[HUDI-607] Fix to allow creation/syncing of Hive tables partitioned by Date type columns (#1330)

hudi-spark/src/test/java/DataSourceUtilsTest.java

@@ -0,0 +1,61 @@
+/*
+ * 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.
+ */
+
+import org.apache.avro.Schema;
+import org.apache.avro.generic.GenericData;
+import org.apache.avro.generic.GenericRecord;
+import org.apache.hudi.DataSourceUtils;
+import org.junit.Test;
+
+import java.time.LocalDate;
+
+import static org.junit.Assert.assertEquals;
+
+public class DataSourceUtilsTest {
+
+  @Test
+  public void testAvroRecordsFieldConversion() {
+    // There are fields event_date1, event_date2, event_date3 with logical type as Date. event_date1 & event_date3 are
+    // of UNION schema type, which is a union of null and date type in different orders. event_date2 is non-union
+    // date type
+    String avroSchemaString  = "{\"type\": \"record\"," + "\"name\": \"events\"," + "\"fields\": [ "
+        + "{\"name\": \"event_date1\", \"type\" : [{\"type\" : \"int\", \"logicalType\" : \"date\"}, \"null\"]},"
+        + "{\"name\": \"event_date2\", \"type\" : {\"type\": \"int\", \"logicalType\" : \"date\"}},"
+        + "{\"name\": \"event_date3\", \"type\" : [\"null\", {\"type\" : \"int\", \"logicalType\" : \"date\"}]},"
+        + "{\"name\": \"event_name\", \"type\": \"string\"},"
+        + "{\"name\": \"event_organizer\", \"type\": \"string\"}"
+        + "]}";
+
+    Schema avroSchema = new Schema.Parser().parse(avroSchemaString);
+    GenericRecord record = new GenericData.Record(avroSchema);
+    record.put("event_date1", 18000);
+    record.put("event_date2", 18001);
+    record.put("event_date3", 18002);
+    record.put("event_name", "Hudi Meetup");
+    record.put("event_organizer", "Hudi PMC");
+
+    assertEquals(LocalDate.ofEpochDay(18000).toString(), DataSourceUtils.getNestedFieldValAsString(record, "event_date1",
+        true));
+    assertEquals(LocalDate.ofEpochDay(18001).toString(), DataSourceUtils.getNestedFieldValAsString(record, "event_date2",
+        true));
+    assertEquals(LocalDate.ofEpochDay(18002).toString(), DataSourceUtils.getNestedFieldValAsString(record, "event_date3",
+        true));
+    assertEquals("Hudi Meetup", DataSourceUtils.getNestedFieldValAsString(record, "event_name", true));
+    assertEquals("Hudi PMC", DataSourceUtils.getNestedFieldValAsString(record, "event_organizer", true));
+  }
+}