本页目录
树莓派3B安装
ThingsBoard云服务
建议你的物联网应用程序使用ThingsBoard云服务完全托管,可扩展和容错的平台。
ThingsBoard云服务适用于想要使用ThingsBoard但又不想自己托管平台实例的每个人。
在树莓派3B上安装ThingsBoard。
第三方组件安装
步骤1. 安装Java 11(OpenJDK)
ThingsBoard服务运行在Java 11请按照以下说明安装OpenJDK 11:
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| sudo apt update
sudo apt install openjdk-11-jdk
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使用以下命令设置默认版本是OpenJDK 11:
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| sudo update-alternatives --config java
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可以使用以下命令检查安装:
命令输出结果:
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| openjdk version "11.0.xx"
OpenJDK Runtime Environment (...)
OpenJDK 64-Bit Server VM (build ...)
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步骤2. 安装服务
下载安装包。
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| wget https://github.com/thingsboard/thingsboard/releases/download/v3.5.1/thingsboard-3.5.1.deb
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安装服务
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| sudo dpkg -i thingsboard-3.5.1.deb
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步骤3. 配置数据库
ThingsBoard团队建议将PostgreSQL用于负载(<5000消息/秒)的开发和生产环境,使用公有云托管的PostgreSQL数据库服务对于某些ThingsBoard实例而言是一种经济高效的方式。
PostgreSQL安装
PostgreSQL安装说明
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| # install **wget** if not already installed:
sudo apt install -y wget
# import the repository signing key:
wget --quiet -O - https://www.postgresql.org/media/keys/ACCC4CF8.asc | sudo apt-key add -
# add repository contents to your system:
RELEASE=$(lsb_release -cs)
echo "deb http://apt.postgresql.org/pub/repos/apt/ ${RELEASE}"-pgdg main | sudo tee /etc/apt/sources.list.d/pgdg.list
# install and launch the postgresql service:
sudo apt update
sudo apt -y install postgresql
sudo service postgresql start
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创建一个新用户或为主用户设置密码
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| sudo su - postgres
psql
\password
\q
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按“Ctrl+D”返回控制台并连接到数据库创建ThingsBoard数据库:
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| psql -U postgres -d postgres -h 127.0.0.1 -W
CREATE DATABASE thingsboard;
\q
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ThingsBoard配置
编辑配置文件
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| sudo nano /etc/thingsboard/conf/thingsboard.conf
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将下面内容添加到配置文件中并替换“PUT_YOUR_POSTGRESQL_PASSWORD_HERE”为postgres帐户密码:
