[docs][udf] Update scalar UDFs, user-defined aggregate functions (UDAFs) description.

4 files changed, 7 insertions, 7 deletions

diff --git a/docs/processor/aggregate-processor.md b/docs/processor/aggregate-processor.md
index d9bcdb0..af82d4e 100644
--- a/docs/processor/aggregate-processor.md
+++ b/docs/processor/aggregate-processor.md
@@ -1,11 +1,11 @@
 # Aggregate Processor
 
-> Processing pipelines for aggregate processor
+> Processing pipelines for aggregate processors using UDAFs
 
 ## Description
 
 Aggregate processor is used to aggregate the data from source to sink. It is a part of the processing pipeline. It can be used in the pre-processing, processing, and post-processing pipeline. Each processor can assemble UDAFs(User-defined Aggregate functions) into a pipeline.
-Within the pipeline, events are processed by each Function in order, top‑>down. The UDAF usage detail can be found in [UDAF](udaf.md).
+Within the pipeline, events are processed by each Function in order, top‑>down. More details can be found in user-defined aggregate functions [(UDAFs)](udaf.md).
 
 ## Options
 Note：Default will output internal fields `__window_start_timestamp` and `__window_end_timestamp` if not set output_fields.
diff --git a/docs/processor/projection-processor.md b/docs/processor/projection-processor.md
index bc4b249..4319f36 100644
--- a/docs/processor/projection-processor.md
+++ b/docs/processor/projection-processor.md
@@ -1,12 +1,12 @@
 # Projection Processor
 
-> Processing pipelines for projection processor
+> Processing pipelines for projection processors using scalar UDFs
 
 ## Description
 
 Projection processor is used to project the data from source to sink. It can be used to filter, remove, and transform fields.
 It is a part of the processing pipeline. It can be used in the pre-processing, processing, and post-processing pipeline. Each processor can assemble UDFs(User-defined functions) into a pipeline.
-Within the pipeline, events are processed by each Function in order, top‑>down. The UDF usage detail can be found in [UDF](udf.md).
+Within the pipeline, events are processed by each Function in order, top‑>down. More details can be found in User Defined Functions [(UDFs)](udf.md).
 
 ## Options
 
diff --git a/docs/processor/udf.md b/docs/processor/udf.md
index cf305ef..170d86f 100644
--- a/docs/processor/udf.md
+++ b/docs/processor/udf.md
@@ -1,6 +1,6 @@
 # UDF
 
-> The functions for projection processors.
+> The functions for projection processors. 
 
   ## Function of content
 
@@ -24,7 +24,7 @@
 
 ## Description
 
-UDF(User Defined Function) is used to extend the functions of projection processor. The UDF is a part of the processing pipeline. It can be used in the pre-processing pipeline, processing pipeline, and post-processing pipeline.
+Scalar UDF(User Defined Function) is used to extend the functions of projection processor. The UDF is a part of the processing pipeline. It can be used in the pre-processing pipeline, processing pipeline, and post-processing pipeline.
 
 ## UDF Definition
 
diff --git a/docs/user-guide.md b/docs/user-guide.md
index 9d5b1c7..e35616f 100644
--- a/docs/user-guide.md
+++ b/docs/user-guide.md
@@ -137,7 +137,7 @@ Based on the filter expression, the event will be passed to downstream if the ex
 ## Processing Pipelines
 
 Processing pipelines are used to define the event processing logic of the job. It can be categorized by functionality into stateless and stateful processors. Based processing order, it can be categorized into pre-processing pipeline, processing pipeline and post-processing pipeline. Each processor can assemble `UDFs`(User-defined functions) into a pipeline. The detail of processor is listed in [Processor](processor).
-
+UDF supports [scalar UDFs](processor/udf.md) , user-defined aggregate functions [(UDAFs)](processor/udaf.md), and user-defined table functions (UDTFs). 
 ## Sinks
 
 Sink is used to define where GrootStream needs to output data. Multiple sinks can be defined in a job. The supported sinks are listed in [Sink Connectors](connector/sink). Each sink has its own specific parameters to define how to output data, and GrootStream also extracts the properties that each sink will use, such as the `topic` and `kafka.bootstrap.servers` of the `Kafka` sink.