
Stopping mongo3                   ... done
Stopping connect                  ... done
Stopping broker                   ... done
Stopping zookeeper                ... done
Removing ksql-cli                 ... 
Removing control-center           ... done
Removing docker_kafka-topics-ui_1 ... done
Removing ksql-server              ... done
Removing rest-proxy               ... done
Removing mongo1                   ... done
Removing mongo2                   ... done
Removing mongo3                   ... done
Removing connect                  ... done
Removing schema-registry          ... done
Removing broker                   ... done
Removing zookeeper                ... done
Removing network docker_default
Removing network docker_localnet

WARNING: Could not reach configured kafka system on http://localhost:8082 
Note: This script requires curl.

最佳答案

我创建了以下 docker-compose 文件(查看 GitHub 中的所有文件):

version: '3.6'
services:
  zookeeper:
    image: confluentinc/cp-zookeeper:5.1.2
    hostname: zookeeper
    container_name: zookeeper
    ports:
      - "2181:2181"
    networks:
      - localnet
    environment:
      ZOOKEEPER_CLIENT_PORT: 2181
      ZOOKEEPER_TICK_TIME: 2000

  broker:
    image: confluentinc/cp-enterprise-kafka:5.1.2
    hostname: broker
    container_name: broker
    depends_on:
      - zookeeper
    ports:
      - "29092:29092"
      - "9092:9092"
    networks:
      - localnet
    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
      CONFLUENT_METRICS_REPORTER_BOOTSTRAP_SERVERS: broker:29092
      CONFLUENT_METRICS_REPORTER_ZOOKEEPER_CONNECT: zookeeper:2181
      CONFLUENT_METRICS_REPORTER_TOPIC_REPLICAS: 1
      CONFLUENT_METRICS_ENABLE: 'true'
      CONFLUENT_SUPPORT_CUSTOMER_ID: 'anonymous'

  connect:
    image: confluentinc/cp-kafka-connect:5.1.2
    build:
      context: .
      dockerfile: Dockerfile
    hostname: connect
    container_name: connect
    depends_on:
      - zookeeper
      - broker
    ports:
      - "8083:8083"
    networks:
      - localnet
    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.json.JsonConverter
      CONNECT_VALUE_CONVERTER: org.apache.kafka.connect.json.JsonConverter
      CONNECT_INTERNAL_KEY_CONVERTER: "org.apache.kafka.connect.json.JsonConverter"
      CONNECT_INTERNAL_VALUE_CONVERTER: "org.apache.kafka.connect.json.JsonConverter"
      CONNECT_LOG4J_ROOT_LOGLEVEL: "INFO"
      CONNECT_LOG4J_LOGGERS: "org.apache.kafka.connect.runtime.rest=WARN,org.reflections=ERROR,com.mongodb.kafka=DEBUG"
      CONNECT_PLUGIN_PATH: /usr/share/confluent-hub-components
      CONNECT_ZOOKEEPER_CONNECT: 'zookeeper:2181'
      # Assumes image is based on confluentinc/kafka-connect-datagen:latest which is pulling 5.2.2 Connect image
      CLASSPATH: /usr/share/java/monitoring-interceptors/monitoring-interceptors-5.2.2.jar
      CONNECT_PRODUCER_INTERCEPTOR_CLASSES: "io.confluent.monitoring.clients.interceptor.MonitoringProducerInterceptor"
      CONNECT_CONSUMER_INTERCEPTOR_CLASSES: "io.confluent.monitoring.clients.interceptor.MonitoringConsumerInterceptor"
    command: "bash -c 'if [ ! -d /usr/share/confluent-hub-components/confluentinc-kafka-connect-datagen ]; then echo \"WARNING: Did not find directory for kafka-connect-datagen (did you remember to run: docker-compose up -d --build ?)\"; fi ; /etc/confluent/docker/run'"
    volumes:
      - ./kafka-connect-mongodb:/usr/share/confluent-hub-components/kafka-connect-mongodb

