adjust rpr and wf to advanced timecho

src/.vuepress/sidebar_timecho/V2.0.x/en-Table.ts

@@ -133,6 +133,7 @@ export const enSidebar = {
         },
         { text: 'Tiered Storage', link: 'Tiered-Storage_timecho' },
         { text: 'Tree-to-Table Mapping', link: 'Tree-to-Table' },
+        { text: 'Timeseries Featured Analysis', link: 'Timeseries-Featured-Analysis_timecho' },
         {
           text: 'System Maintenance',
           collapsible: true,
@@ -246,7 +247,7 @@ export const enSidebar = {
             { text: 'ORDER BY Clause', link: 'OrderBy-Clause' },
             { text: 'LIMIT&OFFSET Clause', link: 'Limit-Offset-Clause' },
             { text: 'Nested Queries', link: 'Nested-Queries' },
-            { text: 'Row Pattern Recognition', link: 'Row-Pattern-Recognition' },
+            { text: 'Pattern Query', link: 'Row-Pattern-Recognition_timecho' },
           ],
         },
         { text: 'Maintenance Statements', link: 'SQL-Maintenance-Statements' },

src/.vuepress/sidebar_timecho/V2.0.x/zh-Table.ts

@@ -122,6 +122,7 @@ export const zhSidebar = {
         },
         { text: '多级存储', link: 'Tiered-Storage_timecho' },
         { text: '树转表视图', link: 'Tree-to-Table' },
+        { text: '时序特色分析', link: 'Timeseries-Featured-Analysis_timecho' },
         {
           text: '系统运维',
           collapsible: true,
@@ -235,7 +236,7 @@ export const zhSidebar = {
             { text: 'ORDER BY子句', link: 'OrderBy-Clause' },
             { text: 'LIMIT&OFFSET子句', link: 'Limit-Offset-Clause' },
             { text: '嵌套查询', link: 'Nested-Queries' },
-            { text: '行模式识别', link: 'Row-Pattern-Recognition' },
+            { text: '模式查询', link: 'Row-Pattern-Recognition_timecho' },
           ],
         },
         { text: '运维语句', link: 'SQL-Maintenance-Statements' },

src/UserGuide/Master/Table/Basic-Concept/Query-Data_timecho.md

@@ -40,11 +40,9 @@ The IoTDB table model query syntax supports the following clauses:
 
