hudi-agent commented on code in PR #18958:
URL: https://github.com/apache/hudi/pull/18958#discussion_r3408524182
##########
hudi-client/hudi-flink-client/src/main/java/org/apache/hudi/util/RowDataToAvroConverters.java:
##########
@@ -148,6 +148,14 @@ public Object convert(HoodieSchema schema, Object object) {
@Override
public Object convert(HoodieSchema schema, Object object) {
+ // The BLOB `type` discriminator is a STRING in Flink but an
ENUM in Avro.
+ // Detect that at call time from the HoodieSchema so the
converter stays
+ // reusable across any row shape — not hard-wired by Flink row
structure alone.
+ if (schema.getNonNullType().getType() ==
HoodieSchemaType.ENUM) {
Review Comment:
🤖 nit: `schema.getNonNullType()` is called twice — once in the condition and
once to assign `enumSchema`. Could you hoist the assignment above the `if` so
the result is reused? e.g. `HoodieSchema nonNullSchema =
schema.getNonNullType(); if (nonNullSchema.getType() == HoodieSchemaType.ENUM)
{ return new GenericData.EnumSymbol(nonNullSchema.toAvroSchema(), ...); }`
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##########
hudi-flink-datasource/hudi-flink/src/test/java/org/apache/hudi/table/ITTestBlobWrite.java:
##########
@@ -0,0 +1,228 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.hudi.table;
+
+import org.apache.hudi.common.model.HoodieTableType;
+import org.apache.hudi.common.schema.HoodieSchema;
+import org.apache.hudi.common.schema.HoodieSchemaField;
+import org.apache.hudi.common.schema.HoodieSchemaUtils;
+import org.apache.hudi.common.table.HoodieTableMetaClient;
+import org.apache.hudi.common.table.TableSchemaResolver;
+import org.apache.hudi.util.HoodieSchemaConverter;
+import org.apache.hudi.util.StreamerUtil;
+import org.apache.hudi.utils.FlinkMiniCluster;
+
+import org.apache.flink.table.api.TableEnvironment;
+import org.apache.flink.table.api.TableResult;
+import org.apache.flink.table.api.config.ExecutionConfigOptions;
+import org.apache.flink.table.catalog.ResolvedSchema;
+import org.apache.flink.table.types.logical.RowType;
+import org.apache.flink.types.Row;
+import org.apache.flink.util.CollectionUtil;
+import org.junit.jupiter.api.Test;
+import org.junit.jupiter.api.extension.ExtendWith;
+import org.junit.jupiter.api.io.TempDir;
+import org.junit.jupiter.params.ParameterizedTest;
+import org.junit.jupiter.params.provider.EnumSource;
+
+import java.io.File;
+import java.util.List;
+import java.util.concurrent.TimeUnit;
+
+import static org.junit.jupiter.api.Assertions.assertEquals;
+import static org.junit.jupiter.api.Assertions.assertNotNull;
+import static org.junit.jupiter.api.Assertions.assertNull;
+import static org.junit.jupiter.api.Assertions.assertTrue;
+
+/**
+ * IT case for writing out-of-line (OOL) BLOB columns through the Flink writer
and reading them back.
+ *
+ * <p>Verifies that the Hudi {@link HoodieSchema.Blob} structure round-trips
through the Flink
+ * write/read pipeline (both COW and MOR), that updates land through the MOR
Avro log path, and that
+ * the stored table schema keeps the BLOB logical type instead of degrading
the column to a generic
+ * Flink/Avro record.
+ */
+@ExtendWith(FlinkMiniCluster.class)
+public class ITTestBlobWrite {
+
+ @TempDir
+ File tempFile;
+
+ private static final String BLOB_COLUMN = "blob_col";
+
+ private static final String BLOB_COLUMN_DDL =
+ " " + BLOB_COLUMN + " ROW<\n"
+ + " `type` STRING NOT NULL,\n"
+ + " `data` BYTES,\n"
+ + " `reference` ROW<\n"
+ + " external_path STRING NOT NULL,\n"
+ + " `offset` BIGINT,\n"
+ + " `length` BIGINT,\n"
+ + " managed BOOLEAN NOT NULL\n"
+ + " >\n"
+ + " >,\n";
+
+ /**
+ * Regression for {@code HoodieSchemaConverter#isBlobStructure}: Flink SQL
{@code CREATE TABLE}
+ * may declare nested {@code ROW} fields as {@code NOT NULL}, but
+ * {@link ResolvedSchema#toPhysicalRowDataType()} does not always preserve
those constraints in
+ * the {@link RowType}. Schema inference must still recognize the BLOB shape
(same path as
+ * {@code HoodieTableFactory#inferAvroSchema}), otherwise {@code blob_col}
would degrade to a
+ * generic RECORD in the committed Hoodie schema.
+ */
+ @Test
+ public void testFlinkSqlDdlPhysicalRowTypeStillMapsToHoodieBlob() {
+ TableEnvironment tableEnv = batchEnv();
+ final String probeTable = "flink_blob_ddl_probe";
+ String createProbeDdl =
+ "CREATE TABLE "
+ + probeTable
+ + " (\n"
+ + " id BIGINT,\n"
+ + " name STRING,\n"
+ + BLOB_COLUMN_DDL
+ + " ts BIGINT\n"
+ + ") WITH ('connector'='blackhole')";
+ tableEnv.executeSql(createProbeDdl);
+
+ ResolvedSchema resolved = tableEnv.from(probeTable).getResolvedSchema();
+ RowType physical = (RowType)
resolved.toPhysicalRowDataType().getLogicalType();
+ int blobIdx = physical.getFieldNames().indexOf(BLOB_COLUMN);
+ RowType blobPhysical = (RowType) physical.getTypeAt(blobIdx);
+ // DDL uses NOT NULL on nested BLOB ROW fields where the canonical Hoodie
BLOB shape is
Review Comment:
🤖 nit: `blobPhysical` is declared here but never referenced again —
`convertToSchema` is called with `physical`, not `blobPhysical`. Could you
either remove this variable or add the assertion/use you intended?
<sub><i>- AI-generated; verify before applying. React 👍/👎 to flag
quality.</i></sub>
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