Make getters final for consistency with other mllib code

hnswlib-spark/src/main/scala/com/github/jelmerk/spark/conversion/VectorConverter.scala

@@ -27,10 +27,10 @@ private[conversion] trait VectorConverterParams extends HasInputCol with HasOutp
     *
     * @group param
     */
-  val outputType: Param[String] = new Param[String](this, "outputType", "type of vector to produce")
+  final val outputType: Param[String] = new Param[String](this, "outputType", "type of vector to produce")
 
   /** @group getParam */
-  def getOutputType: String = $(outputType)
+  final def getOutputType: String = $(outputType)
 
   setDefault(outputType -> "array<float>")
 }

hnswlib-spark/src/main/scala/com/github/jelmerk/spark/knn/KnnAlgorithm.scala

@@ -93,53 +93,53 @@ private[knn] trait KnnModelParams extends Params with HasFeaturesCol with HasPre
     *
     * @group param
     */
-  val queryIdentifierCol = new Param[String](this, "queryIdentifierCol", "column name for the query identifier")
+  final val queryIdentifierCol = new Param[String](this, "queryIdentifierCol", "column name for the query identifier")
 
   /** @group getParam */
-  def getQueryIdentifierCol: String = $(queryIdentifierCol)
+  final def getQueryIdentifierCol: String = $(queryIdentifierCol)
 
   /**
    * Param for the column name for the query partitions.
    *
    * @group param
    */
-  val queryPartitionsCol = new Param[String](this, "queryPartitionsCol", "column name for the query partitions")
+  final val queryPartitionsCol = new Param[String](this, "queryPartitionsCol", "column name for the query partitions")
 
   /** @group getParam */
-  def getQueryPartitionsCol: String = $(queryPartitionsCol)
+  final def getQueryPartitionsCol: String = $(queryPartitionsCol)
 
   /**
     * Param for number of neighbors to find (> 0).
     * Default: 5
     *
     * @group param
     */
-  val k = new IntParam(this, "k", "number of neighbors to find", ParamValidators.gt(0))
+  final val k = new IntParam(this, "k", "number of neighbors to find", ParamValidators.gt(0))
 
   /** @group getParam */
-  def getK: Int = $(k)
+  final def getK: Int = $(k)
 
   /**
     * Param that indicates whether to not return the a candidate when it's identifier equals the query identifier
     * Default: false
     *
     * @group param
     */
-  val excludeSelf = new BooleanParam(this, "excludeSelf", "whether to include the row identifier as a candidate neighbor")
+  final val excludeSelf = new BooleanParam(this, "excludeSelf", "whether to include the row identifier as a candidate neighbor")
 
   /** @group getParam */
-  def getExcludeSelf: Boolean = $(excludeSelf)
+  final def getExcludeSelf: Boolean = $(excludeSelf)
 
   /**
     * Param for the threshold value for inclusion. -1 indicates no threshold
     * Default: -1
     *
     * @group param
     */
-  val similarityThreshold = new DoubleParam(this, "similarityThreshold", "do not return neighbors further away than this distance")
+  final val similarityThreshold = new DoubleParam(this, "similarityThreshold", "do not return neighbors further away than this distance")
 
   /** @group getParam */
-  def getSimilarityThreshold: Double = $(similarityThreshold)
+  final def getSimilarityThreshold: Double = $(similarityThreshold)
 
   /**
     * Param that specifies the number of index replicas to create when querying the index. More replicas means you can
@@ -148,21 +148,21 @@ private[knn] trait KnnModelParams extends Params with HasFeaturesCol with HasPre
     *
     * @group param
     */
-  val numReplicas = new IntParam(this, "numReplicas", "number of index replicas to create when querying")
+  final val numReplicas = new IntParam(this, "numReplicas", "number of index replicas to create when querying")
 
   /** @group getParam */
-  def getNumReplicas: Int = $(numReplicas)
+  final def getNumReplicas: Int = $(numReplicas)
 
   /**
     * Param that specifies the number of threads to use.
     * Default: number of processors available to the Java virtual machine
     *
     * @group param
     */
-  val parallelism = new IntParam(this, "parallelism", "number of threads to use")
+  final val parallelism = new IntParam(this, "parallelism", "number of threads to use")
 
   /** @group getParam */
-  def getParallelism: Int = $(parallelism)
+  final def getParallelism: Int = $(parallelism)
 
   /**
     * Param for the output format to produce. One of "full", "minimal" Setting this to minimal is more efficient
@@ -172,10 +172,10 @@ private[knn] trait KnnModelParams extends Params with HasFeaturesCol with HasPre
     *
     * @group param
     */
-  val outputFormat = new Param[String](this, "outputFormat", "output format to produce")
+  final val outputFormat = new Param[String](this, "outputFormat", "output format to produce")
 
   /** @group getParam */
-  def getOutputFormat: String = $(outputFormat)
+  final def getOutputFormat: String = $(outputFormat)
 
   setDefault(k -> 5, predictionCol -> "prediction", featuresCol -> "features",
     excludeSelf -> false, similarityThreshold -> -1, outputFormat -> "full")
@@ -213,19 +213,19 @@ private[knn] trait KnnAlgorithmParams extends KnnModelParams {
     *
     * @group param
     */
-  val identifierCol = new Param[String](this, "identifierCol", "column name for the row identifier")
+  final val identifierCol = new Param[String](this, "identifierCol", "column name for the row identifier")
 
