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A table format for huge analytic datasets
/*
* 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.spark.data;
import java.math.BigDecimal;
import java.util.List;
import java.util.Map;
import org.apache.iceberg.orc.OrcValueReader;
import org.apache.iceberg.orc.OrcValueReaders;
import org.apache.iceberg.relocated.com.google.common.base.Preconditions;
import org.apache.iceberg.relocated.com.google.common.collect.Lists;
import org.apache.iceberg.types.Types;
import org.apache.orc.storage.ql.exec.vector.BytesColumnVector;
import org.apache.orc.storage.ql.exec.vector.ColumnVector;
import org.apache.orc.storage.ql.exec.vector.DecimalColumnVector;
import org.apache.orc.storage.ql.exec.vector.ListColumnVector;
import org.apache.orc.storage.ql.exec.vector.MapColumnVector;
import org.apache.orc.storage.ql.exec.vector.TimestampColumnVector;
import org.apache.orc.storage.serde2.io.HiveDecimalWritable;
import org.apache.spark.sql.catalyst.InternalRow;
import org.apache.spark.sql.catalyst.expressions.GenericInternalRow;
import org.apache.spark.sql.catalyst.util.ArrayBasedMapData;
import org.apache.spark.sql.catalyst.util.ArrayData;
import org.apache.spark.sql.catalyst.util.GenericArrayData;
import org.apache.spark.sql.catalyst.util.MapData;
import org.apache.spark.sql.types.Decimal;
import org.apache.spark.unsafe.types.UTF8String;
public class SparkOrcValueReaders {
private SparkOrcValueReaders() {
}
public static OrcValueReader utf8String() {
return StringReader.INSTANCE;
}
public static OrcValueReader timestampTzs() {
return TimestampTzReader.INSTANCE;
}
public static OrcValueReader decimals(int precision, int scale) {
if (precision <= Decimal.MAX_LONG_DIGITS()) {
return new SparkOrcValueReaders.Decimal18Reader(precision, scale);
} else if (precision <= 38) {
return new SparkOrcValueReaders.Decimal38Reader(precision, scale);
} else {
throw new IllegalArgumentException("Invalid precision: " + precision);
}
}
static OrcValueReader> struct(
List> readers, Types.StructType struct, Map idToConstant) {
return new StructReader(readers, struct, idToConstant);
}
static OrcValueReader> array(OrcValueReader> elementReader) {
return new ArrayReader(elementReader);
}
static OrcValueReader> map(OrcValueReader> keyReader, OrcValueReader> valueReader) {
return new MapReader(keyReader, valueReader);
}
private static class ArrayReader implements OrcValueReader {
private final OrcValueReader> elementReader;
private ArrayReader(OrcValueReader> elementReader) {
this.elementReader = elementReader;
}
@Override
public ArrayData nonNullRead(ColumnVector vector, int row) {
ListColumnVector listVector = (ListColumnVector) vector;
int offset = (int) listVector.offsets[row];
int length = (int) listVector.lengths[row];
List
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