**MNODE的选择:** TDengine逻辑上有管理节点,但没有单独的执行代码,服务器侧只有一套执行代码taosd。那么哪个数据节点会是管理节点呢?这是系统自动决定的,无需任何人工干预。原则如下:一个数据节点启动时,会检查自己的End Point, 并与获取的mnode EP List进行比对,如果在其中,该数据节点认为自己应该启动mnode模块,成为mnode。如果自己的EP不在mnode EP List里,则不启动mnode模块。在系统的运行过程中,由于负载均衡、宕机等原因,mnode有可能迁移至新的dnode,但一切都是透明的,无需人工干预,配置参数的修改,是mnode自己根据资源做出的决定。
**重定向**:无论是dnode还是taosc,最先都是要发起与mnode的连接,但mnode是系统自动创建并维护的,因此对于用户来说,并不知道哪个dnode在运行mnode。TDengine只要求向系统中任何一个工作的dnode发起连接即可。因为任何一个正在运行的dnode,都维护有目前运行的mnode EP List。当收到一个来自新启动的dnode或taosc的连接请求,如果自己不是mnode,则将mnode EP List回复给对方,taosc或新启动的dnode收到这个list, 就重新尝试建立连接。当mnode EP List发生改变,通过节点之间的消息交互,各个数据节点就很快获取最新列表,并通知taosc。
**MNODE的选择:**TDengine逻辑上有管理节点,但没有单独的执行代码,服务器侧只有一套执行代码taosd。那么哪个数据节点会是管理节点呢?这是系统自动决定的,无需任何人工干预。原则如下:一个数据节点启动时,会检查自己的End Point, 并与获取的mnode EP List进行比对,如果在其中,该数据节点认为自己应该启动mnode模块,成为mnode。如果自己的EP不在mnode EP List里,则不启动mnode模块。在系统的运行过程中,由于负载均衡、宕机等原因,mnode有可能迁移至新的dnode,但一切都是透明的,无需人工干预,配置参数的修改,是mnode自己根据资源做出的决定。
**重定向:**无论是dnode还是taosc,最先都是要发起与mnode的连接,但mnode是系统自动创建并维护的,因此对于用户来说,并不知道哪个dnode在运行mnode。TDengine只要求向系统中任何一个工作的dnode发起连接即可。因为任何一个正在运行的dnode,都维护有目前运行的mnode EP List。当收到一个来自新启动的dnode或taosc的连接请求,如果自己不是mnode,则将mnode EP List回复给对方,taosc或新启动的dnode收到这个list, 就重新尝试建立连接。当mnode EP List发生改变,通过节点之间的消息交互,各个数据节点就很快获取最新列表,并通知taosc。
如果以上步骤不能成功执行,可以参考微软的node.js用户手册[Microsoft's Node.js Guidelines for Windows](https://github.com/Microsoft/nodejs-guidelines/blob/master/windows-environment.md#compiling-native-addon-modules)
如果以上步骤不能成功执行,可以参考微软的node.js用户手册[Microsoft's Node.js Guidelines for Windows](https://github.com/Microsoft/nodejs-guidelines/blob/master/windows-environment.md#compiling-native-addon-modules)。
如果在Windows 10 ARM 上使用ARM64 Node.js,还需添加 "Visual C++ compilers and libraries for ARM64" 和 "Visual C++ ATL for ARM64"。
如果在Windows 10 ARM 上使用ARM64 Node.js,还需添加 "Visual C++ compilers and libraries for ARM64" 和 "Visual C++ ATL for ARM64"。
@@ -9,7 +9,7 @@ Please watch the [video tutorial](https://www.taosdata.com/blog/2020/11/11/1945.
...
@@ -9,7 +9,7 @@ Please watch the [video tutorial](https://www.taosdata.com/blog/2020/11/11/1945.
Different types of data collection points often have different data characteristics, including frequency of data collecting, length of data retention time, number of replicas, size of data blocks, whether to update data or not, and so on. To ensure TDengine working with great efficiency in various scenarios, TDengine suggests creating tables with different data characteristics in different databases, because each database can be configured with different storage strategies. When creating a database, in addition to SQL standard options, the application can also specify a variety of parameters such as retention duration, number of replicas, number of memory blocks, time accuracy, max and min number of records in a file block, whether it is compressed or not, and number of days a data file will be overwritten. For example:
Different types of data collection points often have different data characteristics, including frequency of data collecting, length of data retention time, number of replicas, size of data blocks, whether to update data or not, and so on. To ensure TDengine working with great efficiency in various scenarios, TDengine suggests creating tables with different data characteristics in different databases, because each database can be configured with different storage strategies. When creating a database, in addition to SQL standard options, the application can also specify a variety of parameters such as retention duration, number of replicas, number of memory blocks, time accuracy, max and min number of records in a file block, whether it is compressed or not, and number of days a data file will be overwritten. For example:
```mysql
```mysql
CREATE DATABASE power KEEP 365 DAYS 10 BLOCKS 4 UPDATE 1;
CREATE DATABASE power KEEP 365 DAYS 10 BLOCKS 6 UPDATE 1;
```
```
The above statement will create a database named “power”. The data of this database will be kept for 365 days (it will be automatically deleted 365 days later), one data file created per 10 days, and the number of memory blocks is 4 for data updating. For detailed syntax and parameters, please refer to [Data Management section of TAOS SQL](https://www.taosdata.com/en/documentation/taos-sql#management).
The above statement will create a database named “power”. The data of this database will be kept for 365 days (it will be automatically deleted 365 days later), one data file created per 10 days, and the number of memory blocks is 4 for data updating. For detailed syntax and parameters, please refer to [Data Management section of TAOS SQL](https://www.taosdata.com/en/documentation/taos-sql#management).
tdSql.execute("insert into t6004 using t6 (dev,dev1,dev2) tags ('b50c79bc-b102-48e6-bda1-4212263e46d0','b50c79bc-b102-48e6-bda1-4212263e46d0', 'b50c79bc-b102-48e6-bda1-4212263e46d0') values(now,1,'b50c79bc-b102-48e6-bda1-4212263e46d0')")
print("==============step2")
tdSql.query("select * from t6 where dev='b50c79bc-b102-48e6-bda1-4212263e46d0'")
tdSql.checkRows(1)
tdSql.query("select * from t6 where dev1='b50c79bc-b102-48e6-bda1-4212263e46d0'")
tdSql.checkRows(1)
tdSql.query("select * from t6 where dev2='b50c79bc-b102-48e6-bda1-4212263e46d0'")