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| # DB Configuration
export DATABASE_TS_TYPE=sql
export SPRING_DATASOURCE_URL=jdbc:postgresql://localhost:5432/thingsboard
export SPRING_DATASOURCE_USERNAME=postgres
export SPRING_DATASOURCE_PASSWORD=PUT_YOUR_POSTGRESQL_PASSWORD_HERE
# Specify partitioning size for timestamp key-value storage. Allowed values: DAYS, MONTHS, YEARS, INDEFINITE.
export SQL_POSTGRES_TS_KV_PARTITIONING=MONTHS
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步骤4. 选择消息队列服务
ThingsBoard使用队列服务在微服务之间进行API调用可以选择队列服务有In Memory(默认),AWS,Google发布/订阅或Azure服务总线。
Kafka安装
Apache Kafka是一个开源的流式数据处理平台。
ZooKeeper安装
Kafka基于ZooKeeper运行需要先安装 ZooKeeper 服务:
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| sudo apt-get install zookeeper
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Kafka安装
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| wget https://archive.apache.org/dist/kafka/2.6.0/kafka_2.13-2.6.0.tgz
tar xzf kafka_2.13-2.6.0.tgz
sudo mv kafka_2.13-2.6.0 /usr/local/kafka
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设置ZooKeeper启动服务
创建一个Zookeeper系统文件:
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| sudo nano /etc/systemd/system/zookeeper.service
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Add below contnet:
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| [Unit]
Description=Apache Zookeeper server
Documentation=http://zookeeper.apache.org
Requires=network.target remote-fs.target
After=network.target remote-fs.target
[Service]
Type=simple
ExecStart=/usr/local/kafka/bin/zookeeper-server-start.sh /usr/local/kafka/config/zookeeper.properties
ExecStop=/usr/local/kafka/bin/zookeeper-server-stop.sh
Restart=on-abnormal
[Install]
WantedBy=multi-user.target
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设置Kafka启动服务
创建一个Kafka系统文件:
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| sudo nano /etc/systemd/system/kafka.service
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添加以下内容替换系统的“PUT_YOUR_JAVA_PATH”为实际的JAVA_HOME路径默认路径是“/usr/lib/jvm/java-11-openjdk-xxx”:
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| [Unit]
Description=Apache Kafka Server
Documentation=http://kafka.apache.org/documentation.html
Requires=zookeeper.service
[Service]
Type=simple
Environment="JAVA_HOME=PUT_YOUR_JAVA_PATH"
ExecStart=/usr/local/kafka/bin/kafka-server-start.sh /usr/local/kafka/config/server.properties
ExecStop=/usr/local/kafka/bin/kafka-server-stop.sh
[Install]
WantedBy=multi-user.target
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启动 ZooKeeper 和 Kafka:
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| sudo systemctl start zookeeper
sudo systemctl start kafka
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ThingsBoard配置
编辑配置文件
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| sudo nano /etc/thingsboard/conf/thingsboard.conf
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添加下面配置并将”localhost:9092”替换成真实的Kafka服务器地址:
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| export TB_QUEUE_TYPE=kafka
export TB_KAFKA_SERVERS=localhost:9092
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Kafka安装
Apache Kafka是一个开源的流式数据处理平台。
Kafka安装
使用此说明在Docker容器中安装Kafka。
ThingsBoard配置
编辑配置文件
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| sudo nano /etc/thingsboard/conf/thingsboard.conf
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添加下面配置并将”localhost:9092”替换成真实的Kafka服务器地址:
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| export TB_QUEUE_TYPE=kafka
export TB_KAFKA_SERVERS=localhost:9092
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AWS SQS配置
首先需要创建AWS账户然后访问AWS SQS服务。
使用此说明创建AWS SQS服务凭证。
- Access key ID
- Secret access key
ThingsBoard配置
编辑配置文件
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| sudo nano /etc/thingsboard/conf/thingsboard.conf
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添加配置将”YOUR_KEY”和”YOUR_SECRET”替换为真实的AWS用户凭证并将”YOUR_REGION”替换成AWS SQS帐户区域:
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| export TB_QUEUE_TYPE=aws-sqs
export TB_QUEUE_AWS_SQS_ACCESS_KEY_ID=YOUR_KEY
export TB_QUEUE_AWS_SQS_SECRET_ACCESS_KEY=YOUR_SECRET
export TB_QUEUE_AWS_SQS_REGION=YOUR_REGION
# These params affect the number of requests per second from each partitions per each queue.
# Number of requests to particular Message Queue is calculated based on the formula:
# ((Number of Rule Engine and Core Queues) * (Number of partitions per Queue) + (Number of transport queues)
# + (Number of microservices) + (Number of JS executors)) * 1000 / POLL_INTERVAL_MS
# For example, number of requests based on default parameters is:
# Rule Engine queues:
# Main 10 partitions + HighPriority 10 partitions + SequentialByOriginator 10 partitions = 30
# Core queue 10 partitions
# Transport request Queue + response Queue = 2
# Rule Engine Transport notifications Queue + Core Transport notifications Queue = 2
# Total = 44
# Number of requests per second = 44 * 1000 / 25 = 1760 requests
# Based on the use case, you can compromise latency and decrease number of partitions/requests to the queue, if the message load is low.
