[GitHub] [incubator-iceberg] prodeezy commented on a change in pull request #63: Use Iceberg writers for Parquet data written from Spark.

[GitBox <gi...@apache.org>]

prodeezy commented on a change in pull request #63: Use Iceberg writers for Parquet data written from Spark.
URL: https://github.com/apache/incubator-iceberg/pull/63#discussion_r262391461
 
 

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 File path: spark/src/main/java/com/netflix/iceberg/spark/data/SparkParquetWriters.java
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+/*
+ * 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 com.netflix.iceberg.spark.data;
+
+import com.google.common.base.Preconditions;
+import com.google.common.collect.Lists;
+import com.netflix.iceberg.Schema;
+import com.netflix.iceberg.parquet.ParquetTypeVisitor;
+import com.netflix.iceberg.parquet.ParquetValueReaders.ReusableEntry;
+import com.netflix.iceberg.parquet.ParquetValueWriter;
+import com.netflix.iceberg.parquet.ParquetValueWriters;
+import com.netflix.iceberg.parquet.ParquetValueWriters.PrimitiveWriter;
+import com.netflix.iceberg.parquet.ParquetValueWriters.RepeatedKeyValueWriter;
+import com.netflix.iceberg.parquet.ParquetValueWriters.RepeatedWriter;
+import com.netflix.iceberg.types.TypeUtil;
+import org.apache.parquet.column.ColumnDescriptor;
+import org.apache.parquet.io.api.Binary;
+import org.apache.parquet.schema.DecimalMetadata;
+import org.apache.parquet.schema.GroupType;
+import org.apache.parquet.schema.MessageType;
+import org.apache.parquet.schema.PrimitiveType;
+import org.apache.parquet.schema.Type;
+import org.apache.spark.sql.catalyst.InternalRow;
+import org.apache.spark.sql.catalyst.util.ArrayData;
+import org.apache.spark.sql.catalyst.util.MapData;
+import org.apache.spark.sql.types.DataType;
+import org.apache.spark.sql.types.Decimal;
+import org.apache.spark.unsafe.types.UTF8String;
+import java.math.BigDecimal;
+import java.math.BigInteger;
+import java.util.Iterator;
+import java.util.List;
+import java.util.Map;
+import java.util.NoSuchElementException;
+
+import static com.netflix.iceberg.parquet.ParquetValueWriters.option;
+import static com.netflix.iceberg.spark.SparkSchemaUtil.convert;
+
+public class SparkParquetWriters {
+  private SparkParquetWriters() {
+  }
+
+  @SuppressWarnings("unchecked")
+  public static <T> ParquetValueWriter<T> buildWriter(Schema schema, MessageType type) {
+    return (ParquetValueWriter<T>) ParquetTypeVisitor.visit(type, new WriteBuilder(schema, type));
+  }
+
+  private static class WriteBuilder extends ParquetTypeVisitor<ParquetValueWriter<?>> {
+    private final Schema schema;
+    private final MessageType type;
+
+    WriteBuilder(Schema schema, MessageType type) {
+      this.schema = schema;
+      this.type = type;
+    }
+
+    @Override
+    public ParquetValueWriter<?> message(MessageType message,
+                                         List<ParquetValueWriter<?>> fieldWriters) {
+      return struct(message.asGroupType(), fieldWriters);
+    }
+
+    @Override
+    public ParquetValueWriter<?> struct(GroupType struct,
+                                        List<ParquetValueWriter<?>> fieldWriters) {
+      List<Type> fields = struct.getFields();
+      List<ParquetValueWriter<?>> writers = Lists.newArrayListWithExpectedSize(fieldWriters.size());
+      List<DataType> sparkTypes = Lists.newArrayList();
+      for (int i = 0; i < fields.size(); i += 1) {
+        Type fieldType = struct.getType(i);
+        int fieldD = type.getMaxDefinitionLevel(path(fieldType.getName()));
+        writers.add(option(fieldType, fieldD, fieldWriters.get(i)));
+        sparkTypes.add(convert(schema.findType(fieldType.getId().intValue())));
+      }
+
+      return new InternalRowWriter(writers, sparkTypes);
+    }
+
+    @Override
+    public ParquetValueWriter<?> list(GroupType array, ParquetValueWriter<?> elementWriter) {
+      GroupType repeated = array.getFields().get(0).asGroupType();
+      String[] repeatedPath = currentPath();
+
+      int repeatedD = type.getMaxDefinitionLevel(repeatedPath);
+      int repeatedR = type.getMaxRepetitionLevel(repeatedPath);
+
+      org.apache.parquet.schema.Type elementType = repeated.getType(0);
+      int elementD = type.getMaxDefinitionLevel(path(elementType.getName()));
+
+      DataType elementSparkType = convert(schema.findType(elementType.getId().intValue()));
+
+      return new ArrayDataWriter<>(repeatedD, repeatedR,
+          option(elementType, elementD, elementWriter),
+          elementSparkType);
+    }
+
+    @Override
+    public ParquetValueWriter<?> map(GroupType map,
+                                     ParquetValueWriter<?> keyWriter,
+                                     ParquetValueWriter<?> valueWriter) {
+      GroupType repeatedKeyValue = map.getFields().get(0).asGroupType();
+      String[] repeatedPath = currentPath();
+
+      int repeatedD = type.getMaxDefinitionLevel(repeatedPath);
+      int repeatedR = type.getMaxRepetitionLevel(repeatedPath);
+
+      org.apache.parquet.schema.Type keyType = repeatedKeyValue.getType(0);
+      int keyD = type.getMaxDefinitionLevel(path(keyType.getName()));
+      DataType keySparkType = convert(schema.findType(keyType.getId().intValue()));
+      org.apache.parquet.schema.Type valueType = repeatedKeyValue.getType(1);
+      int valueD = type.getMaxDefinitionLevel(path(valueType.getName()));
+      DataType valueSparkType = convert(schema.findType(valueType.getId().intValue()));
+
+      return new MapDataWriter<>(repeatedD, repeatedR,
+          option(keyType, keyD, keyWriter), option(valueType, valueD, valueWriter),
+          keySparkType, valueSparkType);
+    }
+
+    @Override
+    public ParquetValueWriter<?> primitive(PrimitiveType primitive) {
+      ColumnDescriptor desc = type.getColumnDescription(currentPath());
+
+      if (primitive.getOriginalType() != null) {
+        switch (primitive.getOriginalType()) {
+          case ENUM:
+          case JSON:
+          case UTF8:
+            return utf8Strings(desc);
+          case DATE:
+          case INT_8:
+          case INT_16:
+          case INT_32:
+          case INT_64:
 
 Review comment:
   I realize that INT96 is deprecated as per https://issues.apache.org/jira/browse/PARQUET-323 and don't want to encourage people using it in Iceberg but if people do want to re-write data with INT96 rows into iceberg (as INT64)  would we run into this code? If so should we not handle it by truncating INT96 to INT64? 

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