src/test/e2e/hcatalog/udfs/java/org/apache/hcatalog/utils/SumNumbers.java

/**
 * 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.hcatalog.utils;

import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.DoubleWritable;
import org.apache.hadoop.io.FloatWritable;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.io.Writable;
import org.apache.hadoop.io.WritableComparable;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
import org.apache.hadoop.util.GenericOptionsParser;
import org.apache.hcatalog.common.HCatConstants;
import org.apache.hcatalog.data.HCatRecord;
import org.apache.hcatalog.mapreduce.HCatInputFormat;
import org.apache.hcatalog.mapreduce.InputJobInfo;

/**
 * This is a map reduce test for testing hcat which goes against the "numbers"
 * table. It performs a group by on the first column and a SUM operation on the
 * other columns. This is to simulate a typical operation in a map reduce program
 * to test that hcat hands the right data to the map reduce program
 *
 * Usage: hadoop jar sumnumbers <serveruri> <output dir> <-libjars hive-hcat jar>
 The <tab|ctrla> argument controls the output delimiter
 The hcat jar location should be specified as file://<full path to jar>
 */
public class SumNumbers {

    private static final String NUMBERS_TABLE_NAME = "numbers";
    private static final String TAB = "\t";

    public static class SumMapper
        extends Mapper<WritableComparable, HCatRecord, IntWritable, SumNumbers.ArrayWritable> {

        IntWritable intnum1000;
        // though id is given as a Short by hcat, the map will emit it as an
        // IntWritable so we can just sum in the reduce
        IntWritable id;

        // though intnum5 is handed as a Byte by hcat, the map() will emit it as
        // an IntWritable so we can just sum in the reduce
        IntWritable intnum5;
        IntWritable intnum100;
        IntWritable intnum;
        LongWritable longnum;
        FloatWritable floatnum;
        DoubleWritable doublenum;

        @Override
        protected void map(WritableComparable key, HCatRecord value,
                           org.apache.hadoop.mapreduce.Mapper<WritableComparable, HCatRecord,
                               IntWritable, SumNumbers.ArrayWritable>.Context context)
            throws IOException, InterruptedException {
            intnum1000 = new IntWritable((Integer) value.get(0));
            id = new IntWritable((Short) value.get(1));
            intnum5 = new IntWritable(((Byte) value.get(2)));
            intnum100 = new IntWritable(((Integer) value.get(3)));
            intnum = new IntWritable((Integer) value.get(4));
            longnum = new LongWritable((Long) value.get(5));
            floatnum = new FloatWritable((Float) value.get(6));
            doublenum = new DoubleWritable((Double) value.get(7));
            SumNumbers.ArrayWritable outputValue = new SumNumbers.ArrayWritable(id,
                intnum5, intnum100, intnum, longnum, floatnum, doublenum);
            context.write(intnum1000, outputValue);

        }
    }

    public static class SumReducer extends Reducer<IntWritable, SumNumbers.ArrayWritable,
        LongWritable, Text> {


        LongWritable dummyLong = null;

        @Override
        protected void reduce(IntWritable key, java.lang.Iterable<ArrayWritable>
            values, org.apache.hadoop.mapreduce.Reducer<IntWritable, ArrayWritable, LongWritable, Text>.Context context)
            throws IOException, InterruptedException {
            String output = key.toString() + TAB;
            Long sumid = 0l;
            Long sumintnum5 = 0l;
            Long sumintnum100 = 0l;
            Long sumintnum = 0l;
            Long sumlongnum = 0l;
            Float sumfloatnum = 0.0f;
            Double sumdoublenum = 0.0;
            for (ArrayWritable value : values) {
                sumid += value.id.get();
                sumintnum5 += value.intnum5.get();
                sumintnum100 += value.intnum100.get();
                sumintnum += value.intnum.get();
                sumlongnum += value.longnum.get();
                sumfloatnum += value.floatnum.get();
                sumdoublenum += value.doublenum.get();
            }
            output += sumid + TAB;
            output += sumintnum5 + TAB;
            output += sumintnum100 + TAB;
            output += sumintnum + TAB;
            output += sumlongnum + TAB;
            output += sumfloatnum + TAB;
            output += sumdoublenum + TAB;
            context.write(dummyLong, new Text(output));
        }
    }