# By UI set the parameters - interval (1000) and partitions (1) for Rule Engine queues.
# Sample parameters to fit into 10 requests per second on a "monolith" deployment:
export TB_QUEUE_CORE_POLL_INTERVAL_MS=1000
export TB_QUEUE_CORE_PARTITIONS=2
export TB_QUEUE_RULE_ENGINE_POLL_INTERVAL_MS=1000
export TB_QUEUE_TRANSPORT_REQUEST_POLL_INTERVAL_MS=1000
export TB_QUEUE_TRANSPORT_RESPONSE_POLL_INTERVAL_MS=1000
export TB_QUEUE_TRANSPORT_NOTIFICATIONS_POLL_INTERVAL_MS=1000
export TB_QUEUE_VC_INTERVAL_MS=1000
export TB_QUEUE_VC_PARTITIONS=1
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可以使用UI更新默认规则引擎队列配置(轮询间隔和分区)有关ThingsBoard规则引擎队列的更多信息请参阅文档。
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Google发布/订阅配置
创建一个Google帐户并访问发布/订阅服务。
使用此说明创建一个项目并使用发布/订阅服务。
使用此说明创建服务帐户凭据并编辑角色或管理员后保存json凭据步骤9的文件此处。
ThingsBoard配置
编辑配置文件
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| sudo nano /etc/thingsboard/conf/thingsboard.conf
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添加下面配置内容使用真正用户密码替换“YOUR_PROJECT_ID”, “YOUR_SERVICE_ACCOUNT”:
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| export TB_QUEUE_TYPE=pubsub
export TB_QUEUE_PUBSUB_PROJECT_ID=YOUR_PROJECT_ID
export TB_QUEUE_PUBSUB_SERVICE_ACCOUNT=YOUR_SERVICE_ACCOUNT
# These params affect the number of requests per second from each partitions per each queue.
# Number of requests to particular Message Queue is calculated based on the formula:
# ((Number of Rule Engine and Core Queues) * (Number of partitions per Queue) + (Number of transport queues)
# + (Number of microservices) + (Number of JS executors)) * 1000 / POLL_INTERVAL_MS
# For example, number of requests based on default parameters is:
# Rule Engine queues:
# Main 10 partitions + HighPriority 10 partitions + SequentialByOriginator 10 partitions = 30
# Core queue 10 partitions
# Transport request Queue + response Queue = 2
# Rule Engine Transport notifications Queue + Core Transport notifications Queue = 2
# Total = 44
# Number of requests per second = 44 * 1000 / 25 = 1760 requests
# Based on the use case, you can compromise latency and decrease number of partitions/requests to the queue, if the message load is low.
# By UI set the parameters - interval (1000) and partitions (1) for Rule Engine queues.
# Sample parameters to fit into 10 requests per second on a "monolith" deployment:
export TB_QUEUE_CORE_POLL_INTERVAL_MS=1000
export TB_QUEUE_CORE_PARTITIONS=2
export TB_QUEUE_RULE_ENGINE_POLL_INTERVAL_MS=1000
export TB_QUEUE_TRANSPORT_REQUEST_POLL_INTERVAL_MS=1000
export TB_QUEUE_TRANSPORT_RESPONSE_POLL_INTERVAL_MS=1000
export TB_QUEUE_TRANSPORT_NOTIFICATIONS_POLL_INTERVAL_MS=1000
export TB_QUEUE_VC_INTERVAL_MS=1000
export TB_QUEUE_VC_PARTITIONS=1
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可以使用UI更新默认规则引擎队列配置(轮询间隔和分区)有关ThingsBoard规则引擎队列的更多信息请参阅文档。
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Azure服务总线配置
创建Azure帐户并访问Azure服务总线。
通过使用说明了解并使用总线服务。
使用说明创建共享访问签名。
ThingsBoard配置
编辑配置文件
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| sudo nano /etc/thingsboard/conf/thingsboard.conf
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添加下面配置内容使用真正的服务总线名称空间替换”YOUR_NAMESPACE_NAME”和”YOUR_SAS_KEY_NAME”及”YOUR_SAS_KEY”:
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| export TB_QUEUE_TYPE=service-bus
