jonvex commented on code in PR #10904:
URL: https://github.com/apache/hudi/pull/10904#discussion_r1536639905
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hudi-client/hudi-spark-client/src/main/scala/org/apache/hudi/AvroConversionUtils.scala:
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@@ -98,13 +98,10 @@ object AvroConversionUtils {
*/
def createDataFrame(rdd: RDD[GenericRecord], schemaStr: String, ss:
SparkSession): Dataset[Row] = {
ss.createDataFrame(rdd.mapPartitions { records =>
- if (records.isEmpty) Iterator.empty
- else {
- val schema = new Schema.Parser().parse(schemaStr)
- val dataType = convertAvroSchemaToStructType(schema)
- val converter = createConverterToRow(schema, dataType)
- records.map { r => converter(r) }
- }
+ val schema = new Schema.Parser().parse(schemaStr)
Review Comment:
if (records.isEmpty) Iterator.empty
So wouldn't calling records.map still be empty?
No one I've asked so far knows why we did this, but I am also hesitant to
make this change as well
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