 - **SELECT Clause**: Specifies the columns to be included in the result. Details: [SELECT Clause](../SQL-Manual/Select-Clause.md)
 - **FROM Clause**: Indicates the data source for the query, which can be a single table, multiple tables joined using the `JOIN` clause, or a subquery. Details: [FROM & JOIN Clause](../SQL-Manual/From-Join-Clause.md)
-- **patternRecognition**: Row Pattern Recognition, which supports capturing a segment of continuous data by defining recognition logic for pattern variables and regular expressions, and performs analysis and calculation on each captured data segment. Details:[Row Pattern Recognition](../SQL-Manual/Row-Pattern-Recognition.md)
 - **WHERE Clause**: Filters rows based on specific conditions. Logically executed immediately after the `FROM` clause. Details: [WHERE Clause](../SQL-Manual/Where-Clause.md)
 - **GROUP BY Clause**: Used for aggregating data, specifying the columns for grouping. Details: [GROUP BY Clause](../SQL-Manual/GroupBy-Clause.md)
 - **HAVING Clause**: Applied after the `GROUP BY` clause to filter grouped data, similar to `WHERE` but operates after grouping. Details:[HAVING Clause](../SQL-Manual/Having-Clause.md)
-- **WINDOW FUNCTION**: Window Function, a special function that performs calculations on each row based on a specific set of rows related to the current row (called a "window"). It combines grouping operations, sorting, and definable calculation ranges to implement complex cross-row calculations without collapsing the original data rows. Details: [Window Function](../SQL-Manual/Featured-Functions_timecho.md#_4-Window-Function)
 - **FILL Clause**: Handles missing values in query results by specifying fill methods (e.g., previous non-null value or linear interpolation) for better visualization and analysis. Details:[FILL Clause](../SQL-Manual/Fill-Clause.md)
 - **ORDER BY Clause**: Sorts query results in ascending (`ASC`) or descending (`DESC`) order, with optional handling for null values (`NULLS FIRST` or `NULLS LAST`). Details: [ORDER BY Clause](../SQL-Manual/OrderBy-Clause.md)
 - **OFFSET Clause**: Specifies the starting position for the query result, skipping the first `OFFSET` rows. Often used with the `LIMIT` clause. Details: [LIMIT and OFFSET Clause](../SQL-Manual/Limit-Offset-Clause.md)
@@ -590,77 +588,3 @@ IoTDB> SELECT time, temperature, humidity
 Total line number = 10
 It costs 0.093s
 ```
-
-### 3.9 Row Pattern Recognition
-
-**Example**: Segment data in table1 by time intervals of 24 hours or less, and query the total number of data entries in each segment, as well as the start and end times.
-
-```SQL
-SELECT start_time, end_time, cnt 
-FROM table1 
-MATCH_RECOGNIZE (
-    ORDER BY time 
-    MEASURES 
-        RPR_FIRST(A.time) AS start_time, 
-        RPR_LAST(time) AS end_time, 
-        COUNT() AS cnt 
-    PATTERN (A B*)  
-    DEFINE  B AS (cast(B.time as INT64) - cast(PREV(B.time) as INT64)) <= 86400000
-) AS m
-```
-
-**Result**:
-
-```SQL
-+-----------------------------+-----------------------------+---+
-|                   start_time|                     end_time|cnt|
-+-----------------------------+-----------------------------+---+
-|2024-11-26T13:37:00.000+08:00|2024-11-26T13:38:00.000+08:00|  2|
-|2024-11-27T16:38:00.000+08:00|2024-11-30T14:30:00.000+08:00| 16|
-+-----------------------------+-----------------------------+---+
-Total line number = 2
-```
-
-### 3.10 Window Functions
-
-**Example**: Query the cumulative power consumption values of different devices.
-
-The original data is as follows:
-
-```SQL
-+-----------------------------+------+-----+
-|                         time|device| flow|
-+-----------------------------+------+-----+
-|1970-01-01T08:00:00.000+08:00|    d0|    3|
-|1970-01-01T08:00:00.001+08:00|    d0|    5|
-|1970-01-01T08:00:00.002+08:00|    d0|    3|
-|1970-01-01T08:00:00.003+08:00|    d0|    1|
-|1970-01-01T08:00:00.004+08:00|    d1|    2|
-|1970-01-01T08:00:00.005+08:00|    d1|    4|
-+-----------------------------+------+-----+
-```
-
-**Query Statement**:
-
-```SQL
-IoTDB> SELECT *, sum(flow) OVER(PARTITION BY device ORDER BY flow) as sum FROM device_flow;
-```
-
-After grouping, sorting, and calculation (steps are disassembled as shown in the figure below),
-
-![](/img/window-function-1.png)
-
-**Result**:
-
-```SQL
-+-----------------------------+------+----+----+
-|                         time|device|flow| sum|
-+-----------------------------+------+----+----+
-|1970-01-01T08:00:04.000+08:00|    d1|   2| 2.0|
-|1970-01-01T08:00:05.000+08:00|    d1|   4| 6.0|
-|1970-01-01T08:00:03.000+08:00|    d0|   1| 1.0|
-|1970-01-01T08:00:00.000+08:00|    d0|   3| 7.0|
-|1970-01-01T08:00:02.000+08:00|    d0|   3| 7.0|
-|1970-01-01T08:00:01.000+08:00|    d0|   5|12.0|
-+-----------------------------+------+----+----+
-```

src/UserGuide/Master/Table/QuickStart/QuickStart_timecho.md

@@ -62,7 +62,7 @@ This guide will assist you in quickly installing and deploying IoTDB. You can qu
 
 2. Data Insertion & Updates: IoTDB provides multiple methods for inserting real-time data. For basic data insertion and updating operations, please see [Write&Updata Data](../Basic-Concept/Write-Updata-Data.md)
 
-3. Data Querying: IoTDB offers a rich set of data querying capabilities. For a basic introduction to data querying, please see [Query Data](../Basic-Concept/Query-Data_timecho.md). It includes [Row Pattern Recognition](../SQL-Manual/Row-Pattern-Recognition.md) suitable for business scenarios such as identifying specific patterns in time-series data and detecting specific events, as well as [Window Functions](../SQL-Manual/Featured-Functions_timecho.md#_4-Window-Functions) and other featured functions often used in data analysis scenarios.
+3. Data Querying: IoTDB offers a rich set of data querying capabilities. For a basic introduction to data querying, please see [Query Data](../Basic-Concept/Query-Data.md). It includes pattern queries and window functions applicable to time-series featured analysis. For detailed introductions, please refer to [Timeseries Featured Analysis](../User-Manual/Timeseries-Featured-Analysis_timecho.md).
 
 4. Data Deletion: IoTDB supports two deletion methods: SQL-based deletion and automatic expiration deletion (TTL).