@@ -52,7 +52,7 @@ Start TDengine service and execute `taosBenchmark` (formerly named `taosdemo`) i
...
@@ -52,7 +52,7 @@ Start TDengine service and execute `taosBenchmark` (formerly named `taosdemo`) i
taosBenchmark
taosBenchmark
```
```
This command creates the `meters` supertable in the `test` database. In the `meters` supertable, it then creates 10,000 subtables named `d0` to `d9999`. Each table has 10,000 rows and each row has four columns: `ts`, `current`, `voltage`, and `phase`. The timestamps of the data in these columns range from 2017-07-14 10:40:00 000 to 2017-07-14 10:40:09 999. Each table is randomly assigned a `groupId` tag from 1 to 10 and a `location` tag of either `Campbell`, `Cupertino`, `Los Angeles`, `Mountain View`, `Palo Alto`, `San Diego`, `San Francisco`, `San Jose`, `Santa Clara` or `Sunnyvale`.
This command creates the `meters` supertable in the `test` database. In the `meters` supertable, it then creates 10,000 subtables named `d0` to `d9999`. Each table has 10,000 rows and each row has four columns: `ts`, `current`, `voltage`, and `phase`. The timestamps of the data in these columns range from 2017-07-14 10:40:00 000 to 2017-07-14 10:40:09 999. Each table is randomly assigned a `groupId` tag from 1 to 10 and a `location` tag of either `California.Campbell`, `California.Cupertino`, `California.LosAngeles`, `California.MountainView`, `California.PaloAlto`, `California.SanDiego`, `California.SanFrancisco`, `California.SanJose`, `California.SantaClara` or `California.Sunnyvale`.
The `taosBenchmark` command creates a deployment with 100 million data points that you can use for testing purposes. The time required to create the deployment depends on your hardware. On most modern servers, the deployment is created in ten to twenty seconds.
The `taosBenchmark` command creates a deployment with 100 million data points that you can use for testing purposes. The time required to create the deployment depends on your hardware. On most modern servers, the deployment is created in ten to twenty seconds.
...
@@ -74,10 +74,10 @@ Query the average, maximum, and minimum values of all 100 million rows of data:
...
@@ -74,10 +74,10 @@ Query the average, maximum, and minimum values of all 100 million rows of data:
@@ -221,7 +221,7 @@ Start TDengine service and execute `taosBenchmark` (formerly named `taosdemo`) i
...
@@ -221,7 +221,7 @@ Start TDengine service and execute `taosBenchmark` (formerly named `taosdemo`) i
taosBenchmark
taosBenchmark
```
```
This command creates the `meters` supertable in the `test` database. In the `meters` supertable, it then creates 10,000 subtables named `d0` to `d9999`. Each table has 10,000 rows and each row has four columns: `ts`, `current`, `voltage`, and `phase`. The timestamps of the data in these columns range from 2017-07-14 10:40:00 000 to 2017-07-14 10:40:09 999. Each table is randomly assigned a `groupId` tag from 1 to 10 and a `location` tag of either `Campbell`, `Cupertino`, `Los Angeles`, `Mountain View`, `Palo Alto`, `San Diego`, `San Francisco`, `San Jose`, `Santa Clara` or `Sunnyvale`.
This command creates the `meters` supertable in the `test` database. In the `meters` supertable, it then creates 10,000 subtables named `d0` to `d9999`. Each table has 10,000 rows and each row has four columns: `ts`, `current`, `voltage`, and `phase`. The timestamps of the data in these columns range from 2017-07-14 10:40:00 000 to 2017-07-14 10:40:09 999. Each table is randomly assigned a `groupId` tag from 1 to 10 and a `location` tag of either `California.Campbell`, `California.Cupertino`, `California.LosAngeles`, `California.MountainView`, `California.PaloAlto`, `California.SanDiego`, `California.SanFrancisco`, `California.SanJose`, `California.SantaClara` or `California.Sunnyvale`.
The `taosBenchmark` command creates a deployment with 100 million data points that you can use for testing purposes. The time required to create the deployment depends on your hardware. On most modern servers, the deployment is created in ten to twenty seconds.
The `taosBenchmark` command creates a deployment with 100 million data points that you can use for testing purposes. The time required to create the deployment depends on your hardware. On most modern servers, the deployment is created in ten to twenty seconds.
...
@@ -243,10 +243,10 @@ Query the average, maximum, and minimum values of all 100 million rows of data:
...
@@ -243,10 +243,10 @@ Query the average, maximum, and minimum values of all 100 million rows of data:
tdSql.query("select count(*) from test.meters where groupid >= 0")
tdSql.query("select count(*) from test.meters where groupid >= 0")
tdSql.checkData(0,0,10000)
tdSql.checkData(0,0,10000)
tdSql.query("select count(*) from test.meters where location = 'San Francisco' or location = 'Los Angles' or location = 'San Diego' or location = 'San Jose' or \
tdSql.query(
location = 'Palo Alto' or location = 'Campbell' or location = 'Mountain View' or location = 'Sunnyvale' or location = 'Santa Clara' or location = 'Cupertino' ")
"select count(*) from test.meters where location = 'California.SanFrancisco' or location = 'California.LosAngles' or location = 'California.SanDiego' or location = 'California.SanJose' or \
location = 'California.PaloAlto' or location = 'California.Campbell' or location = 'California.MountainView' or location = 'California.Sunnyvale' or location = 'California.SantaClara' or location = 'California.Cupertino' "