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  1. Spark
  2. SPARK-22320

ORC should support VectorUDT/MatrixUDT

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    Details

    • Type: Bug
    • Status: Resolved
    • Priority: Minor
    • Resolution: Not A Problem
    • Affects Version/s: 2.0.2, 2.1.2, 2.2.0
    • Fix Version/s: None
    • Component/s: SQL
    • Labels:
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      Description

      I save dataframe containing vectors in ORC format, when I read it back, the format is changed.

      scala> import org.apache.spark.ml.linalg._
      import org.apache.spark.ml.linalg._
      
      scala> val data = Seq((1,Vectors.dense(1.0,2.0)), (2,Vectors.sparse(8, Array(4), Array(1.0))))
      data: Seq[(Int, org.apache.spark.ml.linalg.Vector)] = List((1,[1.0,2.0]), (2,(8,[4],[1.0])))
      
      scala> val df = data.toDF("i", "vec")
      df: org.apache.spark.sql.DataFrame = [i: int, vec: vector]
      
      scala> df.schema
      res0: org.apache.spark.sql.types.StructType = StructType(StructField(i,IntegerType,false), StructField(vec,org.apache.spark.ml.linalg.VectorUDT@3bfc3ba7,true))
      
      scala> df.write.orc("/tmp/123")
      
      scala> val df2 = spark.sqlContext.read.orc("/tmp/123")
      df2: org.apache.spark.sql.DataFrame = [i: int, vec: struct<type: tinyint, size: int ... 2 more fields>]
      
      scala> df2.schema
      res3: org.apache.spark.sql.types.StructType = StructType(StructField(i,IntegerType,true), StructField(vec,StructType(StructField(type,ByteType,true), StructField(size,IntegerType,true), StructField(indices,ArrayType(IntegerType,true),true), StructField(values,ArrayType(DoubleType,true),true)),true))
      

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              • Assignee:
                Unassigned
                Reporter:
                podongfeng zhengruifeng
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                Dates

                • Created:
                  Updated:
                  Resolved: