[SPARK-11764][ML] make Param.jsonEncode/jsonDecode support Vector

This PR makes the default read/write work with simple transformers/estimators that have params of type `Param[Vector]`. jkbradley

Author: Xiangrui Meng <meng@databricks.com>

Closes #9776 from mengxr/SPARK-11764.

mllib/src/main/scala/org/apache/spark/ml/param/params.scala

@@ -29,6 +29,7 @@ import org.json4s.jackson.JsonMethods._
 
 import org.apache.spark.annotation.{DeveloperApi, Experimental}
 import org.apache.spark.ml.util.Identifiable
+import org.apache.spark.mllib.linalg.{Vector, Vectors}
 
 /**
  * :: DeveloperApi ::
@@ -88,9 +89,11 @@ class Param[T](val parent: String, val name: String, val doc: String, val isVali
     value match {
       case x: String =>
         compact(render(JString(x)))
+      case v: Vector =>
+        v.toJson
       case _ =>
         throw new NotImplementedError(
-          "The default jsonEncode only supports string. " +
+          "The default jsonEncode only supports string and vector. " +
             s"${this.getClass.getName} must override jsonEncode for ${value.getClass.getName}.")
     }
   }
@@ -100,9 +103,14 @@ class Param[T](val parent: String, val name: String, val doc: String, val isVali
     parse(json) match {
       case JString(x) =>
         x.asInstanceOf[T]
+      case JObject(v) =>
+        val keys = v.map(_._1)
+        assert(keys.contains("type") && keys.contains("values"),
+          s"Expect a JSON serialized vector but cannot find fields 'type' and 'values' in $json.")
+        Vectors.fromJson(json).asInstanceOf[T]
       case _ =>
         throw new NotImplementedError(
-          "The default jsonDecode only supports string. " +
+          "The default jsonDecode only supports string and vector. " +
             s"${this.getClass.getName} must override jsonDecode to support its value type.")
     }
   }

mllib/src/test/scala/org/apache/spark/ml/param/ParamsSuite.scala

@@ -18,6 +18,7 @@
 package org.apache.spark.ml.param
 
 import org.apache.spark.SparkFunSuite
+import org.apache.spark.mllib.linalg.{Vector, Vectors}
 
 class ParamsSuite extends SparkFunSuite {
 
@@ -80,7 +81,7 @@ class ParamsSuite extends SparkFunSuite {
       }
     }
 
-    { // StringParam
+    { // Param[String]
       val param = new Param[String](dummy, "name", "doc")
       // Currently we do not support null.
       for (value <- Seq("", "1", "abc", "quote\"", "newline\n")) {
@@ -89,6 +90,19 @@ class ParamsSuite extends SparkFunSuite {
       }
     }
 
+    { // Param[Vector]
+      val param = new Param[Vector](dummy, "name", "doc")
+      val values = Seq(
+        Vectors.dense(Array.empty[Double]),
+        Vectors.dense(0.0, 2.0),
+        Vectors.sparse(0, Array.empty, Array.empty),
+        Vectors.sparse(2, Array(1), Array(2.0)))
+      for (value <- values) {
+        val json = param.jsonEncode(value)
+        assert(param.jsonDecode(json) === value)
+      }
+    }
+
     { // IntArrayParam
       val param = new IntArrayParam(dummy, "name", "doc")
       val values: Seq[Array[Int]] = Seq(
@@ -138,7 +152,7 @@ class ParamsSuite extends SparkFunSuite {
   test("param") {
     val solver = new TestParams()
     val uid = solver.uid
-    import solver.{maxIter, inputCol}
+    import solver.{inputCol, maxIter}
 
     assert(maxIter.name === "maxIter")
     assert(maxIter.doc === "maximum number of iterations (>= 0)")
@@ -181,7 +195,7 @@ class ParamsSuite extends SparkFunSuite {
 
   test("param map") {
     val solver = new TestParams()
-    import solver.{maxIter, inputCol}
+    import solver.{inputCol, maxIter}
 
     val map0 = ParamMap.empty
 
@@ -220,7 +234,7 @@ class ParamsSuite extends SparkFunSuite {
 
   test("params") {
     val solver = new TestParams()
-    import solver.{handleInvalid, maxIter, inputCol}
+    import solver.{handleInvalid, inputCol, maxIter}
 
     val params = solver.params
     assert(params.length === 3)