es_hk_images_dumps3/target/classes/application-dev.yml

# 数据源配置
spring:
  datasource:
    druid:
      # 主库数据源
      master:
        type: com.alibaba.druid.pool.DruidDataSource
        driverClassName: com.mysql.cj.jdbc.Driver
        # url: jdbc:mysql://h386t1c.nat.ipyingshe.com:58951/shoreline_seats_db?useUnicode=true&characterEncoding=utf8&zeroDateTimeBehavior=convertToNull&useSSL=true&serverTimezone=GMT%2B8
        url: jdbc:mysql://120.25.74.229:8006/ax_seat_show?useUnicode=true&characterEncoding=utf8&zeroDateTimeBehavior=convertToNull&useSSL=true&serverTimezone=GMT%2B8&allowMultiQueries=true
        username: root
        password: ROOT@taiji2022!
      # 从库数据源
      slave:
        type: com.alibaba.druid.pool.DruidDataSource
        driverClassName: com.mysql.cj.jdbc.Driver
        # 从数据源开关/默认关闭
        enabled: true
        url: jdbc:mysql://120.25.74.229:8006/ax_seat_db1?useUnicode=true&characterEncoding=utf8&zeroDateTimeBehavior=convertToNull&useSSL=true&serverTimezone=GMT%2B8
        username: root
        password: ROOT@taiji2022!
      slave1:
        type: com.alibaba.druid.pool.DruidDataSource
        driverClassName: com.mysql.cj.jdbc.Driver
        url: jdbc:mysql://120.25.74.229:8006/ax_seat_db1?useUnicode=true&characterEncoding=utf8&zeroDateTimeBehavior=convertToNull&useSSL=true&serverTimezone=GMT%2B8
        username: root
        password: ROOT@taiji2022!
      screen:
        type: com.alibaba.druid.pool.DruidDataSource
        driverClassName: com.mysql.cj.jdbc.Driver
        url: jdbc:mysql://120.25.74.229:8006/ax_seat_show?useUnicode=true&characterEncoding=utf8&zeroDateTimeBehavior=convertToNull&useSSL=true&serverTimezone=GMT%2B8
        username: axdb
        password: Mysql@2022!
        enabled: false
      # 初始连接数
      initialSize: 5
      # 最小连接池数量
      minIdle: 10
      # 最大连接池数量
      maxActive: 20
      # 配置获取连接等待超时的时间
      maxWait: 60000
      # 配置间隔多久才进行一次检测，检测需要关闭的空闲连接，单位是毫秒
      timeBetweenEvictionRunsMillis: 60000
      # 配置一个连接在池中最小生存的时间，单位是毫秒
      minEvictableIdleTimeMillis: 300000
      # 配置一个连接在池中最大生存的时间，单位是毫秒
      maxEvictableIdleTimeMillis: 900000
      # 配置检测连接是否有效
      validationQuery: SELECT 1
      testWhileIdle: true
      testOnBorrow: false
      testOnReturn: false
      webStatFilter:
        enabled: true
      statViewServlet:
        enabled: true
        # 设置白名单，不填则允许所有访问
        allow:
        url-pattern: /druid/*
        # 控制台管理用户名和密码
        login-username: seat
        login-password: 123456
      filter:
        stat:
          enabled: true
          # 慢SQL记录
          log-slow-sql: true
          slow-sql-millis: 1000
          merge-sql: true
        wall:
          config:
            multi-statement-allow: true
  rabbitmq:
    host: 47.111.231.31
    port: 5672
    username: rabbitmq
    password: root
  # redis 配置
  redis:
    # 地址
    host: 127.0.0.1
    #host: 192.168.1.107
    # 端口，默认为6379
    port: 6379
    # 数据库索引
    database: 0
    # 密码
    password:
    # 连接超时时间
    timeout: 10s
    lettuce:
      pool:
        # 连接池中的最小空闲连接
        min-idle: 0
        # 连接池中的最大空闲连接
        max-idle: 8
        # 连接池的最大数据库连接数
        max-active: 8
        # #连接池最大阻塞等待时间（使用负值表示没有限制）
