shardulm94 commented on a change in pull request #1103:
URL: https://github.com/apache/iceberg/pull/1103#discussion_r439080230



##########
File path: mr/src/main/java/org/apache/iceberg/mr/mapred/IcebergSerDe.java
##########
@@ -0,0 +1,129 @@
+/*
+ * 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.iceberg.mr.mapred;
+
+import java.io.IOException;
+import java.io.UncheckedIOException;
+import java.sql.Date;
+import java.sql.Timestamp;
+import java.time.LocalDate;
+import java.time.LocalDateTime;
+import java.time.LocalTime;
+import java.time.OffsetDateTime;
+import java.util.ArrayList;
+import java.util.Collections;
+import java.util.List;
+import java.util.Properties;
+import javax.annotation.Nullable;
+import org.apache.hadoop.conf.Configuration;
+import org.apache.hadoop.hive.serde2.AbstractSerDe;
+import org.apache.hadoop.hive.serde2.SerDeException;
+import org.apache.hadoop.hive.serde2.SerDeStats;
+import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspector;
+import org.apache.hadoop.io.Writable;
+import org.apache.iceberg.Schema;
+import org.apache.iceberg.SnapshotsTable;
+import org.apache.iceberg.Table;
+import org.apache.iceberg.types.Type;
+import org.apache.iceberg.types.Types;
+
+public class IcebergSerDe extends AbstractSerDe {
+
+  private Schema schema;
+  private ObjectInspector inspector;
+  private List<Object> row;
+
+  @Override
+  public void initialize(@Nullable Configuration configuration, Properties 
serDeProperties) throws SerDeException {
+    Table table = null;
+    try {
+      table = TableResolver.resolveTableFromConfiguration(configuration, 
serDeProperties);
+    } catch (IOException e) {
+      throw new UncheckedIOException("Unable to resolve table from 
configuration: ", e);
+    }
+    this.schema = table.schema();
+    if (table instanceof SnapshotsTable) {
+      try {
+        this.inspector = new 
IcebergObjectInspectorGenerator().createObjectInspector(schema);
+      } catch (Exception e) {
+        throw new SerDeException(e);
+      }
+    } else {
+      List<Types.NestedField> columns = new ArrayList<>(schema.columns());
+      columns.add(Types.NestedField.optional(Integer.MAX_VALUE,
+          SystemTableUtil.snapshotIdVirtualColumnName(serDeProperties), 
Types.LongType.get()));
+      Schema withVirtualColumn = new Schema(columns);
+      try {
+        this.inspector = new 
IcebergObjectInspectorGenerator().createObjectInspector(withVirtualColumn);
+      } catch (Exception e) {
+        throw new SerDeException(e);
+      }
+    }
+  }
+
+  @Override
+  public Class<? extends Writable> getSerializedClass() {
+    return null;
+  }
+
+  @Override
+  public Writable serialize(Object o, ObjectInspector objectInspector) {
+    return null;
+  }
+
+  @Override
+  public SerDeStats getSerDeStats() {
+    return null;
+  }
+
+  @Override
+  public Object deserialize(Writable writable) {

Review comment:
       Instead of using ObjectInspectors, do you think it's worth building a 
ReaderFunc which returns Hive compatible objects instead? We can save one 
conversion that way. e.g Avro objects -> Hive objects, instead of Avro objects 
-> Iceberg Generic objects -> Hive objects. The downside is we will have to 
build a Hive-compatible ReaderFunc for each file format but I don't expect it 
to be too hard.




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