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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
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* Unless required by applicable law or agreed to in writing, software
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package com.netease.arctic.spark.reader;
import com.netease.arctic.hive.io.reader.AbstractAdaptHiveArcticDataReader;
import com.netease.arctic.io.ArcticFileIO;
import com.netease.arctic.spark.SparkInternalRowWrapper;
import com.netease.arctic.spark.util.ArcticSparkUtils;
import com.netease.arctic.table.PrimaryKeySpec;
import com.netease.arctic.shade.org.apache.iceberg.Schema;
import com.netease.arctic.shade.org.apache.iceberg.StructLike;
import com.netease.arctic.shade.org.apache.iceberg.parquet.ParquetValueReader;
import com.netease.arctic.shade.org.apache.iceberg.spark.SparkSchemaUtil;
import com.netease.arctic.shade.org.apache.parquet.schema.MessageType;
import com.netease.arctic.shade.org.apache.spark.sql.catalyst.InternalRow;
import org.apache.spark.sql.types.StructType;
import java.util.Map;
import java.util.function.Function;
public class ArcticSparkKeyedDataReader extends AbstractAdaptHiveArcticDataReader {
public ArcticSparkKeyedDataReader(
ArcticFileIO fileIO,
Schema tableSchema,
Schema projectedSchema,
PrimaryKeySpec primaryKeySpec,
String nameMapping,
boolean caseSensitive) {
super(fileIO, tableSchema, projectedSchema, primaryKeySpec, nameMapping, caseSensitive,
ArcticSparkUtils::convertConstant, false);
}
@Override
protected Function> getNewReaderFunction(
Schema projectSchema,
Map idToConstant) {
return fileSchema -> SparkParquetReaders.buildReader(projectSchema, fileSchema, idToConstant);
}
@Override
protected Function> toStructLikeFunction() {
return schema -> {
final StructType structType = SparkSchemaUtil.convert(schema);
return row -> new SparkInternalRowWrapper(structType).wrap(row);
};
}
}
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