danny0405 commented on code in PR #18958:
URL: https://github.com/apache/hudi/pull/18958#discussion_r3400264649
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hudi-flink-datasource/hudi-flink/src/test/java/org/apache/hudi/utils/TestRowDataToAvroConverters.java:
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@@ -81,4 +85,48 @@ void testRowDataToAvroStringToRowDataWithUtcTimezone()
throws JsonProcessingExce
Assertions.assertEquals("2021-03-30 08:44:29",
formatter.format(LocalDateTime.ofInstant(Instant.ofEpochMilli((Long)
avroRecord.get(0)), ZoneId.of("UTC+1"))));
Assertions.assertEquals("2021-03-30 15:44:29",
formatter.format(LocalDateTime.ofInstant(Instant.ofEpochMilli((Long)
avroRecord.get(0)), ZoneId.of("Asia/Shanghai"))));
}
+
+ @Test
+ void testRowDataToAvroBlobTypeFieldWritesEnumSymbol() {
+ // Flink models the BLOB `type` discriminator as STRING, but its Avro
encoding is an ENUM
+ // (blob_storage_type). The converter must emit a GenericData.EnumSymbol,
not a plain Utf8,
+ // otherwise Avro log-block writes (MOR) fail with "value OUT_OF_LINE (a
Utf8) is not a
+ // blob_storage_type".
+ DataType blobRow = DataTypes.ROW(
+ DataTypes.FIELD(HoodieSchema.Blob.TYPE, DataTypes.STRING().notNull()),
+ DataTypes.FIELD(HoodieSchema.Blob.INLINE_DATA_FIELD,
DataTypes.BYTES().nullable()),
+ DataTypes.FIELD(HoodieSchema.Blob.EXTERNAL_REFERENCE, DataTypes.ROW(
+ DataTypes.FIELD(HoodieSchema.Blob.EXTERNAL_REFERENCE_PATH,
DataTypes.STRING().notNull()),
+ DataTypes.FIELD(HoodieSchema.Blob.EXTERNAL_REFERENCE_OFFSET,
DataTypes.BIGINT().nullable()),
+ DataTypes.FIELD(HoodieSchema.Blob.EXTERNAL_REFERENCE_LENGTH,
DataTypes.BIGINT().nullable()),
+ DataTypes.FIELD(HoodieSchema.Blob.EXTERNAL_REFERENCE_IS_MANAGED,
DataTypes.BOOLEAN().notNull())
+ ).nullable()));
+ RowType rowType = (RowType) DataTypes.ROW(DataTypes.FIELD("blob_col",
blobRow)).getLogicalType();
+
+ GenericRowData reference = new GenericRowData(4);
+ reference.setField(0, StringData.fromString("file1.bin"));
+ reference.setField(1, 0L);
+ reference.setField(2, 100L);
+ reference.setField(3, false);
+
+ GenericRowData blob = new GenericRowData(3);
+ blob.setField(0, StringData.fromString(HoodieSchema.Blob.OUT_OF_LINE));
+ blob.setField(1, null);
+ blob.setField(2, reference);
+
+ GenericRowData top = new GenericRowData(1);
+ top.setField(0, blob);
+
+ RowDataToAvroConverters.RowDataToAvroConverter converter =
+ RowDataToAvroConverters.createConverter(rowType);
+ GenericRecord avroRecord =
+ (GenericRecord)
converter.convert(HoodieSchemaConverter.convertToSchema(rowType), top);
Review Comment:
This test only exercises the inferred-schema path
(`convertToSchema(rowType)`), so it cannot catch the case where the converter
is created from a BLOB-shaped RowType but conversion is invoked with a
pre-existing plain RECORD schema. Given the converter API accepts the
`HoodieSchema` at `convert(...)` time, it would be worth adding a regression
with a plain BLOB-shaped record schema (for example the shape from
`HoodieSchemaTestUtils.createPlainBlobRecord`) to ensure those records still
emit a normal string/Utf8 `type` field instead of taking the BLOB enum path.
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