export TB_QUEUE_SERVICE_BUS_NAMESPACE_NAME=YOUR_NAMESPACE_NAME
export TB_QUEUE_SERVICE_BUS_SAS_KEY_NAME=YOUR_SAS_KEY_NAME
export TB_QUEUE_SERVICE_BUS_SAS_KEY=YOUR_SAS_KEY
# These params affect the number of requests per second from each partitions per each queue.
# Number of requests to particular Message Queue is calculated based on the formula:
# ((Number of Rule Engine and Core Queues) * (Number of partitions per Queue) + (Number of transport queues)
# + (Number of microservices) + (Number of JS executors)) * 1000 / POLL_INTERVAL_MS
# For example, number of requests based on default parameters is:
# Rule Engine queues:
# Main 10 partitions + HighPriority 10 partitions + SequentialByOriginator 10 partitions = 30
# Core queue 10 partitions
# Transport request Queue + response Queue = 2
# Rule Engine Transport notifications Queue + Core Transport notifications Queue = 2
# Total = 44
# Number of requests per second = 44 * 1000 / 25 = 1760 requests
# Based on the use case, you can compromise latency and decrease number of partitions/requests to the queue, if the message load is low.
# By UI set the parameters - interval (1000) and partitions (1) for Rule Engine queues.
# Sample parameters to fit into 10 requests per second on a "monolith" deployment:
export TB_QUEUE_CORE_POLL_INTERVAL_MS=1000
export TB_QUEUE_CORE_PARTITIONS=2
export TB_QUEUE_RULE_ENGINE_POLL_INTERVAL_MS=1000
export TB_QUEUE_TRANSPORT_REQUEST_POLL_INTERVAL_MS=1000
export TB_QUEUE_TRANSPORT_RESPONSE_POLL_INTERVAL_MS=1000
export TB_QUEUE_TRANSPORT_NOTIFICATIONS_POLL_INTERVAL_MS=1000
export TB_QUEUE_VC_INTERVAL_MS=1000
export TB_QUEUE_VC_PARTITIONS=1
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可以使用UI更新默认规则引擎队列配置(轮询间隔和分区)有关ThingsBoard规则引擎队列的更多信息请参阅文档。
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RabbitMQ安装
你可以使用官方文档安装RabbitMQ或按照以下说明:
由于RabbitMQ是用Erlang编写的因此需要先安装Erlang才能使用RabbitMQ:
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| sudo apt-get install erlang
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安装rabbitmq:
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| sudo apt-get install rabbitmq-server
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启动服务
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| sudo systemctl start rabbitmq-server.service
sudo systemctl enable rabbitmq-server.service
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RabbitMQ会默认创建一个名为”guest”的用户密码为”guest”。
你还可以使用以下命令在RabbitMQ服务器上创建自己的管理员帐户。
替换对应用户名和密码“PUT_YOUR_USER_NAME”和”PUT_YOUR_PASSWORD”:
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| sudo rabbitmqctl add_user PUT_YOUR_USER_NAME PUT_YOUR_PASSWORD
sudo rabbitmqctl set_user_tags PUT_YOUR_USER_NAME administrator
sudo rabbitmqctl set_permissions -p / PUT_YOUR_USER_NAME ".*" ".*" ".*"
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ThingsBoard配置
编辑配置文件
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| sudo nano /etc/thingsboard/conf/thingsboard.conf
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将以下行添加到配置文件将“YOUR_USERNAME”和“YOUR_PASSWORD”替换为真实的信息将“localhost”和“5672”替换为真实的RabbitMQ主机和端口:
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| export TB_QUEUE_TYPE=rabbitmq
export TB_QUEUE_RABBIT_MQ_USERNAME=YOUR_USERNAME
export TB_QUEUE_RABBIT_MQ_PASSWORD=YOUR_PASSWORD
export TB_QUEUE_RABBIT_MQ_HOST=localhost
export TB_QUEUE_RABBIT_MQ_PORT=5672
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Confluent配置
你应该创建一个帐户后访问Confluent云然后创建一个Kafka集群和 API Key。
ThingsBoard配置
编辑配置文件
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| sudo nano /etc/thingsboard/conf/thingsboard.conf
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添加下面配置内容使用真正的Confluent云服务器地址替换”CLUSTER_API_KEY”, “CLUSTER_API_SECRET”和”localhost:9092”:
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| export TB_QUEUE_TYPE=kafka
export TB_QUEUE_KAFKA_USE_CONFLUENT_CLOUD=true
export TB_KAFKA_SERVERS=localhost:9092
export TB_QUEUE_KAFKA_REPLICATION_FACTOR=3
export TB_QUEUE_KAFKA_CONFLUENT_SASL_JAAS_CONFIG=org.apache.kafka.common.security.plain.PlainLoginModule required username="CLUSTER_API_KEY" password="CLUSTER_API_SECRET";}
