org.apache.hadoop.mapreduce.lib.db.FloatSplitter.java Source code

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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 org.apache.hadoop.mapreduce.lib.db;

import java.sql.ResultSet;
import java.sql.SQLException;
import java.util.ArrayList;
import java.util.List;

import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import org.apache.hadoop.classification.InterfaceAudience;
import org.apache.hadoop.classification.InterfaceStability;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.mapreduce.InputSplit;
import org.apache.hadoop.mapreduce.MRJobConfig;

/**
 * Implement DBSplitter over floating-point values.
 */
@InterfaceAudience.Public
@InterfaceStability.Evolving
public class FloatSplitter implements DBSplitter {

    private static final Logger LOG = LoggerFactory.getLogger(FloatSplitter.class);

    private static final double MIN_INCREMENT = 10000 * Double.MIN_VALUE;

    public List<InputSplit> split(Configuration conf, ResultSet results, String colName) throws SQLException {

        LOG.warn("Generating splits for a floating-point index column. Due to the");
        LOG.warn("imprecise representation of floating-point values in Java, this");
        LOG.warn("may result in an incomplete import.");
        LOG.warn("You are strongly encouraged to choose an integral split column.");

        List<InputSplit> splits = new ArrayList<InputSplit>();

        if (results.getString(1) == null && results.getString(2) == null) {
            // Range is null to null. Return a null split accordingly.
            splits.add(
                    new DataDrivenDBInputFormat.DataDrivenDBInputSplit(colName + " IS NULL", colName + " IS NULL"));
            return splits;
        }

        double minVal = results.getDouble(1);
        double maxVal = results.getDouble(2);

        // Use this as a hint. May need an extra task if the size doesn't
        // divide cleanly.
        int numSplits = conf.getInt(MRJobConfig.NUM_MAPS, 1);
        double splitSize = (maxVal - minVal) / (double) numSplits;

        if (splitSize < MIN_INCREMENT) {
            splitSize = MIN_INCREMENT;
        }

        String lowClausePrefix = colName + " >= ";
        String highClausePrefix = colName + " < ";

        double curLower = minVal;
        double curUpper = curLower + splitSize;

        while (curUpper < maxVal) {
            splits.add(new DataDrivenDBInputFormat.DataDrivenDBInputSplit(
                    lowClausePrefix + Double.toString(curLower), highClausePrefix + Double.toString(curUpper)));

            curLower = curUpper;
            curUpper += splitSize;
        }

        // Catch any overage and create the closed interval for the last split.
        if (curLower <= maxVal || splits.size() == 1) {
            splits.add(new DataDrivenDBInputFormat.DataDrivenDBInputSplit(
                    lowClausePrefix + Double.toString(curLower), colName + " <= " + Double.toString(maxVal)));
        }

        if (results.getString(1) == null || results.getString(2) == null) {
            // At least one extrema is null; add a null split.
            splits.add(
                    new DataDrivenDBInputFormat.DataDrivenDBInputSplit(colName + " IS NULL", colName + " IS NULL"));
        }

        return splits;
    }
}