MQTT and Microsoft SQL Server Integration
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Table of Contents
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Input and output integration overview
The MQTT plugin reads from the specified topics and creates metrics using the supported input data formats.
Telegraf’s SQL output plugin facilitates the storage of metrics in SQL databases. When configured for Microsoft SQL Server, it supports the specific DSN format and schema requirements, allowing for seamless integration with SQL Server.
Integration details
MQTT
This plugin allows Telegraf to consume metrics from specified MQTT topics. It supports a variety of configuration options to connect to MQTT brokers and manage message subscriptions, including features for handling startup errors and using TLS for secure connections.
Microsoft SQL Server
The SQL output plugin enables Telegraf to write metrics to an SQL database using a dynamic table-per-metric schema. For Microsoft SQL Server, it utilizes the go-mssqldb driver with a DSN that follows the sqlserver URL format.
Configuration
MQTT
[[inputs.mqtt_consumer]]
servers = ["tcp://127.0.0.1:1883"]
topics = [
"telegraf/host01/cpu",
"telegraf/+/mem",
"sensors/#",
]
# topic_tag = "topic"
# qos = 0
# connection_timeout = "30s"
# keepalive = "60s"
# ping_timeout = "10s"
# max_undelivered_messages = 1000
# persistent_session = false
# client_id = ""
# username = "telegraf"
# password = "metricsmetricsmetricsmetrics"
# tls_ca = "/etc/telegraf/ca.pem"
# tls_cert = "/etc/telegraf/cert.pem"
# tls_key = "/etc/telegraf/key.pem"
# insecure_skip_verify = false
# client_trace = false
data_format = "influx"
# [[inputs.mqtt_consumer.topic_parsing]]
# topic = ""
# measurement = ""
# tags = ""
# fields = ""
# [inputs.mqtt_consumer.topic_parsing.types]
# key = type
Microsoft SQL Server
[[outputs.sql]]
## Database driver
## Valid options: mssql (Microsoft SQL Server), mysql (MySQL), pgx (Postgres),
## sqlite (SQLite3), snowflake (snowflake.com), clickhouse (ClickHouse)
driver = "mssql"
## Data source name
## For Microsoft SQL Server, the DSN typically includes the server, port, username, password, and database name.
## Example DSN: "sqlserver://username:password@localhost:1433?database=telegraf"
data_source_name = "sqlserver://username:password@localhost:1433?database=telegraf"
## 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
## You can customize the mapping if needed.
#[outputs.sql.convert]
# integer = "INT"
# real = "DOUBLE"
# text = "TEXT"
# timestamp = "TIMESTAMP"
# defaultvalue = "TEXT"
# unsigned = "UNSIGNED"
# bool = "BOOL"
Input and output integration examples
MQTT
-
Basic Configuration: This example connects to a local MQTT broker, subscribes to specific topics for CPU and memory metrics, and outputs using the Influx data format.
-
Topic Parsing: Extracts tag values from MQTT topics for better data organization and analysis, allowing metrics to be categorized based on their topics.
-
Field Pivoting: Demonstrates how to pivot single-valued metrics into a multi-field metric. This is useful for consolidating data from multiple sensors into a single metric.
Microsoft SQL Server
- Basic MSSQL Setup: Set the driver to ‘mssql’ and configure the DSN with your SQL Server connection details to enable metric storage.
- Custom Schema Management: Adjust the table creation and existence check templates to define a custom schema that meets your organizational standards.
- Initialization SQL: Use the init_sql setting to run any necessary SQL commands to prepare your SQL Server environment before metrics ingestion.
- Connection Tuning: Modify connection pool settings such as connection_max_idle_time and connection_max_open to optimize performance based on your workload.
Feedback
Thank you for being part of our community! If you have any general feedback or found any bugs on these pages, we welcome and encourage your input. Please submit your feedback in the InfluxDB community Slack.
Powerful Performance, Limitless Scale
Collect, organize, and act on massive volumes of high-velocity data. Any data is more valuable when you think of it as time series data. with InfluxDB, the #1 time series platform built to scale with Telegraf.
See Ways to Get Started
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