HTTP接口数据也能定时同步入湖？用DolphinScheduler×SeaTunnel快速搞定！

背景与目标

我们之前曾评估使用过SeaTunnel做CDC入湖验证：SeaTunnel-CDC入湖实践，这些场景都是能直连数据库的场景，业务需求中经常会出现无法直连数据库做CDC进行数据同步的场景，而这些场景就需要使用API进行数据对接，用Apache DolphinScheduler定时同步数据。

举个实际中的例子：

• ERP（SAP）的库存数据进行同步入湖仓做库存分析

同时，本次目标希望其他同事能依样画葫芦，在以后的对接http接口到湖仓的时候能够自行完成，而非每遇到一个对接需求，就需要通过代码方式进行对接。

准备工作

• seatunnel 2.3.10

首先，您需要在${SEATUNNEL_HOME}/config/plugin_config文件中加入连接器名称，然后，执行命令来安装连接器,确认连接器在${SEATUNNEL_HOME}/connectors/目录下即可。

本例中我们会用到：connector-jdbc、connector-paimon

写入StarRocks也可以使用connector-starrocks，本例中的场景比较适合用connector-jdbc，所以使用connector-jdbc。

# 配置连接器名称
--connectors-v2--
connector-jdbc
connector-starrocks
connector-paimon
--end--

# 安装连接器
sh bin/install-plugin.sh 2.3.10

SeaTunnel任务

我们先至少保证能在本地完成SeaTunnel任务，再完成对Apache DolphinScheduler的对接。

• http to starRocks
  example/http2starrocks

  env {
  parallelism = 1
  job.mode = "BATCH"
  }
  
  source {
  Http {
    plugin_output = "stock"
    url = "https://ip/http/prd/query_sap_stock"
    method = "POST"
    headers {
      Authorization = "Basic XXX"
      Content-Type = "application/json"
    }
    body = """{"IT_WERKS": [{"VALUE": "1080"}]}"""
    format = "json"
    content_field = "$.ET_RETURN.*"
    schema {
      fields {
        MATNR = "string"
        MAKTX = "string"
        WERKS = "string"
        NAME1 = "string"
        LGORT = "string"
        LGOBE = "string"
        CHARG = "string"
        MEINS = "string"
        LABST = "double"
        UMLME = "double"
        INSME = "double"
        EINME = "double"
        SPEME = "double"
        RETME = "double"
      }
    }
  }
  }
  
  # 此转换操作主要用于字段从命名等方便用途
  transform {
  Sql {
    plugin_input = "stock"
    plugin_output = "stock-tf-out"
    query = "select MATNR, MAKTX, WERKS,NAME1,LGORT,LGOBE,CHARG,MEINS,LABST,UMLME,INSME,EINME,SPEME,RETME from stock"
  }
  }
  
  # 连接starRocks 进行数据分区覆写,本例适用starRocks建表，按照分区insert overwrite 覆写
  sink {
    jdbc {
        plugin_input = "stock-tf-out"
        url = "jdbc:mysql://XXX:9030/scm?useUnicode=true&characterEncoding=UTF-8&rewriteBatchedStatements=true"
        driver = "com.mysql.cj.jdbc.Driver"
        user = "lab"
        password = "XXX"
        compatible_mode="starrocks"
        query = """insert overwrite ods_sap_stock PARTITION (WERKS='1080') (MATNR, MAKTX, WERKS,NAME1,LGORT,LGOBE,CHARG,MEINS,LABST,UMLME,INSME,EINME,SPEME,RETME) values(?,?,?,?,?,?,?,?,?,?,?,?,?,?)"""
        }
  }
  
  # connector-starrocks进行对接 （未看到支持sql语句进行数据insert overwrite，本例子场景不适合），比较适合表数据全部删除重建场景
  // sink {
  //   StarRocks {
  //     plugin_input = "stock-tf-out"
  //     nodeUrls = ["ip:8030"]
  //     base-url = "jdbc:mysql://ip:9030/"
  //     username = "lab"
  //     password = "XXX"
  //     database = "scm"
  //     table = "ods_sap_stock"
  //     batch_max_rows = 1000
  //     data_save_mode="DROP_DATA"
  //     starrocks.config = {
  //       format = "JSON"
  //       strip_outer_array = true
  //     }
  //     schema_save_mode = "RECREATE_SCHEMA"
  //     save_mode_create_template="""
  //       CREATE TABLE IF NOT EXISTS `scm`.`ods_sap_stock` (
  //         MATNR STRING COMMENT '物料',
  //         WERKS STRING COMMENT '工厂',
  //         LGORT STRING COMMENT '库存地点',
  //         MAKTX STRING COMMENT '物料描述',
  //         NAME1 STRING COMMENT '工厂名称',
  //         LGOBE STRING COMMENT '地点描述',
  //         CHARG STRING COMMENT '批次编号',
  //         MEINS STRING COMMENT '单位',
  //         LABST DOUBLE COMMENT '非限制使用库存',
  //         UMLME DOUBLE COMMENT '在途库存',
  //         INSME DOUBLE COMMENT '质检库存',
  //         EINME DOUBLE COMMENT '受限制使用的库存',
  //         SPEME DOUBLE COMMENT '已冻结的库存',
  //         RETME DOUBLE COMMENT '退货'
  //       ) ENGINE=OLAP
  //       PRIMARY KEY ( MATNR,WERKS,LGORT)
  //       COMMENT 'sap库存'
  //       DISTRIBUTED BY HASH (WERKS) PROPERTIES (
  //       "replication_num" = "1"
  //       )
  //     """
  //   }
  // }

