Remove warning logs during the document build process (#13324)

Signed-off-by: Tai Le Manh <manhtai.lmt@gmail.com>

docs/source/conf.py

@@ -119,3 +119,9 @@
 
 # enable nice rendering of checkboxes for the task lists
 myst_enable_extensions = ["colon_fence", "deflist", "tasklist"]
+
+# Some code blocks (sql) are not being highlighted correctly, due to the
+# presence of some special characters like: 🚀, å, {,... But this isn’t a major
+# issue for our documentation. So, suppress these warnings to keep our build
+# log cleaner.
+suppress_warnings = ['misc.highlighting_failure']

docs/source/contributor-guide/howtos.md

@@ -49,14 +49,15 @@ Below is a checklist of what you need to do to add a new scalar function to Data
   - Run `./dev/update_function_docs.sh` to update docs
 
 [advanced_udf.rs]: https://github.com/apache/datafusion/blob/main/datafusion-examples/examples/advanced_udaf.rs
+[datafusion/expr/src]: https://github.com/apache/datafusion/tree/main/datafusion/expr/src
 [sqllogictest/test_files]: https://github.com/apache/datafusion/tree/main/datafusion/sqllogictest/test_files
 
 ## How to add a new aggregate function
 
 Below is a checklist of what you need to do to add a new aggregate function to DataFusion:
 
 - Add the actual implementation of an `Accumulator` and `AggregateExpr`:
-- In [datafusion/expr/src](../../../datafusion/expr/src/aggregate_function.rs), add:
+- In [datafusion/expr/src], add:
   - a new variant to `AggregateFunction`
   - a new entry to `FromStr` with the name of the function as called by SQL
   - a new line in `return_type` with the expected return type of the function, given an incoming type

docs/source/library-user-guide/profiling.md

@@ -21,7 +21,7 @@
 
 The section contains examples how to perform CPU profiling for Apache DataFusion on different operating systems.
 
-### Building a flamegraph
+## Building a flamegraph
 
 [Video: how to CPU profile DataFusion with a Flamegraph](https://youtu.be/2z11xtYw_xs)
 
@@ -34,19 +34,19 @@ in images such as this:
 
 ## MacOS
 
-#### Step 1: Install the flamegraph Tool
+### Step 1: Install the flamegraph Tool
 
 To install flamegraph, run:
 
 ```shell
 cargo install flamegraph
 ```
 
-#### Step 2: Prepare Your Environment
+### Step 2: Prepare Your Environment
 
 Ensure that you're in the directory containing the necessary data files for your DataFusion query. The flamegraph tool will profile the execution of your query against this data.
 
-#### Step 3: Running the Flamegraph Tool
+### Step 3: Running the Flamegraph Tool
 
 To generate a flamegraph, you'll need to use the -- separator to pass arguments to the binary you're profiling. For datafusion-cli, you need to make sure to run the command with sudo permissions (especially on macOS, where DTrace requires elevated privileges).
 

docs/source/library-user-guide/query-optimizer.md

@@ -68,7 +68,7 @@ let optimizer = Optimizer::with_rules(vec![
 ## Writing Optimization Rules
 
 Please refer to the
-[optimizer_rule.rs](../../datafusion-examples/examples/optimizer_rule.rs)
+[optimizer_rule.rs](../../../datafusion-examples/examples/optimizer_rule.rs)
 example to learn more about the general approach to writing optimizer rules and
 then move onto studying the existing rules.
 

docs/source/user-guide/sql/scalar_functions.md

@@ -3983,44 +3983,42 @@ make_map(['key1', 'key2'], ['value1', 'value2'])
 
 #### Example
 
-````sql
-        -- Using map function
-        SELECT MAP('type', 'test');
-        ----
-        {type: test}
-
-        SELECT MAP(['POST', 'HEAD', 'PATCH'], [41, 33, null]);
-        ----
-        {POST: 41, HEAD: 33, PATCH: }
+```sql
+-- Using map function
+SELECT MAP('type', 'test');
+----
+{type: test}
 
-        SELECT MAP([[1,2], [3,4]], ['a', 'b']);
-        ----
-        {[1, 2]: a, [3, 4]: b}
+SELECT MAP(['POST', 'HEAD', 'PATCH'], [41, 33, null]);
+----
+{POST: 41, HEAD: 33, PATCH: }
 
-        SELECT MAP { 'a': 1, 'b': 2 };
-        ----
-        {a: 1, b: 2}
+SELECT MAP([[1,2], [3,4]], ['a', 'b']);
+----
+{[1, 2]: a, [3, 4]: b}
 
-        -- Using make_map function
-        SELECT MAKE_MAP(['POST', 'HEAD'], [41, 33]);
-        ----
-        {POST: 41, HEAD: 33}
+SELECT MAP { 'a': 1, 'b': 2 };
+----
+{a: 1, b: 2}
 
-        SELECT MAKE_MAP(['key1', 'key2'], ['value1', null]);
-        ----
-        {key1: value1, key2: }
-        ```
+-- Using make_map function
+SELECT MAKE_MAP(['POST', 'HEAD'], [41, 33]);
+----
+{POST: 41, HEAD: 33}
 
+SELECT MAKE_MAP(['key1', 'key2'], ['value1', null]);
+----
+{key1: value1, key2: }
+```
 
 ### `map_extract`
 
 Returns a list containing the value for the given key or an empty list if the key is not present in the map.
 
-````
-
+```
 map_extract(map, key)
+```
 
-````
 #### Arguments
 
 - **map**: Map expression. Can be a constant, column, or function, and any combination of map operators.
@@ -4040,7 +4038,7 @@ SELECT map_extract(MAP {1: 'one', 2: 'two'}, 2);
 SELECT map_extract(MAP {'x': 10, 'y': NULL, 'z': 30}, 'y');
 ----
 []
-````
+```
 
 #### Aliases