未验证 提交 1c281088 编写于 作者: E Elias Soong 提交者: GitHub

Merge pull request #7996 from taosdata/docs/Update-Latest-Feature

Docs/update latest feature
......@@ -16,7 +16,7 @@ TDengine 的模块之一是时序数据库。但除此之外,为减少研发
采用 TDengine,可将典型的物联网、车联网、工业互联网大数据平台的总拥有成本大幅降低。但需要指出的是,因充分利用了物联网时序数据的特点,它无法用来处理网络爬虫、微博、微信、电商、ERP、CRM 等通用型数据。
![TDengine技术生态图](page://images/eco_system.png)
![TDengine技术生态图](../images/eco_system.png)
<center>图 1. TDengine技术生态图</center>
## <a class="anchor" id="scenes"></a>TDengine 总体适用场景
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......@@ -6,7 +6,7 @@
taosd包含rpc, dnode, vnode, tsdb, query, cq, sync, wal, mnode, http, monitor等模块,具体如下图:
![modules.png](page://images/architecture/modules.png)
![modules.png](../../images/architecture/modules.png)
taosd的启动入口是dnode模块,dnode然后启动其他模块,包括可选配置的http, monitor模块。taosc或dnode之间交互的消息都是通过rpc模块进行,dnode模块根据接收到的消息类型,将消息分发到vnode或mnode的消息队列,或由dnode模块自己消费。dnode的工作线程(worker)消费消息队列里的消息,交给mnode或vnode进行处理。下面对各个模块做简要说明。
......@@ -41,13 +41,13 @@ RPC模块还提供数据压缩功能,如果数据包的字节数超过系统
taosd的消息消费由dnode通过读写线程池进行控制,是系统的中枢。该模块内的结构体图如下:
![dnode.png](page://images/architecture/dnode.png)
![dnode.png](../../images/architecture/dnode.png)
## VNODE模块
vnode是一独立的数据存储查询逻辑单元,但因为一个vnode只能容许一个DB,因此vnode内部没有account, DB, user等概念。为实现更好的模块化、封装以及未来的扩展,它有很多子模块,包括负责存储的TSDB,负责查询的Query, 负责数据复制的sync,负责数据库日志的的wal, 负责连续查询的cq(continuous query), 负责事件触发的流计算的event等模块,这些子模块只与vnode模块发生关系,与其他模块没有任何调用关系。模块图如下:
![vnode.png](page://images/architecture/vnode.png)
![vnode.png](../../images/architecture/vnode.png)
vnode模块向下,与dnodeVRead,dnodeVWrite发生互动,向上,与子模块发生互动。它主要的功能有:
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......@@ -90,7 +90,7 @@ TDengine采取的是Master-Slave模式进行同步,与流行的RAFT一致性
具体的流程图如下:
![replica-master.png](page://images/architecture/replica-master.png)
![replica-master.png](../../images/architecture/replica-master.png)
选择Master的具体规则如下:
......@@ -105,7 +105,7 @@ TDengine采取的是Master-Slave模式进行同步,与流行的RAFT一致性
如果vnode A是master, vnode B是slave, vnode A能接受客户端的写请求,而vnode B不能。当vnode A收到写的请求后,遵循下面的流程:
![replica-forward.png](page://images/architecture/replica-forward.png)
![replica-forward.png](../../images/architecture/replica-forward.png)
1. 应用对写请求做基本的合法性检查,通过,则给该请求包打上一个版本号(version, 单调递增)
2. 应用将打上版本号的写请求封装一个WAL Head, 写入WAL(Write Ahead Log)
......@@ -140,7 +140,7 @@ TDengine采取的是Master-Slave模式进行同步,与流行的RAFT一致性
整个数据恢复流程分为两大步骤,第一步,先恢复archived data(file), 然后恢复wal。具体流程如下:
![replica-restore.png](page://images/architecture/replica-restore.png)
![replica-restore.png](../../images/architecture/replica-restore.png)
1. 通过已经建立的TCP连接,发送sync req给master节点
2. master收到sync req后,以client的身份,向vnode B主动建立一新的专用于同步的TCP连接(syncFd)
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......@@ -156,7 +156,7 @@ TDengine 的设计是基于单个硬件、软件系统不可靠,基于任何
TDengine 分布式架构的逻辑结构图如下:
![TDengine架构示意图](page://images/architecture/structure.png)
![TDengine架构示意图](../images/architecture/structure.png)
<center> 图 1 TDengine架构示意图 </center>
一个完整的 TDengine 系统是运行在一到多个物理节点上的,逻辑上,它包含数据节点(dnode)、TDengine应用驱动(taosc)以及应用(app)。系统中存在一到多个数据节点,这些数据节点组成一个集群(cluster)。应用通过taosc的API与TDengine集群进行互动。下面对每个逻辑单元进行简要介绍。
......@@ -207,7 +207,7 @@ TDengine 分布式架构的逻辑结构图如下:
为解释vnode、mnode、taosc和应用之间的关系以及各自扮演的角色,下面对写入数据这个典型操作的流程进行剖析。
