对于大规模实时查询，这不是推荐的配置。为了查询和压缩优化、高速摄取和高可用性，您可能需要考虑 Modbus 和 InfluxDB。
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Telegraf 下载量
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时序数据库
来源：DB Engines
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InfluxDB 下载量
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贡献者
目录
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 的 SQL 插件允许在 SQL 数据库中无缝存储指标。当配置为 Snowflake 时，它采用专门的 DSN 格式和动态表创建，以将指标映射到适当的模式。
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。
Snowflake
Telegraf 的 SQL 插件旨在通过根据传入数据创建表和列，将指标动态写入 SQL 数据库。当配置为 Snowflake 时，它采用 gosnowflake 驱动程序，该驱动程序使用 DSN，该 DSN 以紧凑的格式封装凭据、帐户详细信息和数据库配置。这种设置允许自动生成表，其中每个指标都记录有精确的时间戳，从而确保详细的历史跟踪。虽然此集成被认为是实验性的，但它利用了 Snowflake 强大的数据仓库功能，使其适用于可扩展的、基于云的分析和报告解决方案。
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]},
]
Snowflake
[[outputs.sql]]
## Database driver
## Valid options: mssql (Microsoft SQL Server), mysql (MySQL), pgx (Postgres),
## sqlite (SQLite3), snowflake (snowflake.com), clickhouse (ClickHouse)
driver = "snowflake"
## Data source name
## For Snowflake, the DSN format typically includes the username, password, account identifier, and optional warehouse, database, and schema.
## Example DSN: "username:password@account/warehouse/db/schema"
data_source_name = "username:password@account/warehouse/db/schema"
## 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} - table name as a quoted identifier
table_exists_template = "SELECT 1 FROM {TABLE} LIMIT 1"
## Initialization SQL (optional)
init_sql = ""
## 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
## Metric type to SQL type conversion
## Defaults to ANSI/ISO SQL types unless overridden. Adjust if needed for Snowflake compatibility.
#[outputs.sql.convert]
# integer = "INT"
# real = "DOUBLE"
# text = "TEXT"
# timestamp = "TIMESTAMP"
# defaultvalue = "TEXT"
# unsigned = "UNSIGNED"
# bool = "BOOL"
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 地址对其进行配置，并指定从站 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，在单个配置中定义多个请求以从不同的 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。
Snowflake
-
基于云的数据湖集成：利用此插件将来自各种来源的实时指标流式传输到 Snowflake，从而创建集中式数据湖。此集成支持云数据上的复杂分析和机器学习工作流程。
-
动态商业智能仪表板：利用此插件从传入指标自动生成表，并将它们馈送到 BI 工具。这使企业能够创建动态仪表板，可视化性能趋势和运营洞察，而无需手动模式管理。
-
可扩展的物联网分析：部署此插件以从物联网设备捕获高频数据到 Snowflake。此用例有助于传感器数据的聚合和分析，从而实现大规模的预测性维护和实时监控。
-
用于合规性的历史趋势分析：使用此插件在 Snowflake 中记录和存档详细的指标数据，然后可以查询这些数据以进行长期趋势分析和合规性报告。这种设置确保组织可以维护强大的审计跟踪，并在需要时执行取证分析。
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