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From viirya <...@git.apache.org>
Subject [GitHub] spark pull request: [SPARK-11743][SQL] Add UserDefinedType support...
Date Mon, 16 Nov 2015 09:50:17 GMT
Github user viirya commented on a diff in the pull request:

    https://github.com/apache/spark/pull/9712#discussion_r44904260
  
    --- Diff: sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/encoders/RowEncoderSuite.scala
---
    @@ -68,7 +117,36 @@ class RowEncoderSuite extends SparkFunSuite {
           .add("structOfArray", new StructType().add("array", arrayOfString))
           .add("structOfMap", new StructType().add("map", mapOfString))
           .add("structOfArrayAndMap",
    -        new StructType().add("array", arrayOfString).add("map", mapOfString)))
    +        new StructType().add("array", arrayOfString).add("map", mapOfString))
    +      .add("structOfUDT", structOfUDT))
    +
    +  test(s"encode/decode: arrayOfUDT") {
    +    val schema = new StructType()
    +      .add("arrayOfUDT", arrayOfUDT)
    +
    +    val encoder = RowEncoder(schema)
    +
    +    val input: Row = Row(Seq(new ExamplePoint(0.1, 0.2), new ExamplePoint(0.3, 0.4)))
    +    val row = encoder.toRow(input)
    +    val convertedBack = encoder.fromRow(row)
    +    assert(input.getSeq[ExamplePoint](0) == convertedBack.getSeq[ExamplePoint](0))
    +  }
    +
    +  test(s"encode/decode: Product") {
    +    val schema = new StructType()
    +      .add("structAsProduct",
    +        new StructType()
    +          .add("int", IntegerType)
    +          .add("string", StringType)
    +          .add("double", DoubleType))
    +
    +    val encoder = RowEncoder(schema)
    +
    +    val input: Row = Row((100, "test", 0.123))
    --- End diff --
    
    Hmm, as I tried, I found a problem is we may not always be able to get the type `T` needed
to construct `ProductEncoder` and `FlatEncoder`. Even we can get it, we can't keep it in ScalaUDF
due to serialization issue.


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