fix the broken links due to recent joins rewrite

Author: jovezhong

docs/functions_for_datetime.md

@@ -213,7 +213,7 @@ Supported unit:
 
 ### date_diff_within
 
-`date_diff_within(timegap,time1, time2)` returns true or false. This function only works in [stream-to-stream join](/joins#stream_stream_join). Check whether the gap between `time1` and `time2` are within the specific range. For example `date_diff_within(10s,payment.time,notification.time)` to check whether the payment time and notification time are within 10 seconds or less.
+`date_diff_within(timegap,time1, time2)` returns true or false. This function only works in [stream-to-stream join](/joins). Check whether the gap between `time1` and `time2` are within the specific range. For example `date_diff_within(10s,payment.time,notification.time)` to check whether the payment time and notification time are within 10 seconds or less.
 
 ### date_trunc
 

docs/functions_for_streaming.md

@@ -114,7 +114,7 @@ Otherwise, if you run queries with `dedup(table(my_stream),id)` the earliest eve
 
 ### date_diff_within
 
-`date_diff_within(timegap,time1, time2)` returns true or false. This function only works in [Range Bidirectional Join](/joins##range-join). Check whether the gap between `time1` and `time2` are within the specific range. For example `date_diff_within(10s,payment.time,notification.time)` to check whether the payment time and notification time are within 10 seconds or less.
+`date_diff_within(timegap,time1, time2)` returns true or false. This function only works in [Range Bidirectional Join](/joins#range-join). Check whether the gap between `time1` and `time2` are within the specific range. For example `date_diff_within(10s,payment.time,notification.time)` to check whether the payment time and notification time are within 10 seconds or less.
 
 ✅ streaming query
 

docs/private-beta-1.md

@@ -140,7 +140,7 @@ Last weekly release in Private Beta 1. Starting from August 8, we are transiting
 
 - Streaming engine
   - More math functions are exposed. This can help you to run SQL-based simple ML/prediction models.
-  - (Experimental) [stream-to-stream join](/joins#stream_stream_join) no longer requires a ` date_diff_within(..)`, although it's still recommended to add timestamp constraints to improve performance.
+  - (Experimental) [stream-to-stream join](/joins) no longer requires a ` date_diff_within(..)`, although it's still recommended to add timestamp constraints to improve performance.
   - (Experimental) able to set a retention policy for each stream, either time-based (say only keep recent 7 days' data), or size based(say only keep recent 1GB data)
 - Source and sink
   - (Experimental) support Personal Access Token (PAT) in the REST API, which is long-living (or set an expiration date) and per-user. Tenant-level access token will be deprecated.
@@ -163,7 +163,7 @@ Last weekly release in Private Beta 1. Starting from August 8, we are transiting
 
 - Streaming engine
   - (Experimental) new UI and API to create and query [external streams](/external-stream). You can query real-time data in Confluent Cloud, Apache Kafka or Redpanda immediately, without loading the data into Timeplus.
-  - (Experimental) [stream-to-stream join](/joins#stream_stream_join) is ready to test for beta customers, e.g. `SELECT .. FROM stream1 INNER JOIN stream2 ON stream1.id=stream2.id AND date_diff_within(10s)`
+  - (Experimental) [stream-to-stream join](/joins) is ready to test for beta customers, e.g. `SELECT .. FROM stream1 INNER JOIN stream2 ON stream1.id=stream2.id AND date_diff_within(10s)`
   - New function `date_diff_within` to determine whether 2 datetime are within the specified range. This is necessary for stream to stream join. You can also use more flexible expressions like `date_diff('second',left.time,right.time) between -3 and 5`
 - Source and sink
   - Enhanced the [datapm](https://datapm.io/docs/quick-start/) Timeplus sink to support loading JSON data from PostgreSQL.

docs/public-beta-2.md

@@ -172,7 +172,7 @@ Enhancements:
 
 **Query**
 
-- Simplified the `LATEST JOIN` syntax. No need to write `INNER LATEST JOIN`. [Learn more](/joins#append-left-latest-versioned).
+- Simplified the `LATEST JOIN` syntax. No need to write `INNER LATEST JOIN`. [Learn more](/joins).
 - For historical queries with tumble window aggregation, if there is no event in a window, such window won't be in the results. To show an empty window with default value(0 for numeric types and empty string for string), you can add order by window_start with fill step \<window_size\> .
 - Auto-cleanup recent query logs: if there are more than 500, older queries are removed.
 
