Skip to content

fix sql dialect in common concepts and the link of zeppin in 1.3.x #854

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
CritasWang merged 1 commit into from
Aug 28, 2025
Merged

fix sql dialect in common concepts and the link of zeppin in 1.3.x #854

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion src/.vuepress/sidebar/V1.3.x/zh.ts
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -215,7 +215,7 @@ export const zhSidebar = {
text: '可视化分析',
collapsible: true,
children: [
{ text: 'Apache Zeppelin', link: 'Zeppelin-IoTDB' },
{ text: 'Apache Zeppelin', link: 'Zeppelin-IoTDB_apache' },
{ text: 'Grafana', link: 'Grafana-Connector' },
{ text: 'Grafana插件', link: 'Grafana-Plugin' },
{ text: 'DataEase', link: 'DataEase' },
Expand Down
2 changes: 1 addition & 1 deletion src/.vuepress/sidebar_timecho/V1.3.x/zh.ts
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -226,7 +226,7 @@ export const zhSidebar = {
text: '可视化分析',
collapsible: true,
children: [
{ text: 'Apache Zeppelin', link: 'Zeppelin-IoTDB' },
{ text: 'Apache Zeppelin', link: 'Zeppelin-IoTDB_timecho' },
{ text: 'Grafana', link: 'Grafana-Connector' },
{ text: 'Grafana插件', link: 'Grafana-Plugin' },
{ text: 'DataEase', link: 'DataEase' },
Expand Down
14 changes: 7 additions & 7 deletions src/UserGuide/V1.3.x/Background-knowledge/Cluster-Concept_apache.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -23,14 +23,14 @@

## Sql_dialect Related Concepts

| Concept | Meaning |
| ----------------------- | ------------------------------------------------------------ |
| sql_dialect | IoTDB supports two time-series data models (SQL dialects), both managing devices and measurement points. Tree: Manages data in a hierarchical path manner, where one path corresponds to one measurement point of a device. Table: Manages data in a relational table manner, where one table corresponds to a category of devices. |
| Schema | Schema is the data model information of the database, i.e., tree structure or table structure. It includes definitions such as the names and data types of measurement points. |
| Device | Corresponds to a physical device in an actual scenario, usually containing multiple measurement points. |
| Concept | Meaning |
| ----------------------- |---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| sql_dialect | Tree model: manages devices and measurement points, manages data in a hierarchical path manner, where one path corresponds to one measurement point of a device. |
| Schema | Schema is the data model information of the database, i.e., tree structure. It includes definitions such as the names and data types of measurement points. |
| Device | Corresponds to a physical device in an actual scenario, usually containing multiple measurement points. |
| Timeseries | Also known as: physical quantity, time series, timeline, point location, semaphore, indicator, measurement value, etc. It is a time series formed by arranging multiple data points in ascending order of timestamps. Usually, a Timeseries represents a collection point that can periodically collect physical quantities of the environment it is in. |
| Encoding | Encoding is a compression technique that represents data in binary form to improve storage efficiency. IoTDB supports various encoding methods for different types of data. For more detailed information, please refer to:[Encoding-and-Compression](../Technical-Insider/Encoding-and-Compression.md) |
| Compression | After data encoding, IoTDB uses compression technology to further compress binary data to enhance storage efficiency. IoTDB supports multiple compression methods. For more detailed information, please refer to: [Encoding-and-Compression](../Technical-Insider/Encoding-and-Compression.md) |
| Encoding | Encoding is a compression technique that represents data in binary form to improve storage efficiency. IoTDB supports various encoding methods for different types of data. For more detailed information, please refer to:[Encoding-and-Compression](../Technical-Insider/Encoding-and-Compression.md) |
| Compression | After data encoding, IoTDB uses compression technology to further compress binary data to enhance storage efficiency. IoTDB supports multiple compression methods. For more detailed information, please refer to: [Encoding-and-Compression](../Technical-Insider/Encoding-and-Compression.md) |

## Distributed Related Concepts

Expand Down
14 changes: 7 additions & 7 deletions src/UserGuide/V1.3.x/Background-knowledge/Cluster-Concept_timecho.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -23,14 +23,14 @@

## Sql_dialect Related Concepts

| Concept | Meaning |
| ----------------------- | ------------------------------------------------------------ |
| sql_dialect | IoTDB supports two time-series data models (SQL dialects), both managing devices and measurement points. Tree: Manages data in a hierarchical path manner, where one path corresponds to one measurement point of a device. Table: Manages data in a relational table manner, where one table corresponds to a category of devices. |
| Schema | Schema is the data model information of the database, i.e., tree structure or table structure. It includes definitions such as the names and data types of measurement points. |
| Device | Corresponds to a physical device in an actual scenario, usually containing multiple measurement points. |
| Concept | Meaning |
| ----------------------- |---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| sql_dialect | Tree model: manages devices and measurement points, manages data in a hierarchical path manner, where one path corresponds to one measurement point of a device. |
| Schema | Schema is the data model information of the database, i.e., tree structure. It includes definitions such as the names and data types of measurement points. |
| Device | Corresponds to a physical device in an actual scenario, usually containing multiple measurement points. |
| Timeseries | Also known as: physical quantity, time series, timeline, point location, semaphore, indicator, measurement value, etc. It is a time series formed by arranging multiple data points in ascending order of timestamps. Usually, a Timeseries represents a collection point that can periodically collect physical quantities of the environment it is in. |
| Encoding | Encoding is a compression technique that represents data in binary form to improve storage efficiency. IoTDB supports various encoding methods for different types of data. For more detailed information, please refer to:[Encoding-and-Compression](../Technical-Insider/Encoding-and-Compression.md) |
| Compression | After data encoding, IoTDB uses compression technology to further compress binary data to enhance storage efficiency. IoTDB supports multiple compression methods. For more detailed information, please refer to: [Encoding-and-Compression](../Technical-Insider/Encoding-and-Compression.md) |
| Encoding | Encoding is a compression technique that represents data in binary form to improve storage efficiency. IoTDB supports various encoding methods for different types of data. For more detailed information, please refer to:[Encoding-and-Compression](../Technical-Insider/Encoding-and-Compression.md) |
| Compression | After data encoding, IoTDB uses compression technology to further compress binary data to enhance storage efficiency. IoTDB supports multiple compression methods. For more detailed information, please refer to: [Encoding-and-Compression](../Technical-Insider/Encoding-and-Compression.md) |

