Azure Event Hubs 和 MariaDB 集成

强大的性能和简单的集成,由 InfluxData 构建的开源数据连接器 Telegraf 提供支持。

info

这不是实时大规模查询的推荐配置。为了实现查询和压缩优化、高速摄取和高可用性,您可能需要考虑 Azure Event Hubs 和 InfluxDB

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时间序列数据库
来源:DB Engines

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贡献者

目录

强大的性能,无限的扩展能力

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,它都会变得更有价值。InfluxDB 是排名第一的时间序列平台,旨在与 Telegraf 一起扩展。

查看入门方法

输入和输出集成概述

Azure Event Hubs 输入插件允许 Telegraf 从 Azure Event Hubs 和 Azure IoT Hub 消费数据,从而能够高效地处理和监控来自这些云服务的事件流。

此插件使用参数化的 SQL INSERT 语句将指标从 Telegraf 直接写入 MariaDB,从而提供了一种灵活的方式将指标存储在结构化的关系表中。

集成详情

Azure Event Hubs

此插件充当 Azure Event Hubs 和 Azure IoT Hub 的消费者,允许用户高效地从这些平台摄取数据流。Azure Event Hubs 是一个高度可扩展的数据流平台和事件摄取服务,能够每秒接收和处理数百万个事件,而 Azure IoT Hub 支持物联网应用中安全的设备到云和云到设备通信。Event Hub 输入插件与这些服务无缝交互,提供可靠的消息消费和流处理能力。主要功能包括消费者组的动态管理、防止数据丢失的消息跟踪以及用于预取计数、用户代理和元数据处理的可自定义设置。此插件旨在支持各种用例,包括实时遥测数据收集、物联网数据处理以及与更广泛的 Azure 生态系统中的各种数据分析和监控工具集成。

MariaDB

Telegraf 中的 SQL 输出插件允许通过执行参数化的 SQL 语句将指标直接写入与 SQL 兼容的数据库(如 MariaDB)。凭借对 MySQL 驱动程序的支持,该插件与 MariaDB 无缝集成,实现可靠、结构化的指标存储。此设置非常适合喜欢基于 SQL 的分析或希望将指标与业务数据一起存储以进行统一查询的用户。MariaDB 是 MySQL 的一个社区开发的、企业级的分支,强调性能、安全性和开放性。该插件支持将时间序列指标插入到自定义模式中,从而可以使用 SQL 连接器灵活地进行分析并与 Metabase 或 Grafana 等 BI 工具集成。

配置

Azure Event Hubs

[[inputs.eventhub_consumer]]
  ## The default behavior is to create a new Event Hub client from environment variables.
  ## This requires one of the following sets of environment variables to be set:
  ##
  ## 1) Expected Environment Variables:
  ##    - "EVENTHUB_CONNECTION_STRING"
  ##
  ## 2) Expected Environment Variables:
  ##    - "EVENTHUB_NAMESPACE"
  ##    - "EVENTHUB_NAME"
  ##    - "EVENTHUB_KEY_NAME"
  ##    - "EVENTHUB_KEY_VALUE"

  ## 3) Expected Environment Variables:
  ##    - "EVENTHUB_NAMESPACE"
  ##    - "EVENTHUB_NAME"
  ##    - "AZURE_TENANT_ID"
  ##    - "AZURE_CLIENT_ID"
  ##    - "AZURE_CLIENT_SECRET"

  ## Uncommenting the option below will create an Event Hub client based solely on the connection string.
  ## This can either be the associated environment variable or hard coded directly.
  ## If this option is uncommented, environment variables will be ignored.
  ## Connection string should contain EventHubName (EntityPath)
  # connection_string = ""

  ## Set persistence directory to a valid folder to use a file persister instead of an in-memory persister
  # persistence_dir = ""

  ## Change the default consumer group
  # consumer_group = ""

  ## By default the event hub receives all messages present on the broker, alternative modes can be set below.
  ## The timestamp should be in https://github.com/toml-lang/toml#offset-date-time format (RFC 3339).
  ## The 3 options below only apply if no valid persister is read from memory or file (e.g. first run).
  # from_timestamp =
  # latest = true

  ## Set a custom prefetch count for the receiver(s)
  # prefetch_count = 1000

  ## Add an epoch to the receiver(s)
  # epoch = 0

  ## Change to set a custom user agent, "telegraf" is used by default
  # user_agent = "telegraf"

  ## To consume from a specific partition, set the partition_ids option.
  ## An empty array will result in receiving from all partitions.
  # partition_ids = ["0","1"]

