[java-spanner-jdbc] Bigquery 2.9.16: Using this connector in Spark is resulting in all values in the spark dataframe being the column names

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Please run down the following list and make sure you've tried the usual "quick fixes":

- Search the issues already opened: https://github.com/googleapis/java-spanner-jdbc/issues
- Check for answers on StackOverflow: http://stackoverflow.com/questions/tagged/google-cloud-platform

If you are still having issues, please include as much information as possible:

#### Environment details

1. Specify the API at the beginning of the title. For example, "BigQuery: ...").
General, Core, and Other are also allowed as types
2. OS type and version: Mac 12.0
3. Java version: 20.0.1
4. version(s):

#### Steps to reproduce

1. Hook this connector up in a spark job with the following code:
```scala
def querySpanner[T](sqlQuery: String)(implicit spark: SparkSession, enc: org.apache.spark.sql.Encoder[T]): Dataset[T] = {
val url = "jdbc:cloudspanner:/projects/your-project-id/instances/your-instance-id/databases/your-database-id?credentials=$jsonKeyFilePath"

// Read data using Spark
val df = spark.read
.format("jdbc")
.option("url", url)
.option("dbtable", "myTable")
.option("driver", "com.google.cloud.spanner.jdbc.JdbcDriver")
.load()

// Convert DataFrame to Dataset
df.as[T]
}
```

2. See that it is returning the values as if every row is the column name:
+----+---+
|name| id|
+----+---+
|name| id|
|name| id|
|name| id|
|name| id|
|name| id|
|name| id|
|name| id|
|name| id|
|name| id|
|name| id|
|name| id|
|name| id|
|name| id|
|name| id|
|name| id|
|name| id|
|name| id|
|name| id|
|name| id|
|name| id|
+----+---+
only showing top 20 rows

My query is: "SELECT name, id FROM OrgInfoV2"

#### Any additional information below

It seems similar to this issue:
https://stackoverflow.com/questions/66983401/spark-mariadb-jdbc-sql-query-returns-column-names-instead-of-column-values
or this one:
https://stackoverflow.com/questions/63177736/spark-read-as-jdbc-return-all-rows-as-columns-name

where it appears to be issues with the driver

Following these steps guarantees the quickest resolution possible.

Thanks!