[SPARK-26315][PYSPARK] auto cast threshold from Integer to Float in approxSimilarityJoin of BucketedRandomProjectionLSHModel

## What changes were proposed in this pull request?

If the input parameter 'threshold' to the function approxSimilarityJoin is not a float, we would get an exception.  The fix is to convert the 'threshold' into a float before calling the java implementation method.

## How was this patch tested?

Added a new test case.  Without this fix, the test will throw an exception as reported in the JIRA. With the fix, the test passes.

Please review http://spark.apache.org/contributing.html before opening a pull request.

Closes #23313 from jerryjch/SPARK-26315.

Authored-by: Jing Chen He <jinghe@us.ibm.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
(cherry picked from commit 860f449)
Signed-off-by: Sean Owen <sean.owen@databricks.com>

Author: Jing Chen He

python/pyspark/ml/feature.py

@@ -193,6 +193,7 @@ def approxSimilarityJoin(self, datasetA, datasetB, threshold, distCol="distCol")
                  "datasetA" and "datasetB", and a column "distCol" is added to show the distance
                  between each pair.
         """
+        threshold = TypeConverters.toFloat(threshold)
         return self._call_java("approxSimilarityJoin", datasetA, datasetB, threshold, distCol)
 
 
@@ -240,6 +241,16 @@ class BucketedRandomProjectionLSH(JavaEstimator, LSHParams, HasInputCol, HasOutp
     |  3|  6| 2.23606797749979|
     +---+---+-----------------+
     ...
+    >>> model.approxSimilarityJoin(df, df2, 3, distCol="EuclideanDistance").select(
+    ...     col("datasetA.id").alias("idA"),
+    ...     col("datasetB.id").alias("idB"),
+    ...     col("EuclideanDistance")).show()
+    +---+---+-----------------+
+    |idA|idB|EuclideanDistance|
+    +---+---+-----------------+
+    |  3|  6| 2.23606797749979|
+    +---+---+-----------------+
+    ...
     >>> brpPath = temp_path + "/brp"
     >>> brp.save(brpPath)
     >>> brp2 = BucketedRandomProjectionLSH.load(brpPath)