目录
强大的性能,无限的扩展
收集、组织和处理海量高速数据。当您将任何数据视为时间序列数据时,它会更有价值。借助 InfluxDB,这是 #1 的时间序列平台,旨在与 Telegraf 一起扩展。
查看入门方法
输入和输出集成概述
Modbus 插件允许您使用各种通信方法从 Modbus 设备收集数据,从而增强您监控和控制工业流程的能力。
Telegraf SQL 插件允许您将来自 Telegraf 的指标直接存储到 MySQL 数据库中,从而更轻松地分析和可视化收集的指标。
集成详情
Modbus
Modbus 插件通过 Modbus TCP 或 Modbus RTU/ASCII 收集离散输入、线圈、输入寄存器和保持寄存器。
MySQL
Telegraf 的 SQL 输出插件旨在通过基于传入指标动态创建表和列,将指标数据无缝写入 SQL 数据库。当配置为 MySQL 时,该插件利用 go-sql-driver/mysql,这需要启用 ANSI_QUOTES SQL 模式以确保正确处理带引号的标识符。这种动态模式创建方法确保每个指标都存储在自己的表中,其结构源自其字段和标签,从而提供系统性能的详细、带时间戳的记录。该插件的灵活性使其能够处理高吞吐量环境,使其成为需要强大、精细的指标日志记录和历史数据分析的场景的理想选择。
配置
Modbus
[[inputs.modbus]]
name = "Device"
slave_id = 1
timeout = "1s"
configuration_type = "register"
discrete_inputs = [
{ name = "start", address = [0]},
{ name = "stop", address = [1]},
{ name = "reset", address = [2]},
{ name = "emergency_stop", address = [3]},
]
coils = [
{ name = "motor1_run", address = [0]},
{ name = "motor1_jog", address = [1]},
{ name = "motor1_stop", address = [2]},
]
holding_registers = [
{ name = "power_factor", byte_order = "AB", data_type = "FIXED", scale=0.01, address = [8]},
{ name = "voltage", byte_order = "AB", data_type = "FIXED", scale=0.1, address = [0]},
{ name = "energy", byte_order = "ABCD", data_type = "FIXED", scale=0.001, address = [5,6]},
{ name = "current", byte_order = "ABCD", data_type = "FIXED", scale=0.001, address = [1,2]},
{ name = "frequency", byte_order = "AB", data_type = "UFIXED", scale=0.1, address = [7]},
{ name = "power", byte_order = "ABCD", data_type = "UFIXED", scale=0.1, address = [3,4]},
{ name = "firmware", byte_order = "AB", data_type = "STRING", address = [5, 6, 7, 8, 9, 10, 11, 12]},
]
input_registers = [
{ name = "tank_level", byte_order = "AB", data_type = "INT16", scale=1.0, address = [0]},
{ name = "tank_ph", byte_order = "AB", data_type = "INT16", scale=1.0, address = [1]},
{ name = "pump1_speed", byte_order = "ABCD", data_type = "INT32", scale=1.0, address = [3,4]},
]
MySQL
[[outputs.sql]]
## Database driver
## Valid options: mssql (Microsoft SQL Server), mysql (MySQL), pgx (Postgres),
## sqlite (SQLite3), snowflake (snowflake.com) clickhouse (ClickHouse)
driver = "mysql"
## Data source name
## The format of the data source name is different for each database driver.
## See the plugin readme for details.
data_source_name = "username:password@tcp(host:port)/dbname"
## Timestamp column name
timestamp_column = "timestamp"
## Table creation template
## Available template variables:
## {TABLE} - table name as a quoted identifier
## {TABLELITERAL} - table name as a quoted string literal
## {COLUMNS} - column definitions (list of quoted identifiers and types)
table_template = "CREATE TABLE {TABLE}({COLUMNS})"
## Table existence check template
## Available template variables:
## {TABLE} - tablename as a quoted identifier
table_exists_template = "SELECT 1 FROM {TABLE} LIMIT 1"
## Initialization SQL
init_sql = "SET sql_mode='ANSI_QUOTES';"
## Maximum amount of time a connection may be idle. "0s" means connections are
## never closed due to idle time.
connection_max_idle_time = "0s"
## Maximum amount of time a connection may be reused. "0s" means connections
## are never closed due to age.
connection_max_lifetime = "0s"
## Maximum number of connections in the idle connection pool. 0 means unlimited.
connection_max_idle = 2
## Maximum number of open connections to the database. 0 means unlimited.
connection_max_open = 0
## NOTE: Due to the way TOML is parsed, tables must be at the END of the
## plugin definition, otherwise additional config options are read as part of the
## table
## Metric type to SQL type conversion
## The values on the left are the data types Telegraf has and the values on
## the right are the data types Telegraf will use when sending to a database.
##
## The database values used must be data types the destination database
## understands. It is up to the user to ensure that the selected data type is
## available in the database they are using. Refer to your database
## documentation for what data types are available and supported.
#[outputs.sql.convert]
# integer = "INT"
# real = "DOUBLE"
# text = "TEXT"
# timestamp = "TIMESTAMP"
# defaultvalue = "TEXT"
# unsigned = "UNSIGNED"
# bool = "BOOL"
# ## This setting controls the behavior of the unsigned value. By default the
# ## setting will take the integer value and append the unsigned value to it. The other
# ## option is "literal", which will use the actual value the user provides to
# ## the unsigned option. This is useful for a database like ClickHouse where
# ## the unsigned value should use a value like "uint64".
# # conversion_style = "unsigned_suffix"
输入和输出集成示例
Modbus
- 基本用法:要从单个设备读取数据,请使用设备名称和 IP 地址配置它,指定从站 ID 和感兴趣的寄存器。
- 多个请求:您可以通过指定多个
[[inputs.modbus.request]]
部分,定义多个请求以从单个配置中的不同 Modbus 从站设备获取数据。 - 数据处理:利用缩放功能将原始 Modbus 读数转换为有用的指标,并根据需要调整单位转换。
MySQL
-
实时 Web 分析存储:利用该插件捕获网站性能指标并将它们存储在 MySQL 中。此设置使团队能够监控用户交互、分析流量模式并根据实时数据洞察动态调整站点功能。
-
物联网设备监控:利用该插件从物联网传感器网络收集指标,并将它们记录到 MySQL 数据库中。此用例支持设备运行状况和性能的持续监控,从而实现预测性维护和对异常的即时响应。
-
金融交易日志记录:记录具有精确时间戳的高频金融交易数据。此方法支持强大的审计跟踪、实时欺诈检测以及用于合规性和报告目的的全面历史分析。
-
应用程序性能基准测试:将该插件与应用程序性能监控系统集成,以将指标记录到 MySQL 中。这有助于随着时间的推移进行详细的基准测试和趋势分析,使组织能够有效地识别性能瓶颈并优化资源分配。
反馈
感谢您成为我们社区的一份子!如果您对这些页面有任何一般性反馈或发现任何错误,我们欢迎并鼓励您提出意见。请在 InfluxDB 社区 Slack 中提交您的反馈。
强大的性能,无限的扩展
收集、组织和处理海量高速数据。当您将任何数据视为时间序列数据时,它会更有价值。借助 InfluxDB,这是 #1 的时间序列平台,旨在与 Telegraf 一起扩展。
查看入门方法