Including SessionToken in url with v2 driver causes SQLException: IAM error retrieving temp credentials

## Driver version
2.1.0.9

## Redshift version
PostgreSQL 8.0.2 on i686-pc-linux-gnu, compiled by GCC gcc (GCC) 3.4.2 20041017 (Red Hat 3.4.2-6.fc3), Redshift 1.0.54052

## Client Operating System
Amazon EMR ver6.9

※OS info
NAME="Amazon Linux"
VERSION="2"
ID="amzn"
ID_LIKE="centos rhel fedora"
VERSION_ID="2"
PRETTY_NAME="Amazon Linux 2"
ANSI_COLOR="0;33"
CPE_NAME="cpe:2.3:o:amazon:amazon_linux:2"
HOME_URL="https://amazonlinux.com/"

## JAVA/JVM version
openjdk version "1.8.0_382"
OpenJDK Runtime Environment Corretto-8.382.05.1 (build 1.8.0_382-b05)
OpenJDK 64-Bit Server VM Corretto-8.382.05.1 (build 25.382-b05, mixed mode)

## Table schema

## Problem description

I am using amazon-redshift-jdbc-driver v2 with Pyspark (Spark version 3.3.2).
I get a SQLException when I run the code below.
It seems that an error occurs if the URL has a SessionToken parameter.
After replacing the jdbc-driver with v1 I get ret.count() results successfully without any errors.

Has the behavior changed between v1 and v2 when there is a SessionToken?

//-----------------------------------------------------------
from pyspark import SparkContext
from pyspark.sql import SQLContext
import boto3

redshift_cluster_id = 'sample_cluster'
redshift_dbname = 'sample_db'
bucket_name = 'sample_bucket'

sc = SparkContext.getOrCreate()
credentials = boto3.Session().get_credentials()
region = boto3.Session().region_name
sc._jsc.hadoopConfiguration().set("fs.s3.awsAccessKeyId", credentials.access_key)
sc._jsc.hadoopConfiguration().set("fs.s3.awsSecretAccessKey", credentials.secret_key)

url = f'jdbc:redshift:iam://{redshift_cluster_id}:{region}/{redshift_dbname}?DbUser=test_uesr&DbGroups=test_users_group&AutoCreate=true&AccessKeyID={credentials.access_key}&SecretAccessKey={credentials.secret_key}&user=&password='
token = credentials.token
sc._jsc.hadoopConfiguration().set("fs.s3.awsSessionToken", token)
url = f'{url}&SessionToken={credentials.token}'

sql_context = SQLContext(sc)
dfr = sql_context.read \
.format('io.github.spark_redshift_community.spark.redshift') \
.option('url', url) \
.option('tempdir', f's3a://{bucket_name}/redshift_temp_dir') \
.option('forward_spark_s3_credentials', 'true') \
.option('fetchsize', 10000)

query = f'select * from sample_table'
ret = dfr.option('query', query).load(schema=None)
ret.count()
-----------------------------------------------------------//

