Java AvroOutputFormat类代码示例

import org.apache.avro.mapred.AvroOutputFormat; //导入依赖的package包/类
@Override
public OutputFormat<NullWritable, Object> getOutputFormat()
    throws IOException {

  /**
   * Hadoop output format for AvroStorage.
   */
  class AvroStorageOutputFormat extends
    FileOutputFormat<NullWritable, Object> {

    @Override
    public RecordWriter<NullWritable, Object> getRecordWriter(
        final TaskAttemptContext tc) throws IOException,
    InterruptedException {

      return new AvroRecordWriter(
          // avroStorageOutputFormatSchema,
          getDefaultWorkFile(tc, AvroOutputFormat.EXT),
          tc.getConfiguration());

    }
  }

  return new AvroStorageOutputFormat();

}
 

import org.apache.avro.mapred.AvroOutputFormat; //导入依赖的package包/类
@Test
public void testAvroAsTextFmt() throws IOException {

    AvroAsTextOutputFormat outfmt = new AvroAsTextOutputFormat();
    FileOutputFormat.setOutputPath(defaultConf, file);
    RecordWriter<Text, NullWritable> writer = outfmt.getRecordWriter(file.getFileSystem(defaultConf),
            defaultConf, fname, new dummyReporter());

    writer.write(new Text(tsv), NullWritable.get());
    writer.close(null);

    FileInputFormat.setInputPaths(defaultConf, FileOutputFormat.getTaskOutputPath(defaultConf, fname +
        AvroOutputFormat.EXT));
    AvroAsTextInputFormat informat = new AvroAsTextInputFormat();
    RecordReader<Text, Text> reader = informat.getRecordReader(informat.getSplits(defaultConf, 1)[0],
            defaultConf, new dummyReporter());

    Text k = new Text();
    Text v = new Text();

    reader.next(k, v);
    Assert.assertEquals("read back tsv", tsv, k.toString() + "\t" + v.toString());
}
 

import org.apache.avro.mapred.AvroOutputFormat; //导入依赖的package包/类
@Test
public void testAvroAsJsonFmt() throws IOException {

    AvroAsJsonOutputFormat outfmt = new AvroAsJsonOutputFormat();
    FileOutputFormat.setOutputPath(defaultConf, file2);
            RecordWriter<Text, NullWritable> writer = outfmt.getRecordWriter(file2.getFileSystem(defaultConf),
            defaultConf, fname2, new dummyReporter());

    writer.write(new Text(json), NullWritable.get());
    writer.close(null);

    FileInputFormat.setInputPaths(defaultConf, FileOutputFormat.getTaskOutputPath(defaultConf, fname2 +
        AvroOutputFormat.EXT));
    AvroAsJsonInputFormat informat = new AvroAsJsonInputFormat();
    RecordReader<Text, Text> reader = informat.getRecordReader(informat.getSplits(defaultConf, 1)[0],
            defaultConf, new dummyReporter());

    Text k = new Text();
    Text v = new Text();

    reader.next(k, v);
    ObjectMapper mapper = new ObjectMapper();
    JsonNode n0 = mapper.readTree(k.toString());
    JsonNode n1 = mapper.readTree(json);
    Assert.assertEquals("read back json", n0, n1);
}
 

import org.apache.avro.mapred.AvroOutputFormat; //导入依赖的package包/类
/**
 * The MapReduce driver - setup and launch the job.
 *
 * @param args the command-line arguments
 * @return the process exit code
 * @throws Exception if something goes wrong
 */
public int run(final String[] args) throws Exception {

  Cli cli = Cli.builder().setArgs(args).addOptions(CliCommonOpts.MrIoOpts.values()).build();
  int result = cli.runCmd();

  if (result != 0) {
    return result;
  }

  Path inputPath = new Path(cli.getArgValueAsString(CliCommonOpts.MrIoOpts.INPUT));
  Path outputPath = new Path(cli.getArgValueAsString(CliCommonOpts.MrIoOpts.OUTPUT));

  Configuration conf = super.getConf();

  JobConf job = new JobConf(conf);
  job.setJarByClass(BloomFilterCreator.class);

  job.set(AvroJob.OUTPUT_SCHEMA, AvroBytesRecord.SCHEMA.toString());
  job.set(AvroJob.OUTPUT_CODEC, SnappyCodec.class.getName());

  job.setInputFormat(KeyValueTextInputFormat.class);
  job.setOutputFormat(AvroOutputFormat.class);

  job.setMapperClass(Map.class);
  job.setReducerClass(Reduce.class);

  job.setMapOutputKeyClass(NullWritable.class);
  job.setMapOutputValueClass(BloomFilter.class);

  job.setOutputKeyClass(NullWritable.class);
  job.setOutputValueClass(BloomFilter.class);