![TDengine典型的操作流程](page://images/architecture/message.png)
![TDengine典型的操作流程](../images/architecture/message.png)
<center> 图 2 TDengine典型的操作流程 </center>
1. 应用通过JDBC、ODBC或其他API接口发起插入数据的请求。
......@@ -278,7 +278,7 @@ TDengine除vnode分片之外,还对时序数据按照时间段进行分区。
Master Vnode遵循下面的写入流程:
![TDengine Master写入流程](page://images/architecture/write_master.png)
![TDengine Master写入流程](../images/architecture/write_master.png)
<center> 图 3 TDengine Master写入流程 </center>
1. master vnode收到应用的数据插入请求,验证OK,进入下一步;
......@@ -292,7 +292,7 @@ Master Vnode遵循下面的写入流程:
对于slave vnode,写入流程是:
![TDengine Slave写入流程](page://images/architecture/write_slave.png)
![TDengine Slave写入流程](../images/architecture/write_slave.png)
<center> 图 4 TDengine Slave写入流程 </center>
1. slave vnode收到Master vnode转发了的数据插入请求。检查last version是否与master一致,如果一致,进入下一步。如果不一致,需要进入同步状态。
......@@ -434,7 +434,7 @@ SELECT COUNT(*) FROM d1001 WHERE ts >= '2017-7-14 00:00:00' AND ts < '2017-7-14
TDengine对每个数据采集点单独建表,但在实际应用中经常需要对不同的采集点数据进行聚合。为高效的进行聚合操作,TDengine引入超级表(STable)的概念。超级表用来代表一特定类型的数据采集点,它是包含多张表的表集合,集合里每张表的模式(schema)完全一致,但每张表都带有自己的静态标签,标签可以有多个,可以随时增加、删除和修改。应用可通过指定标签的过滤条件,对一个STable下的全部或部分表进行聚合或统计操作,这样大大简化应用的开发。其具体流程如下图所示:
![多表聚合查询原理图](page://images/architecture/multi_tables.png)
![多表聚合查询原理图](../images/architecture/multi_tables.png)
<center> 图 5 多表聚合查询原理图 </center>
1. 应用将一个查询条件发往系统;
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......@@ -4,7 +4,7 @@
`taos-jdbcdriver` 的实现包括 2 种形式: JDBC-JNI 和 JDBC-RESTful(taos-jdbcdriver-2.0.18 开始支持 JDBC-RESTful)。 JDBC-JNI 通过调用客户端 libtaos.so(或 taos.dll )的本地方法实现, JDBC-RESTful 则在内部封装了 RESTful 接口实现。
![tdengine-connector](page://images/tdengine-jdbc-connector.png)
![tdengine-connector](../../images/tdengine-jdbc-connector.png)
上图显示了 3 种 Java 应用使用连接器访问 TDengine 的方式:
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......@@ -2,7 +2,7 @@
TDengine提供了丰富的应用程序开发接口,其中包括C/C++、Java、Python、Go、Node.js、C# 、RESTful 等,便于用户快速开发应用。
![image-connecotr](page://images/connector.png)
![image-connecotr](../images/connector.png)
目前TDengine的连接器可支持的平台广泛,包括:X64/X86/ARM64/ARM32/MIPS/Alpha等硬件平台,以及Linux/Win64/Win32等开发环境。对照矩阵如下:
......@@ -64,8 +64,7 @@ TDengine提供了丰富的应用程序开发接口,其中包括C/C++、Java、
编辑taos.cfg文件(默认路径/etc/taos/taos.cfg),将firstEP修改为TDengine服务器的End Point,例如:h1.taos.com:6030
**提示: **
**提示:**
1. **如本机没有部署TDengine服务,仅安装了应用驱动,则taos.cfg中仅需配置firstEP,无需配置FQDN。**
2. **为防止与服务器端连接时出现“unable to resolve FQDN”错误,建议确认客户端的hosts文件已经配置正确的FQDN值。**
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......@@ -32,15 +32,15 @@ allow_loading_unsigned_plugins = taosdata-tdengine-datasource
用户可以直接通过 localhost:3000 的网址,登录 Grafana 服务器(用户名/密码:admin/admin),通过左侧 `Configuration -> Data Sources` 可以添加数据源,如下图所示:
![img](page://images/connections/add_datasource1.jpg)
![img](../images/connections/add_datasource1.jpg)
点击 `Add data source` 可进入新增数据源页面,在查询框中输入 TDengine 可选择添加,如下图所示:
![img](page://images/connections/add_datasource2.jpg)
![img](../images/connections/add_datasource2.jpg)
进入数据源配置页面,按照默认提示修改相应配置即可:
![img](page://images/connections/add_datasource3.jpg)
![img](../images/connections/add_datasource3.jpg)
* Host: TDengine 集群的中任意一台服务器的 IP 地址与 TDengine RESTful 接口的端口号(6041),默认 http://localhost:6041 。
* User:TDengine 用户名。
