安装

ThingsBoard安装和配置文档。

基于树莓派3代B安装ThingsBoard


IoT PaaS演示


我们建议使用ThingsBoard专业版在线演示了解并体验最新功能!

使用云端默认提供的设备、仪表板和邮件服务可以节省你的安装和配置时间来创建新客户和用户。

本指南介绍了如何在运行树莓派3代B上安装ThingsBoard。

第三方组件安装

步骤1.安装Java 8(OpenJDK)

ThingsBoard服务运行在Java 8上。请按照以下说明安装OpenJDK 8。

sudo apt update
sudo apt install openjdk-8-jdk

请不要忘记将操作系统配置为默认使用OpenJDK 8。

您可以使用以下命令配置哪个版本是默认版本:

sudo update-alternatives --config java

您可以使用以下命令检查安装:

java -version

命令输出结果:

openjdk version "1.8.0_xxx"
OpenJDK Runtime Environment (...)
OpenJDK 64-Bit Server VM (build ...)

步骤2.ThingsBoard服务安装

下载安装包

wget https://github.com/thingsboard/thingsboard/releases/download/v3.1.1/thingsboard-3.1.1.deb

安装ThingsBoard服务

sudo dpkg -i thingsboard-3.1.1.deb

步骤3.配置ThingsBoard数据库

将PostgreSQL用于开发和生产环境ThingsBoard团队建议负载(<5000消息/秒)。

使用托管的PostgreSQL服务器对于ThingsBoard实例而言都是一种经济高效的解决方案。

PostgreSQL安装

下面列出的说明将帮助您安装PostgreSQL。

# 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-12
sudo service postgresql start

一旦安装了PostgreSQL您可能想要创建一个新用户或为主要用户设置密码。

以下说明帮助你设置PostgreSQL用户密码

sudo su - postgres
psql
\password
\q

然后,按“Ctrl+D”返回主用户控制台并连接到数据库以创建Thingsboard DB:

psql -U postgres -d postgres -h 127.0.0.1 -W
CREATE DATABASE thingsboard;
\q
ThingsBoard配置

编辑ThingsBoard配置文件

sudo nano /etc/thingsboard/conf/thingsboard.conf

将“PUT_YOUR_POSTGRESQL_PASSWORD_HERE”替换postgres用户真实密码

# DB Configuration 
export DATABASE_ENTITIES_TYPE=sql
export DATABASE_TS_TYPE=sql
export SPRING_JPA_DATABASE_PLATFORM=org.hibernate.dialect.PostgreSQLDialect
export SPRING_DRIVER_CLASS_NAME=org.postgresql.Driver
export SPRING_DATASOURCE_URL=jdbc:postgresql://localhost:5432/thingsboard
export SPRING_DATASOURCE_USERNAME=postgres
export SPRING_DATASOURCE_PASSWORD=PUT_YOUR_POSTGRESQL_PASSWORD_HERE
export SPRING_DATASOURCE_MAXIMUM_POOL_SIZE=5
# Specify partitioning size for timestamp key-value storage. Allowed values: DAYS, MONTHS, YEARS, INDEFINITE.
export SQL_POSTGRES_TS_KV_PARTITIONING=MONTHS

步骤4.低性能电脑内存修改(1GB RAM)

编辑ThingsBoard配置文件

sudo nano /etc/thingsboard/conf/thingsboard.conf

将以下行添加到配置文件。

# Update ThingsBoard memory usage and restrict it to 256MB in /etc/thingsboard/conf/thingsboard.conf
export JAVA_OPTS="$JAVA_OPTS -Xms256M -Xmx256M"

步骤5.运行安装脚本

安装ThingsBoard服务并更新数据库配置后,您可以执行以下脚本:

# --loadDemo option will load demo data: users, devices, assets, rules, widgets.
sudo /usr/share/thingsboard/bin/install/install.sh --loadDemo

步骤4. 选择消息队列服务

ThingsBoard使用队列服务进行微服务之间的API调用并能够使用下一个队列服务:内存(默认)AWS SQS,Google发布/订阅或Azure服务总线。

默认使用内置的内存队列无需其他配置。

AWS SQS配置

首先需要创建一个AWS账户然后访问AWS SQS服务。

要使用AWS SQS服务您将需要使用此说明创建下一个凭证。

  • Access key ID
  • Secret access key
ThingsBoard配置

编辑ThingsBoard配置文件

sudo nano /etc/thingsboard/conf/thingsboard.conf

添加配置文件将”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:

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.
# 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_RE_MAIN_POLL_INTERVAL_MS=1000
export TB_QUEUE_RE_MAIN_PARTITIONS=2
export TB_QUEUE_RE_HP_POLL_INTERVAL_MS=1000
export TB_QUEUE_RE_HP_PARTITIONS=1
export TB_QUEUE_RE_SQ_POLL_INTERVAL_MS=1000
export TB_QUEUE_RE_SQ_PARTITIONS=1
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

Google发布/订阅配置

创建一个Google云帐户并访问发布/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管理员后保存json凭据步骤9的文件此处

ThingsBoard配置

编辑ThingsBoard配置文件

sudo nano /etc/thingsboard/conf/thingsboard.conf

添加下面配置内容使用真正用户密码替换“YOUR_PROJECT_ID”, “YOUR_SERVICE_ACCOUNT”:

