diff --git a/src/.vuepress/sidebar/V1.3.x/zh.ts b/src/.vuepress/sidebar/V1.3.x/zh.ts index 57f3b7d45..024e2c324 100644 --- a/src/.vuepress/sidebar/V1.3.x/zh.ts +++ b/src/.vuepress/sidebar/V1.3.x/zh.ts @@ -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' }, diff --git a/src/.vuepress/sidebar_timecho/V1.3.x/zh.ts b/src/.vuepress/sidebar_timecho/V1.3.x/zh.ts index afeaf1a7e..1c10c1988 100644 --- a/src/.vuepress/sidebar_timecho/V1.3.x/zh.ts +++ b/src/.vuepress/sidebar_timecho/V1.3.x/zh.ts @@ -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' }, diff --git a/src/UserGuide/V1.3.x/Background-knowledge/Cluster-Concept_apache.md b/src/UserGuide/V1.3.x/Background-knowledge/Cluster-Concept_apache.md index 674a74e69..1f35d01da 100644 --- a/src/UserGuide/V1.3.x/Background-knowledge/Cluster-Concept_apache.md +++ b/src/UserGuide/V1.3.x/Background-knowledge/Cluster-Concept_apache.md @@ -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 diff --git a/src/UserGuide/V1.3.x/Background-knowledge/Cluster-Concept_timecho.md b/src/UserGuide/V1.3.x/Background-knowledge/Cluster-Concept_timecho.md index 42344aa47..5f0682521 100644 --- a/src/UserGuide/V1.3.x/Background-knowledge/Cluster-Concept_timecho.md +++ b/src/UserGuide/V1.3.x/Background-knowledge/Cluster-Concept_timecho.md @@ -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 diff --git a/src/UserGuide/dev-1.3/Background-knowledge/Cluster-Concept_apache.md b/src/UserGuide/dev-1.3/Background-knowledge/Cluster-Concept_apache.md index 674a74e69..1f35d01da 100644 --- a/src/UserGuide/dev-1.3/Background-knowledge/Cluster-Concept_apache.md +++ b/src/UserGuide/dev-1.3/Background-knowledge/Cluster-Concept_apache.md @@ -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 diff --git a/src/UserGuide/dev-1.3/Background-knowledge/Cluster-Concept_timecho.md b/src/UserGuide/dev-1.3/Background-knowledge/Cluster-Concept_timecho.md index 42344aa47..5f0682521 100644 --- a/src/UserGuide/dev-1.3/Background-knowledge/Cluster-Concept_timecho.md +++ b/src/UserGuide/dev-1.3/Background-knowledge/Cluster-Concept_timecho.md @@ -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 diff --git a/src/zh/UserGuide/V1.3.x/Background-knowledge/Cluster-Concept_apache.md b/src/zh/UserGuide/V1.3.x/Background-knowledge/Cluster-Concept_apache.md index c5e4b8309..6fb96fdf9 100644 --- a/src/zh/UserGuide/V1.3.x/Background-knowledge/Cluster-Concept_apache.md +++ b/src/zh/UserGuide/V1.3.x/Background-knowledge/Cluster-Concept_apache.md @@ -23,14 +23,14 @@ ## 数据模型相关概念 -| 概念 | 含义 | -| ----------------------- | ------------------------------------------------------------ | -| 数据模型（sql_dialect） | IoTDB 支持两种时序数据模型（SQL语法），管理的对象均为设备和测点树：以层级路径的方式管理数据，一条路径对应一个设备的一个测点表：以关系表的方式管理数据，一张表对应一类设备 | -| 元数据（Schema） | 元数据是数据库的数据模型信息，即树形结构或表结构。包括测点的名称、数据类型等定义。 | -| 设备（Device） | 对应一个实际场景中的物理设备，通常包含多个测点。 | -| 测点（Timeseries） | 又名：物理量、时间序列、时间线、点位、信号量、指标、测量值等。是多个数据点按时间戳递增排列形成的一个时间序列。通常一个测点代表一个采集点位，能够定期采集所在环境的物理量。 | -| 编码（Encoding） | 编码是一种压缩技术，将数据以二进制的形式进行表示，可以提高存储效率。IoTDB 支持多种针对不同类型的数据的编码方法，详细信息请查看：[压缩和编码](../Technical-Insider/Encoding-and-Compression.md) | -| 压缩（Compression） | IoTDB 在数据编码后，使用压缩技术进一步压缩二进制数据，提升存储效率。IoTDB 支持多种压缩方法，详细信息请查看：[压缩和编码](../Technical-Insider/Encoding-and-Compression.md) | +| 概念 | 含义 | +|-----------------|----------------------------------------------------------------------------------------------------------------------------| +| 数据模型 | 树模型，管理的对象为设备和测点，以层级路径的方式管理数据，一条路径对应一个设备的一个测点 | +| 元数据（Schema） | 元数据是数据库的数据模型信息，即树形结构，包括测点的名称、数据类型等定义。 | +| 设备（Device） | 对应一个实际场景中的物理设备，通常包含多个测点。 | +| 测点（Timeseries） | 又名：物理量、时间序列、时间线、点位、信号量、指标、测量值等。是多个数据点按时间戳递增排列形成的一个时间序列。通常一个测点代表一个采集点位，能够定期采集所在环境的物理量。 | +| 编码（Encoding） | 编码是一种压缩技术，将数据以二进制的形式进行表示，可以提高存储效率。IoTDB 支持多种针对不同类型的数据的编码方法，详细信息请查看：[压缩和编码](../Technical-Insider/Encoding-and-Compression.md) | +| 压缩（Compression） | IoTDB 在数据编码后，使用压缩技术进一步压缩二进制数据，提升存储效率。IoTDB 支持多种压缩方法，详细信息请查看：[压缩和编码](../Technical-Insider/Encoding-and-Compression.md) | ## 分布式相关概念 diff --git a/src/zh/UserGuide/V1.3.x/Background-knowledge/Cluster-Concept_timecho.md b/src/zh/UserGuide/V1.3.x/Background-knowledge/Cluster-Concept_timecho.md index 4fbd9165d..378424ea7 100644 --- a/src/zh/UserGuide/V1.3.x/Background-knowledge/Cluster-Concept_timecho.md +++ b/src/zh/UserGuide/V1.3.x/Background-knowledge/Cluster-Concept_timecho.md @@ -23,14 +23,14 @@ ## 数据模型相关概念 -| 概念 | 含义 | -| ----------------------- | ------------------------------------------------------------ | -| 数据模型（sql_dialect） | IoTDB 支持两种时序数据模型（SQL语法），管理的对象均为设备和测点树：以层级路径的方式管理数据，一条路径对应一个设备的一个测点表：以关系表的方式管理数据，一张表对应一类设备 | -| 元数据（Schema） | 元数据是数据库的数据模型信息，即树形结构或表结构。包括测点的名称、数据类型等定义。 | -| 设备（Device） | 对应一个实际场景中的物理设备，通常包含多个测点。 | -| 测点（Timeseries） | 又名：物理量、时间序列、时间线、点位、信号量、指标、测量值等。