  FileInputFormat.setInputPaths(job, inputPath);
  FileOutputFormat.setOutputPath(job, outputPath);

  return JobClient.runJob(job).isSuccessful() ? 0 : 1;
}
 

import org.apache.avro.mapred.AvroOutputFormat; //导入依赖的package包/类
@Override
public RecordWriter<Text, Text> getRecordWriter(FileSystem ignored, JobConf job, String name,
    Progressable progress) throws IOException {
  if (schema == null) {
    SchemaLoader loader = new SchemaLoader(job);
    this.schema = loader.load(
      job.get(SCHEMA_LITERAL), job.get(SCHEMA_URL), job.get(SCHEMA_TYPE_NAME));
    this.converter = new JsonConverter(schema);
    this.readKey = job.getBoolean(READ_KEY, true);
  }
  
  DataFileWriter<GenericRecord> writer = new DataFileWriter<GenericRecord>(
      new GenericDatumWriter<GenericRecord>(schema));
  if (getCompressOutput(job)) {
    int level = job.getInt(AvroOutputFormat.DEFLATE_LEVEL_KEY, AvroOutputFormat.DEFAULT_DEFLATE_LEVEL);
    String codecName = job.get(AvroJob.CONF_OUTPUT_CODEC, 
        org.apache.avro.file.DataFileConstants.DEFLATE_CODEC);
    CodecFactory codec = codecName.equals(DataFileConstants.DEFLATE_CODEC)
        ? CodecFactory.deflateCodec(level)
        : CodecFactory.fromString(codecName);
    writer.setCodec(codec);
  }
  writer.setSyncInterval(job.getInt(AvroOutputFormat.SYNC_INTERVAL_KEY,
      DataFileConstants.DEFAULT_SYNC_INTERVAL));
  
  Path path = FileOutputFormat.getTaskOutputPath(job, name + AvroOutputFormat.EXT);
  writer.create(schema, path.getFileSystem(job).create(path));
  
  return new AvroAsJSONRecordWriter(writer, converter, readKey);
}
 

import org.apache.avro.mapred.AvroOutputFormat; //导入依赖的package包/类
/**
 * Run an avro hadoop job with job conf
 * @param conf
 * @throws Exception
 */
public static void runAvroJob(JobConf conf) throws Exception
{
  Path[] inputPaths = AvroInputFormat.getInputPaths(conf);
  _log.info("Running hadoop job with input paths:");
  for (Path inputPath : inputPaths)
  {
    _log.info(inputPath);
  }
  _log.info("Output path="+AvroOutputFormat.getOutputPath(conf));
  Job job = new Job(conf);
  job.setJarByClass(AvroUtils.class);
  job.waitForCompletion(true);
}
 

import org.apache.avro.mapred.AvroOutputFormat; //导入依赖的package包/类
/**
 * The MapReduce driver - setup and launch the job.
 *
 * @param args the command-line arguments
 * @return the process exit code
 * @throws Exception if something goes wrong
 */
public int run(final String[] args) throws Exception {

  Cli cli = Cli.builder().setArgs(args).addOptions(CliCommonOpts.OutputFileOption.values()).build();
  int result = cli.runCmd();

  if (result != 0) {
    return result;
  }

  Path output = new Path(cli.getArgValueAsString(CliCommonOpts.OutputFileOption.OUTPUT));

  Configuration conf = super.getConf();

  DBConfiguration.configureDB(conf, "com.mysql.jdbc.Driver",
      "jdbc:mysql://localhost/sqoop_test" +
          "?user=hip_sqoop_user&password=password");

  JobConf job = new JobConf(conf);
  job.setJarByClass(DBImportMapReduce.class);

  job.setInputFormat(DBInputFormat.class);
  job.setOutputFormat(AvroOutputFormat.class);
  AvroJob.setOutputSchema(job, Stock.SCHEMA$);
  job.set(AvroJob.OUTPUT_CODEC, SnappyCodec.class.getName());

  job.setMapperClass(Map.class);

  job.setNumMapTasks(4);
  job.setNumReduceTasks(0);

  job.setMapOutputKeyClass(AvroWrapper.class);
  job.setMapOutputValueClass(NullWritable.class);

  job.setOutputKeyClass(AvroWrapper.class);
  job.setOutputValueClass(NullWritable.class);

  FileOutputFormat.setOutputPath(job, output);

  DBInputFormat.setInput(
      job,
      StockDbWritable.class,
      "select * from stocks",
      "SELECT COUNT(id) FROM stocks");