1. Expected behaviour:
2. Actual behaviour:
3. Error message/stack trace:
: java.sql.SQLException: IAM error retrieving temp credentials: The security token included in the request is invalid (Service: AmazonRedshift; Status Code: 403; Error Code: InvalidClientTokenId; Request ID: 78fc4d63-34c5-45a1-af4f-454c122d93e5; Proxy: null)
at com.amazon.redshift.util.RedshiftException.getSQLException(RedshiftException.java:56)
at com.amazon.redshift.Driver.connect(Driver.java:339)
at org.apache.spark.sql.execution.datasources.jdbc.DriverWrapper.connect(DriverWrapper.scala:46)
at io.github.spark_redshift_community.spark.redshift.JDBCWrapper.getConnector(RedshiftJDBCWrapper.scala:270)
at io.github.spark_redshift_community.spark.redshift.RedshiftRelation.$anonfun$schema$1(RedshiftRelation.scala:69)
at scala.Option.getOrElse(Option.scala:189)
at io.github.spark_redshift_community.spark.redshift.RedshiftRelation.schema$lzycompute(RedshiftRelation.scala:66)
at io.github.spark_redshift_community.spark.redshift.RedshiftRelation.schema(RedshiftRelation.scala:65)
at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:440)
at org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:228)
at org.apache.spark.sql.DataFrameReader.$anonfun$load$2(DataFrameReader.scala:210)
at scala.Option.getOrElse(Option.scala:189)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:210)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:171)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:182)
at py4j.ClientServerConnection.run(ClientServerConnection.java:106)
at java.lang.Thread.run(Thread.java:750)
Caused by: com.amazonaws.services.redshift.model.AmazonRedshiftException: The security token included in the request is invalid (Service: AmazonRedshift; Status Code: 403; Error Code: InvalidClientTokenId; Request ID: 78fc4d63-34c5-45a1-af4f-454c122d93e5; Proxy: null)
at com.amazonaws.http.AmazonHttpClient$RequestExecutor.handleErrorResponse(AmazonHttpClient.java:1879)
at com.amazonaws.http.AmazonHttpClient$RequestExecutor.handleServiceErrorResponse(AmazonHttpClient.java:1418)
at com.amazonaws.http.AmazonHttpClient$RequestExecutor.executeOneRequest(AmazonHttpClient.java:1387)
at com.amazonaws.http.AmazonHttpClient$RequestExecutor.executeHelper(AmazonHttpClient.java:1157)
at com.amazonaws.http.AmazonHttpClient$RequestExecutor.doExecute(AmazonHttpClient.java:814)
at com.amazonaws.http.AmazonHttpClient$RequestExecutor.executeWithTimer(AmazonHttpClient.java:781)
at com.amazonaws.http.AmazonHttpClient$RequestExecutor.execute(AmazonHttpClient.java:755)
at com.amazonaws.http.AmazonHttpClient$RequestExecutor.access$500(AmazonHttpClient.java:715)
at com.amazonaws.http.AmazonHttpClient$RequestExecutionBuilderImpl.execute(AmazonHttpClient.java:697)
at com.amazonaws.http.AmazonHttpClient.execute(AmazonHttpClient.java:561)
at com.amazonaws.http.AmazonHttpClient.execute(AmazonHttpClient.java:541)
at com.amazonaws.services.redshift.AmazonRedshiftClient.doInvoke(AmazonRedshiftClient.java:9234)
at com.amazonaws.services.redshift.AmazonRedshiftClient.invoke(AmazonRedshiftClient.java:9201)
at com.amazonaws.services.redshift.AmazonRedshiftClient.invoke(AmazonRedshiftClient.java:9190)
at com.amazonaws.services.redshift.AmazonRedshiftClient.executeDescribeClusters(AmazonRedshiftClient.java:4581)
at com.amazonaws.services.redshift.AmazonRedshiftClient.describeClusters(AmazonRedshiftClient.java:4549)
at com.amazon.redshift.core.IamHelper.setClusterCredentials(IamHelper.java:546)
at com.amazon.redshift.core.IamHelper.setIAMCredentials(IamHelper.java:518)
at com.amazon.redshift.core.IamHelper.setIAMProperties(IamHelper.java:279)
at com.amazon.redshift.jdbc.RedshiftConnectionImpl.(RedshiftConnectionImpl.java:260)
at com.amazon.redshift.Driver.makeConnection(Driver.java:502)
at com.amazon.redshift.Driver.connect(Driver.java:315)
... 24 more
5. Any other details that can be helpful:

## JDBC trace logs

## Reproduction code

Start with the supplied PySpark reproduction and the stack-trace entry points com.amazon.redshift.core.IamHelper.setClusterCredentials and Driver.connect. Compare v2 behavior with v1 when SessionToken is present and verify the temporary-credential request using the provided AWS setup. Done means the same read succeeds with v2 and temporary credentials without the InvalidClientTokenId error.

Written by the indexing model from the issue text.