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!!!
export TB_QUEUE_TRANSPORT_REQUEST_POLL_INTERVAL_MS=1000
export TB_QUEUE_TRANSPORT_RESPONSE_POLL_INTERVAL_MS=1000
export TB_QUEUE_CORE_POLL_INTERVAL_MS=1000
export REMOTE_JS_RESPONSE_POLL_INTERVAL_MS=1000
export TB_QUEUE_RULE_ENGINE_POLL_INTERVAL_MS=1000
export TB_QUEUE_RE_MAIN_POLL_INTERVAL_MS=1000
export TB_QUEUE_RE_HP_POLL_INTERVAL_MS=1000
export TB_QUEUE_RE_SQ_POLL_INTERVAL_MS=1000
export TB_QUEUE_TRANSPORT_NOTIFICATIONS_POLL_INTERVAL_MS=1000

# 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.
# 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_RE_MAIN_POLL_INTERVAL_MS=1000
export TB_QUEUE_RE_MAIN_PARTITIONS=2
export TB_QUEUE_RE_HP_POLL_INTERVAL_MS=1000
export TB_QUEUE_RE_HP_PARTITIONS=1
export TB_QUEUE_RE_SQ_POLL_INTERVAL_MS=1000
export TB_QUEUE_RE_SQ_PARTITIONS=1
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

Azure服务总线配置

创建一个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ThingsBoard配置文件

sudo nano /etc/thingsboard/conf/thingsboard.conf

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”:

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!!!
export TB_QUEUE_TRANSPORT_REQUEST_POLL_INTERVAL_MS=1000
export TB_QUEUE_TRANSPORT_RESPONSE_POLL_INTERVAL_MS=1000
export TB_QUEUE_CORE_POLL_INTERVAL_MS=1000
export REMOTE_JS_RESPONSE_POLL_INTERVAL_MS=1000
export TB_QUEUE_RULE_ENGINE_POLL_INTERVAL_MS=1000
export TB_QUEUE_RE_MAIN_POLL_INTERVAL_MS=1000
export TB_QUEUE_RE_HP_POLL_INTERVAL_MS=1000
export TB_QUEUE_RE_SQ_POLL_INTERVAL_MS=1000
export TB_QUEUE_TRANSPORT_NOTIFICATIONS_POLL_INTERVAL_MS=1000

# 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.
# 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_RE_MAIN_POLL_INTERVAL_MS=1000
export TB_QUEUE_RE_MAIN_PARTITIONS=2
export TB_QUEUE_RE_HP_POLL_INTERVAL_MS=1000
export TB_QUEUE_RE_HP_PARTITIONS=1
export TB_QUEUE_RE_SQ_POLL_INTERVAL_MS=1000
export TB_QUEUE_RE_SQ_PARTITIONS=1
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

Confluent云配置

你应该创建一个帐户后访问Confluent云然后创建一个Kafka集群API Key

ThingsBoard配置

编辑ThingsBoard配置文件

sudo nano /etc/thingsboard/conf/thingsboard.conf

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”:

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.
# 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_RE_MAIN_POLL_INTERVAL_MS=1000
export TB_QUEUE_RE_MAIN_PARTITIONS=2
export TB_QUEUE_RE_HP_POLL_INTERVAL_MS=1000
export TB_QUEUE_RE_HP_PARTITIONS=1
export TB_QUEUE_RE_SQ_POLL_INTERVAL_MS=1000
export TB_QUEUE_RE_SQ_PARTITIONS=1
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

步骤5. [可选]低性能配置(1GB内存)

编辑ThingsBoard配置文件

sudo nano /etc/thingsboard/conf/thingsboard.conf

将以下行添加到配置文件。

# Update ThingsBoard memory usage and restrict it to 256MB in /etc/thingsboard/conf/thingsboard.conf
export JAVA_OPTS="$JAVA_OPTS -Xms256M -Xmx256M"

步骤6. 运行安装脚本

安装ThingsBoard服务并更新数据库配置后,您可以执行以下脚本:

# --loadDemo option will load demo data: users, devices, assets, rules, widgets.
sudo /usr/share/thingsboard/bin/install/install.sh --loadDemo

步骤7. 启动服务

执行以下命令以启动ThingsBoard:

sudo service thingsboard start

启动后,您将可以使用以下链接打开Web UI:

http://localhost:8080/

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凭据:

  • 系统管理员: sysadmin@thingsboard.org / sysadmin
  • 租户管理员: tenant@thingsboard.org / tenant
  • 客户: customer@thingsboard.org / customer

您始终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240秒后启动界面。

故障排除

ThingsBoard日志存储在以下目录中:

/var/log/thingsboard

执行如下命令检查后面是否有错误:

cat /var/log/thingsboard/thingsboard.log | grep ERROR

下一步

  • 入门指南 - 这些指南提供了ThingsBoard主要功能的快速概述。

  • 设备连接 - 了解如何根据您的连接方式或解决方案连接设备。

  • 数据看板 - 这些指南包含有关如何配置复杂的ThingsBoard仪表板的说明。

  • 数据处理 - 了解如何使用ThingsBoard规则引擎。

  • 数据分析 - 了解如何使用规则引擎执行基本的分析任务。

  • 硬件样品 - 了解如何将各种硬件平台连接到ThingsBoard。

  • 高级功能 - 了解高级ThingsBoard功能。

  • 开发指南 - 了解ThingsBoard中的贡献和开发。