    public static void main(String[] args) throws Exception {
        Configuration conf = new Configuration();
        args = new GenericOptionsParser(conf, args).getRemainingArgs();
        String[] otherArgs = new String[4];
        int j = 0;
        for (int i = 0; i < args.length; i++) {
            if (args[i].equals("-libjars")) {
                // generic options parser doesn't seem to work!
                conf.set("tmpjars", args[i + 1]);
                i = i + 1; // skip it , the for loop will skip its value
            } else {
                otherArgs[j++] = args[i];
            }
        }
        if (otherArgs.length != 4) {
            System.err.println("Usage: hadoop jar sumnumbers <serveruri> <output dir> <-libjars hive-hcat jar>\n" +
                "The <tab|ctrla> argument controls the output delimiter.\n" +
                "The hcat jar location should be specified as file://<full path to jar>\n");
            System.exit(2);
        }
        String serverUri = otherArgs[0];
        String tableName = NUMBERS_TABLE_NAME;
        String outputDir = otherArgs[1];
        String dbName = "default";

        String principalID = System.getProperty(HCatConstants.HCAT_METASTORE_PRINCIPAL);
        if (principalID != null)
            conf.set(HCatConstants.HCAT_METASTORE_PRINCIPAL, principalID);
        Job job = new Job(conf, "sumnumbers");
        HCatInputFormat.setInput(job, InputJobInfo.create(
            dbName, tableName, null));
        // initialize HCatOutputFormat

        job.setInputFormatClass(HCatInputFormat.class);
        job.setOutputFormatClass(TextOutputFormat.class);
        job.setJarByClass(SumNumbers.class);
        job.setMapperClass(SumMapper.class);
        job.setReducerClass(SumReducer.class);
        job.setMapOutputKeyClass(IntWritable.class);
        job.setMapOutputValueClass(ArrayWritable.class);
        job.setOutputKeyClass(LongWritable.class);
        job.setOutputValueClass(Text.class);
        FileOutputFormat.setOutputPath(job, new Path(outputDir));
        System.exit(job.waitForCompletion(true) ? 0 : 1);
    }

    public static class ArrayWritable implements Writable {

        // though id is given as a Short by hcat, the map will emit it as an
        // IntWritable so we can just sum in the reduce
        IntWritable id;

        // though intnum5 is handed as a Byte by hcat, the map() will emit it as
        // an IntWritable so we can just sum in the reduce
        IntWritable intnum5;

        IntWritable intnum100;
        IntWritable intnum;
        LongWritable longnum;
        FloatWritable floatnum;
        DoubleWritable doublenum;

        /**
         *
         */
        public ArrayWritable() {
            id = new IntWritable();
            intnum5 = new IntWritable();
            intnum100 = new IntWritable();
            intnum = new IntWritable();
            longnum = new LongWritable();
            floatnum = new FloatWritable();
            doublenum = new DoubleWritable();
        }


        /**
         * @param id
         * @param intnum5
         * @param intnum100
         * @param intnum
         * @param longnum
         * @param floatnum
         * @param doublenum
         */
        public ArrayWritable(IntWritable id, IntWritable intnum5,
                             IntWritable intnum100, IntWritable intnum, LongWritable longnum,
                             FloatWritable floatnum, DoubleWritable doublenum) {
            this.id = id;
            this.intnum5 = intnum5;
            this.intnum100 = intnum100;
            this.intnum = intnum;
            this.longnum = longnum;
            this.floatnum = floatnum;
            this.doublenum = doublenum;
        }


        @Override
        public void readFields(DataInput in) throws IOException {
            id.readFields(in);
            intnum5.readFields(in);
            intnum100.readFields(in);
            intnum.readFields(in);
            longnum.readFields(in);
            floatnum.readFields(in);
            doublenum.readFields(in);
        }

        @Override
        public void write(DataOutput out) throws IOException {
            id.write(out);
            intnum5.write(out);
            intnum100.write(out);
            intnum.write(out);
            longnum.write(out);
            floatnum.write(out);
            doublenum.write(out);

        }

    }
}