[SPARK-47750][DOCS][SQL] Postgres: Document Mapping Spark SQL Data Ty…

…pes to PostgreSQL

### What changes were proposed in this pull request?

This PR added user documentation for Mapping Spark SQL Data Types to PostgreSQL

### Why are the changes needed?

doc improvement
### Does this PR introduce _any_ user-facing change?

no

### How was this patch tested?

doc build
![image](https://github.com/apache/spark/assets/8326978/2745aa86-67ef-49ee-bdd2-a49eea800851)

### Was this patch authored or co-authored using generative AI tooling?

Closes apache#45912 from yaooqinn/SPARK-47750.

Authored-by: Kent Yao <[email protected]>
Signed-off-by: Kent Yao <[email protected]>

docs/sql-data-sources-jdbc.md

@@ -1009,3 +1009,185 @@ as the activated JDBC Driver. Note that, different JDBC drivers, or different ve
     </tr>
   </tbody>
 </table>
+
+
+### Mapping Spark SQL Data Types to PostgreSQL
+
+The below table describes the data type conversions from Spark SQL Data Types to PostgreSQL data types,
+when creating, altering, or writing data to a PostgreSQL table using the built-in jdbc data source with
+the [PostgreSQL JDBC Driver](https://mvnrepository.com/artifact/org.postgresql/postgresql) as the activated JDBC Driver.
+
+
+<table>
+  <thead>
+    <tr>
+      <th><b>Spark SQL Data Type</b></th>
+      <th><b>PostgreSQL Data Type</b></th>
+      <th><b>Remarks</b></th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <td>BooleanType</td>
+      <td>boolean</td>
+      <td></td>
+    </tr>
+    <tr>
+      <td>ByteType</td>
+      <td>smallint</td>
+      <td></td>
+    </tr>
+    <tr>
+      <td>ShortType</td>
+      <td>smallint</td>
+      <td></td>
+    </tr>
+    <tr>
+      <td>IntegerType</td>
+      <td>integer</td>
+      <td></td>
+    </tr>
+    <tr>
+      <td>LongType</td>
+      <td>bigint</td>
+      <td></td>
+    </tr>
+    <tr>
+      <td>FloatType</td>
+      <td>float4</td>
+      <td></td>
+    </tr>
+    <tr>
+      <td>DoubleType</td>
+      <td>float8</td>
+      <td></td>
+    </tr>
+    <tr>
+      <td>DecimalType(p, s)</td>
+      <td>numeric(p,s)</td>
+      <td></td>
+    </tr>
+    <tr>
+      <td>DateType</td>
+      <td>date</td>
+      <td></td>
+    </tr>
+    <tr>
+      <td>TimestampType</td>
+      <td>timestamp</td>
+      <td></td>
+    </tr>
+    <tr>
+      <td>TimestampNTZType</td>
+      <td>timestamp</td>
+      <td></td>
+    </tr>
+    <tr>
+      <td>StringType</td>
+      <td>text</td>
+      <td></td>
+    </tr>
+    <tr>
+      <td>BinaryType</td>
+      <td>bytea</td>
+      <td></td>
+    </tr>
+    <tr>
+      <td>CharType(n)</td>
+      <td>CHAR(n)</td>
+      <td></td>
+    </tr>
+    <tr>
+      <td>VarcharType(n)</td>
+      <td>VARCHAR(n)</td>
+      <td></td>
+    </tr>
+    <tr>
+      <td>ArrayType</td>
+      <td><table>
+          <thead>
+            <tr>
+              <th><b>Element type</b></th>
+              <th><b>PG Array</b></th>
+            </tr>
+          </thead>
+          <tbody>
+            <tr>
+              <td>BooleanType</td>
+              <td>boolean[]</td>
+            </tr>
+            <tr>
+              <td>ByteType</td>
+              <td>smallint[]</td>
+            </tr>
+            <tr>
+              <td>ShortType</td>
+              <td>smallint[]</td>
+            </tr>
+            <tr>
+              <td>IntegerType</td>
+              <td>integer[]</td>
+            </tr>
+            <tr>
+              <td>LongType</td>
+              <td>bigint[]</td>
+            </tr>
+            <tr>
+              <td>FloatType</td>
+              <td>float4[]</td>
+            </tr>
+            <tr>
+              <td>DoubleType</td>
+              <td>float8[]</td>
+            </tr>
+            <tr>
+              <td>DecimalType(p, s)</td>
+              <td>numeric(p,s)[]</td>
+            </tr>
+            <tr>
+              <td>DateType</td>
+              <td>date[]</td>
+            </tr>
+            <tr>
+              <td>TimestampType</td>
+              <td>timestamp[]</td>
+            </tr>
+            <tr>
+              <td>TimestampNTZType</td>
+              <td>timestamp[]</td>
+            </tr>
+            <tr>
+              <td>StringType</td>
+              <td>text[]</td>
+            </tr>
+            <tr>
+              <td>BinaryType</td>
+              <td>bytea[]</td>
+            </tr>
+            <tr>
+              <td>CharType(n)</td>
+              <td>char(n)[]</td>
+            </tr>
+            <tr>
+              <td>VarcharType(n)</td>
+              <td>varchar(n)[]</td>
+            </tr>
+          </tbody>
+        </table></td>
+      <td>If the element type is an ArrayType, it converts to Postgres multidimensional array. <br>For instance, <br><code>ArrayType(ArrayType(StringType))</code> converts to <code>text[][]</code>, <br><code>ArrayType(ArrayType(ArrayType(LongType)))</code> converts to <code>bigint[][][]</code></td>
+    </tr>
+  </tbody>
+</table>
+
+The Spark Catalyst data types below are not supported with suitable PostgreSQL types.
+
+- DayTimeIntervalType
+- YearMonthIntervalType
+- CalendarIntervalType
+- ArrayType - if the element type is not listed above
+- MapType
+- StructType
+- UserDefinedType
+- NullType
+- ObjectType
+- VariantType