• http to paimon
  example/http2paimon

  env {
  parallelism = 1
  job.mode = "BATCH"
  }
  
  source {
  Http {
    plugin_output = "stock"
    url = "https://ip/http/prd/query_sap_stock"
    method = "POST"
    headers {
      Authorization = "Basic XXX"
      Content-Type = "application/json"
    }
    body = """{"IT_WERKS": [{"VALUE": "1080"}]}"""
    format = "json"
    content_field = "$.ET_RETURN.*"
    schema {
      fields {
        MATNR = "string"
        MAKTX = "string"
        WERKS = "string"
        NAME1 = "string"
        LGORT = "string"
        LGOBE = "string"
        CHARG = "string"
        MEINS = "string"
        LABST = "double"
        UMLME = "double"
        INSME = "double"
        EINME = "double"
        SPEME = "double"
        RETME = "double"
      }
    }
  }
  }
  # 此转换操作主要用于字段从命名等方便用途
  transform {
  Sql {
    plugin_input = "stock"
    plugin_output = "stock-tf-out"
    query = "select MATNR, MAKTX, WERKS,NAME1,LGORT,LGOBE,CHARG,MEINS,LABST,UMLME,INSME,EINME,SPEME,RETME from stock"
  }
  }
  
  # 连接paimon进行数据同步，paimon 暂时 未看到有支持 insert overwrite 分区覆写，此例仅作为参考，不适用本此例子需求
  sink {
  Paimon {
    warehouse = "s3a://test/"
    database = "sap"
    table = "ods_sap_stock"
    paimon.hadoop.conf = {
        fs.s3a.access-key=XXX
        fs.s3a.secret-key=XXX
        fs.s3a.endpoint="http://minio:9000"
        fs.s3a.path.style.access=true
        fs.s3a.aws.credentials.provider=org.apache.hadoop.fs.s3a.SimpleAWSCredentialsProvider
    }
  }
  }
  

  DolphinScheduler集成SeaTunnel

• 制作worker镜像

  FROM dolphinscheduler.docker.scarf.sh/apache/dolphinscheduler-worker:3.2.2
  RUN mkdir /opt/seatunnel
  RUN mkdir /opt/seatunnel/apache-seatunnel-2.3.10
  # 容器集成seatunnel
  COPY apache-seatunnel-2.3.10/ /opt/seatunnel/apache-seatunnel-2.3.10/

  打包镜像，推送到镜像仓库

  docker build --platform=linux/amd64 -t apache/dolphinscheduler-worker:3.2.2-seatunnel .

• 使用新镜像部署一个worker，此处修改docker-compose.yaml，增加一个dolphinscheduler-worker-seatunnel节点。

  ...
  dolphinscheduler-worker-seatunnel:
    image: xxx/dolphinscheduler-worker:3.2.2-seatunnel
    profiles: ["all"]
    env_file: .env
    healthcheck:
      test: [ "CMD", "curl", "http://localhost:1235/actuator/health" ]
      interval: 30s
      timeout: 5s
      retries: 3
    depends_on:
      dolphinscheduler-zookeeper:
        condition: service_healthy
    volumes:
      - ./dolphinscheduler-worker-seatunnel-data:/tmp/dolphinscheduler
      - ./dolphinscheduler-logs:/opt/dolphinscheduler/logs
      - ./dolphinscheduler-shared-local:/opt/soft
      - ./dolphinscheduler-resource-local:/dolphinscheduler
    networks:
      dolphinscheduler:
        ipv4_address: 172.15.0.18
  ...

• DolphinScheduler配置SeaTunnel分组及环境配置

  • 安全中心-Worker分组管理,创建一个这个节点ip的分组，用于以后需要seatunnel的任务跑该分组

  

  • 环境管理-创建环境，增加一个用于执行seatunnel的环境，同时需要绑定Worker分组为上一步创建的seatunnel分组

  

  • 创建工作流定义，把上面的seatunnel任务配置填写上

  

  • 运行时候，选择seatunnel的worker分组和环境即可跑在这个集成了seatunnel的环境上