......@@ -48,13 +48,13 @@ allow_loading_unsigned_plugins = taosdata-tdengine-datasource
点击 `Save & Test` 进行测试,成功会有如下提示:
![img](page://images/connections/add_datasource4.jpg)
![img](../images/connections/add_datasource4.jpg)
#### 创建 Dashboard
回到主界面创建 Dashboard,点击 Add Query 进入面板查询页面:
![img](page://images/connections/create_dashboard1.jpg)
![img](../images/connections/create_dashboard1.jpg)
如上图所示,在 Query 中选中 `TDengine` 数据源,在下方查询框可输入相应 sql 进行查询,具体说明如下:
......@@ -65,7 +65,7 @@ allow_loading_unsigned_plugins = taosdata-tdengine-datasource
按照默认提示查询当前 TDengine 部署所在服务器指定间隔系统内存平均使用量如下:
![img](page://images/connections/create_dashboard2.jpg)
![img](../images/connections/create_dashboard2.jpg)
> 关于如何使用Grafana创建相应的监测界面以及更多有关使用Grafana的信息,请参考Grafana官方的[文档](https://grafana.com/docs/)。
......@@ -75,11 +75,11 @@ allow_loading_unsigned_plugins = taosdata-tdengine-datasource
点击左侧 `Import` 按钮,并上传 `tdengine-grafana.json` 文件:
![img](page://images/connections/import_dashboard1.jpg)
![img](../images/connections/import_dashboard1.jpg)
导入完成之后可看到如下效果:
![img](page://images/connections/import_dashboard2.jpg)
![img](../images/connections/import_dashboard2.jpg)
## <a class="anchor" id="matlab"></a>MATLAB
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......@@ -15,7 +15,8 @@ One of the modules of TDengine is the time-series database. However, in addition
With TDengine, the total cost of ownership of typical IoT, Internet of Vehicles, and Industrial Internet Big Data platforms can be greatly reduced. However, since it makes full use of the characteristics of IoT time-series data, TDengine cannot be used to process general data from web crawlers, microblogs, WeChat, e-commerce, ERP, CRM, and other sources.
![TDengine Technology Ecosystem](page://images/eco_system.png)
![TDengine Technology Ecosystem](../images/eco_system.png)
<center>Figure 1. TDengine Technology Ecosystem</center>
## <a class="anchor" id="scenes"></a>Overall Scenarios of TDengine
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......@@ -154,7 +154,7 @@ The design of TDengine is based on the assumption that one single node or softwa
Logical structure diagram of TDengine distributed architecture as following:
![TDengine architecture diagram](page://images/architecture/structure.png)
![TDengine architecture diagram](../images/architecture/structure.png)
<center> Figure 1: TDengine architecture diagram </center>
A complete TDengine system runs on one or more physical nodes. Logically, it includes data node (dnode), TDEngine application driver (TAOSC) and application (app). There are one or more data nodes in the system, which form a cluster. The application interacts with the TDengine cluster through TAOSC's API. The following is a brief introduction to each logical unit.
......@@ -197,7 +197,7 @@ A complete TDengine system runs on one or more physical nodes. Logically, it inc
To explain the relationship between vnode, mnode, TAOSC and application and their respective roles, the following is an analysis of a typical data writing process.
![typical process of TDengine](page://images/architecture/message.png)
![typical process of TDengine](../images/architecture/message.png)
