content: /*
   * 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 com.aliyun.odps.mapred.local.bugfix;
  
  import java.io.IOException;
  import java.util.Iterator;
  
  import org.junit.Before;
  import org.junit.Test;
  
  import com.aliyun.odps.counter.Counter;
  import com.aliyun.odps.data.Record;
  import com.aliyun.odps.data.TableInfo;
  import com.aliyun.odps.mapred.JobClient;
  import com.aliyun.odps.mapred.MapperBase;
  import com.aliyun.odps.mapred.ReducerBase;
  import com.aliyun.odps.mapred.conf.JobConf;
  import com.aliyun.odps.mapred.local.utils.TestUtils;
  import com.aliyun.odps.mapred.utils.InputUtils;
  import com.aliyun.odps.mapred.utils.OutputUtils;
  
  /**
   * This is an example ODPS Map/Reduce application. It reads the input table, map
   * each column into words and counts them. The output is a locally sorted list
   * of words and the count of how often they occurred.
   * <p>
   * To run: jar -libjars mapreduce-examples.jar -classpath
   * clt/lib/mapreduce-examples.jar com.aliyun.odps.mapreduce.examples.WordCount
   * <i>in-tbl</i> <i>out-tbl</i>
   */
  public class GetTableInfoTest {
  
    @Before
    public void setUp() throws Exception {
      TestUtils.setEnvironment(TestUtils.odps_test_mrtask);
    }
  
    /**
     * Counts the words in each record. For each record, emit each column as
     * (<b>word</b>, <b>1</b>).
     */
    public static class TokenizerMapper extends MapperBase {
  
      Counter gCnt;
      Record result;
  
      @Override
      public void setup(TaskContext context) throws IOException {
  
        help(context, "mapSetup");
  
        gCnt = context.getCounter("MyCounters", "global_counts");
      }
  
      @Override
      public void map(long recordNum, Record record, TaskContext context) throws IOException {
        help(context, "map");
      }
  
      public void help(TaskContext context, String stage) throws IOException {
        // columns=project:STRING,table:STRING,type:STRING,colNum:BIGINT,cols:STRING,stage:STRING
  
        Record result = context.createOutputRecord();
        TableInfo info = context.getInputTableInfo();
        result.set(0, info.toString());
        result.set(1, "in");
        String[] cols = info.getCols();
        result.set(2, cols.length);
  
        String colNames = "";
        for (int i = 0; i < cols.length; i++) {
          if (colNames.length() > 0) {
            colNames += ",";
          }
          colNames += cols[i];
        }
  
        result.set(3, colNames);
        result.set(4, stage);
  
        context.write(result);
  
        TableInfo[] outputTableInfos = context.getOutputTableInfo();
        for (int i = 0; i < outputTableInfos.length; i++) {
          info = outputTableInfos[i];
  
          result.set(0, info.toString());
          result.set(1, "out");
          cols = info.getCols();
          result.set(2, cols.length);
  
          colNames = "";
          for (i = 0; i < cols.length; i++) {
            if (colNames.length() > 0) {
              colNames += ",";
            }
            colNames += cols[i];
          }
  
          result.set(3, colNames);
          result.set(4, stage);
  
          context.write(result);
        }
  
      }
    }
  
    /**
     * A combiner class that combines map output by sum them.
     */
    public static class SumCombiner extends ReducerBase {
  
      private Record count;
  
      @Override
      public void setup(TaskContext context) throws IOException {
        count = context.createMapOutputValueRecord();
      }
  
      @Override
      public void reduce(Record key, Iterator<Record> values, TaskContext context)
          throws IOException {
        long c = 0;
        while (values.hasNext()) {
          Record val = values.next();
          c += (Long) val.get(0);
        }
        count.set(0, c);
        context.write(key, count);
      }
    }
  
    /**
     * A reducer class that just emits the sum of the input values.
     */
    public static class SumReducer extends ReducerBase {
  
      @Override
      public void setup(TaskContext context) throws IOException {
  
      }
  
      @Override
      public void reduce(Record key, Iterator<Record> values, TaskContext context)
          throws IOException {
  
      }
    }
  
    @Test
    public void test() throws Exception {
      String[] args = new String[4];
      args[0] = "l_ss";
      args[1] = "l_p_ss";
      args[2] = "getTableInfo_out";
  
      JobConf job = new JobConf();
      job.setMapperClass(TokenizerMapper.class);
      job.setCombinerClass(SumCombiner.class);
      job.setReducerClass(SumReducer.class);
      job.setNumReduceTasks(0);
  
      InputUtils.addTable(TableInfo.builder().tableName(args[0]).build(), job);
      InputUtils.addTable(TableInfo.builder().tableName(args[1]).partSpec("p1=1/p2=2").build(), job);
      InputUtils.addTable(TableInfo.builder().tableName(args[1]).partSpec("p1=1").build(), job);
      OutputUtils.addTable(TableInfo.builder().tableName(args[2]).build(), job);
  
      JobClient.runJob(job);
    }
  
  }
  