[DOCS] Standardize whitespace in Markdown files

docs/api/sql/Optimizer.md

@@ -284,7 +284,7 @@ GROUP BY (lcs_geom, rcs_geom)
 
 This also works for distance join. You first need to use `ST_Buffer(geometry, distance)` to wrap one of your original geometry column. If your original geometry column contains points, this `ST_Buffer` will make them become circles with a radius of `distance`.
 
-Since the coordinates are in the longitude and latitude system, so the unit of `distance` should be degree instead of meter or mile. You can get an approximation by performing `METER_DISTANCE/111000.0`, then filter out false-positives.  Note that this might lead to inaccurate results if your data is close to the poles or antimeridian.
+Since the coordinates are in the longitude and latitude system, so the unit of `distance` should be degree instead of meter or mile. You can get an approximation by performing `METER_DISTANCE/111000.0`, then filter out false-positives. Note that this might lead to inaccurate results if your data is close to the poles or antimeridian.
 
 In a nutshell, run this query first on the left table before Step 1. Please replace `METER_DISTANCE` with a meter distance. In Step 1, generate S2 IDs based on the `buffered_geom` column. Then run Step 2, 3, 4 on the original `geom` column.
 

docs/community/contributor.md

@@ -130,14 +130,14 @@ to guide the direction of the project.
 
 Being a committer does not require you to
 participate any more than you already do. It does
-tend to make one even more committed.  You will
+tend to make one even more committed. You will
 probably find that you spend more time here.
 
 Of course, you can decline and instead remain as a
 contributor, participating as you do now.
 
 A. This personal invitation is a chance for you to
-accept or decline in private.  Either way, please
+accept or decline in private. Either way, please
 let us know in reply to the [email protected]
 address only.
 

docs/community/publication.md

@@ -50,4 +50,4 @@ GeoSpark Perspective and Beyond"](https://jiayuasu.github.io/files/paper/GeoSpar
 
 ### A Tutorial about Geospatial Data Management in Spark
 
-["Geospatial Data Management in Apache Spark: A Tutorial"](https://jiayuasu.github.io/files/talk/jia-icde19-tutorial.pdf) (Tutorial) Jia Yu and Mohamed Sarwat.  In Proceedings of the International Conference on Data Engineering, ICDE, 2019
+["Geospatial Data Management in Apache Spark: A Tutorial"](https://jiayuasu.github.io/files/talk/jia-icde19-tutorial.pdf) (Tutorial) Jia Yu and Mohamed Sarwat. In Proceedings of the International Conference on Data Engineering, ICDE, 2019

docs/community/release-manager.md

@@ -19,7 +19,7 @@ If your Maven (`mvn --version`) points to other JDK versions, you must change it
 JAVA_HOME="${JAVA_HOME:-$(/usr/libexec/java_home)}" exec "/usr/local/Cellar/maven/3.6.3/libexec/bin/mvn" "$@"
 ```
 
-4. Change `JAVA_HOME:-$(/usr/libexec/java_home)}` to `JAVA_HOME:-$(/usr/libexec/java_home -v 1.8)}`.  The resulting content will be like this:
+4. Change `JAVA_HOME:-$(/usr/libexec/java_home)}` to `JAVA_HOME:-$(/usr/libexec/java_home -v 1.8)}`. The resulting content will be like this:
 
 ```
 #!/bin/bash

docs/community/rule.md

@@ -13,7 +13,7 @@ It is important to confirm that your contribution is acceptable. You should crea
 Code contributions should include the following:
 
 * Detailed documentations on classes and methods.
-* Unit Tests to demonstrate code correctness and allow this to be maintained going forward.  In the case of bug fixes the unit test should demonstrate the bug in the absence of the fix (if any).  Unit Tests can be JUnit test or Scala test. Some Sedona functions need to be tested in both Scala and Java.
+* Unit Tests to demonstrate code correctness and allow this to be maintained going forward. In the case of bug fixes the unit test should demonstrate the bug in the absence of the fix (if any). Unit Tests can be JUnit test or Scala test. Some Sedona functions need to be tested in both Scala and Java.
 * Updates on corresponding Sedona documentation if necessary.
 