  ## Max undelivered messages
  ## This plugin uses tracking metrics, which ensure messages are read to
  ## outputs before acknowledging them to the original broker to ensure data
  ## is not lost. This option sets the maximum messages to read from the
  ## broker that have not been written by an output.
  ##
  ## This value needs to be picked with awareness of the agent's
  ## metric_batch_size value as well. Setting max undelivered messages too high
  ## can result in a constant stream of data batches to the output. While
  ## setting it too low may never flush the broker's messages.
  # max_undelivered_messages = 1000

  ## Set either option below to true to use a system property as timestamp.
  ## You have the choice between EnqueuedTime and IoTHubEnqueuedTime.
  ## It is recommended to use this setting when the data itself has no timestamp.
  # enqueued_time_as_ts = true
  # iot_hub_enqueued_time_as_ts = true

  ## Tags or fields to create from keys present in the application property bag.
  ## These could for example be set by message enrichments in Azure IoT Hub.
  # application_property_tags = []
  # application_property_fields = []

  ## Tag or field name to use for metadata
  ## By default all metadata is disabled
  # sequence_number_field = "SequenceNumber"
  # enqueued_time_field = "EnqueuedTime"
  # offset_field = "Offset"
  # partition_id_tag = "PartitionID"
  # partition_key_tag = "PartitionKey"
  # iot_hub_device_connection_id_tag = "IoTHubDeviceConnectionID"
  # iot_hub_auth_generation_id_tag = "IoTHubAuthGenerationID"
  # iot_hub_connection_auth_method_tag = "IoTHubConnectionAuthMethod"
  # iot_hub_connection_module_id_tag = "IoTHubConnectionModuleID"
  # iot_hub_enqueued_time_field = "IoTHubEnqueuedTime"

  ## Data format to consume.
  ## Each data format has its own unique set of configuration options, read
  ## more about them here:
  ## https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md
  data_format = "influx"

MariaDB

[[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})"

  ## SQL INSERT statement with placeholders. Telegraf will substitute values at runtime.
  ## table_template = "INSERT INTO metrics (timestamp, name, value, tags) VALUES (?, ?, ?, ?)"

  ## 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

Azure Event Hubs

  1. 实时物联网设备监控:使用 Azure Event Hubs 插件监控来自物联网设备(如传感器和执行器)的遥测数据。通过将设备数据流式传输到监控仪表板,组织可以深入了解系统性能、跟踪使用模式并快速响应异常情况。此设置允许对设备进行主动管理,从而提高运营效率并减少停机时间。

  2. 事件驱动的数据处理工作流:利用此插件响应从 Azure Event Hubs 收到的事件来触发数据处理工作流。例如,当新事件到达时,它可以启动数据转换、聚合或存储过程,从而使企业能够更有效地自动化其工作流。这种集成增强了响应能力并简化了跨系统的运营。

  3. 与分析平台集成:实施该插件以将事件数据输送到 Azure Synapse 或 Power BI 等分析平台。通过将实时流数据集成到分析工具中,组织可以执行全面的数据分析、推动商业智能工作并创建交互式可视化效果,从而为决策提供信息。

  4. 跨平台数据同步:利用 Azure Event Hubs 插件跨不同系统或平台同步数据流。通过从 Azure Event Hubs 消费数据并将其转发到数据库或云存储等其他系统,组织可以在其整个架构中维护一致且最新的信息,从而实现有凝聚力的数据策略。

MariaDB

  1. 商业智能集成:将应用程序性能指标直接存储到 MariaDB 中,并将其连接到 Metabase 或 Apache Superset 等 BI 工具。此设置允许将运营数据与业务 KPI 相结合,以实现统一的仪表板,从而提高跨部门的可见性。

  2. 具有历史指标的合规性报告:使用此插件将指标记录到 MariaDB 中,用于审计和合规性用例。关系模型能够使用带时间戳的条目精确查询过去的绩效指标,从而支持监管文档。

  3. 基于 SQL 逻辑的自定义警报:将指标插入到 MariaDB 中,并使用自定义 SQL 查询来定义警报阈值或条件。与 cron 作业或计划脚本结合使用,这可以实现传统指标平台无法实现的高级警报工作流。

  4. 物联网传感器指标存储:通过 Telegraf 收集来自物联网设备的传感器数据,并使用规范化模式将其存储在 MariaDB 中。这种方法经济高效,并且与现有的基于 SQL 的系统集成良好,可用于实时或历史分析。

反馈

感谢您成为我们社区的一份子!如果您有任何一般性反馈或在这些页面上发现了任何错误,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,无限的扩展能力

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,它都会变得更有价值。InfluxDB 是排名第一的时间序列平台,旨在与 Telegraf 一起扩展。

查看入门方法

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