# These params affect the number of requests per second from each partitions per each queue.
# Number of requests to particular Message Queue is calculated based on the formula:
# ((Number of Rule Engine and Core Queues) * (Number of partitions per Queue) + (Number of transport queues)
# + (Number of microservices) + (Number of JS executors)) * 1000 / POLL_INTERVAL_MS
# For example, number of requests based on default parameters is:
# Rule Engine queues:
# Main 10 partitions + HighPriority 10 partitions + SequentialByOriginator 10 partitions = 30
# Core queue 10 partitions
# Transport request Queue + response Queue = 2
# Rule Engine Transport notifications Queue + Core Transport notifications Queue = 2
# Total = 44
# Number of requests per second = 44 * 1000 / 25 = 1760 requests
# Based on the use case, you can compromise latency and decrease number of partitions/requests to the queue, if the message load is low.
# By UI set the parameters - interval (1000) and partitions (1) for Rule Engine queues.
# Sample parameters to fit into 10 requests per second on a "monolith" deployment:
export TB_QUEUE_CORE_POLL_INTERVAL_MS=1000
export TB_QUEUE_CORE_PARTITIONS=2
export TB_QUEUE_RULE_ENGINE_POLL_INTERVAL_MS=1000
export TB_QUEUE_TRANSPORT_REQUEST_POLL_INTERVAL_MS=1000
export TB_QUEUE_TRANSPORT_RESPONSE_POLL_INTERVAL_MS=1000
export TB_QUEUE_TRANSPORT_NOTIFICATIONS_POLL_INTERVAL_MS=1000
export TB_QUEUE_VC_INTERVAL_MS=1000
export TB_QUEUE_VC_PARTITIONS=1
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可以使用UI更新默认规则引擎队列配置(轮询间隔和分区)有关ThingsBoard规则引擎队列的更多信息请参阅文档。
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步骤5. [可选]低性能配置(1GB内存)
编辑配置文件
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| sudo nano /etc/thingsboard/conf/thingsboard.conf
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将以下行添加到配置文件
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| # Update ThingsBoard memory usage and restrict it to 256MB in /etc/thingsboard/conf/thingsboard.conf
export JAVA_OPTS="$JAVA_OPTS -Xms256M -Xmx256M"
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步骤6. 运行安装脚本
执行以下脚本安装ThingsBoard服务并初始化演示数据:
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| # --loadDemo option will load demo data: users, devices, assets, rules, widgets.
sudo /usr/share/thingsboard/bin/install/install.sh --loadDemo
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步骤7. 启动服务
执行以下命令以启动ThingsBoard:
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| sudo service thingsboard start
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启动后使用以下链接打开Web UI:
如果在安装脚本的执行过程中指定了-loadDemo则可以使用以下默认帐号:
- System Administrator: sysadmin@thingsboard.org / sysadmin
- Tenant Administrator: tenant@thingsboard.org / tenant
- Customer User: customer@thingsboard.org / customer
可以在帐户详情页面中更改每个帐户的密码。
如果是1-2核CPU或1-2G内存的计算机请等待90秒后启动界面。
安装完成并配置
ThingsBoard日志存储在以下目录中:
执行如下命令检查后面是否有错误:
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| cat /var/log/thingsboard/thingsboard.log | grep ERROR
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下一步
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入门指南 - 快速学习ThingsBoard相关功能。
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连接设备 - 学习如何根据你的连接方式或解决方案连接设备。
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可 视 化 - 学习如何配置复杂的ThingsBoard仪表板说明。
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数据处理 - 学习如何使用ThingsBoard规则引擎。
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数据分析 - 学习如何使用规则引擎执行基本的分析任务。
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硬件样品 - 学习如何将各种硬件平台连接到ThingsBoard。
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高级功能 - 学习高级ThingsBoard功能。
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开发指南 - 学习ThingsBoard中的贡献和开发。