        max-wait: -1ms
  ##kafka
  kafka:
    bootstrap-servers: 120.25.232.213:9092
    consumer:
      auto-commit-interval: 1S
      # 该属性指定了消费者在读取一个没有偏移量的分区或者偏移量无效的情况下该作何处理：
      # latest（默认值）在偏移量无效的情况下，消费者将从最新的记录开始读取数据（在消费者启动之后生成的记录）
      # earliest ：在偏移量无效的情况下，消费者将从起始位置读取分区的记录
        # 自动提交的时间间隔 在spring boot 2.X 版本中这里采用的是值的类型为Duration 需要符合特定的格式，如1S,1M,2H,5D
        # 该属性指定了消费者在读取一个没有偏移量的分区或者偏移量无效的情况下该作何处理：
        # latest（默认值）在偏移量无效的情况下，消费者将从最新的记录开始读取数据（在消费者启动之后生成的记录）
        # earliest ：在偏移量无效的情况下，消费者将从起始位置读取分区的记录
      auto-offset-reset: latest
        # 是否自动提交偏移量，默认值是true,为了避免出现重复数据和数据丢失，可以把它设置为false,然后手动提交偏移量
      enable-auto-commit: false
      key-deserializer: org.apache.kafka.common.serialization.StringDeserializer
      value-deserializer: org.apache.kafka.common.serialization.StringDeserializer
    producer:
      retries: 3
      batch-size: 16384
      buffer-memory: 33554432
      key-serializer: org.apache.kafka.common.serialization.StringSerializer
      value-serializer:  org.apache.kafka.common.serialization.StringSerializer
      # acks=0 ： 生产者在成功写入消息之前不会等待任何来自服务器的响应。
      # acks=1 ： 只要集群的首领节点收到消息，生产者就会收到一个来自服务器成功响应。
      # acks=all ：只有当所有参与复制的节点全部收到消息时，生产者才会收到一个来自服务器的成功响应。
      acks: 1
    properties:
          security:
            protocol: SASL_PLAINTEXT
          sasl:
            mechanism: SCRAM-SHA-512
            jaas:
              config: 'org.apache.kafka.common.security.scram.ScramLoginModule required username="user01" password="user01";'
    listener:
          # 在侦听器容器中运行的线程数。
          concurrency: 5
          #listner负责ack，每调用一次，就立即commit
          ack-mode: manual_immediate
          missing-topics-fatal: false
taiji:
  openservice:
    enable: false
    url: http://127.0.0.1:8080
  elasticsearch.rest:
    uris: 120.25.233.10:9200
    username: elastic       #如果你设置了基于x-pack的验证就要填写账号和密码
    password: root@2022!       #没有则不用配置
    connection-timeout: 100 #连接超时
    max-connection: 100  #最大连接数
  kafka:
    consumer:
      groupId: 202112301442_116
      taiji_ax_person_warning_record:
        group: ${random.uuid}
        topic: taiji_ax_person_warning_record
      ship_warning_record:
        topic: taiji_ax_ship_warning_record
      car_warning_record:
        topic: taiji_ax_car_warning_record
      multiple_warning_record:
        topic: taiji_ax_multiple_warning_record
      dynamic-ship-track-partition:
        topic: 'taiji_ax_ship_dynamic_fusion'
        group: ${random.uuid}
        partitions0: 0
        partitions1: 1
        partitions2: 2
        partitions3: 3
        partitions4: 4
        id-key: merge_id
        longitude-key: target_longitude
        latitude-key: target_latitude
      hlx_ax_ship_camera_structured_info:
          topic: 'hlx_ax_ship_camera_structured_info'
    producer:
      taiji_ax_warning_biz_data_sync_message:
          topic: 'taiji_ax_warning_biz_data_sync_message'
  esindex:
    state: 0
    ship_warning_record_index: index_seat_warning_ship_record

shop:
  warning:
    record:
      ship: warningcode:ship:prod118
      car: warningcode:car:prod118
      person: warningcode:person:prod118
      multiple: warningcode:multiple:prod118