# MongoDB Replica Set
  mongo1:
    image: "mongo:4.0-xenial"
    container_name: mongo1
    command: --replSet rs0 --smallfiles --oplogSize 128
    volumes:
      - rs1:/data/db
    networks:
      - localnet
    ports:
      - "27017:27017"
    restart: always
  mongo2:
    image: "mongo:4.0-xenial"
    container_name: mongo2
    command: --replSet rs0 --smallfiles --oplogSize 128
    volumes:
      - rs2:/data/db
    networks:
      - localnet
    ports:
      - "27018:27017"
    restart: always
  mongo3:
    image: "mongo:4.0-xenial"
    container_name: mongo3
    command: --replSet rs0 --smallfiles --oplogSize 128
    volumes:
      - rs3:/data/db
    networks:
      - localnet
    ports:
      - "27019:27017"
    restart: always

networks:
  localnet:
    attachable: true

volumes:
  rs1:
  rs2:
  rs3:

执行 docker-compose up 后，您必须配置您的 MongoDB 集群:

docker-compose exec mongo1 /usr/bin/mongo --eval '''if (rs.status()["ok"] == 0) {
    rsconf = {
      _id : "rs0",
      members: [
        { _id : 0, host : "mongo1:27017", priority: 1.0 },
        { _id : 1, host : "mongo2:27017", priority: 0.5 },
        { _id : 2, host : "mongo3:27017", priority: 0.5 }
      ]
    };
    rs.initiate(rsconf);
}
rs.conf();'''

确保您的插件已安装:

curl localhost:8083/connector-plugins | jq

[
  {
    "class": "com.mongodb.kafka.connect.MongoSinkConnector",
    "type": "sink",
    "version": "0.2"
  },
  {
    "class": "com.mongodb.kafka.connect.MongoSourceConnector",
    "type": "source",
    "version": "0.2"
  },
  {
    "class": "io.confluent.connect.gcs.GcsSinkConnector",
    "type": "sink",
    "version": "5.0.1"
  },
  {
    "class": "io.confluent.connect.storage.tools.SchemaSourceConnector",
    "type": "source",
    "version": "2.1.1-cp1"
  },
  {
    "class": "org.apache.kafka.connect.file.FileStreamSinkConnector",
    "type": "sink",
    "version": "2.1.1-cp1"
  },
  {
    "class": "org.apache.kafka.connect.file.FileStreamSourceConnector",
    "type": "source",
    "version": "2.1.1-cp1"
  }
]

正如您在上面看到的，MongoDB 连接器插件可供使用。假设您有一个名为 mydb 的数据库和一个名为 products 的集合，我创建了一个名为 sink-connector.json 的 JSON 文件:

{
    "name": "mongo-sink",
    "config": {
        "connector.class": "com.mongodb.kafka.connect.MongoSinkConnector",
        "tasks.max": "1",
        "topics": "product.events",
        "connection.uri": "mongodb://mongo1:27017,mongo2:27017,mongo3:27017",
        "database": "mydb",
        "collection": "products",
        "key.converter": "org.apache.kafka.connect.storage.StringConverter",
        "value.converter": "org.apache.kafka.connect.json.JsonConverter",
        "value.converter.schemas.enable": "false"
    }
}

现在使用连接 RESTful API 创建连接器:

curl -X POST -H "Content-Type: application/json" -d @sink-connector.json http://localhost:8083/connectors | jq

您可以查看连接器的状态:

curl http://localhost:8083/connectors/mongo-sink/status | jq
    {
"name": "mongo-sink",
"connector": {
    "state": "RUNNING",
    "worker_id": "connect:8083"
},
"tasks": [
    {
    "id": 0,
    "state": "RUNNING",
    "worker_id": "connect:8083"
    }
],
"type": "sink"
}

现在让我们创建一个 Kafka 主题。首先，我们必须连接到 Kafka 容器:

docker-compose exec broker bash

然后创建主题:

kafka-topics --zookeeper zookeeper:2181 --create --topic product.events --partitions 1 --replication-factor 1

现在生产产品进入主题:

kafka-console-producer --broker-list localhost:9092 --topic product.events
>{"Name": "Hat", "Price": 25}
>{"Name": "Shoe", "Price": 15}

您可以在图像中查看结果: enter image description here

希望对您有所帮助。

关于mongodb - 将 dockerized kafka 接收器连接器实现到 mongo，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/57544201/

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