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https://issues.apache.org/jira/browse/SPARK-27388?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16817089#comment-16817089
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Taoufik DACHRAOUI commented on SPARK-27388:
-------------------------------------------
Currently we modified JavaTypeInference to be able to create encoders for Avro
objects; we have now two solutions, the one in this PR and another one using
Encoders.bean (fewer code changes); which one is better? how to proceed? we
should create another PR for the Encoders.bean solution?
The test we used for Encoders.bean is as follows:
{code:java}
implicit val avroExampleEncoder =
Encoders.bean[AvroExample1](classOf[AvroExample1]).asInstanceOf[ExpressionEncoder[AvroExample1]]
val input: AvroExample1 = AvroExample1.newBuilder()
.setMyarray(List("Foo", "Bar").asJava)
.setMyboolean(true)
.setMybytes(java.nio.ByteBuffer.wrap("MyBytes".getBytes()))
.setMydouble(2.5)
.setMyfixed(new Magic("magic".getBytes))
.setMyfloat(25.0F)
.setMyint(100)
.setMylong(10L)
.setMystring("hello")
.setMymap(Map(
"foo" -> new java.lang.Integer(1),
"bar" -> new java.lang.Integer(2)).asJava)
.setMymoney(Money.newBuilder().setAmount(100.0F).setCurrency(Currency.EUR).build())
.build()
val row: InternalRow = avroExampleEncoder.toRow(input)
val output: AvroExample1 = avroExampleEncoder.resolveAndBind().fromRow(row)
val ds: Dataset[AvroExample1] = List(input).toDS()
println(ds.schema)
println(ds.collect().toList)
ds.write.format("avro").save("example1")
val fooDF = spark.read.format("avro").load("example1")
val fooDS = fooDF.as[AvroExample1]
println(fooDS.collect().toList)
{code}
The change is made in the branch
[https://github.com/mazeboard/spark/tree/bean-encoder]
*with 105 additions and 39 deletions. (excluding the code for tests)*
> expression encoder for avro objects
> -----------------------------------
>
> Key: SPARK-27388
> URL: https://issues.apache.org/jira/browse/SPARK-27388
> Project: Spark
> Issue Type: New Feature
> Components: SQL
> Affects Versions: 2.4.1
> Reporter: Taoufik DACHRAOUI
> Priority: Major
>
> *What changes were proposed in this pull request?*
> The PR adds support for bean objects, java.util.List, java.util.Map,
> java.nio.ByteBuffer and java enums to ScalaReflection; unlike the existing
> javaBean Encoder, properties can be named without the set/get prefix (this is
> one of the key points that allows the encoding of Avro Fixed types. I
> believe, the other key point is that the addition must be in ScalaReflection).
> Reminder of Avro types:
> * primitive types: null, boolean, int, long, float, double, bytes, string
> * complex types: Records, Enums, Arrays, Maps, Unions, Fixed
> This PR supports simple unions (having a null type and a non-null type) but
> not complex unions for the simple reason that the Avro compiler will generate
> java code with type Object for all complex unions, and fields with simple
> unions will be typed as the non-null type of the union.
>
> *How was this patch tested?*
> currently only 1 encodeDecodeTest was added to ExpressionEncoderSuite; the
> test uses the following avro schema:
> {code:java}
> {"namespace": "org.apache.spark.sql.catalyst.encoders", "type": "record",
> "name": "AvroExample1",
> "fields": [
>
> {"name":"mymoney","type":["null",{"type":"record","name":"Money","namespace":"org.apache.spark.sql.catalyst.encoders","fields":[
> {"name":"amount","type":"float","default":0},
>
> {"name":"currency","type":{"type":"enum","name":"Currency","symbols":["EUR","USD","BRL"]},"default":"EUR"}]}],
> "default":null},
> {"name": "myfloat", "type": "float"},
> {"name": "mylong", "type": "long"},
> {"name": "myint", "type": "int"},
> {"name": "mydouble", "type": "double"},
> {"name": "myboolean", "type": "boolean"},
> {"name": "mystring", "type": "string"},
> {"name": "mybytes", "type": "bytes"},
> {"name": "myfixed", "type": {"type": "fixed", "name": "Magic", "size": 4}},
> {"name": "myarray", "type": {"type": "array", "items": "string"}},
> {"name": "mymap", "type": {"type": "map", "values": "int"}}
> ] }{code}
>
>
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