From 6b47513e074d56507efca3147a5e362ffd2c57ac Mon Sep 17 00:00:00 2001 From: gccgdb1234 Date: Tue, 23 Jul 2024 09:14:38 +0800 Subject: [PATCH] doc: refactor document --- docs/zh/07-operation/01-intro.md | 88 ++ docs/zh/07-operation/02-planning.md | 156 ++++ docs/zh/07-operation/03-deployment.md | 828 ++++++++++++++++++ docs/zh/07-operation/index.md | 5 + docs/zh/07-operation/tdengine-topology.png | Bin 0 -> 251989 bytes docs/zh/08-connector/26-rust.mdx | 8 +- docs/zh/08-connector/43-r-lang.mdx | 2 +- .../01-connect/_category_.yml | 0 .../01-connect/_connect_c.mdx | 0 .../01-connect/_connect_cs.mdx | 0 .../01-connect/_connect_go.mdx | 0 .../01-connect/_connect_java.mdx | 0 .../01-connect/_connect_node.mdx | 0 .../01-connect/_connect_php.mdx | 0 .../01-connect/_connect_python.mdx | 0 .../01-connect/_connect_r.mdx | 0 .../01-connect/_connect_rust.mdx | 0 .../01-connect/connection-type-zh.webp | Bin .../01-connect/index.md | 0 .../02-model/_category_.yml | 0 .../02-model/index.mdx | 0 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100644 docs/zh/10-deployment/05-helm.md delete mode 100644 docs/zh/10-deployment/_category_.yml delete mode 100644 docs/zh/10-deployment/index.md diff --git a/docs/zh/07-operation/01-intro.md b/docs/zh/07-operation/01-intro.md new file mode 100644 index 0000000000..e7d7641808 --- /dev/null +++ b/docs/zh/07-operation/01-intro.md @@ -0,0 +1,88 @@ +--- +sidebar_label: 组件介绍 +title: 组件介绍 +toc_max_heading_level: 4 +--- + +在 TDengine 的安装包中，除了 TDengine 数据库引擎 taosd 以外，还提供了一些附加组件，以方便用户的使用。taosAdapter 是应用和 TDengine 之间的桥梁；taosKeeper 是TDengine 监控指标的导出工具；taosX 是数据管道（data pipeline）工具；taosExplorer 是可视化图形管理工具；taosc 是 TDengine 客户端驱动。下图展示了整个 TDengine 产品生态的拓扑架构（组件 taosX、taosX Agent 仅 TDengine Enterprise 提供）。 + +![TDengine 产品生态拓扑架构](./tdengine-topology.png) + +## taosd + +在 TDengine 中，taosd 是一个关键的守护进程，同时也是核心服务进程。它负责处理所有与数据相关的操作，包括数据写入、查询和管理等。在 Linux 操作系统中，用户可以利用 systemd 命令来便捷地启动、停止 taosd 进程。为了查看 taosd 的所有命令行参数，用户可以执行 taosd -h 命令。 + +taosd 进程的日志默认存储在 /var/log/taos/ 目录下，方便用户进行日志查看和管理。 + +TDengine 采用 vnode 机制对存储的数据进行切分，每个 vnode 包含一定数量的数据采集点的数据。为了提供高可用服务，TDengine 采用多副本方式，确保数据的可靠性和持久性。不同节点上的 vnode 可以组成一个 vgroup，实现实时数据同步。这种设计不仅提高了数据的可用性和容错能力，还有助于实现负载均衡和高效的数据处理。 + +## taosc + +taosc 是 TDengine 的客户端程序，为开发人员提供了一组函数和接口，以便编写应用程序并连接到 TDengine，执行各种 SQL。由于 taosc 是用 C 语言编写的，因此可以轻松地与 C/C++ 应用程序集成。 + +当使用其他编程语言与 TDengine 交互时，如果使用原生连接，也需要依赖 taosc。这是因为 taosc 提供了与 TDengine 通信所需的底层协议和数据结构，确保了不同编程语言应用程序能够顺利地与 TDengine 进行交互。 + +通过使用 taosc，开发人员可以轻松地构建与 TDengine 交互的应用程序，实现数据的存储、查询和管理等功能。这种设计提高了应用程序的可维护性和可扩展性，同时降低了开发难度，使得开发人员能够专注于业务逻辑的实现。 + +## taosAdapter + +taosAdapter 是 TDengine 安装包中的一个标准组件，充当着 TDengine 集群与应用程序之间的桥梁和适配器角色。它支持用户通过 RESTful 接口和 WebSocket 连接访问TDengine 服务，实现数据的便捷接入和处理。 + +taosAdapter 能够与各种数据收集代理工具（如 Telegraf、StatsD、collectd 等）无缝对接，从而将数据导入 TDengine。此外，它还提供了与 InfluxDB/OpenTSDB 兼容的数据写入接口，使得原本使用 InfluxDB/OpenTSDB 的应用程序能够轻松移植到 TDengine 上，无须进行大量修改。 + +通过 taosAdapter，用户可以灵活地将 TDengine 集成到现有的应用系统中，实现数据的实时存储、查询和分析。 + +taosAdapter 提供了以下功能： +- RESTful 接口； +- WebSocket 连接； +- 兼容 InfluxDB v1 格式写入； +- 兼容 OpenTSDB JSON 和 Telnet 格式写入； +- 无缝连接到 Telegraf； +- 无缝连接到 collectd； +- 无缝连接到 StatsD； +- 支持 Prometheus remote_read 和 remote_write。 + +## taosKeeper + +taosKeeper 是 TDengine 3.0 版本中新增的监控指标导出工具，旨在方便用户对TDengine 的运行状态和性能指标进行实时监控。通过简单的配置，TDengine 能够将其运行状态、指标等信息上报给 taosKeeper。当接收到监控数据后，taosKeeper 会利用 taosAdapter 提供的 RESTful 接口，将这些数据存储到 TDengine 中。 + +taosKeeper 的一个重要价值在于，它能够将多个甚至一批 TDengine 集群的监控数据集中存储在一个统一的平台上。这使得监控软件能够轻松获取这些数据，从而实现对 TDengine 集群的全面监控和实时分析。通过 taosKeeper，用户可以更加便捷地掌握TDengine 的运行状况，及时发现并解决潜在问题，确保系统的稳定性和高效性。 + +## taosExplorer + +为了简化用户对数据库的使用和管理，TDengine Enterprise 引入了一个全新的可视化组件—taosExplorer。这个工具为用户提供了一个直观的界面，方便用户轻松管理数据库系统中的各类元素，如数据库、超级表、子表等，以及它们的生命周期。 + +通过 taosExplorer，用户可以执行 SQL 查询，实时监控系统状态、管理用户权限、完成数据的备份和恢复操作。此外，它还支持与其他集群之间的数据同步、导出数据，以及管理主题和流计算等功能。 + +值得一提的是，taosExplorer 的社区版与企业版在功能上有所区别。企业版提供了更丰富的功能和更高级别的技术支持，以满足企业用户的需求。具体的差异和详细信息，用户可以查阅 TDengine 的官方文档。 + +## taosX + +taosX 作为 TDengine Enterprise 的数据管道功能组件，旨在为用户提供一种无须编写代码即可轻松对接第三方数据源的方法，实现数据的便捷导入。目前，taosX 已支持众多主流数据源，包括 AVEVA PI System、AVEVA Historian、OPC-UA/DA、InfluxDB、OpenTSDB、MQTT、Kafka、CSV、TDengine 2.x、TDengine 3.x、MySQL、PostgreSQL和 Oracle 等。 + +在实际使用中， 用户通常无须直接与 taosX 进行交互。 相反， 他们可以通 过taosExplorer 提供的浏览器用户界面轻松访问和使用 taosX 的强大功能。这种设计简化了操作流程，降低了使用门槛，使得用户能够更加专注于数据处理和分析，从而提高工作效率。 + +## taosX Agent + +taosX Agent 是 TDengine Enterprise 数据管道功能的重要组成部分，它与 taosX 协同工作，负责接收 taosX 下发的外部数据源导入任务。taosX Agent 能够启动连接器或直接从外部数据源获取数据，随后将采集的数据转发给 taosX 进行处理。 + +在边云协同场景中，taosX Agent 通常部署在边缘侧，尤其适用于那些外部数据源无法直接通过公网访问的情况。通过在边缘侧部署 taosX Agent，可以有效地解决网络限制和数据传输延迟等问题，确保数据的实时性和安全性。 + +## 应用程序或第三方工具 + +通过与各类应用程序、可视化和 BI（Business Intelligence，商业智能）工具以及数据源集成，TDengine 为用户提供了灵活、高效的数据处理和分析能力，以满足不同场景下的业务需求。应用程序或第三方工具主要包括以下几类。 + +1. 应用程序 + +这些应用程序负责向业务集群写入、查询业务数据以及订阅数据。应用程序可以通过以下 3 种方式与业务集群进行交互。 +- 基于 taosc 的应用程序：采用原生连接的应用程序，直接连接到业务集群，默认端口为 6030。 +- 基于 RESTful 连接的应用程序：使用 RESTful 接口访问业务集群的应用程序，需要通过 taosAdapter 进行连接，默认端口为 6041。 +- 基于 WebSkcket 连接的应用程序：采用 WebSocket 连接的应用程序，同样需要通过 taosAdapter 进行连接，默认端口为 6041。 + +2. 可视化/BI 工具 + +TDengine 支持与众多可视化及 BI 工具无缝对接，如 Grafana、Power BI 以及国产的可视化和 BI 工具。此外，用户还可以利用 Grafana 等工具来监测 TDengine 集群的运行状态。 + +3. 数据源 + +TDengine 具备强大的数据接入能力，可以对接各种数据源，如 MQTT、OPC-UA/DA、Kafka、AVEVA PI System、AVEVA Historian 等。这使得 TDengine 能够轻松整合来自不同数据源的数据，为用户提供全面、统一的数据视图。 \ No newline at end of file diff --git a/docs/zh/07-operation/02-planning.md b/docs/zh/07-operation/02-planning.md new file mode 100644 index 0000000000..dc119b5166 --- /dev/null +++ b/docs/zh/07-operation/02-planning.md @@ -0,0 +1,156 @@ +--- +sidebar_label: 容量规划 +title: 容量规划 +toc_max_heading_level: 4 +--- + +若计划使用 TDengine 搭建一个时序数据平台，须提前对计算资源、存储资源和网络资源进行详细规划，以确保满足业务场景的需求。通常 TDengine 会运行多个进程，包括taosd、taosadapter、taoskeeper、taos-explorer 和 taosx。 + +在这些进程中，taoskeeper、taos-explorer、taosadapter 和 taosx 的资源占用相对较少，通常不需要特别关注。此外，这些进程对存储空间的需求也较低，其占用的 CPU 和内存资源一般为 taosd 进程的十分之一到几分之一（特殊场景除外，如数据同步和历史数据迁移。在这些情况下，涛思数据的技术支持团队将提供一对一的服务）。系统管理员应定期监控这些进程的资源消耗，并及时进行相应处理。 + +在本节中，我们将重点讨论 TDengine 数据库引擎的核心进程—taosd 的资源规划。合理的资源规划将确保 taosd 进程的高效运行，从而提高整个时序数据平台的性能和稳定性。 + +## 服务器内存需求 + +每个数据库能够创建固定数量的 vgroup，默认情况下为两个。在创建数据库时，可以通过 `vgroups` 参数指定 vgroup 的数量，而副本数则由 `replica` 参数确定。由于每个 vgroup 中的副本会对应一个 vnode，因此数据库所占用的内存由参数 vgroups、replica、buffer、pages、pagesize 和 cachesize 确定。 + +为了帮助用户更好地理解和配置这些参数，TDengine 的官方文档的数据库管理部分提供了详细说明。根据这些参数，可以估算出一个数据库所需的内存大小，具体计算方式如下（具体数值须根据实际情况进行调整）。 +vgroups ×replica × (buffer + pages × pagesize + cachesize) + +需要明确的是，这些内存资源并非仅由单一服务器承担，而是由整个集群中的所有dnode 共同分摊，也就是说，这些资源的负担实际上是由这些 dnode 所在的服务器集群共同承担的。若集群内存在多个数据库，那么所需的内存总量还须将这些数据库的需求累加起来。更为复杂的情形在于，如果集群中的 dnode 并非一开始就全部部署完毕，而是在使用过程中随着节点负载的上升逐步添加服务器和 dnode，那么新加入的数据库可能会导致新旧 dnode 之间的负载分布不均。在这种情况下，简单地进行理论计算是不够准确的，必须考虑到各个 dnode 的实际负载状况来进行综合评估。 + +系统管理员可以通过如下 SQL 查看 information_schema 库中的 ins_vnodes 表来获得所有数据库所有 vnodes 在各个 dnode 上的分布。 + +```sql +select * from information_schema.ins_vnodes; +dnode_id |vgroup_id | db_name | status | role_time | start_time | restored | +=============================================================================================== + 1| 3 | log | leader | 2024-01-16 13:52:13.618 | 2024-01-16 13:52:01.628 | true | + 1| 4 | log | leader | 2024-01-16 13:52:13.630 | 2024-01-16 13:52:01.702 | true | +``` + +## 客户端内存需求 + +1. 原生连接方式 + +由于客户端应用程序采用 taosc 与服务器进行通信，因此会产生一定的内存消耗。这些内存消耗主要源于：写入操作中的 SQL、表元数据信息的缓存，以及固有的结构开销。假设该数据库服务能够支持的最大表数量为 N（每个通过超级表创建的表的元数据开销约为 256B），最大并发写入线程数为 T，以及最大 SQL 语句长度为 S（通常情况下为1MB）。基于这些参数，我们可以对客户端的内存消耗进行估算（单位为 MB）。 +M = (T × S × 3 + (N / 4096) + 100) + +例如，用户最大并发写入线程数为 100，子表数为 10 000 000，那么客户端的内存最低要求如下： +100 × 3 + (10000000 / 4096) + 100 ≈ 2841 (MB) +即配置 3GB 内存是最低要求。 + +2. RESTful/WebSocket 连接方式 + +当将 WebSocket 连接方式用于数据写入时，如果内存占用不大，通常可以不予关注。然而，在执行查询操作时，WebSocket 连接方式会消耗一定量的内存。接下来，我们将详细讨论查询场景下的内存使用情况。 + +当客户端通过 WebSocket 连接方式发起查询请求时，为了接收并处理查询结果，必须预留足够的内存空间。得益于 WebSocket 连接方式的特性，数据可以分批次接收和解码，这样就能够在确保每个连接所需内存固定的同时处理大量数据。 + +计算客户端内存占用的方法相对简单：只须将每个连接所需的读 / 写缓冲区容量相加即可。通常每个连接会额外占用 8MB 的内存。因此，如果有 C 个并发连接，那么总的额 +外内存需求就是 8×C（单位 MB）。 + +例如，如果用户最大并发连接数为 10，则客户端的额外内存最低要求是 80（8×10）MB。 + +与 WebSocket 连接方式相比，RESTful 连接方式在内存占用上更大，除了缓冲区所需的内存以外，还需要考虑每个连接响应结果的内存开销。这种内存开销与响应结果的JSON 数据大小密切相关，特别是在查询数据量很大时，会占用大量内存。 + +由于 RESTful 连接方式不支持分批获取查询数据，这就导致在查询获取超大结果集时，可能会占用特别大的内存，从而导致内存溢出，因此，在大型项目中，建议打开batchfetch=true 选项，以启用 WebSocket 连接方式，实现流式结果集返回，从而避免内存溢出的风险 + +**注意** +- 建议采用 RESTful/WebSocket 连接方式来访问 TDengine 集群，而不采用taosc 原生连接方式。 +- 在绝大多数情形下，RESTful/WebSocket 连接方式均满足业务写入和查询要求，并且该连接方式不依赖于 taosc，集群服务器升级与客户端连接方式完全解耦，使得服务器维护、升级更容易。 + +## CPU 需求 + +TDengine 用户对 CPU 的需求主要受以下 3 个因素影响： +- 数据分片：在 TDengine 中，每个 CPU 核心可以服务 1 至 2 个 vnode。假设一个集群配置了 100 个 vgroup，并且采用三副本策略，那么建议该集群的 CPU 核心数量为 150~300 个，以实现最佳性能。 +- 数据写入：TDengine 的单核每秒至少能处理 10 000 个写入请求。值得注意的是，每个写入请求可以包含多条记录，而且一次写入一条记录与同时写入 10 条记录相比，消耗的计算资源相差无几。因此，每次写入的记录数越多，写入效率越高。例如，如果一个写入请求包含 200 条以上记录，单核就能实现每秒写入 100 万条记录的速度。然而，这要求前端数据采集系统具备更高的能力，因为它需要缓存记录，然后批量写入。 +- 查询需求：虽然 TDengine 提供了高效的查询功能，但由于每个应用场景的查询差异较大，且查询频次也会发生变化，因此很难给出一个具体的数字来衡量查询所需的计算资源。用户需要根据自己的实际场景编写一些查询语句，以便更准确地确定所需的计算资源。 + +综上所述，对于数据分片和数据写入，CPU 的需求是可以预估的。然而，查询需求所消耗的计算资源则难以预测。在实际运行过程中，建议保持 CPU 使用率不超过 50%，以确保系统的稳定性和性能。一旦 CPU 使用率超过这一阈值，就需要考虑增加新的节点或增加 CPU 核心数量，以提供更多的计算资源。 + +## 存储需求 + +相较于传统通用数据库，TDengine 在数据压缩方面表现出色，拥有极高的压缩率。在大多数应用场景中，TDengine 的压缩率通常不低于 5 倍。在某些特定情况下，压缩率 +甚至可以达到 10 倍乃至上百倍，这主要取决于实际场景中的数据特征。 + +要计算压缩前的原始数据大小，可以采用以下方式： +RawDataSize = numOfTables × rowSizePerTable × rowsPerTable + +示例：1000 万块智能电表，电表每 15min 采集一次数据，每次采集的数据量为 20B，那么一年的原始数据量约 7TB。TDengine 大概需要消耗 1.4TB 存储空间。 + +为了迎合不同用户在数据存储时长及成本方面的个性化需求，TDengine 赋予了用户极大的灵活性，用户可以通过一系列数据库参数配置选项来定制存储策略。其中，keep参数尤其引人注目，它赋予用户自主设定数据在存储空间上的最长保存期限的能力。这一功能设计使得用户能够依据业务的重要性和数据的时效性，精准调控数据的存储生命周期，进而实现存储成本的精细化控制。 + +然而，单纯依赖 keep 参数来优化存储成本仍显不足。为此，TDengine 进一步创新，推出了多级存储策略。 + +此外，为了加速数据处理流程，TDengine 特别支持配置多块硬盘，以实现数据的并发写入与读取。这种并行处理机制能够最大化利用多核 CPU 的处理能力和硬盘 I/O 带宽，大幅提高数据传输速度，完美应对高并发、大数据量的应用场景挑战。 + +**技巧** 如何估算 TDengine 压缩率 +```text +用户可以利用性能测试工具 taosBenchmark 来评估 TDengine 的数据压缩效果。通过使用 -f 选项指定写入配置文件，taosBenchmark 可以将指定数量的 CSV 样例数据写入指定的库参数和表结构中。 +在完成数据写入后，用户可以在 taos shell 中执行 flush database 命令，将所有数据强制写入硬盘。接着，通过 Linux 操作系统的 du 命令获取指定 vnode 的数据文件夹大小。最后，将原始数据大小除以实际存储的数据大小，即可计算出真实的压缩率。 +``` + +通过如下命令可以获得 TDengine 占用的存储空间。 +```shell +taos> flush database ; +$ du -hd1 /vnode --exclude=wal +``` + +## 多级存储 + +除了存储容量的需求以外，用户可能还希望在特定容量下降低存储成本。为了满足这一需求，TDengine 推出了多级存储功能。该功能允许将近期产生且访问频率较高的数据存储在高成本存储设备上，而将时间较长且访问频率较低的数据存储在低成本存储设备上。通过这种方式，TDengine 实现了以下目标。 +- 降低存储成本：通过将海量极冷数据存储在廉价存储设备上，可以显著降低存储成本。 +- 提高写入性能：每级存储支持多个挂载点，WAL 文件也支持 0 级的多挂载点并行写入，这些措施极大地提高了写入性能（实际场景中的持续写入速度可达 3 亿测 +点 / 秒），在机械硬盘上也能获得极高的硬盘 I/O 吞吐（实测可达 2GB/s）。 + +用户可以根据冷热数据的比例来决定高速和低成本存储设备之间的容量划分。 + +TDengine 的多级存储功能在使用上还具备以下优点。 +- 方便维护：配置各级存储挂载点后，数据迁移等工作无须人工干预，存储扩容更加灵活、方便。 +- 对 SQL 透明：无论查询的数据是否跨级，一个 SQL 即可返回所有数据，简洁高效 + +## 网络带宽需求 + +网络带宽需求可以分为两个主要部分—写入查询和集群内部通信。 + +写入查询是指面向业务请求的带宽需求，即客户端向服务器发送数据以进行写入操作的带宽需求。 + +集群内部通信的带宽需求进一步分为两部分： +- 各节点间正常通信的带宽需求，例如，leader 将数据分发给各 follower，taosAdapter 将写入请求分发给各 vgroup leader 等。 +- 集群为响应维护指令而额外需要的内部通信带宽，如从单副本切换到三副本导致的数据复制、修复指定 dnode 引发的数据复制等情况。 + +为了估算入站带宽需求，我们可以采用以下方式： +由 于 taosc 写入在 RPC 通信过程中自带压缩功能，因此写入带宽需求相对于RESTful/WebSocket 连接方式较低。在这里，我们将基于 RESTful/WebSocket 连接方式的 +带宽需求来估算写入请求的带宽。 + +示例：1000 万块智能电表，电表每 15min 采集一次数据，每次采集的数据量为 20B，可计算出平均带宽需求为 0.22MB。 + +考虑到智能电表存在集中上报的情况，在计算带宽需求时须结合实际项目情况增加带宽需求。考虑到 RESTful 请求以明文传输，实际带宽需求还应乘以倍数，只有这样才能得到估算值。 + + +**提示** +```text +网络带宽和通信延迟对于分布式系统的性能与稳定性至关重要，特别是在服务器节点间的网络连接方面。 +我们强烈建议为服务器节点间的网络专门分配 VLAN，以避免外部通信干扰。在带宽选择上，建议使用万兆网络，至少也要千兆网络，并确保丢包率低于万分之一。 +如果采用分布式存储方案，必须将存储网络和集群内部通信网络分开规划。一个常见的做法是采用双万兆网络，即两套独立的万兆网络。这样可以确保存储数据和集群内部通信互不干扰，提高整体性能。 +对于入站网络，除了要保证足够的接入带宽以外，还须确保丢包率同样低于万分之一。这将有助于减少数据传输过程中的错误和重传，从而提高系统的可靠性和效率。 +``` + +## 服务器数量 + +根据前面对内存、CPU、存储和网络带宽的预估，我们可以得出整个 TDengine 集群所需的内存容量、CPU 核数、存储空间以及网络带宽。若数据副本数不是 1，还需要将总需求量乘以副本数以得到实际所需资源。 + +得益于 TDengine 出色的水平扩展能力，我们可以轻松计算出资源需求的总量。接下来，只须将这个总量除以单台物理机或虚拟机的资源量，便能大致确定需要购买多少台物理机或虚拟机来部署 TDengine 集群。 + +## 网络端口要求 + +下表列出了 TDengine 的一些接口或组件的常用端口，这些端口均可以通过配置文件中的参数进行修改。 + +|接口或组件 | 端口 | +|:---------------------------:|:---------:| +|原生接口（taosc） | 6030 | +|RESTful 接口 | 6041 | +|WebSocket 接口 |6041 | +|taosKeeper | 6043 | +|taosX | 6055 | +|taosExplorer | 6060 | \ No newline at end of file diff --git a/docs/zh/07-operation/03-deployment.md b/docs/zh/07-operation/03-deployment.md new file mode 100644 index 0000000000..e1ff48da04 --- /dev/null +++ b/docs/zh/07-operation/03-deployment.md @@ -0,0 +1,828 @@ +--- +sidebar_label: 集群部署 +title: 集群部署 +toc_max_heading_level: 4 +--- + +由于 TDengine 设计之初就采用了分布式架构，具有强大的水平扩展能力，以满足不断增长的数据处理需求，因此 TDengine 支持集群，并将此核心功能开源。用户可以根据实际环境和需求选择 4 种部署方式—手动部署、Docker 部署、Kubernetes 部署和 Helm 部署。 + +## 手动部署 + +按照以下步骤手动搭建 TDengine 集群。 + +### 清除数据 + +如果搭建集群的物理节点中存在之前的测试数据或者装过其他版本（如 1.x/2.x）的TDengine，请先将其删除，并清空所有数据。 + +### 检查环境 + +在进行 TDengine 集群部署之前，全面检查所有 dnode 以及应用程序所在物理节点的网络设置至关重要。以下是检查步骤： + +第 1 步，在每个物理节点上执行 hostname -f 命令，以查看并确认所有节点的hostname 是唯一的。对于应用程序驱动所在的节点，这一步骤可以省略。 +第 2 步，在每个物理节点上执行 ping host 命令，其中 host 是其他物理节点的 hostname。这一步骤旨在检测当前节点与其他物理节点之间的网络连通性。如果发现无法 ping 通，请立即检查网络和 DNS 设置。对于 Linux 操作系统，请检查 /etc/hosts 文件；对于 Windows 操作系统，请检查C:\Windows\system32\drivers\etc\hosts 文件。网络不通畅将导致无法组建集群，请务必解决此问题。 +第 3 步，在应用程序运行的物理节点上重复上述网络监测步骤。如果发现网络不通畅，应用程序将无法连接到 taosd 服务。此时，请仔细检查应用程序所在物理节点的DNS 设置或 hosts 文件，确保其配置正确无误。 +第 4 步，检查端口，确保集群中所有主机在端口 6030 上的 TCP 能够互通。 + +通过以上步骤，你可以确保所有节点在网络层面顺利通信，从而为成功部署TDengine 集群奠定坚实基础 + +### 安装 TDengine + +为了确保集群内各物理节点的一致性和稳定性，请在所有物理节点上安装相同版本的 TDengine。 + +### 修改配置 + +修改 TDengine 的配置文件（所有节点的配置文件都需要修改）。假设准备启动的第 1 个 dnode 的 endpoint 为 h1.taosdata.com:6030，其与集群配置相关参数如下。 + +```shell +# firstEp 是每个 dnode 首次启动后连接的第 1 个 dnode +firstEp h1.taosdata.com:6030 +# 必须配置为本 dnode 的 FQDN，如果本机只有一个 hostname，可注释或删除如下这行代码 +fqdn h1.taosdata.com +# 配置本 dnode 的端口，默认是 6030 +serverPort 6030 +``` + +一定要修改的参数是 f irstEp 和 fqdn。对于每个 dnode，f irstEp 配置应该保持一致，但 fqdn 一定要配置成其所在 dnode 的值。其他参数可不做任何修改，除非你很清楚为什么要修改。 + +对于希望加入集群的 dnode 节点，必须确保下表所列的与 TDengine 集群相关的参数设置完全一致。任何参数的不匹配都可能导致 dnode 节点无法成功加入集群。 + +| 参数名称 | 含义 | +|:---------------:|:----------------------------------------------------------:| +|statusInterval | dnode 向 mnode 报告状态的间隔 | +|timezone | 时区 | +|locale | 系统区位信息及编码格式 | +|charset | 字符集编码 | +|ttlChangeOnWrite | ttl 到期时间是否伴随表的修改操作而改变 | + +### 启动集群 + +按照前述步骤启动第 1 个 dnode，例如 h1.taosdata.com。接着在终端中执行 taos，启动 TDengine 的 CLI 程序 taos，并在其中执行 show dnodes 命令，以查看当前集群中的所有 dnode 信息。 + +```shell +taos> show dnodes; + id | endpoint | vnodes|support_vnodes|status| create_time | note | +=================================================================================== + 1| h1.taosdata.com:6030 | 0| 1024| ready| 2022-07-16 10:50:42.673 | | +``` + +可以看到，刚刚启动的 dnode 节点的 endpoint 为 h1.taosdata.com:6030。这个地址就是新建集群的 first Ep。 + +### 添加 dnode + +按照前述步骤，在每个物理节点启动 taosd。每个 dnode 都需要在 taos.cfg 文件中将 firstEp 参数配置为新建集群首个节点的 endpoint，在本例中是 h1.taosdata.com:6030。在第 1 个 dnode 所在机器，在终端中运行 taos，打开 TDengine 的 CLI 程序 taos，然后登录TDengine 集群，执行如下 SQL。 + +```shell +create dnode "h2.taosdata.com:6030" +``` + +将新 dnode 的 endpoint 添加进集群的 endpoint 列表。需要为 `fqdn:port` 加上双引号，否则运行时出错。请注意将示例的 h2.taosdata.com:6030 替换为这个新 dnode 的 endpoint。然后执行如下 SQL 查看新节点是否成功加入。若要加入的 dnode 当前处于离线状态，请参考本节后面的 “常见问题”部分进行解决。 + +```shell +show dnodes; +``` + +在日志中，请确认输出的 dnode 的 fqdn 和端口是否与你刚刚尝试添加的 endpoint 一致。如果不一致，请修正为正确的 endpoint。遵循上述步骤，你可以持续地将新的 dnode 逐个加入集群，从而扩展集群规模并提高整体性能。确保在添加新节点时遵循正确的流程，这有助于维持集群的稳定性和可靠性。 + +**Tips** +- 任何已经加入集群的 dnode 都可以作为后续待加入节点的 firstEp。firstEp 参数仅仅在该 dnode 首次加入集群时起作用，加入集群后，该 dnode 会保存最新的 mnode 的 endpoint 列表，后续不再依赖这个参数。之后配置文件中的 firstEp 参数主要用于客户端连接，如果没有为 TDengine 的 CLI 设置参数，则默认连接由 firstEp 指定的节点。 +- 两个没有配置 firstEp 参数的 dnode 在启动后会独立运行。这时无法将其中一个dnode 加入另外一个 dnode，形成集群。 +- TDengine 不允许将两个独立的集群合并成新的集群。 + +### 添加 mnode + +在创建 TDengine 集群时，首个 dnode 将自动成为集群的 mnode，负责集群的管理和协调工作。为了实现 mnode 的高可用性，后续添加的 dnode 需要手动创建 mnode。请注意，一个集群最多允许创建 3 个 mnode，且每个 dnode 上只能创建一个 mnode。当集群中的 dnode 数量达到或超过 3 个时，你可以为现有集群创建 mnode。在第 1个 dnode 中，首先通过 TDengine 的 CLI 程序 taos 登录 TDengine，然后执行如下 SQL。 + +```shell +create mnode on dnode +``` + +请注意将上面示例中的 dnodeId 替换为刚创建 dnode 的序号（可以通过执行 `show dnodes` 命令获得）。最后执行如下 `show mnodes`，查看新创建的 mnode 是否成功加入集群。 + +### 删除 dnode + +对于错误加入集群的 dnode 可以通过 `drop dnode ` 命令删除。 + +**Tips** +- 一旦 dnode 被删除，它将无法直接重新加入集群。如果需要重新加入此类节点，你应首先对该节点进行初始化操作，即清空其数据文件夹。 +- 在执行 drop dnode 命令时，集群会先将待删除 dnode 上的数据迁移至其他节点。请注意，drop dnode 与停止 taosd 进程是两个截然不同的操作，请勿混淆。由于删除 dnode 前须执行数据迁移，因此被删除的 dnode 必须保持在线状态，直至删除操作完成。删除操作结束后，方可停止 taosd 进程。 +- 一旦 dnode 被删除，集群中的其他节点将感知到此操作，并且不再接收该 dnodeId 的请求。dnodeId 是由集群自动分配的，用户无法手动指定。 + +### 常见问题 + +在搭建 TDengine 集群的过程中，如果在执行 create dnode 命令以添加新节点后，新节点始终显示为离线状态，请按照以下步骤进行排查。 +第 1 步，检查新节点上的 taosd 服务是否已经正常启动。你可以通过查看日志文件或使用 ps 命令来确认。 +第 2 步，如果 taosd 服务已启动，接下来请检查新节点的网络连接是否畅通，并确认防火墙是否已关闭。网络不通或防火墙设置可能会阻止节点与集群的其他节点通信。 +第 3 步，使用 taos -h fqdn 命令尝试连接到新节点，然后执行 show dnodes 命令。这将显示新节点作为独立集群的运行状态。如果显示的列表与主节点上显示的不一致，说明新节点可能已自行组成一个单节点集群。要解决这个问题，请按照以下步骤操作。首先，停止新节点上的 taosd 服务。其次，清空新节点上 taos.cfg 配置文件中指定的 dataDir 目录下的所有文件。这将删除与该节点相关的所有数据和配置信息。最后，重新启动新节点上的 taosd 服务。这将使新节点恢复到初始状态，并准备好重新加入主集群。 + +### 部署 taosAdapter + +本节讲述如何部署 taosAdapter，taosAdapter 为 TDengine 集群提供 RESTful 和 WebSocket 接入能力，因而在集群中扮演着很重要的角色。 + +1. 安装 + +TDengine Enterprise 安装完成后，即可使用 taosAdapter。如果想在不同的服务器上分别部署 taosAdapter，需要在这些服务器上都安装 TDengine Enterprise。 + +2. 单一实例部署 + +部署 taosAdapter 的单一实例非常简单，具体命令和配置参数请参考手册中 taosAdapter 部分。 + +3. 多实例部署 + +部署 taosAdapter 的多个实例的主要目的如下： +- 提升集群的吞吐量，避免 taosAdapter 成为系统瓶颈。 +- 提升集群的健壮性和高可用能力，当有一个实例因某种故障而不再提供服务时，可以将进入业务系统的请求自动路由到其他实例。 + +在部署 taosAdapter 的多个实例时，需要解决负载均衡问题，以避免某个节点过载而其他节点闲置。在部署过程中，需要分别部署多个单一实例，每个实例的部署步骤与部署单一实例完全相同。接下来关键的部分是配置 Nginx。以下是一个经过验证的较佳实践配置，你只须将其中的 endpoint 替换为实际环境中的正确地址即可。关于各参数的含义，请参考 Nginx 的官方文档。 + +```json +user root; +worker_processes auto; +error_log /var/log/nginx_error.log; + + +events { + use epoll; + worker_connections 1024; +} + +http { + + access_log off; + + map $http_upgrade $connection_upgrade { + default upgrade; + '' close; + } + + server { + listen 6041; + location ~* { + proxy_pass http://dbserver; + proxy_read_timeout 600s; + proxy_send_timeout 600s; + proxy_connect_timeout 600s; + proxy_next_upstream error http_502 non_idempotent; + proxy_http_version 1.1; + proxy_set_header Upgrade $http_upgrade; + proxy_set_header Connection $http_connection; + } + } + server { + listen 6043; + location ~* { + proxy_pass http://keeper; + proxy_read_timeout 60s; + proxy_next_upstream error http_502 http_500 non_idempotent; + } + } + + server { + listen 6060; + location ~* { + proxy_pass http://explorer; + proxy_read_timeout 60s; + proxy_next_upstream error http_502 http_500 non_idempotent; + } + } + upstream dbserver { + least_conn; + server 172.16.214.201:6041 max_fails=0; + server 172.16.214.202:6041 max_fails=0; + server 172.16.214.203:6041 max_fails=0; + } + upstream keeper { + ip_hash; + server 172.16.214.201:6043 ; + server 172.16.214.202:6043 ; + server 172.16.214.203:6043 ; + } + upstream explorer{ + ip_hash; + server 172.16.214.201:6060 ; + server 172.16.214.202:6060 ; + server 172.16.214.203:6060 ; + } +} +``` + +## Docker 部署 + +本节将介绍如何在 Docker 容器中启动 TDengine 服务并对其进行访问。你可以在 docker run 命令行或者 docker-compose 文件中使用环境变量来控制容器中服务的行为。 + +### 启动 TDengine + +TDengine 镜像启动时默认激活 HTTP 服务，使用下列命令便可创建一个带有 HTTP 服务的容器化 TDengine 环境。 +```shell +docker run -d --name tdengine \ +-v ~/data/taos/dnode/data:/var/lib/taos \ +-v ~/data/taos/dnode/log:/var/log/taos \ +-p 6041:6041 tdengine/tdengine +``` + +详细的参数说明如下。 +- /var/lib/taos：TDengine 默认数据文件目录，可通过配置文件修改位置。 +- /var/log/taos：TDengine 默认日志文件目录，可通过配置文件修改位置。 + +以上命令启动了一个名为 tdengine 的容器，并把其中的 HTTP 服务的端口 6041 映射到主机端口 6041。如下命令可以验证该容器中提供的 HTTP 服务是否可用。 + +```shell +curl -u root:taosdata -d "show databases" localhost:6041/rest/sql +``` + +运行如下命令可在容器中访问 TDengine。 +```shell +$ docker exec -it tdengine taos + +taos> show databases; + name | +================================= + information_schema | + performance_schema | +Query OK, 2 rows in database (0.033802s) +``` + +在容器中，TDengine CLI 或者各种连接器（例如 JDBC-JNI）与服务器通过容器的 hostname 建立连接。从容器外访问容器内的 TDengine 比较复杂，通过 RESTful/WebSocket 连接方式是最简单的方法。 + +### 在 host 网络模式下启动 TDengine + +运行以下命令可以在 host 网络模式下启动 TDengine，这样可以使用主机的 FQDN 建立连接，而不是使用容器的 hostname。 +```shell +docker run -d --name tdengine --network host tdengine/tdengine +``` + +这种方式与在主机上使用 systemctl 命令启动 TDengine 的效果相同。在主机上已安装 TDengine 客户端的情况下，可以直接使用下面的命令访问 TDengine 服务。 +```shell +$ taos + +taos> show dnodes; + id | endpoint | vnodes | support_vnodes | status | create_time | note | +================================================================================================================================================= + 1 | vm98:6030 | 0 | 32 | ready | 2022-08-19 14:50:05.337 | | +Query OK, 1 rows in database (0.010654s) +``` + +### 以指定的 hostname 和 port 启动 TDengine + +使用如下命令可以利用 TAOS_FQDN 环境变量或者 taos.cfg 中的 fqdn 配置项使TDengine 在指定的 hostname 上建立连接。这种方式为部署 TDengine 提供了更大的灵活性。 + +```shell +docker run -d \ + --name tdengine \ + -e TAOS_FQDN=tdengine \ + -p 6030:6030 \ + -p 6041-6049:6041-6049 \ + -p 6041-6049:6041-6049/udp \ + tdengine/tdengine +``` + +首先，上面的命令在容器中启动一个 TDengine 服务，其所监听的 hostname 为tdengine，并将容器的端口 6030 映射到主机的端口 6030，将容器的端口段 6041~6049 映射到主机的端口段 6041~6049。如果主机上该端口段已经被占用，可以修改上述命令以指定一个主机上空闲的端口段。 + +其次，要确保 tdengine 这个 hostname 在 /etc/hosts 中可解析。通过如下命令可将正确的配置信息保存到 hosts 文件中。 +```shell +echo 127.0.0.1 tdengine |sudo tee -a /etc/hosts +``` + +最后，可以通过 TDengine CLI 以 tdengine 为服务器地址访问 TDengine 服务，命令如下。 +```shell +taos -h tdengine -P 6030 +``` + +如果 TAOS_FQDN 被设置为与所在主机名相同，则效果与“在 host 网络模式下启动TDengine”相同。 + +## Kubernetes 部署 + +作为面向云原生架构设计的时序数据库，TDengine 本身就支持 Kubernetes 部署。这里介绍如何使用 YAML 文件从头一步一步创建一个可用于生产使用的高可用 TDengine 集群，并重点介绍 Kubernetes 环境下 TDengine 的常用操作。本小节要求读者对 Kubernetes 有一定的了解，可以熟练运行常见的 kubectl 命令，了解 statefulset、service、pvc 等概念，对这些概念不熟悉的读者，可以先参考 Kubernetes 的官网进行学习。 +为了满足高可用的需求，集群需要满足如下要求： +- 3 个及以上 dnode ：TDengine 的同一个 vgroup 中的多个 vnode ，不允许同时分布在一个 dnode ，所以如果创建 3 副本的数据库，则 dnode 数大于等于 3 +- 3 个 mnode ：mnode 负责整个集群的管理工作，TDengine 默认是一个 mnode。如果这个 mnode 所在的 dnode 掉线，则整个集群不可用。 +- 数据库的 3 副本：TDengine 的副本配置是数据库级别，所以数据库 3 副本可满足在 3 个 dnode 的集群中，任意一个 dnode 下线，都不影响集群的正常使用。如果下线 dnode 个数为 2 时，此时集群不可用，因为 RAFT 无法完成选举。（企业版：在灾难恢复场景，任一节点数据文件损坏，都可以通过重新拉起 dnode 进行恢复） + +### 前置条件 + +要使用 Kubernetes 部署管理 TDengine 集群，需要做好如下准备工作。 +- 本文适用 Kubernetes v1.19 以上版本 +- 本文使用 kubectl 工具进行安装部署，请提前安装好相应软件 +- Kubernetes 已经安装部署并能正常访问使用或更新必要的容器仓库或其他服务 + +### 配置 Service 服务 + +创建一个 Service 配置文件：taosd-service.yaml，服务名称 metadata.name （此处为 "taosd"） 将在下一步中使用到。首先添加 TDengine 所用到的端口，然后在选择器设置确定的标签 app （此处为 “tdengine”）。 + +```yaml +--- +apiVersion: v1 +kind: Service +metadata: + name: "taosd" + labels: + app: "tdengine" +spec: + ports: + - name: tcp6030 + protocol: "TCP" + port: 6030 + - name: tcp6041 + protocol: "TCP" + port: 6041 + selector: + app: "tdengine" +``` + +### 有状态服务 StatefulSet + +根据 Kubernetes 对各类部署的说明，我们将使用 StatefulSet 作为 TDengine 的部署资源类型。 创建文件 tdengine.yaml，其中 replicas 定义集群节点的数量为 3。节点时区为中国（Asia/Shanghai），每个节点分配 5G 标准（standard）存储，你也可以根据实际情况进行相应修改。 + +请特别注意 startupProbe 的配置，在 dnode 的 Pod 掉线一段时间后，再重新启动，这个时候新上线的 dnode 会短暂不可用。如果 startupProbe 配置过小，Kubernetes 会认为该 Pod 处于不正常的状态，并尝试重启该 Pod，该 dnode 的 Pod 会频繁重启，始终无法恢复到正常状态。 + +```yaml +--- +apiVersion: apps/v1 +kind: StatefulSet +metadata: + name: "tdengine" + labels: + app: "tdengine" +spec: + serviceName: "taosd" + replicas: 3 + updateStrategy: + type: RollingUpdate + selector: + matchLabels: + app: "tdengine" + template: + metadata: + name: "tdengine" + labels: + app: "tdengine" + spec: + containers: + - name: "tdengine" + image: "tdengine/tdengine:3.2.3.0" + imagePullPolicy: "IfNotPresent" + ports: + - name: tcp6030 + protocol: "TCP" + containerPort: 6030 + - name: tcp6041 + protocol: "TCP" + containerPort: 6041 + env: + # POD_NAME for FQDN config + - name: POD_NAME + valueFrom: + fieldRef: + fieldPath: metadata.name + # SERVICE_NAME and NAMESPACE for fqdn resolve + - name: SERVICE_NAME + value: "taosd" + - name: STS_NAME + value: "tdengine" + - name: STS_NAMESPACE + valueFrom: + fieldRef: + fieldPath: metadata.namespace + # TZ for timezone settings, we recommend to always set it. + - name: TZ + value: "Asia/Shanghai" + # Environment variables with prefix TAOS_ will be parsed and converted into corresponding parameter in taos.cfg. For example, serverPort in taos.cfg should be configured by TAOS_SERVER_PORT when using K8S to deploy + - name: TAOS_SERVER_PORT + value: "6030" + # Must set if you want a cluster. + - name: TAOS_FIRST_EP + value: "$(STS_NAME)-0.$(SERVICE_NAME).$(STS_NAMESPACE).svc.cluster.local:$(TAOS_SERVER_PORT)" + # TAOS_FQND should always be set in k8s env. + - name: TAOS_FQDN + value: "$(POD_NAME).$(SERVICE_NAME).$(STS_NAMESPACE).svc.cluster.local" + volumeMounts: + - name: taosdata + mountPath: /var/lib/taos + startupProbe: + exec: + command: + - taos-check + failureThreshold: 360 + periodSeconds: 10 + readinessProbe: + exec: + command: + - taos-check + initialDelaySeconds: 5 + timeoutSeconds: 5000 + livenessProbe: + exec: + command: + - taos-check + initialDelaySeconds: 15 + periodSeconds: 20 + volumeClaimTemplates: + - metadata: + name: taosdata + spec: + accessModes: + - "ReadWriteOnce" + storageClassName: "standard" + resources: + requests: + storage: "5Gi" +``` + +### 使用 kubectl 命令部署 TDengine 集群 + +首先创建对应的 namespace dengine-test，以及 pvc，并保证 storageClassName 是 standard 的剩余空间足够。然后顺序执行以下命令： +```shell +kubectl apply -f taosd-service.yaml -n tdengine-test +``` + +上面的配置将生成一个三节点的 TDengine 集群，dnode 为自动配置，可以使用 show dnodes 命令查看当前集群的节点： +```shell +kubectl exec -it tdengine-0 -n tdengine-test -- taos -s "show dnodes" +kubectl exec -it tdengine-1 -n tdengine-test -- taos -s "show dnodes" +kubectl exec -it tdengine-2 -n tdengine-test -- taos -s "show dnodes" +``` + +输出如下： +```shell +taos show dnodes + id | endpoint | vnodes | support_vnodes | status | create_time | reboot_time | note | active_code | c_active_code | +============================================================================================================================================================================================================================================= + 1 | tdengine-0.ta... | 0 | 16 | ready | 2023-07-19 17:54:18.552 | 2023-07-19 17:54:18.469 | | | | + 2 | tdengine-1.ta... | 0 | 16 | ready | 2023-07-19 17:54:37.828 | 2023-07-19 17:54:38.698 | | | | + 3 | tdengine-2.ta... | 0 | 16 | ready | 2023-07-19 17:55:01.141 | 2023-07-19 17:55:02.039 | | | | +Query OK, 3 row(s) in set (0.001853s) +``` + +查看当前 mnode +```shell +kubectl exec -it tdengine-1 -n tdengine-test -- taos -s "show mnodes\G" +taos> show mnodes\G +*************************** 1.row *************************** + id: 1 + endpoint: tdengine-0.taosd.tdengine-test.svc.cluster.local:6030 + role: leader + status: ready +create_time: 2023-07-19 17:54:18.559 +reboot_time: 2023-07-19 17:54:19.520 +Query OK, 1 row(s) in set (0.001282s) +``` + +创建 mnode +```shell +kubectl exec -it tdengine-0 -n tdengine-test -- taos -s "create mnode on dnode 2" +kubectl exec -it tdengine-0 -n tdengine-test -- taos -s "create mnode on dnode 3" +``` + +查看 mnode +```shell +kubectl exec -it tdengine-1 -n tdengine-test -- taos -s "show mnodes\G" + +taos> show mnodes\G +*************************** 1.row *************************** + id: 1 + endpoint: tdengine-0.taosd.tdengine-test.svc.cluster.local:6030 + role: leader + status: ready +create_time: 2023-07-19 17:54:18.559 +reboot_time: 2023-07-20 09:19:36.060 +*************************** 2.row *************************** + id: 2 + endpoint: tdengine-1.taosd.tdengine-test.svc.cluster.local:6030 + role: follower + status: ready +create_time: 2023-07-20 09:22:05.600 +reboot_time: 2023-07-20 09:22:12.838 +*************************** 3.row *************************** + id: 3 + endpoint: tdengine-2.taosd.tdengine-test.svc.cluster.local:6030 + role: follower + status: ready +create_time: 2023-07-20 09:22:20.042 +reboot_time: 2023-07-20 09:22:23.271 +Query OK, 3 row(s) in set (0.003108s) +``` + +### 端口转发 + +利用 kubectl 端口转发功能可以使应用可以访问 Kubernetes 环境运行的 TDengine 集群。 + +```shell +kubectl port-forward -n tdengine-test tdengine-0 6041:6041 & +``` + +使用 curl 命令验证 TDengine REST API 使用的 6041 接口。 +```shell +curl -u root:taosdata -d "show databases" 127.0.0.1:6041/rest/sql +{"code":0,"column_meta":[["name","VARCHAR",64]],"data":[["information_schema"],["performance_schema"],["test"],["test1"]],"rows":4} +``` + +### 集群扩容 + +TDengine 支持集群扩容： +```shell +kubectl scale statefulsets tdengine -n tdengine-test --replicas=4 +``` + +上面命令行中参数 `--replica=4` 表示要将 TDengine 集群扩容到 4 个节点，执行后首先检查 POD 的状态： +```shell +kubectl get pod -l app=tdengine -n tdengine-test -o wide +``` + +输出如下： +```text +NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES +tdengine-0 1/1 Running 4 (6h26m ago) 6h53m 10.244.2.75 node86 +tdengine-1 1/1 Running 1 (6h39m ago) 6h53m 10.244.0.59 node84 +tdengine-2 1/1 Running 0 5h16m 10.244.1.224 node85 +tdengine-3 1/1 Running 0 3m24s 10.244.2.76 node86 +``` + +此时 Pod 的状态仍然是 Running，TDengine 集群中的 dnode 状态要等 Pod 状态为 ready 之后才能看到： +```shell +kubectl exec -it tdengine-3 -n tdengine-test -- taos -s "show dnodes" +``` + +扩容后的四节点 TDengine 集群的 dnode 列表： +```text +taos> show dnodes + id | endpoint | vnodes | support_vnodes | status | create_time | reboot_time | note | active_code | c_active_code | +============================================================================================================================================================================================================================================= + 1 | tdengine-0.ta... | 10 | 16 | ready | 2023-07-19 17:54:18.552 | 2023-07-20 09:39:04.297 | | | | + 2 | tdengine-1.ta... | 10 | 16 | ready | 2023-07-19 17:54:37.828 | 2023-07-20 09:28:24.240 | | | | + 3 | tdengine-2.ta... | 10 | 16 | ready | 2023-07-19 17:55:01.141 | 2023-07-20 10:48:43.445 | | | | + 4 | tdengine-3.ta... | 0 | 16 | ready | 2023-07-20 16:01:44.007 | 2023-07-20 16:01:44.889 | | | | +Query OK, 4 row(s) in set (0.003628s) +``` + +### 清理集群 + +**Warning** +删除 pvc 时需要注意下 pv persistentVolumeReclaimPolicy 策略，建议改为 Delete，这样在删除 pvc 时才会自动清理 pv，同时会清理底层的 csi 存储资源，如果没有配置删除 pvc 自动清理 pv 的策略，再删除 pvc 后，在手动清理 pv 时，pv 对应的 csi 存储资源可能不会被释放。 + +完整移除 TDengine 集群，需要分别清理 statefulset、svc、pvc，最后删除命名空间。 + +```shell +kubectl delete statefulset -l app=tdengine -n tdengine-test +kubectl delete svc -l app=tdengine -n tdengine-test +kubectl delete pvc -l app=tdengine -n tdengine-test +kubectl delete namespace tdengine-test +``` + +### 集群灾备能力 + +对于在 Kubernetes 环境下 TDengine 的高可用和高可靠来说，对于硬件损坏、灾难恢复，分为两个层面来讲： +- 底层的分布式块存储具备的灾难恢复能力，块存储的多副本，当下流行的分布式块存储如 Ceph，就具备多副本能力，将存储副本扩展到不同的机架、机柜、机房、数据中心（或者直接使用公有云厂商提供的块存储服务） +- TDengine 的灾难恢复，在 TDengine Enterprise 中，本身具备了当一个 dnode 永久下线（物理机磁盘损坏，数据分拣丢失）后，重新拉起一个空白的 dnode 来恢复原 dnode 的工作。 + +## 使用 Helm 部署 TDengine 集群 + +Helm 是 Kubernetes 的包管理器。 +上一节使用 Kubernetes 部署 TDengine 集群的操作已经足够简单，但 Helm 可以提供更强大的能力。 + +### 安装 Helm + +```shell +curl -fsSL -o get_helm.sh \ + https://raw.githubusercontent.com/helm/helm/master/scripts/get-helm-3 +chmod +x get_helm.sh +./get_helm.sh +``` + +Helm 会使用 kubectl 和 kubeconfig 的配置来操作 Kubernetes，可以参考 Rancher 安装 Kubernetes 的配置来进行设置。 + +### 安装 TDengine Chart + +TDengine Chart 尚未发布到 Helm 仓库，当前可以从 GitHub 直接下载： +```shell +wget https://github.com/taosdata/TDengine-Operator/raw/3.0/helm/tdengine-3.0.2.tgz +``` + +获取当前 Kubernetes 的存储类： +```shell +kubectl get storageclass +``` + +在 minikube 默认为 standard。之后，使用 helm 命令安装： +```shell +helm install tdengine tdengine-3.0.2.tgz \ + --set storage.className= \ + --set image.tag=3.2.3.0 + +``` + +在 minikube 环境下，可以设置一个较小的容量避免超出磁盘可用空间： +```shell +helm install tdengine tdengine-3.0.2.tgz \ + --set storage.className=standard \ + --set storage.dataSize=2Gi \ + --set storage.logSize=10Mi \ + --set image.tag=3.2.3.0 +``` + +部署成功后，TDengine Chart 将会输出操作 TDengine 的说明： +```shell +export POD_NAME=$(kubectl get pods --namespace default \ + -l "app.kubernetes.io/name=tdengine,app.kubernetes.io/instance=tdengine" \ + -o jsonpath="{.items[0].metadata.name}") +kubectl --namespace default exec $POD_NAME -- taos -s "show dnodes; show mnodes" +kubectl --namespace default exec -it $POD_NAME -- taos +``` + +可以创建一个表进行测试： +```shell +kubectl --namespace default exec $POD_NAME -- \ + taos -s "create database test; + use test; + create table t1 (ts timestamp, n int); + insert into t1 values(now, 1)(now + 1s, 2); + select * from t1;" +``` + +### 配置 values + +TDengine 支持 `values.yaml` 自定义。 +通过 helm show values 可以获取 TDengine Chart 支持的全部 values 列表： +```shell +helm show values tdengine-3.0.2.tgz +``` + +你可以将结果保存为 values.yaml，之后可以修改其中的各项参数，如 replica 数量，存储类名称，容量大小，TDengine 配置等，然后使用如下命令安装 TDengine 集群： +```shell +helm install tdengine tdengine-3.0.2.tgz -f values.yaml +``` + +全部参数如下： +```yaml +# Default values for tdengine. +# This is a YAML-formatted file. +# Declare variables to be passed into helm templates. + +replicaCount: 1 + +image: + prefix: tdengine/tdengine + #pullPolicy: Always + # Overrides the image tag whose default is the chart appVersion. +# tag: "3.0.2.0" + +service: + # ClusterIP is the default service type, use NodeIP only if you know what you are doing. + type: ClusterIP + ports: + # TCP range required + tcp: [6030, 6041, 6042, 6043, 6044, 6046, 6047, 6048, 6049, 6060] + # UDP range + udp: [6044, 6045] + + +# Set timezone here, not in taoscfg +timezone: "Asia/Shanghai" + +resources: + # We usually recommend not to specify default resources and to leave this as a conscious + # choice for the user. This also increases chances charts run on environments with little + # resources, such as Minikube. If you do want to specify resources, uncomment the following + # lines, adjust them as necessary, and remove the curly braces after 'resources:'. + # limits: + # cpu: 100m + # memory: 128Mi + # requests: + # cpu: 100m + # memory: 128Mi + +storage: + # Set storageClassName for pvc. K8s use default storage class if not set. + # + className: "" + dataSize: "100Gi" + logSize: "10Gi" + +nodeSelectors: + taosd: + # node selectors + +clusterDomainSuffix: "" +# Config settings in taos.cfg file. +# +# The helm/k8s support will use environment variables for taos.cfg, +# converting an upper-snake-cased variable like `TAOS_DEBUG_FLAG`, +# to a camelCase taos config variable `debugFlag`. +# +# See the variable list at https://www.taosdata.com/cn/documentation/administrator . +# +# Note: +# 1. firstEp/secondEp: should not be set here, it's auto generated at scale-up. +# 2. serverPort: should not be set, we'll use the default 6030 in many places. +# 3. fqdn: will be auto generated in kubernetes, user should not care about it. +# 4. role: currently role is not supported - every node is able to be mnode and vnode. +# +# Btw, keep quotes "" around the