@@ -209,7 +209,7 @@ Enhancements:
   - Introduce a new function `earliest_timestamp()` to return `1970-1-1 00:00:00`(UTC) You can also call this with `earliest_ts()`. A typical usage is `select * from stream where _tp_time>earliest_ts()` to list all data in the past and future. Again, the previous syntax `settings seek_to='earliest'` has been deprecated and will be removed soon.
   - You can also use `where _tp_time >..` multiple times in a query with JOIN/UNION, to time travel to different starting points for different streams.
   - To improve readability, you can use numeric literals with underscores, e.g. `select * from iot where age_second > 86_400 `. Underscores `_` inside numeric literals are ignored.
-  - Added a new [LATEST JOIN](/joins#append-left-latest-versioned) for streaming SQL. For two append-only streams, if you use `a LEFT INNER LATEST JOIN b on a.key=b.key`, any time when the key changes on either stream, the previous join result will be canceled and a new result will be added.
+  - Added a new [LATEST JOIN](/joins) for streaming SQL. For two append-only streams, if you use `a LEFT INNER LATEST JOIN b on a.key=b.key`, any time when the key changes on either stream, the previous join result will be canceled and a new result will be added.
 
 ## February 17, 2023
 

docs/sql-create-disk.md

@@ -15,7 +15,7 @@ CREATE DISK name disk(
 )
 ```
 
-Please refer to [S3 External Table](/s3-externl) for how to connect to the S3 storage. It's not recommended to hardcode the access key and secret access key in the DDL. Instead, users should use environment variables or IAM role to secure these credentials.
+Please refer to [S3 External Table](/s3-external) for how to connect to the S3 storage. It's not recommended to hardcode the access key and secret access key in the DDL. Instead, users should use environment variables or IAM role to secure these credentials.
 
 You can use the following SQL to list the disks:
 ```sql

docs/sql-show-disks.md

@@ -10,4 +10,4 @@ SHOW DISKS;
 ```
 
 ## See also
-* [CREATE DISKS](/sql-create-disks) - Create disks
+* [CREATE DISKS](/sql-create-disk) - Create disks

docs/v1-release-notes.md

@@ -40,7 +40,7 @@ _Timeplus Console:_
 
 _Timeplus Core Engine (Proton v1.5.7):_
 
-- You can now join multiple [versioned streams](/versioned-stream) using `LEFT JOIN` and by assigning primary key(s). Results will be emitted whenever there are updates to either side of the JOIN. [Learn more](/joins#version-left-version)
+- You can now join multiple [versioned streams](/versioned-stream) using `LEFT JOIN` and by assigning primary key(s). Results will be emitted whenever there are updates to either side of the JOIN. [Learn more](/joins)
 - New examples in the Timeplus Proton repo /examples folder:
   - [One Billion Rows Challenge (1BRC)](https://github.com/timeplus-io/proton/tree/develop/examples/onebrc), contributed by Timeplus Community member [Saïd Abiola](https://github.com/ayewo)
   - [Real-time retrieval-augmented generation (RAG)](https://github.com/timeplus-io/proton/tree/develop/examples/real-time-ai)

docs/why-timeplus.md

@@ -28,7 +28,7 @@ Timeplus scales easily from edge devices to multi-node clusters, and with its Ap
 
 Stream processing involves combining multiple data sources, and [MULTI-JOINs](/joins) are essential for enriching and correlating events in streaming queries. Timeplus allows you to run ad-hoc historical queries on the same data, reducing the need for denormalization in downstream data warehouses.
 
-In many cases, Business Intelligence and analytical queries can be executed directly in Timeplus, eliminating the need for a separate data warehouse. [ASOF JOINs](/joins#append-asof-versioned) enable approximate time-based lookups for comparing recent versus historical data.
+In many cases, Business Intelligence and analytical queries can be executed directly in Timeplus, eliminating the need for a separate data warehouse. [ASOF JOINs](/joins) enable approximate time-based lookups for comparing recent versus historical data.
 
 ## Python and JavaScript UDF {#udf}
 We understand that SQL may not be able to express all business logic for streaming or querying. [JavaScript](/js-udf) and Python User Defined Functions (UDFs) and User Defined Aggregate Functions (UDAFs) can be used to extend Timeplus to encapsulate custom logic for both stateless and stateful queries.