 Code contributions must include an Apache 2.0 license header at the top of each file.

docs/setup/databricks.md

@@ -71,7 +71,7 @@ Of course, you can also do the steps above manually.
 ### Create an init script
 
 !!!warning
-    Starting from December 2023, Databricks has disabled all DBFS based init script (/dbfs/XXX/<script-name>.sh).  So you will have to store the init script from a workspace level (`/Workspace/Users/<user-name>/<script-name>.sh`) or Unity Catalog volume (`/Volumes/<catalog>/<schema>/<volume>/<path-to-script>/<script-name>.sh`). Please see [Databricks init scripts](https://docs.databricks.com/en/init-scripts/cluster-scoped.html#configure-a-cluster-scoped-init-script-using-the-ui) for more information.
+    Starting from December 2023, Databricks has disabled all DBFS based init script (/dbfs/XXX/<script-name>.sh). So you will have to store the init script from a workspace level (`/Workspace/Users/<user-name>/<script-name>.sh`) or Unity Catalog volume (`/Volumes/<catalog>/<schema>/<volume>/<path-to-script>/<script-name>.sh`). Please see [Databricks init scripts](https://docs.databricks.com/en/init-scripts/cluster-scoped.html#configure-a-cluster-scoped-init-script-using-the-ui) for more information.
 
 !!!note
     If you are creating a Shared cluster, you won't be able to use init scripts and jars stored under `Workspace`. Please instead store them in `Volumes`. The overall process should be the same.

docs/tutorial/raster.md

@@ -242,7 +242,7 @@ The output will look like this:
 For multiple raster data files use the following code to load the data [from path](https://github.com/apache/sedona/blob/0eae42576c2588fe278f75cef3b17fee600eac90/spark/common/src/test/resources/raster/) and create raw DataFrame.
 
 !!!note
-    The above code works too for loading multiple raster data files.  if the raster files are in separate directories and the option also makes sure that only `.tif` or `.tiff` files are being loaded.
+    The above code works too for loading multiple raster data files. If the raster files are in separate directories and the option also makes sure that only `.tif` or `.tiff` files are being loaded.
 
 === "Scala"
     ```scala

docs/tutorial/snowflake/sql.md

@@ -346,7 +346,7 @@ GROUP BY (lcs_geom, rcs_geom)
 
 This also works for distance join. You first need to use `ST_Buffer(geometry, distance)` to wrap one of your original geometry column. If your original geometry column contains points, this `ST_Buffer` will make them become circles with a radius of `distance`.
 
-Since the coordinates are in the longitude and latitude system, so the unit of `distance` should be degree instead of meter or mile. You can get an approximation by performing `METER_DISTANCE/111000.0`, then filter out false-positives.  Note that this might lead to inaccurate results if your data is close to the poles or antimeridian.
+Since the coordinates are in the longitude and latitude system, so the unit of `distance` should be degree instead of meter or mile. You can get an approximation by performing `METER_DISTANCE/111000.0`, then filter out false-positives. Note that this might lead to inaccurate results if your data is close to the poles or antimeridian.
 
 In a nutshell, run this query first on the left table before Step 1. Please replace `METER_DISTANCE` with a meter distance. In Step 1, generate S2 IDs based on the `buffered_geom` column. Then run Step 2, 3, 4 on the original `geom` column.
 

docs/tutorial/sql-pure-sql.md

@@ -31,7 +31,7 @@ This will register all Sedona types, functions and optimizations in SedonaSQL an
 
 ## Load data
 
-Let use data from `examples/sql`.  To load data from CSV file we need to execute two commands:
+Let use data from `examples/sql`. To load data from CSV file we need to execute two commands:
 
 Use the following code to load the data and create a raw DataFrame:
 

docs/tutorial/zeppelin.md

@@ -1,4 +1,4 @@
-Sedona provides a Helium visualization plugin tailored for [Apache Zeppelin](https://zeppelin.apache.org/). This finally bridges the gap between Sedona and Zeppelin.  Please read [Install Sedona-Zeppelin](../setup/zeppelin.md) to learn how to install this plugin in Zeppelin.
+Sedona provides a Helium visualization plugin tailored for [Apache Zeppelin](https://zeppelin.apache.org/). This finally bridges the gap between Sedona and Zeppelin. Please read [Install Sedona-Zeppelin](../setup/zeppelin.md) to learn how to install this plugin in Zeppelin.
 
 Sedona-Zeppelin equips two approaches to visualize spatial data in Zeppelin. The first approach uses Zeppelin to plot all spatial objects on the map. The second one leverages SedonaViz to generate map images and overlay them on maps.