<center> Figure 2: Typical process of TDengine </center>
1. Application initiates a request to insert data through JDBC, ODBC, or other APIs.
......@@ -266,7 +266,7 @@ If a database has N replicas, thus a virtual node group has N virtual nodes, but
Master Vnode uses a writing process as follows:
![TDengine Master Writing Process](page://images/architecture/write_master.png)
![TDengine Master Writing Process](../images/architecture/write_master.png)
<center> Figure 3: TDengine Master writing process </center>
1. Master vnode receives the application data insertion request, verifies, and moves to next step;
......@@ -280,7 +280,7 @@ Master Vnode uses a writing process as follows:
For a slave vnode, the write process as follows:
![TDengine Slave Writing Process](page://images/architecture/write_slave.png)
![TDengine Slave Writing Process](../images/architecture/write_slave.png)
<center> Figure 4: TDengine Slave Writing Process </center>
1. Slave vnode receives a data insertion request forwarded by Master vnode;
......@@ -412,7 +412,7 @@ For the data collected by device D1001, the number of records per hour is counte
TDengine creates a separate table for each data collection point, but in practical applications, it is often necessary to aggregate data from different data collection points. In order to perform aggregation operations efficiently, TDengine introduces the concept of STable. STable is used to represent a specific type of data collection point. It is a table set containing multiple tables. The schema of each table in the set is the same, but each table has its own static tag. The tags can be multiple and be added, deleted and modified at any time. Applications can aggregate or statistically operate all or a subset of tables under a STABLE by specifying tag filters, thus greatly simplifying the development of applications. The process is shown in the following figure:
![Diagram of multi-table aggregation query](page://images/architecture/multi_tables.png)
![Diagram of multi-table aggregation query](../images/architecture/multi_tables.png)
<center> Figure 5: Diagram of multi-table aggregation query </center>
1. Application sends a query condition to system;
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......@@ -4,7 +4,7 @@
The taos-jdbcdriver is implemented in two forms: JDBC-JNI and JDBC-RESTful (supported from taos-jdbcdriver-2.0.18). JDBC-JNI is implemented by calling the local methods of libtaos.so (or taos.dll) on the client, while JDBC-RESTful encapsulates the RESTful interface implementation internally.
![tdengine-connector](page://images/tdengine-jdbc-connector.png)
![tdengine-connector](../../images/tdengine-jdbc-connector.png)
The figure above shows the three ways Java applications can access the TDengine:
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......@@ -2,7 +2,7 @@
TDengine provides many connectors for development, including C/C++, JAVA, Python, RESTful, Go, Node.JS, etc.
![image-connector](page://images/connector.png)
![image-connector](../images/connector.png)
At present, TDengine connectors support a wide range of platforms, including hardware platforms such as X64/X86/ARM64/ARM32/MIPS/Alpha, and development environments such as Linux/Win64/Win32. The comparison matrix is as follows:
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......@@ -26,15 +26,15 @@ sudo cp -rf /usr/local/taos/connector/grafanaplugin /var/lib/grafana/plugins/tde
You can log in the Grafana server (username/password:admin/admin) through localhost:3000, and add data sources through `Configuration -> Data Sources` on the left panel, as shown in the following figure:
![img](page://images/connections/add_datasource1.jpg)
![img](../images/connections/add_datasource1.jpg)
Click `Add data source` to enter the Add Data Source page, and enter TDengine in the query box to select Add, as shown in the following figure:
![img](page://images/connections/add_datasource2.jpg)
![img](../images/connections/add_datasource2.jpg)
Enter the data source configuration page and modify the corresponding configuration according to the default prompt:
![img](page://images/connections/add_datasource3.jpg)
![img](../images/connections/add_datasource3.jpg)
- Host: IP address of any server in TDengine cluster and port number of TDengine RESTful interface (6041), default [http://localhost:6041](http://localhost:6041/)
- User: TDengine username.
......@@ -42,13 +42,13 @@ Enter the data source configuration page and modify the corresponding configurat
Click `Save & Test` to test. Success will be prompted as follows:
![img](page://images/connections/add_datasource4.jpg)
![img](../images/connections/add_datasource4.jpg)
#### Create Dashboard
Go back to the home to create Dashboard, and click `Add Query` to enter the panel query page:
![img](page://images/connections/create_dashboard1.jpg)
![img](../images/connections/create_dashboard1.jpg)
As shown in the figure above, select the TDengine data source in Query, and enter the corresponding sql in the query box below to query. Details are as follows:
......@@ -58,7 +58,7 @@ As shown in the figure above, select the TDengine data source in Query, and ente
According to the default prompt, query the average system memory usage at the specified interval of the server where the current TDengine deployed in as follows:
![img](page://images/connections/create_dashboard2.jpg)
![img](../images/connections/create_dashboard2.jpg)
> Please refer to Grafana [documents](https://grafana.com/docs/) for how to use Grafana to create the corresponding monitoring interface and for more about Grafana usage.
......@@ -68,11 +68,11 @@ A `tdengine-grafana.json` importable dashboard is provided under the Grafana plu
Click the `Import` button on the left panel and upload the `tdengine-grafana.json` file:
![img](page://images/connections/import_dashboard1.jpg)
![img](../images/connections/import_dashboard1.jpg)
You can see as follows after Dashboard imported.
![img](page://images/connections/import_dashboard2.jpg)
![img](../images/connections/import_dashboard2.jpg)
## <a class="anchor" id="matlab"></a> MATLAB
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