diff --git a/docs/en/07-develop/09-udf.md b/docs/en/07-develop/09-udf.md
index b0124b9c3fb93bfaa30bdba6a344acda0a2c7c3f..5a98ff2789037693e479c12129b530d97cc0ad3e 100644
--- a/docs/en/07-develop/09-udf.md
+++ b/docs/en/07-develop/09-udf.md
@@ -10,7 +10,7 @@ User-defined functions can be scalar functions or aggregate functions. Scalar fu
 
 TDengine supports user-defined functions written in C or Python. This document describes the usage of user-defined functions.
 
-## Implement a UDF in C 
+## Implement a UDF in C
 
 When you create a user-defined function, you must implement standard interface functions:
 - For scalar functions, implement the `scalarfn` interface function.
@@ -111,13 +111,13 @@ Interface functions return a value that indicates whether the operation was succ
 For information about the parameters for interface functions, see Data Model
 
 #### Scalar Interface
- `int32_t scalarfn(SUdfDataBlock* inputDataBlock, SUdfColumn *resultColumn)` 
- 
+ `int32_t scalarfn(SUdfDataBlock* inputDataBlock, SUdfColumn *resultColumn)`
+
  Replace `scalarfn` with the name of your function. This function performs scalar calculations on data blocks. You can configure a value through the parameters in the `resultColumn` structure.
 
 The parameters in the function are defined as follows:
   - inputDataBlock: The data block to input.
-  - resultColumn: The column to output. The column to output. 
+  - resultColumn: The column to output. The column to output.
 
 #### Aggregate Interface
 
@@ -197,7 +197,7 @@ The data structure is described as follows:
 - The SUdfDataBlock block includes the number of rows (numOfRows) and the number of columns (numCols). udfCols[i] (0 <= i <= numCols-1) indicates that each column is of type SUdfColumn.
 - SUdfColumn includes the definition of the data type of the column (colMeta) and the data in the column (colData).
 - The member definitions of SUdfColumnMeta are the same as the data type definitions in `taos.h`.
-- The data in SUdfColumnData can become longer. varLenCol indicates variable-length data, and fixLenCol indicates fixed-length data. 
+- The data in SUdfColumnData can become longer. varLenCol indicates variable-length data, and fixLenCol indicates fixed-length data.
 - SUdfInterBuf defines the intermediate structure `buffer` and the number of results in the buffer `numOfResult`.
 
 Additional functions are defined in `taosudf.h` to make it easier to work with these structures.
@@ -285,9 +285,9 @@ def init():
 def destroy():
     # destroy
 def process(input: datablock) -> tuple[output_type]:
-    # process input datablock, 
+    # process input datablock,
     # datablock.data(row, col) is to access the python object in location(row,col)
-    # return tuple object consisted of object of type outputtype   
+    # return tuple object consisted of object of type outputtype
 ```
 
 ### Implement an Aggregate UDF in Python
@@ -303,12 +303,12 @@ def start() -> bytes:
     #return serialize(init_state)
 def reduce(inputs: datablock, buf: bytes) -> bytes
     # deserialize buf to state
-    # reduce the inputs and state into new_state. 
-    # use inputs.data(i,j) to access python ojbect of location(i,j)
+    # reduce the inputs and state into new_state.
+    # use inputs.data(i,j) to access python object of location(i,j)
     # serialize new_state into new_state_bytes
-    return new_state_bytes   
+    return new_state_bytes
 def finish(buf: bytes) -> output_type:
-    #return obj of type outputtype   
+    #return obj of type outputtype
 ```
 
 ### Python UDF Interface Definition
@@ -328,7 +328,7 @@ def finish(buf: bytes) -> output_type:
 ```
 
 - first `start()` is called to return the initial result in type `bytes`
-- then the input data are divided into multiple data blocks and for each block `input`, `reduce` is called with the data block `input` and the current result `buf` bytes and generates a new intermediate result buffer. 
+- then the input data are divided into multiple data blocks and for each block `input`, `reduce` is called with the data block `input` and the current result `buf` bytes and generates a new intermediate result buffer.
 - finally, the `finish` function is called on the intermediate result `buf` and outputs 0 or 1 data of type `output_type`
 
 
@@ -337,7 +337,7 @@ def finish(buf: bytes) -> output_type:
 def init()
 def destroy()
 ```
-Implement `init` for initialization and `destroy` for termination. 
+Implement `init` for initialization and `destroy` for termination.
 
 ### Data Mapping between TDengine SQL and Python UDF
 
@@ -360,7 +360,7 @@ sudo pip install taospyudf
 ldconfig
 ```
 2. If PYTHONPATH is needed to find Python packages when the Python UDF executes, include the PYTHONPATH contents into the udfdLdLibPath variable of the taos.cfg configuration file
- 
+
 ### Python UDF Sample Code
 #### Scalar Function [pybitand](https://github.com/taosdata/TDengine/blob/3.0/tests/script/sh/pybitand.py)
 
diff --git a/docs/en/14-reference/12-config/index.md b/docs/en/14-reference/12-config/index.md
index 3ce63fb6cceded0f309691ed47ad8bda38db5bfa..52ded6208a5f946dd0901410605907c826813226 100644
--- a/docs/en/14-reference/12-config/index.md
+++ b/docs/en/14-reference/12-config/index.md
@@ -111,7 +111,7 @@ The parameters described in this document by the effect that they have on the sy
 | Attribute     | Description                                    |
 | ------------- | ---------------------------------------------- |
 | Applicable    | Client/Server                                  |
-| Meaning       | The maximum waiting time to get avaliable conn |
+| Meaning       | The maximum waiting time to get available conn |
 | Value Range   | 10-50000000(ms)                                |
 | Default Value | 500000                                         |