#netty的配置信息
webSocket:
  netty:
    port: 6999
    path: /webSocket
    readerIdleTime: 120  #读空闲超时时间设置(Netty心跳检测配置)
    writerIdleTime: 120  #写空闲超时时间设置(Netty心跳检测配置)
    allIdleTime: 120     #读写空闲超时时间设置(Netty心跳检测配置)

# 海康威视kafka密钥
infovision-kafka:
  ip: 74.10.28.97  #host
  port: 443       #port
  appkey: 20938619 #key
  secret: 2028DRKPt0ZzGocgCNJd #secret
  groupId:
    face: ${random.uuid}
    car: ${random.uuid}

infovision-rabbit:
  groupId: ${random.uuid}

# 海康威视全量密钥
infovision:
  ip: 74.10.28.97  #host
  port: 443       #port
  appkey: 26491753 #key
  secret: nSWbgqChFBSdGPSnb59i #secret

#海康
#重点人员人脸库唯一标识
key-personlibid: 1634291086413
# 岸线-人脸布控库id
face-personlibid: 16345463113275
# 岸线-人员布控库id
control-personlibid: 1634547649335
# 岸线-重点车辆库id
key-vehiclelibid: 1634546401514
# 岸线-车辆布控库id
control-vehiclelibid: 16345463664888


# 巡逻防控 —— 轨迹查询开关
patrolinfoboolean: false


# 重点对象同步海康请求开关
key-boolean: false


# MQTT Config 开发环境默认关闭 mqtt协议已弃用,请勿开启
mqtt:
  #  host: tcp://74.10.28.97:1883
  host: tcp://localhost:1883
  userName: mqtt
  passWord: mqtt
  keepLiveTime: 100
  enabled: false
  cilentId: ${random.uuid}
  face:
    topic: artemis/event_face/3187675137/admin
  car:
    topic: artemis/event_veh/3204452353/admin

workflow:
  auditRole:
    watchman: '派出所值班用户'
    policeRole: '派出所民警'
    detachmentPoliceRole: '支队民警'
    shipPoliceRole: '派出所船管民警'
    directorRole: '派出所所长'
    policeLeaderRole: '派出所领导'
    brigadeRole: '大队领导'
    detachmentRole: '支队领导'
    teamRole: '总队领导'
    commandAndDispatchRole: '指挥调度'
  auditModel:
    one: ${workflow.auditRole.policeRole}_${workflow.auditRole.policeLeaderRole}_${workflow.auditRole.detachmentRole}_${workflow.auditRole.teamRole}
    two: ${workflow.auditRole.policeRole}_${workflow.auditRole.policeLeaderRole}_${workflow.auditRole.brigadeRole}
    three: ${workflow.auditRole.policeRole}_${workflow.auditRole.policeLeaderRole}_${workflow.auditRole.detachmentRole}
    four: ${workflow.auditRole.policeRole}_${workflow.auditRole.policeLeaderRole}
    five: ${workflow.auditRole.policeRole}_${workflow.auditRole.policeLeaderRole}_${workflow.auditRole.detachmentRole}
    six: ${workflow.auditRole.policeRole}_${workflow.auditRole.policeLeaderRole}_${workflow.auditRole.detachmentRole}_${workflow.auditRole.teamRole}
    seven: ${workflow.auditRole.detachmentPoliceRole}_${workflow.auditRole.detachmentRole}
    eight: ${workflow.auditRole.detachmentPoliceRole}_${workflow.auditRole.detachmentRole}_${workflow.auditRole.teamRole}
    nine: ${workflow.auditRole.policeRole}_${workflow.auditRole.policeLeaderRole}_${workflow.auditRole.brigadeRole}