是多个数据点按时间戳递增排列形成的一个时间序列。通常一个测点代表一个采集点位，能够定期采集所在环境的物理量。 | -| 编码（Encoding） | 编码是一种压缩技术，将数据以二进制的形式进行表示，可以提高存储效率。IoTDB 支持多种针对不同类型的数据的编码方法，详细信息请查看：[压缩和编码](../Technical-Insider/Encoding-and-Compression.md) | -| 压缩（Compression） | IoTDB 在数据编码后，使用压缩技术进一步压缩二进制数据，提升存储效率。IoTDB 支持多种压缩方法，详细信息请查看：[压缩和编码](../Technical-Insider/Encoding-and-Compression.md) | +| 概念 | 含义 | +|-----------------|----------------------------------------------------------------------------------------------------------------------------| +| 数据模型 | 树模型，管理的对象为设备和测点，以层级路径的方式管理数据，一条路径对应一个设备的一个测点 | +| 元数据（Schema） | 元数据是数据库的数据模型信息，即树形结构，包括测点的名称、数据类型等定义。 | +| 设备（Device） | 对应一个实际场景中的物理设备，通常包含多个测点。 | +| 测点（Timeseries） | 又名：物理量、时间序列、时间线、点位、信号量、指标、测量值等。是多个数据点按时间戳递增排列形成的一个时间序列。通常一个测点代表一个采集点位，能够定期采集所在环境的物理量。 | +| 编码（Encoding） | 编码是一种压缩技术，将数据以二进制的形式进行表示，可以提高存储效率。IoTDB 支持多种针对不同类型的数据的编码方法，详细信息请查看：[压缩和编码](../Technical-Insider/Encoding-and-Compression.md) | +| 压缩（Compression） | IoTDB 在数据编码后，使用压缩技术进一步压缩二进制数据，提升存储效率。IoTDB 支持多种压缩方法，详细信息请查看：[压缩和编码](../Technical-Insider/Encoding-and-Compression.md) | ## 分布式相关概念 diff --git a/src/zh/UserGuide/dev-1.3/Background-knowledge/Cluster-Concept_apache.md b/src/zh/UserGuide/dev-1.3/Background-knowledge/Cluster-Concept_apache.md index c5e4b8309..6fb96fdf9 100644 --- a/src/zh/UserGuide/dev-1.3/Background-knowledge/Cluster-Concept_apache.md +++ b/src/zh/UserGuide/dev-1.3/Background-knowledge/Cluster-Concept_apache.md @@ -23,14 +23,14 @@ ## 数据模型相关概念 -| 概念 | 含义 | -| ----------------------- | ------------------------------------------------------------ | -| 数据模型（sql_dialect） | IoTDB 支持两种时序数据模型（SQL语法），管理的对象均为设备和测点树：以层级路径的方式管理数据，一条路径对应一个设备的一个测点表：以关系表的方式管理数据，一张表对应一类设备 | -| 元数据（Schema） | 元数据是数据库的数据模型信息，即树形结构或表结构。包括测点的名称、数据类型等定义。 | -| 设备（Device） | 对应一个实际场景中的物理设备，通常包含多个测点。 | -| 测点（Timeseries） | 又名：物理量、时间序列、时间线、点位、信号量、指标、测量值等。是多个数据点按时间戳递增排列形成的一个时间序列。通常一个测点代表一个采集点位，能够定期采集所在环境的物理量。 | -| 编码（Encoding） | 编码是一种压缩技术，将数据以二进制的形式进行表示，可以提高存储效率。IoTDB 支持多种针对不同类型的数据的编码方法，详细信息请查看：[压缩和编码](../Technical-Insider/Encoding-and-Compression.md) | -| 压缩（Compression） | IoTDB 在数据编码后，使用压缩技术进一步压缩二进制数据，提升存储效率。IoTDB 支持多种压缩方法，详细信息请查看：[压缩和编码](../Technical-Insider/Encoding-and-Compression.md) | +| 概念 | 含义 | +|-----------------|----------------------------------------------------------------------------------------------------------------------------| +| 数据模型 | 树模型，管理的对象为设备和测点，以层级路径的方式管理数据，一条路径对应一个设备的一个测点 | +| 元数据（Schema） | 元数据是数据库的数据模型信息，即树形结构，包括测点的名称、数据类型等定义。 | +| 设备（Device） | 对应一个实际场景中的物理设备，通常包含多个测点。 | +| 测点（Timeseries） | 又名：物理量、时间序列、时间线、点位、信号量、指标、测量值等。是多个数据点按时间戳递增排列形成的一个时间序列。通常一个测点代表一个采集点位，能够定期采集所在环境的物理量。 | +| 编码（Encoding） | 编码是一种压缩技术，将数据以二进制的形式进行表示，可以提高存储效率。IoTDB 支持多种针对不同类型的数据的编码方法，详细信息请查看：[压缩和编码](../Technical-Insider/Encoding-and-Compression.md) | +| 压缩（Compression） | IoTDB 在数据编码后，使用压缩技术进一步压缩二进制数据，提升存储效率。IoTDB 支持多种压缩方法，详细信息请查看：[压缩和编码](../Technical-Insider/Encoding-and-Compression.md) | ## 分布式相关概念 diff --git a/src/zh/UserGuide/dev-1.3/Background-knowledge/Cluster-Concept_timecho.md b/src/zh/UserGuide/dev-1.3/Background-knowledge/Cluster-Concept_timecho.md index 4fbd9165d..378424ea7 100644 --- a/src/zh/UserGuide/dev-1.3/Background-knowledge/Cluster-Concept_timecho.md +++ b/src/zh/UserGuide/dev-1.3/Background-knowledge/Cluster-Concept_timecho.md @@ -23,14 +23,14 @@ ## 数据模型相关概念 -| 概念 | 含义 | -| ----------------------- | ------------------------------------------------------------ | -| 数据模型（sql_dialect） | IoTDB 支持两种时序数据模型（SQL语法），管理的对象均为设备和测点树：以层级路径的方式管理数据，一条路径对应一个设备的一个测点表：以关系表的方式管理数据，一张表对应一类设备 | -| 元数据（Schema） | 元数据是数据库的数据模型信息，即树形结构或表结构。包括测点的名称、数据类型等定义。 | -| 设备（Device） | 对应一个实际场景中的物理设备，通常包含多个测点。 | -| 测点（Timeseries） | 又名：物理量、时间序列、时间线、点位、信号量、指标、测量值等。是多个数据点按时间戳递增排列形成的一个时间序列。通常一个测点代表一个采集点位，能够定期采集所在环境的物理量。 | -| 编码（Encoding） | 编码是一种压缩技术，将数据以二进制的形式进行表示，可以提高存储效率。IoTDB 支持多种针对不同类型的数据的编码方法，详细信息请查看：[压缩和编码](../Technical-Insider/Encoding-and-Compression.md) | -| 压缩（Compression） | IoTDB 在数据编码后，使用压缩技术进一步压缩二进制数据，提升存储效率。IoTDB 支持多种压缩方法，详细信息请查看：[压缩和编码](../Technical-Insider/Encoding-and-Compression.md) | +| 概念 | 含义 | +|-----------------|----------------------------------------------------------------------------------------------------------------------------| +| 数据模型 | 树模型，管理的对象为设备和测点，以层级路径的方式管理数据，一条路径对应一个设备的一个测点 | +| 元数据（Schema） | 元数据是数据库的数据模型信息，即树形结构，包括测点的名称、数据类型等定义。 | +| 设备（Device） | 对应一个实际场景中的物理设备，通常包含多个测点。 | +| 测点（Timeseries） | 又名：物理量、时间序列、时间线、点位、信号量、指标、测量值等。是多个数据点按时间戳递增排列形成的一个时间序列。通常一个测点代表一个采集点位，能够定期采集所在环境的物理量。 | +| 编码（Encoding） | 编码是一种压缩技术，将数据以二进制的形式进行表示，可以提高存储效率。IoTDB 支持多种针对不同类型的数据的编码方法，详细信息请查看：[压缩和编码](../Technical-Insider/Encoding-and-Compression.md) | +| 压缩（Compression） | IoTDB 在数据编码后，使用压缩技术进一步压缩二进制数据，提升存储效率。IoTDB 支持多种压缩方法，详细信息请查看：[压缩和编码](../Technical-Insider/Encoding-and-Compression.md) | ## 分布式相关概念