org.datacleaner.spark.functions.ValuesToInputRowFunction Maven / Gradle / Ivy
/**
* DataCleaner (community edition)
* Copyright (C) 2014 Neopost - Customer Information Management
*
* This copyrighted material is made available to anyone wishing to use, modify,
* copy, or redistribute it subject to the terms and conditions of the GNU
* Lesser General Public License, as published by the Free Software Foundation.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY
* or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License
* for more details.
*
* You should have received a copy of the GNU Lesser General Public License
* along with this distribution; if not, write to:
* Free Software Foundation, Inc.
* 51 Franklin Street, Fifth Floor
* Boston, MA 02110-1301 USA
*/
package org.datacleaner.spark.functions;
import java.util.List;
import org.apache.metamodel.schema.Table;
import org.apache.spark.api.java.function.Function;
import org.datacleaner.api.InputColumn;
import org.datacleaner.api.InputRow;
import org.datacleaner.data.MockInputRow;
import org.datacleaner.spark.SparkJobContext;
import scala.Tuple2;
/**
* Mapper function that changes takes Object arrays representing physical
* records into the format of an {@link InputRow}.
*
* Currently this is implemented very strictly by just investigating the column
* indices of the job's source columns.
*
* It is assumed that the job is based on a single source {@link Table}.
*/
public class ValuesToInputRowFunction implements Function, InputRow> {
private static final long serialVersionUID = 1L;
private final SparkJobContext _sparkJobContext;
public ValuesToInputRowFunction(final SparkJobContext sparkJobContext) {
_sparkJobContext = sparkJobContext;
}
@Override
public InputRow call(final Tuple2 tuple) throws Exception {
final Object[] values = tuple._1;
final Long rowNumber = tuple._2;
final MockInputRow inputRow = new MockInputRow(rowNumber.intValue());
final List> sourceColumns = _sparkJobContext.getAnalysisJob().getSourceColumns();
for (final InputColumn sourceColumn : sourceColumns) {
assert sourceColumn.isPhysicalColumn();
final int columnIndex = sourceColumn.getPhysicalColumn().getColumnNumber();
final Object value = values[columnIndex];
inputRow.put(sourceColumn, value);
}
return inputRow;
}
}