maven - ハイブを備えたApache Spark

Question

ハイブとの間でデータを読み書きするにはどうすればよいですか? ハイブとやり取りするには、ハイブプロファイルでスパークをコンパイルする必要がありますか? ハイブとやり取りするには、どの Maven 依存関係が必要ですか?

ハイブを操作するために段階的に従うべき適切なドキュメントが見つかりませんでした。

現在、ここに私のコードがあります

val sc = new SparkContext(new SparkConf().setMaster("local").setAppName("test"))
    val HiveContext = new org.apache.spark.sql.hive.HiveContext(sc)
    val sqlCon = new SQLContext(sc)
val schemaString = "Date:string,Open:double,High:double,Low:double,Close:double,Volume:double,Adj_Close:double"
val schema =
  StructType(
    schemaString.split(",").map(fieldName => StructField(fieldName.split(":")(0),
      getFieldTypeInSchema(fieldName.split(":")(1)), true)))
val rdd = sc.textFile("hdfs://45.55.159.119:9000/yahoo_stocks.csv")
//val rdd = sc.parallelize(arr)
val rowRDDx = noHeader.map(p => {
  var list: collection.mutable.Seq[Any] = collection.mutable.Seq.empty[Any]
  var index = 0
  val regex = rowSplittingRegexBuilder(Seq(","))
  var tokens = p.split(regex)
  tokens.foreach(value => {
    var valType = schema.fields(index).dataType
    var returnVal: Any = null
    valType match {
      case IntegerType => returnVal = value.toString.toInt
      case DoubleType => returnVal = value.toString.toDouble
      case LongType => returnVal = value.toString.toLong
      case FloatType => returnVal = value.toString.toFloat
      case ByteType => returnVal = value.toString.toByte
      case StringType => returnVal = value.toString
      case TimestampType => returnVal = value.toString
    }
    list = list :+ returnVal
    index += 1
  })
  Row.fromSeq(list)
})
val df = sqlCon.applySchema(rowRDDx, schema)
HiveContext.sql("create table yahoo_orc_table (date STRING, open_price FLOAT, high_price FLOAT, low_price FLOAT, close_price FLOAT, volume INT, adj_price FLOAT) stored as orc")
df.saveAsTable("hive", "org.apache.spark.sql.hive.orc", SaveMode.Append)

次の例外が発生しています

15/10/12 14:57:36 INFO storage.BlockManagerMaster: Registered BlockManager 
15/10/12 14:57:38 INFO scheduler.EventLoggingListener: Logging events to hdfs://host:9000/spark/logs/local-1444676256555
Exception in thread "main" java.lang.VerifyError: Bad return type 
Exception Details: 
  Location: 
    org/apache/spark/sql/catalyst/expressions/Pmod.inputType()Lorg/apache/spark/sql/types/AbstractDataType; @3: areturn 
  Reason: 
    Type 'org/apache/spark/sql/types/NumericType$' (current frame, stack[0]) is not assignable to 'org/apache/spark/sql/types/AbstractDataType' (from method signature) 
  Current Frame: 
    bci: @3 
    flags: { } 
    locals: { 'org/apache/spark/sql/catalyst/expressions/Pmod' } 
    stack: { 'org/apache/spark/sql/types/NumericType$' } 
  Bytecode: 
    0000000: b200 63b0 

        at java.lang.Class.getDeclaredConstructors0(Native Method) 
        at java.lang.Class.privateGetDeclaredConstructors(Class.java:2595) 
        at java.lang.Class.getConstructor0(Class.java:2895) 
        at java.lang.Class.getDeclaredConstructor(Class.java:2066) 
        at org.apache.spark.sql.catalyst.analysis.FunctionRegistry$$anonfun$4.apply(FunctionRegistry.scala:267) 
        at org.apache.spark.sql.catalyst.analysis.FunctionRegistry$$anonfun$4.apply(FunctionRegistry.scala:267) 
        at scala.util.Try$.apply(Try.scala:161) 
        at org.apache.spark.sql.catalyst.analysis.FunctionRegistry$.expression(FunctionRegistry.scala:267) 
        at org.apache.spark.sql.catalyst.analysis.FunctionRegistry$.<init>(FunctionRegistry.scala:148) 
        at org.apache.spark.sql.catalyst.analysis.FunctionRegistry$.<clinit>(FunctionRegistry.scala) 
        at org.apache.spark.sql.hive.HiveContext.functionRegistry$lzycompute(HiveContext.scala:414) 
        at org.apache.spark.sql.hive.HiveContext.functionRegistry(HiveContext.scala:413) 
        at org.apache.spark.sql.UDFRegistration.<init>(UDFRegistration.scala:39) 
        at org.apache.spark.sql.SQLContext.<init>(SQLContext.scala:203) 
        at org.apache.spark.sql.hive.HiveContext.<init>(HiveContext.scala:72)

ありがとう