alexeykudinkin commented on a change in pull request #4789:
URL: https://github.com/apache/hudi/pull/4789#discussion_r813383960
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File path:
hudi-client/hudi-spark-client/src/main/scala/org/apache/hudi/AvroConversionUtils.scala
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@@ -41,8 +107,8 @@ object AvroConversionUtils {
else {
val schema = new Schema.Parser().parse(schemaStr)
val dataType = convertAvroSchemaToStructType(schema)
- val convertor = AvroConversionHelper.createConverterToRow(schema,
dataType)
- records.map { x => convertor(x).asInstanceOf[Row] }
+ val converter = createConverterToRow(schema, dataType)
Review comment:
@yihua you brought up legitimate concerns, there are a few
considerations here
- First of all, we already depend on `InternalRow` quite a bit (we even
have out own `HoodieInternalRow` extension)
- `InternalRow` is a core component of Spark that is unlikely to change
substantially (as that would mean that quite a bit of Spark will have to be
re-written to accommodate for any substantial changes to it, which, again, i
don't think are likely)
At the same time avoiding `InternalRow` > `Row` conversion has some
considerable performance advantages , and it's exactly how Spark operates
internally: all of its internal `Plan`s, expressions, operators, operate on
`InternalRow` and defer such deserialization (`InternalRow` to `Row`) only to
cases when you dereference it to `RDD[Row]`.
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