[HUDI-9172] Fix timestamp millis being read as micros for log files #13288
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jonvex
changed the title
jonvex
changed the title
| @@ -152,8 +153,8 @@ class HoodieFileGroupReaderBasedParquetFileFormat(tablePath: String, | |||
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| // schema that we want fg reader to output to us | |||
| val requestedSchema = StructType(requiredSchema.fields ++ partitionSchema.fields.filter(f => mandatoryFields.contains(f.name))) | |||
| val requestedAvroSchema = AvroConversionUtils.convertStructTypeToAvroSchema(requestedSchema, sanitizedTableName) | |||
| val dataAvroSchema = AvroConversionUtils.convertStructTypeToAvroSchema(dataSchema, sanitizedTableName) | |||
| val requestedAvroSchema = HoodieAvroUtils.repairSchema(AvroConversionUtils.convertStructTypeToAvroSchema(requestedSchema, sanitizedTableName), avroTableSchema) | |||
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Instead of constructing a schema that needs repair, is it possible to just incorporate this into the initial conversion?
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+1, why not just fix the original conversion, is the Spark StructType missed something?
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yes, it only uses microseconds. Also it's missing enum type as well
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Hmm, I think StructType at least suppors timestamp with explicit precision? like timestamp(3) or timestamp(9)? Did you try that?
linliu-code
reviewed
May 20, 2025
| } | ||
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| // Only repair timestamp-millis <-> timestamp-micros logical types | ||
| if (convertedSchema.getType() == Schema.Type.LONG && tableSchema.getType() == Schema.Type.LONG) { |
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We can also fix the Enum -> String -> Enum issue here. I think the logically they are the same. CC: @yihua , @nsivabalan
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