  RunningJob runningJob = JobClient.runJob(job);

  return runningJob.isSuccessful() ? 0 : 1;
}
 

import org.apache.avro.mapred.AvroOutputFormat; //导入依赖的package包/类
/**
 * Sets up various standard settings in the JobConf. You probably don't want to mess with this.
 * 
 * @return A configured JobConf.
 * @throws IOException
 * @throws URISyntaxException 
 */
protected  JobConf createJobConf() throws IOException, URISyntaxException
{
  JobConf conf = new JobConf();
  
  conf.setJobName(getJobId());
  conf.setInputFormat(AvroInputFormat.class);
  conf.setOutputFormat(AvroOutputFormat.class);
  
  AvroOutputFormat.setDeflateLevel(conf, 9);
  
  String hadoop_ugi = _config.getString("hadoop.job.ugi", null);
  if (hadoop_ugi != null)
  {
      conf.set("hadoop.job.ugi", hadoop_ugi);
  }
  if (_config.getBoolean("is.local", false))
  {
    conf.set("mapred.job.tracker", "local");
    conf.set("fs.default.name", "file:///");
    conf.set("mapred.local.dir", "/tmp/map-red");

    _log.info("Running locally, no hadoop jar set.");
  }
  
  // set JVM options if present
  if (_config.containsKey("mapred.child.java.opts"))
  {
    conf.set("mapred.child.java.opts", _config.getString("mapred.child.java.opts"));
    _log.info("mapred.child.java.opts set to " + _config.getString("mapred.child.java.opts"));
  }

  if (_config.containsKey(INPUT_PATHS))
  {
    List<String> inputPathnames = _config.getStringList(INPUT_PATHS);
    for (String pathname : inputPathnames)
    {
      AvroUtils.addAllSubPaths(conf, new Path(pathname));
    }
    AvroJob.setInputSchema(conf, AvroUtils.getAvroInputSchema(conf));
  }

  if (_config.containsKey(OUTPUT_PATH))
  {
    Path path = new Path(_config.get(OUTPUT_PATH));
    AvroOutputFormat.setOutputPath(conf, path);

    if (_config.getBoolean("force.output.overwrite", false))
    {
      FileSystem fs = FileOutputFormat.getOutputPath(conf).getFileSystem(conf);
      fs.delete(FileOutputFormat.getOutputPath(conf), true);
    }
  }
  // set all hadoop configs
  for (String key : _config.keySet()) 
  {
    String lowerCase = key.toLowerCase();
    if ( lowerCase.startsWith(HADOOP_PREFIX)) 
    {
        String newKey = key.substring(HADOOP_PREFIX.length());
        conf.set(newKey, _config.get(key));
    }
  }
  return conf;
}
 

import org.apache.avro.mapred.AvroOutputFormat; //导入依赖的package包/类
/**
 * The MapReduce driver - setup and launch the job.
 *
 * @param args the command-line arguments
 * @return the process exit code
 * @throws Exception if something goes wrong
 */
public int run(final String[] args) throws Exception {


  Cli cli = Cli.builder().setArgs(args).addOptions(CliCommonOpts.MrIoOpts.values()).build();
  int result = cli.runCmd();

  if (result != 0) {
    return result;
  }

  Path inputPath = new Path(cli.getArgValueAsString(CliCommonOpts.MrIoOpts.INPUT));
  Path outputPath = new Path(cli.getArgValueAsString(CliCommonOpts.MrIoOpts.OUTPUT));

  Configuration conf = super.getConf();

  JobConf job = new JobConf(conf);
  job.setJarByClass(AvroMixedMapReduce.class);

  job.set(AvroJob.INPUT_SCHEMA, Stock.SCHEMA$.toString());
  job.set(AvroJob.OUTPUT_SCHEMA, StockAvg.SCHEMA$.toString());
  job.set(AvroJob.OUTPUT_CODEC, SnappyCodec.class.getName());

  job.setInputFormat(AvroInputFormat.class);
  job.setOutputFormat(AvroOutputFormat.class);

  job.setMapperClass(Map.class);
  job.setReducerClass(Reduce.class);

  job.setMapOutputKeyClass(Text.class);
  job.setMapOutputValueClass(DoubleWritable.class);

  job.setOutputKeyClass(Text.class);
  job.setOutputValueClass(DoubleWritable.class);

  FileInputFormat.setInputPaths(job, inputPath);
  FileOutputFormat.setOutputPath(job, outputPath);

  return JobClient.runJob(job).isSuccessful() ? 0 : 1;
}