value like below, even the value will be number or not. +taoscfg: + # Starts as cluster or not, must be 0 or 1. + # 0: all pods will start as a separate TDengine server + # 1: pods will start as TDengine server cluster. [default] + CLUSTER: "1" + + # number of replications, for cluster only + TAOS_REPLICA: "1" + + + # TAOS_NUM_OF_RPC_THREADS: number of threads for RPC + #TAOS_NUM_OF_RPC_THREADS: "2" + + # + # TAOS_NUM_OF_COMMIT_THREADS: number of threads to commit cache data + #TAOS_NUM_OF_COMMIT_THREADS: "4" + + # enable/disable installation / usage report + #TAOS_TELEMETRY_REPORTING: "1" + + # time interval of system monitor, seconds + #TAOS_MONITOR_INTERVAL: "30" + + # time interval of dnode status reporting to mnode, seconds, for cluster only + #TAOS_STATUS_INTERVAL: "1" + + # time interval of heart beat from shell to dnode, seconds + #TAOS_SHELL_ACTIVITY_TIMER: "3" + + # minimum sliding window time, milli-second + #TAOS_MIN_SLIDING_TIME: "10" + + # minimum time window, milli-second + #TAOS_MIN_INTERVAL_TIME: "1" + + # the compressed rpc message, option: + # -1 (no compression) + # 0 (all message compressed), + # > 0 (rpc message body which larger than this value will be compressed) + #TAOS_COMPRESS_MSG_SIZE: "-1" + + # max number of connections allowed in dnode + #TAOS_MAX_SHELL_CONNS: "50000" + + # stop writing logs when the disk size of the log folder is less than this value + #TAOS_MINIMAL_LOG_DIR_G_B: "0.1" + + # stop writing temporary files when the disk size of the tmp folder is less than this value + #TAOS_MINIMAL_TMP_DIR_G_B: "0.1" + + # if disk free space is less than this value, taosd service exit directly within startup process + #TAOS_MINIMAL_DATA_DIR_G_B: "0.1" + + # One mnode is equal to the number of vnode consumed + #TAOS_MNODE_EQUAL_VNODE_NUM: "4" + + # enbale/disable http service + #TAOS_HTTP: "1" + + # enable/disable system monitor + #TAOS_MONITOR: "1" + + # enable/disable async log + #TAOS_ASYNC_LOG: "1" + + # + # time of keeping log files, days + #TAOS_LOG_KEEP_DAYS: "0" + + # The following parameters are used for debug purpose only. + # debugFlag 8 bits mask: FILE-SCREEN-UNUSED-HeartBeat-DUMP-TRACE_WARN-ERROR + # 131: output warning and error + # 135: output debug, warning and error + # 143: output trace, debug, warning and error to log + # 199: output debug, warning and error to both screen and file + # 207: output trace, debug, warning and error to both screen and file + # + # debug flag for all log type, take effect when non-zero value\ + #TAOS_DEBUG_FLAG: "143" + + # generate core file when service crash + #TAOS_ENABLE_CORE_FILE: "1" +``` + +### 扩容 + +关于扩容可参考上一节的说明，有一些额外的操作需要从 helm 的部署中获取。 +首先，从部署中获取 StatefulSet 的名称。 +```shell +export STS_NAME=$(kubectl get statefulset \ + -l "app.kubernetes.io/name=tdengine" \ + -o jsonpath="{.items[0].metadata.name}") +``` + +扩容操作极其简单，增加 replica 即可。以下命令将 TDengine 扩充到三节点： +```shell +kubectl scale --replicas 3 statefulset/$STS_NAME +``` + +使用命令 `show dnodes` 和 `show mnodes` 检查是否扩容成功。 + +### 清理集群 + +Helm 管理下，清理操作也变得简单： + +```shell +helm uninstall tdengine +``` + +但 Helm 也不会自动移除 PVC，需要手动获取 PVC 然后删除掉。 \ No newline at end of file diff --git a/docs/zh/07-operation/index.md 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z2s|HvJ#|m>WW9&Jv&d*bp4>YtASev`5}@2y2!3I`z_>!k`&xkR2qRqFbxAdsg46Q6^O6W`))&w*QsKp9)qFc_}A=-T~|NyjwijC@)yOFokEb%1pC|F` z2j%AB;Cvuz;-#1*a_wSa4zI|cLdv4=@!b~(D&)|OC7Hr*o~w= zJGKO8Hvx4I6i$$v+GDrRe^rL>1J{yZhlLe)R{Uv7H?n34I(ee2@@XU{Xx}DfC>DYT zCz>KFixS8~5~G^cv6D@1^Ppw>&Di2faE7-e^!3j!rHse^pP&0)-baFDU|*l5*`J)? ze|0|V^J2s9^JHgJZw=$C-+27HH-GnQNUN`4hE|b5!&Y-|K$(L!Ix#@;EK7K9-y| iA)P@Z0)y#43=n-c+|4l^vJXz}Aa{^jh|*j4pZ_1{g11os literal 0 HcmV?d00001 diff --git a/docs/zh/08-connector/26-rust.mdx b/docs/zh/08-connector/26-rust.mdx index 7f8019377d..dada93ce32 100644 --- a/docs/zh/08-connector/26-rust.mdx +++ b/docs/zh/08-connector/26-rust.mdx @@ -8,10 +8,10 @@ import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem'; import Preparation from "./_preparation.mdx" -import RustInsert from "../07-develop/03-insert-data/_rust_sql.mdx" -import RustBind from "../07-develop/03-insert-data/_rust_stmt.mdx" -import RustSml from "../07-develop/03-insert-data/_rust_schemaless.mdx" -import RustQuery from "../07-develop/04-query-data/_rust.mdx" +import RustInsert from "../08-develop/03-insert-data/_rust_sql.mdx" +import RustBind from "../08-develop/03-insert-data/_rust_stmt.mdx" +import RustSml from "../08-develop/03-insert-data/_rust_schemaless.mdx" +import RustQuery from "../08-develop/04-query-data/_rust.mdx" import RequestId from "./_request_id.mdx"; [![Crates.io](https://img.shields.io/crates/v/taos)](https://crates.io/crates/taos) ![Crates.io](https://img.shields.io/crates/d/taos) [![docs.rs](https://img.shields.io/docsrs/taos)](https://docs.rs/taos) diff --git a/docs/zh/08-connector/43-r-lang.mdx b/docs/zh/08-connector/43-r-lang.mdx index a181f68aba..f2a74dcd7f 100644 --- a/docs/zh/08-connector/43-r-lang.mdx +++ b/docs/zh/08-connector/43-r-lang.mdx @@ -7,7 +7,7 @@ title: R Language Connector import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem'; -import Rdemo from "../07-develop/01-connect/_connect_r.mdx" +import Rdemo from "../08-develop/01-connect/_connect_r.mdx" 通过 R 语言中的 RJDBC 库可以使 R 语言程序支持访问 TDengine 数据。以下是安装过程、配置过程以及 R 语言示例代码。 diff --git a/docs/zh/07-develop/01-connect/_category_.yml b/docs/zh/08-develop/01-connect/_category_.yml similarity index 100% rename from docs/zh/07-develop/01-connect/_category_.yml rename to docs/zh/08-develop/01-connect/_category_.yml diff --git a/docs/zh/07-develop/01-connect/_connect_c.mdx b/docs/zh/08-develop/01-connect/_connect_c.mdx similarity index 100% rename from docs/zh/07-develop/01-connect/_connect_c.mdx rename to docs/zh/08-develop/01-connect/_connect_c.mdx diff --git a/docs/zh/07-develop/01-connect/_connect_cs.mdx b/docs/zh/08-develop/01-connect/_connect_cs.mdx similarity index 100% rename from docs/zh/07-develop/01-connect/_connect_cs.mdx rename to docs/zh/08-develop/01-connect/_connect_cs.mdx diff --git a/docs/zh/07-develop/01-connect/_connect_go.mdx b/docs/zh/08-develop/01-connect/_connect_go.mdx similarity index 100% rename from docs/zh/07-develop/01-connect/_connect_go.mdx rename to docs/zh/08-develop/01-connect/_connect_go.mdx diff --git a/docs/zh/07-develop/01-connect/_connect_java.mdx b/docs/zh/08-develop/01-connect/_connect_java.mdx similarity index 100% rename from docs/zh/07-develop/01-connect/_connect_java.mdx rename to docs/zh/08-develop/01-connect/_connect_java.mdx diff --git a/docs/zh/07-develop/01-connect/_connect_node.mdx b/docs/zh/08-develop/01-connect/_connect_node.mdx similarity index 100% rename from docs/zh/07-develop/01-connect/_connect_node.mdx rename to docs/zh/08-develop/01-connect/_connect_node.mdx diff --git a/docs/zh/07-develop/01-connect/_connect_php.mdx b/docs/zh/08-develop/01-connect/_connect_php.mdx similarity index 100% rename from docs/zh/07-develop/01-connect/_connect_php.mdx rename to docs/zh/08-develop/01-connect/_connect_php.mdx diff --git a/docs/zh/07-develop/01-connect/_connect_python.mdx b/docs/zh/08-develop/01-connect/_connect_python.mdx similarity index 100% rename from docs/zh/07-develop/01-connect/_connect_python.mdx rename to docs/zh/08-develop/01-connect/_connect_python.mdx diff --git a/docs/zh/07-develop/01-connect/_connect_r.mdx b/docs/zh/08-develop/01-connect/_connect_r.mdx similarity index 100% rename from docs/zh/07-develop/01-connect/_connect_r.mdx rename to docs/zh/08-develop/01-connect/_connect_r.mdx diff --git a/docs/zh/07-develop/01-connect/_connect_rust.mdx b/docs/zh/08-develop/01-connect/_connect_rust.mdx similarity index 100% rename from docs/zh/07-develop/01-connect/_connect_rust.mdx rename to docs/zh/08-develop/01-connect/_connect_rust.mdx diff --git a/docs/zh/07-develop/01-connect/connection-type-zh.webp b/docs/zh/08-develop/01-connect/connection-type-zh.webp similarity index 100% rename from docs/zh/07-develop/01-connect/connection-type-zh.webp rename to docs/zh/08-develop/01-connect/connection-type-zh.webp diff --git a/docs/zh/07-develop/01-connect/index.md b/docs/zh/08-develop/01-connect/index.md similarity index 100% rename from docs/zh/07-develop/01-connect/index.md rename to 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第零步 - -规划集群所有物理节点的 FQDN，将规划好的 FQDN 分别添加到每个物理节点的 /etc/hosts；修改每个物理节点的 /etc/hosts，将所有集群物理节点的 IP 与 FQDN 的对应添加好。【如部署了 DNS，请联系网络管理员在 DNS 上做好相关配置】 - -### 第一步 - -如果搭建集群的物理节点中，存有之前的测试数据，或者装过其他版本的 TDengine，请先将其删除，并清空所有数据（如果需要保留原有数据，请联系涛思交付团队进行旧版本升级、数据迁移），具体步骤请参考博客[《TDengine 多种安装包的安装和卸载》](https://www.taosdata.com/blog/2019/08/09/566.html)。 - -:::note -因为 FQDN 的信息会写进文件，如果之前没有配置或者更改 FQDN，且启动了 TDengine。请一定在确保数据无用或者备份的前提下，清理一下之前的数据（rm -rf /var/lib/taos/\*）； -::: - -:::note -客户端所在服务器也需要配置，确保它可以正确解析每个节点的 FQDN 配置，不管是通过 DNS 服务，还是修改 hosts 文件。 -::: - -### 第二步 - -确保集群中所有主机在端口 6030-6042 上的 TCP/UDP 协议能够互通。 - -### 第三步 - -在所有物理节点安装 TDengine，且版本必须是一致的，但不要启动 taosd。安装时，提示输入是否要加入一个已经存在的 TDengine 集群时，第一个物理节点直接回车创建新集群，后续物理节点则输入该集群任何一个在线的物理节点的 FQDN:端口号（默认 6030）； - -### 第四步 - -检查所有数据节点，以及应用程序所在物理节点的网络设置： - -每个物理节点上执行命令 `hostname -f`，查看和确认所有节点的 hostname 是不相同的（应用驱动所在节点无需做此项检查）； - -每个物理节点上执行 ping host，其中 host 是其他物理节点的 hostname，看能否 ping 通其它物理节点；如果不能 ping 通，需要检查网络设置，或 /etc/hosts 文件（Windows 系统默认路径为 C:\Windows\system32\drivers\etc\hosts），或 DNS 的配置。如果无法 ping 通，是无法组成集群的； - -从应用运行的物理节点，ping taosd 运行的数据节点，如果无法 ping 通，应用是无法连接 taosd 的，请检查应用所在物理节点的 DNS 设置或 hosts 文件； - -每个数据节点的 End Point 就是输出的 hostname 外加端口号，比如 h1.taosdata.com:6030。 - -### 第五步 - -修改 TDengine 的配置文件（所有节点的文件 /etc/taos/taos.cfg 都需要修改）。假设准备启动的第一个数据节点 End Point 为 h1.taosdata.com:6030，其与集群配置相关参数如下： - -```c -// firstEp 是每个数据节点首次启动后连接的第一个数据节点 -firstEp h1.taosdata.com:6030 - -// 必须配置为本数据节点的 FQDN，如果本机只有一个 hostname，可注释掉本项 -fqdn h1.taosdata.com - -// 配置本数据节点的端口号，缺省是 6030 -serverPort 6030 - -``` - -一定要修改的参数是 firstEp 和 fqdn。在每个数据节点，firstEp 需全部配置成一样，但 fqdn 一定要配置成其所在数据节点的值。其他参数可不做任何修改，除非你很清楚为什么要修改。 - -加入到集群中的数据节点 dnode，下表中涉及集群相关的参数必须完全相同，否则不能成功加入到集群中。 - -| **#** | **配置参数名称** | **含义** | -| ----- | ---------------- | ------------------------------------ | -| 1 | statusInterval | dnode 向 mnode 报告状态时长 | -| 2 | timezone | 时区 | -| 3 | locale | 系统区位信息及编码格式 | -| 4 | charset | 字符集编码 | -| 5 | ttlChangeOnWrite | ttl 到期时间是否伴随表的修改操作改变 | - -## 启动集群 - -按照《立即开始》里的步骤，启动第一个数据节点，例如 h1.taosdata.com，然后执行 taos，启动 TDengine CLI，在其中执行命令 “SHOW DNODES”，如下所示： - -``` -taos> show dnodes; -id | endpoint | vnodes | support_vnodes | status | create_time | note | -============================================================================================================================================ -1 | h1.taosdata.com:6030 | 0 | 1024 | ready | 2022-07-16 10:50:42.673 | | -Query OK, 1 rows affected (0.007984s) - - -``` - -上述命令里，可以看到刚启动的数据节点的 End Point 是：h1.taos.com:6030，就是这个新集群的 firstEp。 - -## 添加数据节点 - -将后续的数据节点添加到现有集群，具体有以下几步： - -按照《立即开始》一章的方法在每个物理节点启动 taosd；（注意：每个物理节点都需要在 taos.cfg 文件中将 firstEp 参数配置为新集群首个节点的 End Point——在本例中是 h1.taos.com:6030） - -在第一个数据节点，使用 CLI 程序 taos，登录进 TDengine 系统，执行命令： - -```sql -CREATE DNODE "h2.taos.com:6030"; -```` - -将新数据节点的 End Point（准备工作中第四步获知的）添加进集群的 EP 列表。“fqdn:port”需要用双引号引起来，否则出错。请注意将示例的“h2.taos.com:6030” 替换为这个新数据节点的 End Point。 - -然后执行命令 - -```sql -SHOW DNODES; -``` - -查看新节点是否被成功加入。如果该被加入的数据节点处于离线状态，请做两个检查： - -查看该数据节点的 taosd 是否正常工作，如果没有正常运行，需要先检查为什么? -查看该数据节点 taosd 日志文件 taosdlog.0 里前面几行日志（一般在 /var/log/taos 目录），看日志里输出的该数据节点 fqdn 以及端口号是否为刚添加的 End Point。如果不一致，需要将正确的 End Point 添加进去。 -按照上述步骤可以源源不断的将新的数据节点加入到集群。 - -:::tip - -任何已经加入集群在线的数据节点，都可以作为后续待加入节点的 firstEp。 -firstEp 这个参数仅仅在该数据节点首次加入集群时有作用，加入集群后，该数据节点会保存最新的 mnode 的 End Point 列表，不再依赖这个参数。 -接下来，配置文件中的 firstEp 参数就主要在客户端连接的时候使用了，例如 TDengine CLI 如果不加参数，会默认连接由 firstEp 指定的节点。 -两个没有配置 firstEp 参数的数据节点 dnode 启动后，会独立运行起来。这个时候，无法将其中一个数据节点加入到另外一个数据节点，形成集群。无法将两个独立的集群合并成为新的集群。 - -::: - -## 查看数据节点 - -启动 TDengine CLI 程序 taos，然后执行： - -```sql -SHOW DNODES; -``` - -它将列出集群中所有的 dnode，每个 dnode 的 ID，end_point（fqdn:port），状态（ready，offline 等），vnode 数目，还未使用的 vnode 数目等信息。在添加或删除一个数据节点后，可以使用该命令查看。 - -输出如下（具体内容仅供参考，取决于实际的集群配置） - -``` -taos> show dnodes; - id | endpoint | vnodes | support_vnodes | status | create_time | note | -============================================================================================================================================ - 1 | trd01:6030 | 100 | 1024 | ready | 2022-07-15 16:47:47.726 | | -Query OK, 1 rows affected (0.006684s) -``` - -## 查看虚拟节点组 - -为充分利用多核技术，并提供横向扩展能力，数据需要分片处理。因此 TDengine 会将一个 DB 的数据切分成多份，存放在多个 vnode 里。这些 vnode 可能分布在多个数据节点 dnode 里，这样就实现了水平扩展。一个 vnode 仅仅属于一个 DB，但一个 DB 可以有多个 vnode。vnode 所在的数据节点是 mnode 根据当前系统资源的情况，自动进行分配的，无需任何人工干预。 - -启动 CLI 程序 taos，然后执行： - -```sql -USE SOME_DATABASE; -SHOW VGROUPS; -``` - -输出如下（具体内容仅供参考，取决于实际的集群配置） - -``` -taos> use db; -Database changed. - -taos> show vgroups; - vgroup_id | db_name | tables | v1_dnode | v1_status | v2_dnode | v2_status | v3_dnode | v3_status | status | nfiles | file_size | tsma | -================================================================================================================================================================================================ - 2 | db | 0 | 1 | leader | NULL | NULL | NULL | NULL | NULL | NULL | NULL | 0 | - 3 | db | 0 | 1 | leader | NULL | NULL | NULL | NULL | NULL | NULL | NULL | 0 | - 4 | db | 0 | 1 | leader | NULL | NULL | NULL | NULL | NULL | NULL | NULL | 0 | -Query OK, 8 row(s) in set (0.001154s) -``` - -## 删除数据节点 - -启动 CLI 程序 taos，执行： - -```sql -DROP DNODE dnodeId; -``` - -dnodeId 可以通过 SHOW DNODES 获得。 - -:::warning - -数据节点一旦被 drop 之后，不能重新加入集群。需要将此节点重新部署（清空数据文件夹）。集群在完成 `drop dnode` 操作之前，会将该 dnode 的数据迁移走。 -请注意 `drop dnode` 和 停止 taosd 进程是两个不同的概念，不要混淆：因为删除 dnode 之前要执行迁移数据的操作，因此被删除的 dnode 必须保持在线状态。待删除操作结束之后，才能停止 taosd 进程。 -一个数据节点被 drop 之后，其他节点都会感知到这个 dnodeID 的删除操作，任何集群中的节点都不会再接收此 dnodeID 的请求。 -dnodeID 是集群自动分配的，不得人工指定。它在生成时是递增的，不会重复。 - -::: - -## 常见问题 - -1、建立集群时使用 CREATE DNODE 增加新节点后，新节点始终显示 offline 状态？ -```sql - 1）首先要检查增加的新节点上的 taosd 服务是否已经正常启动 - - 2）如果已经启动，再检查到新节点的网络是否通畅，可以使用 ping fqdn 验证下 - - 3）如果前面两步都没有问题，这一步要检查新节点做为独立集群在运行了，可以使用 taos -h fqdn 连接上后，show dnodes; 命令查看. - 如果显示的列表与你主节点上显示的不一致，说明此节点自己单独成立了一个集群，解决的方法是停止新节点上的服务，然后清空新节点上 - taos.cfg 中配置的 dataDir 目录下的所有文件，重新启动新节点服务即可解决。 -``` diff --git a/docs/zh/10-deployment/02-docker.md b/docs/zh/10-deployment/02-docker.md deleted file mode 100644 index 3dbfabca7d..0000000000 --- a/docs/zh/10-deployment/02-docker.md +++ /dev/null @@ -1,507 +0,0 @@ ---- -title: 用 Docker 部署 TDengine -sidebar_label: Docker -description: '本章主要介绍如何在容器中启动 TDengine 服务并访问它' ---- - -本章主要介绍如何在容器中启动 TDengine 服务并访问它。可以在 docker run 命令行中或者 docker-compose 文件中使用环境变量来控制容器中服务的行为。 - -## 启动 TDengine - -TDengine 镜像启动时默认激活 HTTP 服务，使用下列命令 - -```shell -docker run -d --name tdengine \ --v ~/data/taos/dnode/data:/var/lib/taos \ --v ~/data/taos/dnode/log:/var/log/taos \ --p 6041:6041 tdengine/tdengine -``` -:::note - -- /var/lib/taos: TDengine 默认数据文件目录。可通过[配置文件]修改位置。你可以修改~/data/taos/dnode/data为你自己的数据目录 -- /var/log/taos: TDengine 默认日志文件目录。可通过[配置文件]修改位置。你可以修改~/data/taos/dnode/log为你自己的日志目录 - -::: - -以上命令启动了一个名为“tdengine”的容器，并把其中的 HTTP 服务的端 6041 映射到了主机端口 6041。使用如下命令可以验证该容器中提供的 HTTP 服务是否可用： - -```shell -curl -u root:taosdata -d "show databases" localhost:6041/rest/sql -``` - -使用如下命令可以在该容器中执行 TDengine 的客户端 taos 对 TDengine 进行访问： - -```shell -$ docker exec -it tdengine taos - -taos> show databases; - name | -================================= - information_schema | - performance_schema | -Query OK, 2 rows in database (0.033802s) -``` - -因为运行在容器中的 TDengine 服务端使用容器的 hostname 建立连接，使用 TDengine CLI 或者各种连接器（例如 JDBC-JNI）从容器外访问容器内的 TDengine 比较复杂，所以上述方式是访问容器中 TDengine 服务的最简单的方法，适用于一些简单场景。如果在一些复杂场景下想要从容器化使用 TDengine CLI 或者各种连接器访问容器中的 TDengine 服务，请参考下一节。 - -## 在 host 网络上启动 TDengine - -```shell -docker run -d --name tdengine --network host tdengine/tdengine -``` - -上面的命令在 host 网络上启动 TDengine，并使用主机的 FQDN 建立连接而不是使用容器的 hostname 。这种方式和在主机上使用 `systemctl` 启动 TDengine 效果相同。在主机已安装 TDengine 客户端情况下，可以直接使用下面的命令访问它。 - -```shell -$ taos - -taos> show dnodes; - id | endpoint | vnodes | support_vnodes | status | create_time | note | -================================================================================================================================================= - 1 | vm98:6030 | 0 | 32 | ready | 2022-08-19 14:50:05.337 | | -Query OK, 1 rows in database (0.010654s) - -``` - -## 以指定的 hostname 和 port 启动 TDengine - -利用 `TAOS_FQDN` 环境变量或者 `taos.cfg` 中的 `fqdn` 配置项可以使 TDengine 在指定的 hostname 上建立连接。这种方式可以为部署提供更大的灵活性。 - -```shell -docker run -d \ - --name tdengine \ - -e TAOS_FQDN=tdengine \ - -p 6030:6030 \ - -p 6041-6049:6041-6049 \ - -p 6041-6049:6041-6049/udp \ - tdengine/tdengine -``` - -上面的命令在容器中启动一个 TDengine 服务，其所监听的 hostname 为 tdengine ，并将容器的 6030 端口映射到主机的 6030 端口（TCP，只能映射主机 6030 端口），6041-6049 端口段映射到主机 6041-6049 端口段（tcp 和 udp 都需要映射，如果主机上该端口段已经被占用，可以修改上述命令指定一个主机上空闲的端口段）。 - -接下来，要确保 "tdengine" 这个 hostname 在 `/etc/hosts` 中可解析。 - -```shell -echo 127.0.0.1 tdengine |sudo tee -a /etc/hosts -``` - -最后，可以从 TDengine CLI 或者任意连接器以 "tdengine" 为服务端地址访问 TDengine 服务。 - -```shell -taos -h tdengine -P 6030 -``` - -如果 `TAOS_FQDN` 被设置为与所在主机名相同，则效果与 “在 host 网络上启动 TDengine” 相同。 - -## 在指定网络上启动 TDengine - -也可以在指定的特定网络上启动 TDengine。下面是详细步骤： - -1. 首先，创建一个 docker 网络，命名为 td-net - - ```shell - docker network create td-net - ``` - -2. 启动 TDengine - - 以下命令在 td-net 网络上启动 TDengine 服务 - - ```shell - docker run -d --name tdengine --network td-net \ - -e TAOS_FQDN=tdengine \ - tdengine/tdengine - ``` - -3. 在同一网络上的另一容器中启动 TDengine 客户端 - - ```shell - docker run --rm -it --network td-net -e TAOS_FIRST_EP=tdengine --entrypoint=taos tdengine/tdengine - # or - #docker run --rm -it --network td-net --entrypoint=taos tdengine/tdengine -h tdengine - ``` - -## 在容器中启动客户端应用 - -如果想在容器中启动自己的应用的话，需要将相应的对 TDengine 的依赖也要加入到镜像中，例如： - -```docker -FROM ubuntu:20.04 -RUN apt-get update && apt-get install -y wget -ENV TDENGINE_VERSION=3.0.0.0 -RUN wget -c https://www.tdengine.com/assets-download/3.0/TDengine-client-${TDENGINE_VERSION}-Linux-x64.tar.gz \ - && tar xvf TDengine-client-${TDENGINE_VERSION}-Linux-x64.tar.gz \ - && cd TDengine-client-${TDENGINE_VERSION} \ - && ./install_client.sh \ - && cd ../ \ - && rm -rf TDengine-client-${TDENGINE_VERSION}-Linux-x64.tar.gz TDengine-client-${TDENGINE_VERSION} -## add your application next, eg. go, build it in builder stage, copy the binary to the runtime -#COPY --from=builder /path/to/build/app /usr/bin/ -#CMD ["app"] -``` - -以下是一个 go 应用程序的示例： - -* 创建 go mod 项目： - -```bash -go mod init app -``` - -* 创建 main.go： - -```go -/* - * In this test program, we'll create a database and insert 4 records then select out. - */ -package main - -import ( - "database/sql" - "flag" - "fmt" - "time" - - _ "github.com/taosdata/driver-go/v3/taosSql" -) - -type config struct { - hostName string - serverPort string - user string - password string -} - -var configPara config -var taosDriverName = "taosSql" -var url string - -func init() { - flag.StringVar(&configPara.hostName, "h", "", "The host to connect to TDengine server.") - flag.StringVar(&configPara.serverPort, "p", "", "The TCP/IP port number to use for the connection to TDengine server.") - flag.StringVar(&configPara.user, "u", "root", "The TDengine user name to use when connecting to the server.") - flag.StringVar(&configPara.password, "P", "taosdata", "The password to use when connecting to the server.") - flag.Parse() -} - -func printAllArgs() { - fmt.Printf("============= args parse result: =============\n") - fmt.Printf("hostName: %v\n", configPara.hostName) - fmt.Printf("serverPort: %v\n", configPara.serverPort) - fmt.Printf("usr: %v\n", configPara.user) - fmt.Printf("password: %v\n", configPara.password) - fmt.Printf("================================================\n") -} - -func main() { - printAllArgs() - - url = "root:taosdata@/tcp(" + configPara.hostName + ":" + configPara.serverPort + ")/" - - taos, err := sql.Open(taosDriverName, url) - checkErr(err, "open database error") - defer taos.Close() - - taos.Exec("create database if not exists test") - taos.Exec("use test") - taos.Exec("create table if not exists tb1 (ts timestamp, a int)") - _, err = taos.Exec("insert into tb1 values(now, 0)(now+1s,1)(now+2s,2)(now+3s,3)") - checkErr(err, "failed to insert") - rows, err := taos.Query("select * from tb1") - checkErr(err, "failed to select") - - defer rows.Close() - for rows.Next() { - var r struct { - ts time.Time - a int - } - err := rows.Scan(&r.ts, &r.a) - if err != nil { - fmt.Println("scan error:\n", err) - return - } - fmt.Println(r.ts, r.a) - } -} - -func checkErr(err error, prompt string) { - if err != nil { - fmt.Println("ERROR: %s\n", prompt) - panic(err) - } -} -``` - -* 更新 go mod - -```bash -go mod tidy -``` - -如下是完整版本的 dockerfile： - -```dockerfile -FROM golang:1.19.0-buster as builder -ENV TDENGINE_VERSION=3.0.0.0 -RUN wget -c https://www.tdengine.com/assets-download/3.0/TDengine-client-${TDENGINE_VERSION}-Linux-x64.tar.gz \ - && tar xvf TDengine-client-${TDENGINE_VERSION}-Linux-x64.tar.gz \ - && cd TDengine-client-${TDENGINE_VERSION} \ - && ./install_client.sh \ - && cd ../ \ - && rm -rf TDengine-client-${TDENGINE_VERSION}-Linux-x64.tar.gz TDengine-client-${TDENGINE_VERSION} -WORKDIR /usr/src/app/ -ENV GOPROXY="https://goproxy.io,direct" -COPY ./main.go ./go.mod ./go.sum /usr/src/app/ -RUN go env -RUN go mod tidy -RUN go build - -FROM ubuntu:20.04 -RUN apt-get update && apt-get install -y wget -ENV TDENGINE_VERSION=3.0.0.0 -RUN wget -c https://www.tdengine.com/assets-download/3.0/TDengine-client-${TDENGINE_VERSION}-Linux-x64.tar.gz \ - && tar xvf TDengine-client-${TDENGINE_VERSION}-Linux-x64.tar.gz \ - && cd TDengine-client-${TDENGINE_VERSION} \ - && ./install_client.sh \ - && cd ../ \ - && rm -rf TDengine-client-${TDENGINE_VERSION}-Linux-x64.tar.gz TDengine-client-${TDENGINE_VERSION} - -## add your application next, eg. go, build it in builder stage, copy the binary to the runtime -COPY --from=builder /usr/src/app/app /usr/bin/ -CMD ["app"] -``` - -目前我们已经有了 `main.go`, `go.mod`, `go.sum`, `app.dockerfile`， 现在可以构建出这个应用程序并在 `td-net` 网络上启动它 - -```shell -$ docker build -t app -f app.dockerfile . -$ docker run --rm --network td-net app app -h tdengine -p 6030 -============= args parse result: ============= -hostName: tdengine -serverPort: 6030 -usr: root -password: taosdata -================================================ -2022-08-19 07:43:51.68 +0000 UTC 0 -2022-08-19 07:43:52.68 +0000 UTC 1 -2022-08-19 07:43:53.68 +0000 UTC 2 -2022-08-19 07:43:54.68 +0000 UTC 3 -``` - -## 用 docker-compose 启动 TDengine 集群 - -1. 如下 docker-compose 文件启动一个 三节点 TDengine 集群。 - -```yml -version: "3" -services: - td-1: - image: tdengine/tdengine:$VERSION - environment: - TAOS_FQDN: "td-1" - TAOS_FIRST_EP: "td-1" - ports: - - 6041:6041 - - 6030:6030 - volumes: - # /var/lib/taos: TDengine 默认数据文件目录。可通过[配置文件]修改位置。你可以修改~/data/taos/dnode1/data为你自己的数据目录 - - ~/data/taos/dnode1/data:/var/lib/taos - # /var/log/taos: TDengine 默认日志文件目录。可通过[配置文件]修改位置。