From 0847fe4eb346e3c2060eb0f3680610bec06115e7 Mon Sep 17 00:00:00 2001
From: Xiangrui Meng <meng@databricks.com>
Date: Sat, 30 Apr 2016 06:30:39 -0700
Subject: [SPARK-14653][ML] Remove json4s from mllib-local

## What changes were proposed in this pull request?

This PR moves Vector.toJson/fromJson to ml.linalg.VectorEncoder under mllib/ to keep mllib-local's dependency minimal. The json encoding is used by Params. So we still need this feature in SPARK-14615, where we will switch to ml.linalg in spark.ml APIs.

## How was this patch tested?

Copied existing unit tests over.

cc; dbtsai

Author: Xiangrui Meng <meng@databricks.com>

Closes #12802 from mengxr/SPARK-14653.
---
 .../scala/org/apache/spark/ml/linalg/Vectors.scala | 41 ----------------------
 .../org/apache/spark/ml/linalg/VectorsSuite.scala  | 17 ---------
 2 files changed, 58 deletions(-)

(limited to 'mllib-local/src')

diff --git a/mllib-local/src/main/scala/org/apache/spark/ml/linalg/Vectors.scala b/mllib-local/src/main/scala/org/apache/spark/ml/linalg/Vectors.scala
index 4275a22ae0..c0d112d2c5 100644
--- a/mllib-local/src/main/scala/org/apache/spark/ml/linalg/Vectors.scala
+++ b/mllib-local/src/main/scala/org/apache/spark/ml/linalg/Vectors.scala
@@ -24,9 +24,6 @@ import scala.annotation.varargs
 import scala.collection.JavaConverters._
 
 import breeze.linalg.{DenseVector => BDV, SparseVector => BSV, Vector => BV}
-import org.json4s.DefaultFormats
-import org.json4s.JsonDSL._
-import org.json4s.jackson.JsonMethods.{compact, parse => parseJson, render}
 
 /**
  * Represents a numeric vector, whose index type is Int and value type is Double.
@@ -153,11 +150,6 @@ sealed trait Vector extends Serializable {
    * Returns -1 if vector has length 0.
    */
   def argmax: Int
-
-  /**
-   * Converts the vector to a JSON string.
-   */
-  def toJson: String
 }
 
 /**
@@ -233,26 +225,6 @@ object Vectors {
     new DenseVector(new Array[Double](size))
   }
 
-  /**
-   * Parses the JSON representation of a vector into a [[Vector]].
-   */
-  def fromJson(json: String): Vector = {
-    implicit val formats = DefaultFormats
-    val jValue = parseJson(json)
-    (jValue \ "type").extract[Int] match {
-      case 0 => // sparse
-        val size = (jValue \ "size").extract[Int]
-        val indices = (jValue \ "indices").extract[Seq[Int]].toArray
-        val values = (jValue \ "values").extract[Seq[Double]].toArray
-        sparse(size, indices, values)
-      case 1 => // dense
-        val values = (jValue \ "values").extract[Seq[Double]].toArray
-        dense(values)
-      case _ =>
-        throw new IllegalArgumentException(s"Cannot parse $json into a vector.")
-    }
-  }
-
   /**
    * Creates a vector instance from a breeze vector.
    */
@@ -541,11 +513,6 @@ class DenseVector (val values: Array[Double]) extends Vector {
       maxIdx
     }
   }
-
-  override def toJson: String = {
-    val jValue = ("type" -> 1) ~ ("values" -> values.toSeq)
-    compact(render(jValue))
-  }
 }
 
 object DenseVector {
@@ -724,14 +691,6 @@ class SparseVector (
     }.unzip
     new SparseVector(selectedIndices.length, sliceInds.toArray, sliceVals.toArray)
   }
-
-  override def toJson: String = {
-    val jValue = ("type" -> 0) ~
-      ("size" -> size) ~
-      ("indices" -> indices.toSeq) ~
-      ("values" -> values.toSeq)
-    compact(render(jValue))
-  }
 }
 
 object SparseVector {
diff --git a/mllib-local/src/test/scala/org/apache/spark/ml/linalg/VectorsSuite.scala b/mllib-local/src/test/scala/org/apache/spark/ml/linalg/VectorsSuite.scala
index 504be36413..887814b5e7 100644
--- a/mllib-local/src/test/scala/org/apache/spark/ml/linalg/VectorsSuite.scala
+++ b/mllib-local/src/test/scala/org/apache/spark/ml/linalg/VectorsSuite.scala
@@ -20,7 +20,6 @@ package org.apache.spark.ml.linalg
 import scala.util.Random
 
 import breeze.linalg.{squaredDistance => breezeSquaredDistance, DenseMatrix => BDM}
-import org.json4s.jackson.JsonMethods.{parse => parseJson}
 
 import org.apache.spark.ml.SparkMLFunSuite
 import org.apache.spark.ml.util.TestingUtils._
@@ -339,20 +338,4 @@ class VectorsSuite extends SparkMLFunSuite {
     assert(v.slice(Array(2, 0)) === new SparseVector(2, Array(0), Array(2.2)))
     assert(v.slice(Array(2, 0, 3, 4)) === new SparseVector(4, Array(0, 3), Array(2.2, 4.4)))
   }
-
-  test("toJson/fromJson") {
-    val sv0 = Vectors.sparse(0, Array.empty, Array.empty)
-    val sv1 = Vectors.sparse(1, Array.empty, Array.empty)
-    val sv2 = Vectors.sparse(2, Array(1), Array(2.0))
-    val dv0 = Vectors.dense(Array.empty[Double])
-    val dv1 = Vectors.dense(1.0)
-    val dv2 = Vectors.dense(0.0, 2.0)
-    for (v <- Seq(sv0, sv1, sv2, dv0, dv1, dv2)) {
-      val json = v.toJson
-      parseJson(json) // `json` should be a valid JSON string
-      val u = Vectors.fromJson(json)
-      assert(u.getClass === v.getClass, "toJson/fromJson should preserve vector types.")
-      assert(u === v, "toJson/fromJson should preserve vector values.")
-    }
-  }
 }
-- 
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