   /** @group getParam */
-  def getIdentifierCol: String = $(identifierCol)
+  final def getIdentifierCol: String = $(identifierCol)
 
   /**
     * Number of partitions (default: 1)
     */
-  val numPartitions = new IntParam(this, "numPartitions",
+  final val numPartitions = new IntParam(this, "numPartitions",
     "number of partitions", ParamValidators.gt(0))
 
   /** @group getParam */
-  def getNumPartitions: Int = $(numPartitions)
+  final def getNumPartitions: Int = $(numPartitions)
 
   /**
     * Param for the distance function to use. One of "bray-curtis", "canberra",  "cosine", "correlation", "euclidean",
@@ -234,15 +234,15 @@ private[knn] trait KnnAlgorithmParams extends KnnModelParams {
     *
     * @group param
     */
-  val distanceFunction = new Param[String](this, "distanceFunction", "distance function to use")
+  final val distanceFunction = new Param[String](this, "distanceFunction", "distance function to use")
 
   /** @group getParam */
-  def getDistanceFunction: String = $(distanceFunction)
+  final def getDistanceFunction: String = $(distanceFunction)
 
-  val partitionCol = new Param[String](this, "partitionCol", "column name for the partition identifier")
+  final val partitionCol = new Param[String](this, "partitionCol", "column name for the partition identifier")
 
   /** @group getParam */
-  def getPartitionCol: String = $(partitionCol)
+  final def getPartitionCol: String = $(partitionCol)
 
   setDefault(identifierCol -> "id", distanceFunction -> "cosine", numPartitions -> 1, numReplicas -> 0)
 }

hnswlib-spark/src/main/scala/com/github/jelmerk/spark/knn/evaluation/KnnSimilarityEvaluator.scala

@@ -32,35 +32,35 @@ class KnnSimilarityEvaluator(override val uid: String) extends Evaluator with De
     *
     * @group param
     */
-  val approximateNeighborsCol = new Param[String](this, "approximateNeighborsCol", "column containing the approximate neighbors")
+  final val approximateNeighborsCol = new Param[String](this, "approximateNeighborsCol", "column containing the approximate neighbors")
 
   /**
     * @group getParam
     */
-  def getApproximateNeighborsCol: String = $(approximateNeighborsCol)
+  final def getApproximateNeighborsCol: String = $(approximateNeighborsCol)
 
   /**
     * @group setParam
     */
-  def setApproximateNeighborsCol(value: String): this.type = set(approximateNeighborsCol, value)
+  final def setApproximateNeighborsCol(value: String): this.type = set(approximateNeighborsCol, value)
 
   /**
     * Param for the column name for the exact results.
     * Default: "exactNeighbors"
     *
     * @group param
     */
-  val exactNeighborsCol = new Param[String](this, "exactNeighborsCol", "column containing the exact neighbors")
+  final val exactNeighborsCol = new Param[String](this, "exactNeighborsCol", "column containing the exact neighbors")
 
   /**
     * @group getParam
     */
-  def getExactNeighborsCol: String = $(exactNeighborsCol)
+  final def getExactNeighborsCol: String = $(exactNeighborsCol)
 
   /**
     * @group setParam
     */
-  def setExactNeighborsCol(value: String): this.type = set(exactNeighborsCol, value)
+  final def setExactNeighborsCol(value: String): this.type = set(exactNeighborsCol, value)
 
   /**
     * Returns the accuracy of the approximate results.

hnswlib-spark/src/main/scala/com/github/jelmerk/spark/knn/hnsw/HnswSimilarity.scala

@@ -23,23 +23,23 @@ private[hnsw] trait HnswParams extends KnnAlgorithmParams with HnswModelParams {
     *
     * @group param
     */
-  val m = new IntParam(this, "m",
+  final val m = new IntParam(this, "m",
     "number of bi-directional links created for every new element during construction", ParamValidators.gt(0))
 
   /** @group getParam */
-  def getM: Int = $(m)
+  final def getM: Int = $(m)
 
   /**
     * Has the same meaning as ef, but controls the index time / index precision.
     * Default: 200
     *
     * @group param
     */
-  val efConstruction = new IntParam(this, "efConstruction",
+  final val efConstruction = new IntParam(this, "efConstruction",
     "has the same meaning as ef, but controls the index time / index precision", ParamValidators.gt(0))
 
   /** @group getParam */
-  def getEfConstruction: Int = $(efConstruction)
+  final def getEfConstruction: Int = $(efConstruction)
 
   setDefault(m -> 16, efConstruction -> 200)
 }
@@ -55,11 +55,11 @@ private[hnsw] trait HnswModelParams extends KnnModelParams {
     *
     * @group param
     */
-  val ef = new IntParam(this, "ef",
+  final val ef = new IntParam(this, "ef",
     "size of the dynamic list for the nearest neighbors (used during the search)", ParamValidators.gt(0))
 
   /** @group getParam */
-  def getEf: Int = $(ef)
+  final def getEf: Int = $(ef)
 
   setDefault(ef -> 10)
 }