你可以修改~/data/taos/dnode1/log为你自己的日志目录 - - ~/data/taos/dnode1/log:/var/log/taos - td-2: - image: tdengine/tdengine:$VERSION - environment: - TAOS_FQDN: "td-2" - TAOS_FIRST_EP: "td-1" - volumes: - - ~/data/taos/dnode2/data:/var/lib/taos - - ~/data/taos/dnode2/log:/var/log/taos - td-3: - image: tdengine/tdengine:$VERSION - environment: - TAOS_FQDN: "td-3" - TAOS_FIRST_EP: "td-1" - volumes: - - ~/data/taos/dnode3/data:/var/lib/taos - - ~/data/taos/dnode3/log:/var/log/taos -``` - -:::note - -* `VERSION` 环境变量被用来设置 tdengine image tag -* 在新创建的实例上必须设置 `TAOS_FIRST_EP` 以使其能够加入 TDengine 集群；如果有高可用需求，则需要同时使用 `TAOS_SECOND_EP` - -::: - -2. 启动集群 - -```shell -$ VERSION=3.0.0.0 docker-compose up -d -Creating network "test-docker_default" with the default driver -Creating volume "test-docker_taosdata-td1" with default driver -Creating volume "test-docker_taoslog-td1" with default driver -Creating volume "test-docker_taosdata-td2" with default driver -Creating volume "test-docker_taoslog-td2" with default driver -Creating volume "test-docker_taosdata-td3" with default driver -Creating volume "test-docker_taoslog-td3" with default driver - -Creating test-docker_td-3_1 ... done -Creating test-docker_td-1_1 ... done -Creating test-docker_td-2_1 ... done -``` - -3. 查看节点状态 - -```shell - docker-compose ps - Name Command State Ports - -------------------------------------------------------------------- -test-docker_td-1_1 /tini -- /usr/bin/entrypoi ... Up -test-docker_td-2_1 /tini -- /usr/bin/entrypoi ... Up -test-docker_td-3_1 /tini -- /usr/bin/entrypoi ... Up -``` - -4. 用 TDengine CLI 查看 dnodes - -```shell - -$ docker-compose exec td-1 taos -s "show dnodes" - -taos> show dnodes - - id | endpoint | vnodes | support_vnodes | status | create_time | note | -================================================================================================================================================= - - 1 | td-1:6030 | 0 | 32 | ready | 2022-08-19 07:57:29.971 | | - 2 | td-2:6030 | 0 | 32 | ready | 2022-08-19 07:57:31.415 | | - 3 | td-3:6030 | 0 | 32 | ready | 2022-08-19 07:57:31.417 | | -Query OK, 3 rows in database (0.021262s) - -``` - -## taosAdapter - -1. taosAdapter 在 TDengine 容器中默认是启动的。如果想要禁用它，在启动时指定环境变量 `TAOS_DISABLE_ADAPTER=true` - -2. 同时为了部署灵活起见，可以在独立的容器中启动 taosAdapter - -```docker -services: - # ... - adapter: - image: tdengine/tdengine:$VERSION - command: taosadapter -``` - -如果要部署多个 taosAdapter 来提高吞吐量并提供高可用性，推荐配置方式为使用 nginx 等反向代理来提供统一的访问入口。具体配置方法请参考 nginx 的官方文档。如下是示例： - -```yml -version: "3" - -networks: - inter: - -services: - td-1: - image: tdengine/tdengine:$VERSION - environment: - TAOS_FQDN: "td-1" - TAOS_FIRST_EP: "td-1" - volumes: - # /var/lib/taos: TDengine 默认数据文件目录。可通过[配置文件]修改位置。你可以修改~/data/taos/dnode1/data为你自己的数据目录 - - ~/data/taos/dnode1/data:/var/lib/taos - # /var/log/taos: TDengine 默认日志文件目录。可通过[配置文件]修改位置。你可以修改~/data/taos/dnode1/log为你自己的日志目录 - - ~/data/taos/dnode1/log:/var/log/taos - td-2: - image: tdengine/tdengine:$VERSION - environment: - TAOS_FQDN: "td-2" - TAOS_FIRST_EP: "td-1" - volumes: - - ~/data/taos/dnode2/data:/var/lib/taos - - ~/data/taos/dnode2/log:/var/log/taos - adapter: - image: tdengine/tdengine:$VERSION - entrypoint: "taosadapter" - networks: - - inter - environment: - TAOS_FIRST_EP: "td-1" - TAOS_SECOND_EP: "td-2" - deploy: - replicas: 4 - nginx: - image: nginx - depends_on: - - adapter - networks: - - inter - ports: - - 6041:6041 - - 6044:6044/udp - command: [ - "sh", - "-c", - "while true; - do curl -s http://adapter:6041/-/ping >/dev/null && break; - done; - printf 'server{listen 6041;location /{proxy_pass http://adapter:6041;}}' - > /etc/nginx/conf.d/rest.conf; - printf 'stream{server{listen 6044 udp;proxy_pass adapter:6044;}}' - >> /etc/nginx/nginx.conf;cat /etc/nginx/nginx.conf; - nginx -g 'daemon off;'", - ] -``` - -## 使用 docker swarm 部署 - -如果要想将基于容器的 TDengine 集群部署在多台主机上，可以使用 docker swarm。首先要在这些主机上建立 docke swarm 集群，请参考 docker 官方文档。 - -docker-compose 文件可以参考上节。下面是使用 docker swarm 启动 TDengine 的命令： - -```shell -$ VERSION=3.0.0.0 docker stack deploy -c docker-compose.yml taos -Creating network taos_inter -Creating service taos_nginx -Creating service taos_td-1 -Creating service taos_td-2 -Creating service taos_adapter -``` - -查看和管理 - -```shell -$ docker stack ps taos -ID NAME IMAGE NODE DESIRED STATE CURRENT STATE ERROR PORTS -7m3sbf532bqp taos_adapter.1 tdengine/tdengine:3.0.0.0 vm98 Running Running about a minute ago -pj403n6ofmmh taos_adapter.2 tdengine/tdengine:3.0.0.0 vm98 Running Running about a minute ago -rxqfwsyk5q1h taos_adapter.3 tdengine/tdengine:3.0.0.0 vm98 Running Running about a minute ago -qj40lpxr40oc taos_adapter.4 tdengine/tdengine:3.0.0.0 vm98 Running Running about a minute ago -oe3455ulxpze taos_nginx.1 nginx:latest vm98 Running Running about a minute ago -o0tsg70nrrc6 taos_td-1.1 tdengine/tdengine:3.0.0.0 vm98 Running Running about a minute ago -q5m1oxs589cp taos_td-2.1 tdengine/tdengine:3.0.0.0 vm98 Running Running about a minute ago -$ docker service ls -ID NAME MODE REPLICAS IMAGE PORTS -ozuklorgl8bs taos_adapter replicated 4/4 tdengine/tdengine:3.0.0.0 -crmhdjw6vxw0 taos_nginx replicated 1/1 nginx:latest *:6041->6041/tcp, *:6044->6044/udp -o86ngy7csv5n taos_td-1 replicated 1/1 tdengine/tdengine:3.0.0.0 -rma040ny4tb0 taos_td-2 replicated 1/1 tdengine/tdengine:3.0.0.0 -``` - -从上面的输出可以看到有两个 dnode， 和四个 taosAdapter，以及一个 nginx 反向代理服务。 - -接下来，我们可以减少 taosAdapter 服务的数量 - -```shell -$ docker service scale taos_adapter=1 -taos_adapter scaled to 1 -overall progress: 1 out of 1 tasks -1/1: running [==================================================>] -verify: Service converged - -$ docker service ls -f name=taos_adapter -ID NAME MODE REPLICAS IMAGE PORTS -ozuklorgl8bs taos_adapter replicated 1/1 tdengine/tdengine:3.0.0.0 -``` diff --git a/docs/zh/10-deployment/03-k8s.md b/docs/zh/10-deployment/03-k8s.md deleted file mode 100644 index 4ac66610a9..0000000000 --- a/docs/zh/10-deployment/03-k8s.md +++ /dev/null @@ -1,544 +0,0 @@ ---- -sidebar_label: Kubernetes -title: 在 Kubernetes 上部署 TDengine 集群 -description: 利用 Kubernetes 部署 TDengine 集群的详细指南 ---- - -## 概述 - -作为面向云原生架构设计的时序数据库，TDengine 本身就支持 Kubernetes 部署。这里介绍如何使用 YAML 文件从头一步一步创建一个可用于生产使用的高可用 TDengine 集群，并重点介绍 Kubernetes 环境下 TDengine 的常用操作。 - -为了满足[高可用](https://docs.taosdata.com/tdinternal/high-availability/)的需求，集群需要满足如下要求： - -- 3 个及以上 dnode ：TDengine 的同一个 vgroup 中的多个 vnode ，不允许同时分布在一个 dnode ，所以如果创建 3 副本的数据库，则 dnode 数大于等于 3 -- 3 个 mnode ：mnode 负责整个集群的管理工作，TDengine 默认是一个 mnode。如果这个 mnode 所在的 dnode 掉线，则整个集群不可用。 -- 数据库的 3 副本：TDengine 的副本配置是数据库级别，所以数据库 3 副本可满足在 3 个 dnode 的集群中，任意一个 dnode 下线，都不影响集群的正常使用。**如果下线** **dnode** **个数为 2 时，此时集群不可用，\*\***因为\***\*RAFT 无法完成选举\*\***。\*\*（企业版：在灾难恢复场景，任一节点数据文件损坏，都可以通过重新拉起 dnode 进行恢复） - -## 前置条件 - -要使用 Kubernetes 部署管理 TDengine 集群，需要做好如下准备工作。 - -- 本文适用 Kubernetes v1.19 以上版本 -- 本文使用 kubectl 工具进行安装部署，请提前安装好相应软件 -- Kubernetes 已经安装部署并能正常访问使用或更新必要的容器仓库或其他服务 - -以下配置文件也可以从 [GitHub 仓库](https://github.com/taosdata/TDengine-Operator/tree/3.0/src/tdengine) 下载。 - -## 配置 Service 服务 - -创建一个 Service 配置文件：`taosd-service.yaml`，服务名称 `metadata.name` (此处为 "taosd") 将在下一步中使用到。首先添加 TDengine 所用到的端口，然后在选择器设置确定的标签 app (此处为 “tdengine”)。 - -```YAML ---- -apiVersion: v1 -kind: Service -metadata: - name: "taosd" - labels: - app: "tdengine" -spec: - ports: - - name: tcp6030 - protocol: "TCP" - port: 6030 - - name: tcp6041 - protocol: "TCP" - port: 6041 - selector: - app: "tdengine" -``` - -## 有状态服务 StatefulSet - -根据 Kubernetes 对各类部署的说明，我们将使用 StatefulSet 作为 TDengine 的部署资源类型。 创建文件 `tdengine.yaml`，其中 replicas 定义集群节点的数量为 3。节点时区为中国（Asia/Shanghai），每个节点分配 5G 标准（standard）存储（参考[Storage Classes](https://kubernetes.io/docs/concepts/storage/storage-classes/) 配置 storage class ）。你也可以根据实际情况进行相应修改。 - -请特别注意 startupProbe 的配置，在 dnode 的 Pod 掉线一段时间后，再重新启动，这个时候新上线的 dnode 会短暂不可用。如果 startupProbe 配置过小，Kubernetes 会认为该 Pod 处于不正常的状态，并尝试重启该 Pod，该 dnode 的 Pod 会频繁重启，始终无法恢复到正常状态。参考 [Configure Liveness, Readiness and Startup Probes](https://kubernetes.io/docs/tasks/configure-pod-container/configure-liveness-readiness-startup-probes/) - -```YAML ---- -apiVersion: apps/v1 -kind: StatefulSet -metadata: - name: "tdengine" - labels: - app: "tdengine" -spec: - serviceName: "taosd" - replicas: 3 - updateStrategy: - type: RollingUpdate - selector: - matchLabels: - app: "tdengine" - template: - metadata: - name: "tdengine" - labels: - app: "tdengine" - spec: - containers: - - name: "tdengine" - image: "tdengine/tdengine:3.0.7.1" - imagePullPolicy: "IfNotPresent" - ports: - - name: tcp6030 - protocol: "TCP" - containerPort: 6030 - - name: tcp6041 - protocol: "TCP" - containerPort: 6041 - env: - # POD_NAME for FQDN config - - name: POD_NAME - valueFrom: - fieldRef: - fieldPath: metadata.name - # SERVICE_NAME and NAMESPACE for fqdn resolve - - name: SERVICE_NAME - value: "taosd" - - name: STS_NAME - value: "tdengine" - - name: STS_NAMESPACE - valueFrom: - fieldRef: - fieldPath: metadata.namespace - # TZ for timezone settings, we recommend to always set it. - - name: TZ - value: "Asia/Shanghai" - # Environment variables with prefix TAOS_ will be parsed and converted into corresponding parameter in taos.cfg. For example, serverPort in taos.cfg should be configured by TAOS_SERVER_PORT when using K8S to deploy - - name: TAOS_SERVER_PORT - value: "6030" - # Must set if you want a cluster. - - name: TAOS_FIRST_EP - value: "$(STS_NAME)-0.$(SERVICE_NAME).$(STS_NAMESPACE).svc.cluster.local:$(TAOS_SERVER_PORT)" - # TAOS_FQND should always be set in k8s env. - - name: TAOS_FQDN - value: "$(POD_NAME).$(SERVICE_NAME).$(STS_NAMESPACE).svc.cluster.local" - volumeMounts: - - name: taosdata - mountPath: /var/lib/taos - startupProbe: - exec: - command: - - taos-check - failureThreshold: 360 - periodSeconds: 10 - readinessProbe: - exec: - command: - - taos-check - initialDelaySeconds: 5 - timeoutSeconds: 5000 - livenessProbe: - exec: - command: - - taos-check - initialDelaySeconds: 15 - periodSeconds: 20 - volumeClaimTemplates: - - metadata: - name: taosdata - spec: - accessModes: - - "ReadWriteOnce" - storageClassName: "standard" - resources: - requests: - storage: "5Gi" -``` - -## 使用 kubectl 命令部署 TDengine 集群 - -首先创建对应的 namespace，然后顺序执行以下命令： - -```Bash -kubectl apply -f taosd-service.yaml -n tdengine-test -kubectl apply -f tdengine.yaml -n tdengine-test -``` - -上面的配置将生成一个三节点的 TDengine 集群，dnode 为自动配置，可以使用 show dnodes 命令查看当前集群的节点： - -```Bash -kubectl exec -it tdengine-0 -n tdengine-test -- taos -s "show dnodes" -kubectl exec -it tdengine-1 -n tdengine-test -- taos -s "show dnodes" -kubectl exec -it tdengine-2 -n tdengine-test -- taos -s "show dnodes" -``` - -输出如下： - -```Bash -taos> show dnodes - id | endpoint | vnodes | support_vnodes | status | create_time | reboot_time | note | active_code | c_active_code | -============================================================================================================================================================================================================================================= - 1 | tdengine-0.ta... | 0 | 16 | ready | 2023-07-19 17:54:18.552 | 2023-07-19 17:54:18.469 | | | | - 2 | tdengine-1.ta... | 0 | 16 | ready | 2023-07-19 17:54:37.828 | 2023-07-19 17:54:38.698 | | | | - 3 | tdengine-2.ta... | 0 | 16 | ready | 2023-07-19 17:55:01.141 | 2023-07-19 17:55:02.039 | | | | -Query OK, 3 row(s) in set (0.001853s) -``` - -查看当前 mnode - -```Bash -kubectl exec -it tdengine-1 -n tdengine-test -- taos -s "show mnodes\G" -taos> show mnodes\G -*************************** 1.row *************************** - id: 1 - endpoint: tdengine-0.taosd.tdengine-test.svc.cluster.local:6030 - role: leader - status: ready -create_time: 2023-07-19 17:54:18.559 -reboot_time: 2023-07-19 17:54:19.520 -Query OK, 1 row(s) in set (0.001282s) -``` - -## 创建 mnode - -```Bash -kubectl exec -it tdengine-0 -n tdengine-test -- taos -s "create mnode on dnode 2" -kubectl exec -it tdengine-0 -n tdengine-test -- taos -s "create mnode on dnode 3" -``` - -查看 mnode - -```Bash -kubectl exec -it tdengine-1 -n tdengine-test -- taos -s "show mnodes\G" - -taos> show mnodes\G -*************************** 1.row *************************** - id: 1 - endpoint: tdengine-0.taosd.tdengine-test.svc.cluster.local:6030 - role: leader - status: ready -create_time: 2023-07-19 17:54:18.559 -reboot_time: 2023-07-20 09:19:36.060 -*************************** 2.row *************************** - id: 2 - endpoint: tdengine-1.taosd.tdengine-test.svc.cluster.local:6030 - role: follower - status: ready -create_time: 2023-07-20 09:22:05.600 -reboot_time: 2023-07-20 09:22:12.838 -*************************** 3.row *************************** - id: 3 - endpoint: tdengine-2.taosd.tdengine-test.svc.cluster.local:6030 - role: follower - status: ready -create_time: 2023-07-20 09:22:20.042 -reboot_time: 2023-07-20 09:22:23.271 -Query OK, 3 row(s) in set (0.003108s) -``` - -## 使能端口转发 - -利用 kubectl 端口转发功能可以使应用可以访问 Kubernetes 环境运行的 TDengine 集群。 - -```Plain -kubectl port-forward -n tdengine-test tdengine-0 6041:6041 & -``` - -使用 curl 命令验证 TDengine REST API 使用的 6041 接口。 - -```Plain -curl -u root:taosdata -d "show databases" 127.0.0.1:6041/rest/sql -{"code":0,"column_meta":[["name","VARCHAR",64]],"data":[["information_schema"],["performance_schema"],["test"],["test1"]],"rows":4} -``` - -## 集群测试 - -### 数据准备 - -#### taosBenchmark - -通过 taosBenchmark 创建一个 3 副本的数据库，同时写入 1 亿条数据，同时查看数据 - -```Bash -kubectl exec -it tdengine-0 -n tdengine-test -- taosBenchmark -I stmt -d test -n 10000 -t 10000 -a 3 - -# query data -kubectl exec -it tdengine-0 -n tdengine-test -- taos -s "select count(*) from test.meters;" - -taos> select count(*) from test.meters; - count(*) | -======================== - 100000000 | -Query OK, 1 row(s) in set (0.103537s) -``` - -查看 vnode 分布，通过 show dnodes - -```Bash -kubectl exec -it tdengine-0 -n tdengine-test -- taos -s "show dnodes" - -taos> show dnodes - id | endpoint | vnodes | support_vnodes | status | create_time | reboot_time | note | active_code | c_active_code | -============================================================================================================================================================================================================================================= - 1 | tdengine-0.ta... | 8 | 16 | ready | 2023-07-19 17:54:18.552 | 2023-07-19 17:54:18.469 | | | | - 2 | tdengine-1.ta... | 8 | 16 | ready | 2023-07-19 17:54:37.828 | 2023-07-19 17:54:38.698 | | | | - 3 | tdengine-2.ta... | 8 | 16 | ready | 2023-07-19 17:55:01.141 | 2023-07-19 17:55:02.039 | | | | -Query OK, 3 row(s) in set (0.001357s) -``` - -通过 show vgroup 查看 vnode 分布情况 - -```Bash -kubectl exec -it tdengine-0 -n tdengine-test -- taos -s "show test.vgroups" - -taos> show test.vgroups - vgroup_id | db_name | tables | v1_dnode | v1_status | v2_dnode | v2_status | v3_dnode | v3_status | v4_dnode | v4_status | cacheload | cacheelements | tsma | -============================================================================================================================================================================================== - 2 | test | 1267 | 1 | follower | 2 | follower | 3 | leader | NULL | NULL | 0 | 0 | 0 | - 3 | test | 1215 | 1 | follower | 2 | leader | 3 | follower | NULL | NULL | 0 | 0 | 0 | - 4 | test | 1215 | 1 | leader | 2 | follower | 3 | follower | NULL | NULL | 0 | 0 | 0 | - 5 | test | 1307 | 1 | follower | 2 | leader | 3 | follower | NULL | NULL | 0 | 0 | 0 | - 6 | test | 1245 | 1 | follower | 2 | follower | 3 | leader | NULL | NULL | 0 | 0 | 0 | - 7 | test | 1275 | 1 | follower | 2 | leader | 3 | follower | NULL | NULL | 0 | 0 | 0 | - 8 | test | 1231 | 1 | leader | 2 | follower | 3 | follower | NULL | NULL | 0 | 0 | 0 | - 9 | test | 1245 | 1 | follower | 2 | follower | 3 | leader | NULL | NULL | 0 | 0 | 0 | -Query OK, 8 row(s) in set (0.001488s) -``` - -#### 手工创建 - -创建一个三副本的test1，并创建一张表，写入2条数据 - -```Bash -kubectl exec -it tdengine-0 -n tdengine-test -- \ - taos -s \ - "create database if not exists test1 replica 3; - use test1; - create table if not exists t1(ts timestamp, n int); - insert into t1 values(now, 1)(now+1s, 2);" -``` - -通过show test1.vgroup 查看vnode分布情况 - -```Bash -kubectl exec -it tdengine-0 -n tdengine-test -- taos -s "show test1.vgroups" - -taos> show test1.vgroups - vgroup_id | db_name | tables | v1_dnode | v1_status | v2_dnode | v2_status | v3_dnode | v3_status | v4_dnode | v4_status | cacheload | cacheelements | tsma | -============================================================================================================================================================================================== - 10 | test1 | 1 | 1 | follower | 2 | follower | 3 | leader | NULL | NULL | 0 | 0 | 0 | - 11 | test1 | 0 | 1 | follower | 2 | leader | 3 | follower | NULL | NULL | 0 | 0 | 0 | -Query OK, 2 row(s) in set (0.001489s) -``` - -### 容错测试 - -Mnode leader 所在的 dnode 掉线，dnode1 - -```Bash -kubectl get pod -l app=tdengine -n tdengine-test -o wide -NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES -tdengine-0 0/1 ErrImagePull 2 (2s ago) 20m 10.244.2.75 node86 -tdengine-1 1/1 Running 1 (6m48s ago) 20m 10.244.0.59 node84 -tdengine-2 1/1 Running 0 21m 10.244.1.223 node85 -``` - -此时集群 mnode 发生重新选举，dnode2 上的 monde 成为 leader - -```Bash -kubectl exec -it tdengine-1 -n tdengine-test -- taos -s "show mnodes\G" -Welcome to the TDengine Command Line Interface, Client Version:3.0.7.1.202307190706 -Copyright (c) 2022 by TDengine, all rights reserved. - -taos> show mnodes\G -*************************** 1.row *************************** - id: 1 - endpoint: tdengine-0.taosd.tdengine-test.svc.cluster.local:6030 - role: offline - status: offline -create_time: 2023-07-19 17:54:18.559 -reboot_time: 1970-01-01 08:00:00.000 -*************************** 2.row *************************** - id: 2 - endpoint: tdengine-1.taosd.tdengine-test.svc.cluster.local:6030 - role: leader - status: ready -create_time: 2023-07-20 09:22:05.600 -reboot_time: 2023-07-20 09:32:00.227 -*************************** 3.row *************************** - id: 3 - endpoint: tdengine-2.taosd.tdengine-test.svc.cluster.local:6030 - role: follower - status: ready -create_time: 2023-07-20 09:22:20.042 -reboot_time: 2023-07-20 09:32:00.026 -Query OK, 3 row(s) in set (0.001513s) -``` - -集群可以正常读写 - -```Bash -# insert -kubectl exec -it tdengine-0 -n tdengine-test -- taos -s "insert into test1.t1 values(now, 1)(now+1s, 2);" - -taos> insert into test1.t1 values(now, 1)(now+1s, 2); -Insert OK, 2 row(s) affected (0.002098s) - -# select -kubectl exec -it tdengine-0 -n tdengine-test -- taos -s "select *from test1.t1" - -taos> select *from test1.t1 - ts | n | -======================================== - 2023-07-19 18:04:58.104 | 1 | - 2023-07-19 18:04:59.104 | 2 | - 2023-07-19 18:06:00.303 | 1 | - 2023-07-19 18:06:01.303 | 2 | -Query OK, 4 row(s) in set (0.001994s) -``` - -同理，至于非 leader 得 mnode 掉线，读写当然可以正常进行，这里就不做过多的展示。 - -## 集群扩容 - -TDengine 集群支持自动扩容： - -```Bash -kubectl scale statefulsets tdengine --replicas=4 -``` - -上面命令行中参数 `--replica=4` 表示要将 TDengine 集群扩容到 4 个节点，执行后首先检查 POD 的状态： - -```Bash -kubectl get pod -l app=tdengine -n tdengine-test -o wide -``` - -输出如下： - -```Plain -NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES -tdengine-0 1/1 Running 4 (6h26m ago) 6h53m 10.244.2.75 node86 -tdengine-1 1/1 Running 1 (6h39m ago) 6h53m 10.244.0.59 node84 -tdengine-2 1/1 Running 0 5h16m 10.244.1.224 node85 -tdengine-3 1/1 Running 0 3m24s 10.244.2.76 node86 -``` - -此时 Pod 的状态仍然是 Running，TDengine 集群中的 dnode 状态要等 Pod 状态为 `ready` 之后才能看到： - -```Bash -kubectl exec -it tdengine-3 -n tdengine-test -- taos -s "show dnodes" -``` - -扩容后的四节点 TDengine 集群的 dnode 列表: - -```Plain -taos> show dnodes - id | endpoint | vnodes | support_vnodes | status | create_time | reboot_time | note | active_code | c_active_code | -============================================================================================================================================================================================================================================= - 1 | tdengine-0.ta... | 10 | 16 | ready | 2023-07-19 17:54:18.552 | 2023-07-20 09:39:04.297 | | | | - 2 | tdengine-1.ta... | 10 | 16 | ready | 2023-07-19 17:54:37.828 | 2023-07-20 09:28:24.240 | | | | - 3 | tdengine-2.ta... | 10 | 16 | ready | 2023-07-19 17:55:01.141 | 2023-07-20 10:48:43.445 | | | | - 4 | tdengine-3.ta... | 0 | 16 | ready | 2023-07-20 16:01:44.007 | 2023-07-20 16:01:44.889 | | | | -Query OK, 4 row(s) in set (0.003628s) -``` - -## 集群缩容 - -由于 TDengine 集群在扩缩容时会对数据进行节点间迁移，使用 kubectl 命令进行缩容需要首先使用 "drop dnodes" 命令（**如果集群中存在 3 副本的 db，那么缩容后的** **dnode** **个数也要必须大于等于 3，否则 drop dnode 操作会被中止**），然后再节点删除完成后再进行 Kubernetes 集群缩容。 - -注意：由于 Kubernetes Statefulset 中 Pod 的只能按创建顺序逆序移除，所以 TDengine drop dnode 也需要按照创建顺序逆序移除，否则会导致 Pod 处于错误状态。 - -```Bash -kubectl exec -it tdengine-0 -n tdengine-test -- taos -s "drop dnode 4" -kubectl exec -it tdengine-0 -n tdengine-test -- taos -s "show dnodes" - -taos> show dnodes - id | endpoint | vnodes | support_vnodes | status | create_time | reboot_time | note | active_code | c_active_code | -============================================================================================================================================================================================================================================= - 1 | tdengine-0.ta... | 10 | 16 | ready | 2023-07-19 17:54:18.552 | 2023-07-20 09:39:04.297 | | | | - 2 | tdengine-1.ta... | 10 | 16 | ready | 2023-07-19 17:54:37.828 | 2023-07-20 09:28:24.240 | | | | - 3 | tdengine-2.ta... | 10 | 16 | ready | 2023-07-19 17:55:01.141 | 2023-07-20 10:48:43.445 | | | | -Query OK, 3 row(s) in set (0.003324s) -``` - -确认移除成功后（使用 kubectl exec -i -t tdengine-0 -- taos -s "show dnodes" 查看和确认 dnode 列表），使用 kubectl 命令移除 POD： - -```Plain -kubectl scale statefulsets tdengine --replicas=3 -n tdengine-test -``` - -最后一个 POD 将会被删除。使用命令 kubectl get pods -l app=tdengine 查看 POD 状态： - -```Plain -kubectl get pod -l app=tdengine -n tdengine-test -o wide -NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES -tdengine-0 1/1 Running 4 (6h55m ago) 7h22m 10.244.2.75 node86 -tdengine-1 1/1 Running 1 (7h9m ago) 7h23m 10.244.0.59 node84 -tdengine-2 1/1 Running 0 5h45m 10.244.1.224 node85 -``` - -POD 删除后，需要手动删除 PVC，否则下次扩容时会继续使用以前的数据导致无法正常加入集群。 - -```Bash -kubectl delete pvc aosdata-tdengine-3 -n tdengine-test -``` - -此时的集群状态是安全的，需要时还可以再次进行扩容： - -```Bash -kubectl scale statefulsets tdengine --replicas=4 -n tdengine-test -statefulset.apps/tdengine scaled - -kubectl get pod -l app=tdengine -n tdengine-test -o wide -NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES -tdengine-0 1/1 Running 4 (6h59m ago) 7h27m 10.244.2.75 node86 -tdengine-1 1/1 Running 1 (7h13m ago) 7h27m 10.244.0.59 node84 -tdengine-2 1/1 Running 0 5h49m 10.244.1.224 node85 -tdengine-3 1/1 Running 0 20s 10.244.2.77 node86 - -kubectl exec -it tdengine-0 -n tdengine-test -- taos -s "show dnodes" - -taos> show dnodes - id | endpoint | vnodes | support_vnodes | status | create_time | reboot_time | note | active_code | c_active_code | -============================================================================================================================================================================================================================================= - 1 | tdengine-0.ta... | 10 | 16 | ready | 2023-07-19 17:54:18.552 | 2023-07-20 09:39:04.297 | | | | - 2 | tdengine-1.ta... | 10 | 16 | ready | 2023-07-19 17:54:37.828 | 2023-07-20 09:28:24.240 | | | | - 3 | tdengine-2.ta... | 10 | 16 | ready | 2023-07-19 17:55:01.141 | 2023-07-20 10:48:43.445 | | | | - 5 | tdengine-3.ta... | 0 | 16 | ready | 2023-07-20 16:31:34.092 | 2023-07-20 16:38:17.419 | | | | -Query OK, 4 row(s) in set (0.003881s) -``` - -## 清理 TDengine 集群 - -> **删除 pvc 时需要注意下 pv persistentVolumeReclaimPolicy 策略，建议改为 Delete，这样在删除 pvc 时才会自动清理 pv，同时会清理底层的 csi 存储资源，如果没有配置删除 pvc 自动清理 pv 的策略，再删除 pvc 后，在手动清理 pv 时，pv 对应的 csi 存储资源可能不会被释放。** - -完整移除 TDengine 集群，需要分别清理 statefulset、svc、configmap、pvc。 - -```Bash -kubectl delete statefulset -l app=tdengine -n tdengine-test -kubectl delete svc -l app=tdengine -n tdengine-test -kubectl delete pvc -l app=tdengine -n tdengine-test -kubectl delete configmap taoscfg -n tdengine-test -``` - -## 常见错误 - -### 错误一 - -未进行 "drop dnode" 直接进行缩容，由于 TDengine 尚未删除节点，缩容 pod 导致 TDengine 集群中部分节点处于 offline 状态。 - -```Plain -kubectl exec -it tdengine-0 -n tdengine-test -- taos -s "show dnodes" - -taos> show dnodes - id | endpoint | vnodes | support_vnodes | status | create_time | reboot_time | note | active_code | c_active_code | -============================================================================================================================================================================================================================================= - 1 | tdengine-0.ta... | 10 | 16 | ready | 2023-07-19 17:54:18.552 | 2023-07-20 09:39:04.297 | | | | - 2 | tdengine-1.ta... | 10 | 16 | ready | 2023-07-19 17:54:37.828 | 2023-07-20 09:28:24.240 | | | | - 3 | tdengine-2.ta... | 10 | 16 | ready | 2023-07-19 17:55:01.141 | 2023-07-20 10:48:43.445 | | | | - 5 | tdengine-3.ta... | 0 | 16 | offline | 2023-07-20 16:31:34.092 | 2023-07-20 16:38:17.419 | status msg timeout | | | -Query OK, 4 row(s) in set (0.003862s) -``` - -## 最后 - -对于在 Kubernetes 环境下 TDengine 的高可用和高可靠来说，对于硬件损坏、灾难恢复，分为两个层面来讲： - -1. 底层的分布式块存储具备的灾难恢复能力，块存储的多副本，当下流行的分布式块存储如 Ceph，就具备多副本能力，将存储副本扩展到不同的机架、机柜、机房、数据中心（或者直接使用公有云厂商提供的块存储服务） -2. TDengine 的灾难恢复，在 TDengine Enterprise 中，本身具备了当一个 dnode 永久下线（物理机磁盘损坏，数据分拣丢失）后，重新拉起一个空白的 dnode 来恢复原 dnode 的工作。 - -最后，欢迎使用[TDengine Cloud](https://cloud.taosdata.com/)，来体验一站式全托管的 TDengine 云服务。 - -> TDengine Cloud 是一个极简的全托管时序数据处理云服务平台，它是基于开源的时序数据库 TDengine 而开发的。除高性能的时序数据库之外，它还具有缓存、订阅和流计算等系统功能，而且提供了便利而又安全的数据分享、以及众多的企业级功能。它可以让物联网、工业互联网、金融、IT 运维监控等领域企业在时序数据的管理上大幅降低人力成本和运营成本。 diff --git a/docs/zh/10-deployment/05-helm.md b/docs/zh/10-deployment/05-helm.md deleted file mode 100644 index b2c405033f..0000000000 --- a/docs/zh/10-deployment/05-helm.md +++ /dev/null @@ -1,298 +0,0 @@ ---- -sidebar_label: Helm -title: 使用 Helm 部署 TDengine 集群 -description: 使用 Helm 部署 TDengine 集群的详细指南 ---- - -Helm 是 Kubernetes 的包管理器，上一节使用 Kubernetes 部署 TDengine 集群的操作已经足够简单，但 Helm 依然可以提供更强大的能力。 - -## 安装 Helm - -```bash -curl -fsSL -o get_helm.sh \ - https://raw.githubusercontent.com/helm/helm/master/scripts/get-helm-3 -chmod +x get_helm.sh -./get_helm.sh - -``` - -Helm 会使用 kubectl 和 kubeconfig 的配置来操作 Kubernetes，可以参考 Rancher 安装 Kubernetes 的配置来进行设置。 - -## 安装 TDengine Chart - -TDengine Chart 尚未发布到 Helm 仓库，当前可以从 GitHub 直接下载： - -```bash -wget https://github.com/taosdata/TDengine-Operator/raw/3.0/helm/tdengine-3.0.2.tgz - -``` - -获取当前 Kubernetes 的存储类： - -```bash -kubectl get storageclass - -``` - -在 minikube 默认为 standard. - -之后，使用 helm 命令安装： - -```bash -helm install tdengine tdengine-3.0.2.tgz \ - --set storage.className= - -``` - -在 minikube 环境下，可以设置一个较小的容量避免超出磁盘可用空间： - -```bash -helm install tdengine tdengine-3.0.2.tgz \ - --set storage.className=standard \ - --set storage.dataSize=2Gi \ - --set storage.logSize=10Mi - -``` - -部署成功后，TDengine Chart 将会输出操作 TDengine 的说明： - -```bash -export POD_NAME=$(kubectl get pods --namespace default \ - -l "app.kubernetes.io/name=tdengine,app.kubernetes.io/instance=tdengine" \ - -o jsonpath="{.items[0].metadata.name}") -kubectl --namespace default exec $POD_NAME -- taos -s "show dnodes; show mnodes" -kubectl --namespace default exec -it $POD_NAME -- taos - -``` - -可以创建一个表进行测试： - -```bash -kubectl --namespace default exec $POD_NAME -- \ - taos -s "create database test; - use test; - create table t1 (ts timestamp, n int); - insert into t1 values(now, 1)(now + 1s, 2); - select * from t1;" - -``` - -## 配置 Values - -TDengine 支持 `values.yaml` 自定义。 - -通过 helm show values 可以获取 TDengine Chart 支持的全部 values 列表： - -```bash -helm show values tdengine-3.0.2.tgz - -``` - -你可以将结果保存为 values.yaml，之后可以修改其中的各项参数，如 replica 数量，存储类名称，容量大小，TDengine 配置等，然后使用如下命令安装 TDengine 集群： - -```bash -helm install tdengine tdengine-3.0.2.tgz -f values.yaml - -``` - -全部参数如下： - -```yaml -# Default values for tdengine. -# This is a YAML-formatted file. -# Declare variables to be passed into helm templates. - -replicaCount: 1 - -image: - prefix: tdengine/tdengine - #pullPolicy: Always - # Overrides the image tag whose default is the chart appVersion. -# tag: "3.0.2.0" - -service: - # ClusterIP is the default service type, use NodeIP only if you know what you are doing. - type: ClusterIP - ports: - # TCP range required - tcp: [6030, 6041, 6042, 6043, 6044, 6046, 6047, 6048, 6049, 6060] - # UDP range - udp: [6044, 6045] - - -# Set timezone here, not in taoscfg -timezone: "Asia/Shanghai" - -resources: - # We usually recommend not to specify default resources and to leave this as a conscious - # choice for the user. This also increases chances charts run on environments with little - # resources, such as Minikube. If you do want to specify resources, uncomment the following - # lines, adjust them as necessary, and remove the curly braces after 'resources:'. - # limits: - # cpu: 100m - # memory: 128Mi - # requests: - # cpu: 100m - # memory: 128Mi - -storage: - # Set storageClassName for pvc. K8s use default storage class if not set. - # - className: "" - dataSize: "100Gi" - logSize: "10Gi" - -nodeSelectors: - taosd: - # node selectors - -clusterDomainSuffix: "" -# Config settings in taos.cfg file. -# -# The helm/k8s support will use environment variables for taos.cfg, -# converting an upper-snake-cased variable like `TAOS_DEBUG_FLAG`, -# to a camelCase taos config variable `debugFlag`. -# -# See the variable list at https://www.taosdata.com/cn/documentation/administrator . -# -# Note: -# 1. firstEp/secondEp: should not be set here, it's auto generated at scale-up. -# 2. serverPort: should not be set, we'll use the default 6030 in many places. -# 3. fqdn: will be auto generated in kubernetes, user should not care about it. -# 4. role: currently role is not supported - every node is able to be mnode and vnode. -# -# Btw, keep quotes "" around the value like below, even the value will be number or not. -taoscfg: - # Starts as cluster or not, must be 0 or 1. - # 0: all pods will start as a separate TDengine server - # 1: pods will start as TDengine server cluster. [default] - CLUSTER: "1" - - # number of replications, for cluster only - TAOS_REPLICA: "1" - - - # TAOS_NUM_OF_RPC_THREADS: number of threads for RPC - #TAOS_NUM_OF_RPC_THREADS: "2" - - # - # TAOS_NUM_OF_COMMIT_THREADS: number of threads to commit cache data - #TAOS_NUM_OF_COMMIT_THREADS: "4" - - # enable/disable installation / usage report - #TAOS_TELEMETRY_REPORTING: "1" - - # time interval of system monitor, seconds - #TAOS_MONITOR_INTERVAL: "30" - - # time interval of dnode status reporting to mnode, seconds, for cluster only - #TAOS_STATUS_INTERVAL: "1" - - # time interval of heart beat from shell to dnode, seconds - #TAOS_SHELL_ACTIVITY_TIMER: "3" - - # minimum sliding window time, milli-second - #TAOS_MIN_SLIDING_TIME: "10" - - # minimum time window, milli-second - #TAOS_MIN_INTERVAL_TIME: "1" - - # the compressed rpc message, option: - # -1 (no compression) - # 0 (all message compressed), - # > 0 (rpc message body which larger than this value will be compressed) - #TAOS_COMPRESS_MSG_SIZE: "-1" - - # max number of connections allowed in dnode - #TAOS_MAX_SHELL_CONNS: "50000" - - # stop writing logs when the disk size of the log folder is less than this value - #TAOS_MINIMAL_LOG_DIR_G_B: "0.1" - - # stop writing temporary files when the disk size of the tmp folder is less than this value - #TAOS_MINIMAL_TMP_DIR_G_B: "0.1" - - # if disk free space is less than this value, taosd service exit directly within startup process - #TAOS_MINIMAL_DATA_DIR_G_B: "0.1" - - # One mnode is equal to the number of vnode consumed - #TAOS_MNODE_EQUAL_VNODE_NUM: "4" - - # enbale/disable http service - #TAOS_HTTP: "1" - - # enable/disable system monitor - #TAOS_MONITOR: "1" - - # enable/disable async log - #TAOS_ASYNC_LOG: "1" - - # - # time of keeping log files, days - #TAOS_LOG_KEEP_DAYS: "0" - - # The following parameters are used for debug purpose only. - # debugFlag 8 bits mask: FILE-SCREEN-UNUSED-HeartBeat-DUMP-TRACE_WARN-ERROR - # 131: output warning and error - # 135: output debug, warning and error - # 143: output trace, debug, warning and error to log - # 199: output debug, warning and error to both screen and file - # 207: output trace, debug, warning and error to both screen and file - # - # debug flag for all log type, take effect when non-zero value\ - #TAOS_DEBUG_FLAG: "143" - - # generate core file when service crash - #TAOS_ENABLE_CORE_FILE: "1" -``` - -## 扩容 - -关于扩容可参考上一节的说明，有一些额外的操作需要从 helm 的部署中获取。 - -首先，从部署中获取 StatefulSet 的名称。 - -```bash -export STS_NAME=$(kubectl get statefulset \ - -l "app.kubernetes.io/name=tdengine" \ - -o jsonpath="{.items[0].metadata.name}") - -``` - -扩容操作极其简单，增加 replica 即可。以下命令将 TDengine 扩充到三节点： - -```bash -kubectl scale --replicas 3 statefulset/$STS_NAME - -``` - -使用命令 `show dnodes` 和 `show mnodes` 检查是否扩容成功。 - -## 缩容 - -:::warning -缩容操作并没有完整测试，可能造成数据风险，请谨慎使用。 - -::: - -获取需要缩容的 dnode 列表，并手动 Drop。 - -```bash -kubectl --namespace default exec $POD_NAME -- \ - cat /var/lib/taos/dnode/dnodeEps.json \ - | jq '.dnodeInfos[1:] |map(.dnodeFqdn + ":" + (.dnodePort|tostring)) | .[]' -r -kubectl --namespace default exec $POD_NAME -- taos -s "show dnodes" -kubectl --namespace default exec $POD_NAME -- taos -s 'drop dnode ""' - -``` - -## 清理集群 - -Helm 管理下，清理操作也变得简单： - -```bash -helm uninstall tdengine - -``` - -但 Helm 也不会自动移除 PVC，需要手动获取 PVC 然后删除掉。 diff --git a/docs/zh/10-deployment/_category_.yml b/docs/zh/10-deployment/_category_.yml deleted file mode 100644 index 38363bd571..0000000000 --- a/docs/zh/10-deployment/_category_.yml +++ /dev/null @@ -1 +0,0 @@ -label: 部署集群 diff --git a/docs/zh/10-deployment/index.md b/docs/zh/10-deployment/index.md deleted file mode 100644 index f2ce519837..0000000000 --- a/docs/zh/10-deployment/index.md +++ /dev/null @@ -1,16 +0,0 @@ ---- -sidebar_label: 部署集群 -title: 部署集群 -description: 部署 TDengine 集群的多种方式 ---- - -TDengine 支持集群，提供水平扩展的能力。如果需要获得更高的处理能力，只需要多增加节点即可。TDengine 采用虚拟节点技术，将一个节点虚拟化为多个虚拟节点，以实现负载均衡。同时，TDengine可以将多个节点上的虚拟节点组成虚拟节点组，通过多副本机制，以保证供系统的高可用。TDengine的集群功能完全开源。 - -本章节主要介绍如何在主机上人工部署集群，docker部署，以及如何使用 Kubernetes 和 Helm部署集群。 - -```mdx-code-block -import DocCardList from '@theme/DocCardList'; -import {useCurrentSidebarCategory} from '@docusaurus/theme-common'; - - -```