[DOP-18232] Add PySpark to usage examples

docs/using_the_dialect.md

@@ -2,31 +2,98 @@
 
 This section provides instructions on how to configure Apache Spark to use the Spark Dialect Extension, enabling custom handling of JDBC data types.
 
-### Configuration Steps
+### Add the JAR to Spark
 
-To integrate the Spark Dialect Extension into your Spark application, you need to add the compiled JAR file to the Spark classpath. The extension, via ``<DBMS>DialectRegistry`` classes, will dynamically detect the Spark version and load the corresponding dialect.
+#### Using release version
 
-#### Add the JAR to Spark
+##### Using SparkConf
 
-1. **Locate the Compiled JAR**: Ensure you have built the project and locate the `.jar`: `/path/to/spark-dialect-extension_2.12-0.1.jar` directory.
+For PySpark:
 
-2. **Configure Spark**: Add the JAR to your Spark job's classpath by modifying the `spark.jars` configuration parameter. This can be done in several ways depending on how you are running your Spark application:
+```python
+from pyspark.sql import SparkSession
 
-- **Spark Submit Command**:
-  ```bash
-  spark-submit --jars /path/to/spark-dialect-extension_2.12-0.1.jar --class YourMainClass your-application.jar
-  ```
+spark = (
+  SparkSession.builder
+  .appName("My Spark App")
+  .config("spark.jars.packages", "io.github.mtsongithub.doetl:spark-dialect-extension_2.12:0.0.1")
+  .getOrCreate()
+)
+```
+
+For Spark on Scala:
+
+```scala
+import org.apache.spark.sql.SparkSession
+
+val spark = SparkSession.builder()
+.appName("My Spark App")
+.config("spark.jars.packages", "io.github.mtsongithub.doetl:spark-dialect-extension_2.12:0.0.1")
+.getOrCreate()
+```
+
+##### Using Spark Submit
+
+```bash
+spark-submit --conf spark.jars.packages=io.github.mtsongithub.doetl:spark-dialect-extension_2.12:0.0.1
+```
+
+#### Compile from source
+
+##### Build .jar file
+
+See [CONTRIBUTING.md](../CONTRIBUTING.md) for build instructions.
+
+After build you'll have a file `/path/to/cloned-repo/target/scala_2.12/spark-dialect-extension_2.12-0.0.1.jar`
+
+##### Using SparkConf
+
+For PySpark:
 
-- **Programmatically** (within your Spark application):
-  ```scala
-  import io.github.mtsongithub.doetl.sparkdialectextensions.clickhouse.ClickhouseDialectRegistry
-  import org.apache.spark.sql.SparkSession
-
-  val spark = SparkSession.builder()
+```python
+from pyspark.sql import SparkSession
+
+spark = (
+  SparkSession.builder
   .appName("My Spark App")
-  .config("spark.jars", "/path/to/spark-dialect-extension_2.12-0.1.jar")
+  .config("spark.jars", "/path/to/cloned-repo/target/scala_2.12/spark-dialect-extension_2.12-0.0.1.jar")
   .getOrCreate()
-
-  // Register custom Clickhouse dialect based on Spark version
-  ClickhouseDialectRegistry.register()
-  ```
+)
+```
+
+For Spark on Scala:
+
+```scala
+import org.apache.spark.sql.SparkSession
+
+val spark = SparkSession.builder()
+.appName("My Spark App")
+.config("spark.jars", "/path/to/cloned-repo/target/scala_2.12/spark-dialect-extension_2.12-0.0.1.jar")
+.getOrCreate()
+```
+
+##### Using Spark Submit
+
+```bash
+spark-submit --jars /path/to/cloned-repo/target/scala_2.12/spark-dialect-extension_2.12-0.0.1.jar
+```
+
+### Register a dialect
+
+To integrate the Spark Dialect Extension into your Spark application, you need to use ``<DBMS>DialectRegistry`` classes, which dynamically detect the Spark version and register the corresponding dialect.
+
+For PySpark:
+
+```python
+# Register custom Clickhouse dialect
+ClickhouseDialectRegistry = spark._jvm.io.github.mtsongithub.doetl.sparkdialectextensions.clickhouse.ClickhouseDialectRegistry
+ClickhouseDialectRegistry.register()
+```
+
+For Spark on Scala:
+```scala
+// Register custom Clickhouse dialect
+import io.github.mtsongithub.doetl.sparkdialectextensions.clickhouse.ClickhouseDialectRegistry
+
+ClickhouseDialectRegistry.register()
+```