## Distributed Related Concepts

Expand Down
14 changes: 7 additions & 7 deletions src/UserGuide/dev-1.3/Background-knowledge/Cluster-Concept_apache.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -23,14 +23,14 @@

## Sql_dialect Related Concepts

| Concept | Meaning |
| ----------------------- | ------------------------------------------------------------ |
| sql_dialect | IoTDB supports two time-series data models (SQL dialects), both managing devices and measurement points. Tree: Manages data in a hierarchical path manner, where one path corresponds to one measurement point of a device. Table: Manages data in a relational table manner, where one table corresponds to a category of devices. |
| Schema | Schema is the data model information of the database, i.e., tree structure or table structure. It includes definitions such as the names and data types of measurement points. |
| Device | Corresponds to a physical device in an actual scenario, usually containing multiple measurement points. |
| Concept | Meaning |
| ----------------------- |---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| sql_dialect | Tree model: manages devices and measurement points, manages data in a hierarchical path manner, where one path corresponds to one measurement point of a device. |
| Schema | Schema is the data model information of the database, i.e., tree structure. It includes definitions such as the names and data types of measurement points. |
| Device | Corresponds to a physical device in an actual scenario, usually containing multiple measurement points. |
| Timeseries | Also known as: physical quantity, time series, timeline, point location, semaphore, indicator, measurement value, etc. It is a time series formed by arranging multiple data points in ascending order of timestamps. Usually, a Timeseries represents a collection point that can periodically collect physical quantities of the environment it is in. |
| Encoding | Encoding is a compression technique that represents data in binary form to improve storage efficiency. IoTDB supports various encoding methods for different types of data. For more detailed information, please refer to:[Encoding-and-Compression](../Technical-Insider/Encoding-and-Compression.md) |
| Compression | After data encoding, IoTDB uses compression technology to further compress binary data to enhance storage efficiency. IoTDB supports multiple compression methods. For more detailed information, please refer to: [Encoding-and-Compression](../Technical-Insider/Encoding-and-Compression.md) |
| Encoding | Encoding is a compression technique that represents data in binary form to improve storage efficiency. IoTDB supports various encoding methods for different types of data. For more detailed information, please refer to:[Encoding-and-Compression](../Technical-Insider/Encoding-and-Compression.md) |
| Compression | After data encoding, IoTDB uses compression technology to further compress binary data to enhance storage efficiency. IoTDB supports multiple compression methods. For more detailed information, please refer to: [Encoding-and-Compression](../Technical-Insider/Encoding-and-Compression.md) |

## Distributed Related Concepts

Expand Down
14 changes: 7 additions & 7 deletions src/UserGuide/dev-1.3/Background-knowledge/Cluster-Concept_timecho.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -23,14 +23,14 @@

## Sql_dialect Related Concepts

| Concept | Meaning |
| ----------------------- | ------------------------------------------------------------ |
| sql_dialect | IoTDB supports two time-series data models (SQL dialects), both managing devices and measurement points. Tree: Manages data in a hierarchical path manner, where one path corresponds to one measurement point of a device. Table: Manages data in a relational table manner, where one table corresponds to a category of devices. |
| Schema | Schema is the data model information of the database, i.e., tree structure or table structure. It includes definitions such as the names and data types of measurement points. |
| Device | Corresponds to a physical device in an actual scenario, usually containing multiple measurement points. |
| Concept | Meaning |
| ----------------------- |---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| sql_dialect | Tree model: manages devices and measurement points, manages data in a hierarchical path manner, where one path corresponds to one measurement point of a device. |
| Schema | Schema is the data model information of the database, i.e., tree structure. It includes definitions such as the names and data types of measurement points. |
| Device | Corresponds to a physical device in an actual scenario, usually containing multiple measurement points. |
| Timeseries | Also known as: physical quantity, time series, timeline, point location, semaphore, indicator, measurement value, etc. It is a time series formed by arranging multiple data points in ascending order of timestamps. Usually, a Timeseries represents a collection point that can periodically collect physical quantities of the environment it is in. |
| Encoding | Encoding is a compression technique that represents data in binary form to improve storage efficiency. IoTDB supports various encoding methods for different types of data. For more detailed information, please refer to:[Encoding-and-Compression](../Technical-Insider/Encoding-and-Compression.md) |
| Compression | After data encoding, IoTDB uses compression technology to further compress binary data to enhance storage efficiency. IoTDB supports multiple compression methods. For more detailed information, please refer to: [Encoding-and-Compression](../Technical-Insider/Encoding-and-Compression.md) |
| Encoding | Encoding is a compression technique that represents data in binary form to improve storage efficiency. IoTDB supports various encoding methods for different types of data. For more detailed information, please refer to:[Encoding-and-Compression](../Technical-Insider/Encoding-and-Compression.md) |
| Compression | After data encoding, IoTDB uses compression technology to further compress binary data to enhance storage efficiency. IoTDB supports multiple compression methods. For more detailed information, please refer to: [Encoding-and-Compression](../Technical-Insider/Encoding-and-Compression.md) |

## Distributed Related Concepts

Expand Down
Loading