update statements

Author: jackylee-ch

docs/docs/spark-getting-started.md

@@ -36,7 +36,7 @@ spark-shell --packages org.apache.iceberg:iceberg-spark-runtime-{{ sparkVersionM
 
 !!! info
     <!-- markdown-link-check-disable-next-line -->
-    If you want to include Iceberg in your Spark installation, add the [`iceberg-spark-runtime-{{ sparkVersionMajor }}` Jar](https://search.maven.org/remotecontent?filepath=org/apache/iceberg/iceberg-spark-runtime-{{ sparkVersion }}_{{ scalaVersion }}/{{ icebergVersion }}/iceberg-spark-runtime-{{ sparkVersion }}_{{ scalaVersion }}-{{ icebergVersion }}.jar) to Spark's `jars` folder.
+    If you want to include Iceberg in your Spark installation, add the [`iceberg-spark-runtime-{{ sparkVersionMajor }}` Jar](https://search.maven.org/remotecontent?filepath=org/apache/iceberg/iceberg-spark-runtime-{{ sparkVersionMajor }}/{{ icebergVersion }}/iceberg-spark-runtime-{{ sparkVersionMajor }}-{{ icebergVersion }}.jar) to Spark's `jars` folder.
 
 
 ### Adding catalogs

docs/docs/spark-procedures.md

@@ -22,7 +22,7 @@ title: "Procedures"
 
 To use Iceberg in Spark, first configure [Spark catalogs](spark-configuration.md).  
 For Spark 3.x, stored procedures are only available when using [Iceberg SQL extensions](spark-configuration.md#sql-extensions) in Spark.  
-For Spark 4.0, stored procedures are supported natively without requiring the Iceberg SQL extensions. However, note that they are _q_case-sensitive__ in Spark 4.0.
+For Spark 4.0, stored procedures are supported natively without requiring the Iceberg SQL extensions. However, note that they are __case-sensitive__ in Spark 4.0.
 
 ## Usage
 

docs/docs/spark-structured-streaming.md

@@ -73,7 +73,7 @@ data.writeStream
     .outputMode("append")
     .trigger(Trigger.ProcessingTime(1, TimeUnit.MINUTES))
     .option("checkpointLocation", checkpointPath)
-    .to_table("database.table_name")
+    .toTable("database.table_name")
 ```
 
 In the case of the directory-based Hadoop catalog:
@@ -112,7 +112,7 @@ data.writeStream
     .trigger(Trigger.ProcessingTime(1, TimeUnit.MINUTES))
     .option("fanout-enabled", "true")
     .option("checkpointLocation", checkpointPath)
-    .to_table("database.table_name")
+    .toTable("database.table_name")
 ```
 
 Fanout writer opens the files per partition value and doesn't close these files till the write task finishes. Avoid using the fanout writer for batch writing, as explicit sort against output rows is cheap for batch workloads.

site/docs/spark-quickstart.md

@@ -332,7 +332,7 @@ If you already have a Spark environment, you can add Iceberg, using the `--packa
     You can download the runtime by visiting to the [Releases](releases.md) page.
 
 <!-- markdown-link-check-disable-next-line -->
-[spark-runtime-jar]: https://search.maven.org/remotecontent?filepath=org/apache/iceberg/iceberg-spark-runtime-{{ sparkVersionMajor }}/{{ icebergVersion }}/iceberg-spark-runtime-{{ sparkVersion }}_{{ scalaVersion }}-{{ icebergVersion }}.jar
+[spark-runtime-jar]: https://search.maven.org/remotecontent?filepath=org/apache/iceberg/iceberg-spark-runtime-{{ sparkVersionMajor }}/{{ icebergVersion }}/iceberg-spark-runtime-{{ sparkVersionMajor }}-{{ icebergVersion }}.jar
 
 #### Learn More