Java DefaultStringifier.store方法代码示例

import org.apache.hadoop.io.DefaultStringifier; //导入方法依赖的package包/类
private void configureGenericRecordExportInputFormat(Job job, String tableName)
    throws IOException {
  ConnManager connManager = context.getConnManager();
  Map<String, Integer> columnTypeInts;
  if (options.getCall() == null) {
    columnTypeInts = connManager.getColumnTypes(
        tableName,
        options.getSqlQuery());
  } else {
    columnTypeInts = connManager.getColumnTypesForProcedure(
        options.getCall());
  }
  String[] specifiedColumns = options.getColumns();
  MapWritable columnTypes = new MapWritable();
  for (Map.Entry<String, Integer> e : columnTypeInts.entrySet()) {
    String column = e.getKey();
    column = (specifiedColumns == null) ? column : options.getColumnNameCaseInsensitive(column);
    if (column != null) {
      Text columnName = new Text(column);
      Text columnType = new Text(connManager.toJavaType(tableName, column, e.getValue()));
      columnTypes.put(columnName, columnType);
    }
  }
  DefaultStringifier.store(job.getConfiguration(), columnTypes,
      AvroExportMapper.AVRO_COLUMN_TYPES_MAP);
}
 

import org.apache.hadoop.io.DefaultStringifier; //导入方法依赖的package包/类
@Override
public void checkOutputSpecs(Configuration conf, ContentSource cs) 
throws IOException {
    // check for required configuration
    if (conf.get(OUTPUT_QUERY) == null) {
        throw new IllegalArgumentException(OUTPUT_QUERY + 
        " is not specified.");
    }
    // warn against unsupported configuration
    if (conf.get(BATCH_SIZE) != null) {
        LOG.warn("Config entry for " +
                "\"mapreduce.marklogic.output.batchsize\" is not " +
                "supported for " + this.getClass().getName() + 
                " and will be ignored.");
    }
    String queryLanguage = conf.get(OUTPUT_QUERY_LANGUAGE);
    if (queryLanguage != null) {
        InternalUtilities.checkQueryLanguage(queryLanguage);
    }
    // store hosts into config system
    DefaultStringifier.store(conf, queryHosts(cs), OUTPUT_FOREST_HOST);
}
 

import org.apache.hadoop.io.DefaultStringifier; //导入方法依赖的package包/类
@Override
protected void configureInputFormat(Job job, String tableName,
    String tableClassName, String splitByCol)
    throws ClassNotFoundException, IOException {

  fileType = getInputFileType();

  super.configureInputFormat(job, tableName, tableClassName, splitByCol);

  if (fileType == FileType.AVRO_DATA_FILE) {
    LOG.debug("Configuring for Avro export");
    ConnManager connManager = context.getConnManager();
    Map<String, Integer> columnTypeInts =
      connManager.getColumnTypes(tableName, options.getSqlQuery());
    MapWritable columnTypes = new MapWritable();
    for (Map.Entry<String, Integer> e : columnTypeInts.entrySet()) {
      Text columnName = new Text(e.getKey());
      Text columnText = new Text(
          connManager.toJavaType(tableName, e.getKey(), e.getValue()));
      columnTypes.put(columnName, columnText);
    }
    DefaultStringifier.store(job.getConfiguration(), columnTypes,
        AvroExportMapper.AVRO_COLUMN_TYPES_MAP);
  }

}
 

import org.apache.hadoop.io.DefaultStringifier; //导入方法依赖的package包/类
@Override
public void checkOutputSpecs(Configuration conf, ContentSource cs)
    throws IOException {
    super.checkOutputSpecs(conf, cs);

    // store mimetypes map into config system
    DefaultStringifier.store(conf, getMimetypesMap(),
        ConfigConstants.CONF_MIMETYPES);
}
 

import org.apache.hadoop.io.DefaultStringifier; //导入方法依赖的package包/类
@Override
public void checkOutputSpecs(Configuration conf, ContentSource cs) 
throws IOException {
    // warn against unsupported configuration
    if (conf.get(BATCH_SIZE) != null) {
        LOG.warn("Config entry for " +
                "\"mapreduce.marklogic.output.batchsize\" is not " +
                "supported for " + this.getClass().getName() + 
                " and will be ignored.");
    }     
    // store hosts into config system
    DefaultStringifier.store(conf, queryHosts(cs), OUTPUT_FOREST_HOST);
}
 

import org.apache.hadoop.io.DefaultStringifier; //导入方法依赖的package包/类
@Override
public void checkOutputSpecs(Configuration conf, ContentSource cs) 
throws IOException {
    // warn against unsupported configuration
    if (conf.get(BATCH_SIZE) != null) {
        LOG.warn("Config entry for " +
                "\"mapreduce.marklogic.output.batchsize\" is not " +
                "supported for " + this.getClass().getName() + 
                " and will be ignored.");
    }      
    // store hosts into config system
    DefaultStringifier.store(conf, queryHosts(cs), OUTPUT_FOREST_HOST);
}
 

import org.apache.hadoop.io.DefaultStringifier; //导入方法依赖的package包/类
/**
 * Stores the given object in the configuration under the given dataKey
 * @param obj the object to store
 * @param conf the configuration to store the object into
 * @param dataKey the key to store the data
 */
public static<T> void storeToConf(T obj, Configuration conf, String dataKey)
  throws IOException {
  String classKey = dataKey + "._class";
  conf.set(classKey, obj.getClass().getName());
  DefaultStringifier.store(conf, obj, dataKey);
}
 

import org.apache.hadoop.io.DefaultStringifier; //导入方法依赖的package包/类
@Override
protected void configureInputFormat(Job job, String tableName,
    String tableClassName, String splitByCol)
    throws ClassNotFoundException, IOException {

  fileType = getInputFileType();

  super.configureInputFormat(job, tableName, tableClassName, splitByCol);

  if (isHCatJob) {
    SqoopHCatUtilities.configureExportInputFormat(options, job,
      context.getConnManager(), tableName, job.getConfiguration());
    return;
  } else if (fileType == FileType.AVRO_DATA_FILE) {
    LOG.debug("Configuring for Avro export");
    ConnManager connManager = context.getConnManager();
    Map<String, Integer> columnTypeInts;
    if (options.getCall() == null) {
      columnTypeInts = connManager.getColumnTypes(
        tableName,
        options.getSqlQueryRich());
    } else {
      columnTypeInts = connManager.getColumnTypesForProcedure(
        options.getCall());
    }
    MapWritable columnTypes = new MapWritable();
    for (Map.Entry<String, Integer> e : columnTypeInts.entrySet()) {
      Text columnName = new Text(e.getKey());
      Text columnText = new Text(
          connManager.toJavaType(tableName, e.getKey(), e.getValue()));
      columnTypes.put(columnName, columnText);
    }
    DefaultStringifier.store(job.getConfiguration(), columnTypes,
        AvroExportMapper.AVRO_COLUMN_TYPES_MAP);
  }

}
 

import org.apache.hadoop.io.DefaultStringifier; //导入方法依赖的package包/类
/**
 * Stores the given object in the configuration under the given dataKey.
 *
 * @param obj the object to store.
 * @param conf the configuration to store the object into.
 * @param dataKey the key to store the data.
 * @param <T> the given object class type.
 * @throws IOException when failed storing the given data in Hadoop conf.
 */
public static<T> void storeToConf(T obj, Configuration conf, String dataKey)
  throws IOException {
  String classKey = dataKey + "._class";
  conf.set(classKey, obj.getClass().getName());
  DefaultStringifier.store(conf, obj, dataKey);
}