报错代码：

import org.apache.spark.ml.feature.BucketedRandomProjectionLSH
import org.apache.spark.ml.linalg.Vectors
import org.apache.spark.sql.SparkSession
import org.apache.spark.sql.functions.col

val dfA = spark.createDataFrame(Seq(
  (0, Vectors.dense(1.0, 1.0)),
  (1, Vectors.dense(1.0, -1.0)),
  (2, Vectors.dense(-1.0, -1.0)),
  (3, Vectors.dense(-1.0, 1.0))
)).toDF("id", "features")

val dfB = spark.createDataFrame(Seq(
  (4, Vectors.dense(1.0, 0.0)),
  (5, Vectors.dense(-1.0, 0.0)),
  (6, Vectors.dense(0.0, 1.0)),
  (7, Vectors.dense(0.0, -1.0))
)).toDF("id", "features")

val key = Vectors.dense(1.0, 0.0)

val brp = new BucketedRandomProjectionLSH()
  .setBucketLength(2.0)
  .setNumHashTables(3)
  .setInputCol("features")
  .setOutputCol("hashes")

val model = brp.fit(dfA)

// Feature Transformation
println("The hashed dataset where hashed values are stored in the column 'hashes':")
model.transform(dfA).show()

// Compute the locality sensitive hashes for the input rows, then perform approximate
// similarity join.
// We could avoid computing hashes by passing in the already-transformed dataset, e.g.
// `model.approxSimilarityJoin(transformedA, transformedB, 1.5)`
println("Approximately joining dfA and dfB on Euclidean distance smaller than 1.5:")
model.approxSimilarityJoin(dfA, dfB, 1.5, "EuclideanDistance")
  .select(col("datasetA.id").alias("idA"),
    col("datasetB.id").alias("idB"),
    col("EuclideanDistance")).show()

// Compute the locality sensitive hashes for the input rows, then perform approximate nearest
// neighbor search.
// We could avoid computing hashes by passing in the already-transformed dataset, e.g.
// `model.approxNearestNeighbors(transformedA, key, 2)`
println("Approximately searching dfA for 2 nearest neighbors of the key:")
model.approxNearestNeighbors(dfA, key, 2).show()

报错信息：

java.lang.NoSuchMethodError: org.json4s.jackson.JsonMethods$.parse(Lorg/json4s/JsonInput；Z)

排查问题：

如果在pom文件引入了某一个包，并且打包之后也可以在具体的位置找到，但是最终还是报错NoSuchMethodError，那么基本上就是包和包之前版本不匹配，版本冲突会导致，所以我需要排查下是否我的包版本存在冲突：

本地idea的json4s版本：

<dependency>
      <groupId>org.json4s</groupId>
      <artifactId>json4s-jackson_2.11</artifactId>
      <version>3.5.3</version>
    </dependency>

    <!-- https://mvnrepository.com/artifact/org.json4s/json4s-native-->
    <dependency>
      <groupId>org.json4s</groupId>
      <artifactId>json4s-native_2.11</artifactId>
      <version>3.5.3</version>
    </dependency>

环境中的spark版本：

这里排查后发现确实冲突了，所以这里将pom文件中的json包修改版本即可运行。

解决方式可以选择：
1、修改本地pom文件jar包版本，和环境spark的保持一致
2、使用shade打包，将重名的类修改为自定义，这样可以同时存在于spark中，因为类名不同所以不会引起冲突。