Java DataBlockEncoding.valueOf方法代码示例

import org.apache.hadoop.hbase.io.encoding.DataBlockEncoding; //导入方法依赖的package包/类
public static HFileDataBlockEncoder createFromFileInfo(
    FileInfo fileInfo) throws IOException {
  DataBlockEncoding encoding = DataBlockEncoding.NONE;
  byte[] dataBlockEncodingType = fileInfo.get(DATA_BLOCK_ENCODING);
  if (dataBlockEncodingType != null) {
    String dataBlockEncodingStr = Bytes.toString(dataBlockEncodingType);
    try {
      encoding = DataBlockEncoding.valueOf(dataBlockEncodingStr);
    } catch (IllegalArgumentException ex) {
      throw new IOException("Invalid data block encoding type in file info: "
        + dataBlockEncodingStr, ex);
    }
  }

  if (encoding == DataBlockEncoding.NONE) {
    return NoOpDataBlockEncoder.INSTANCE;
  }
  return new HFileDataBlockEncoderImpl(encoding);
}
 

import org.apache.hadoop.hbase.io.encoding.DataBlockEncoding; //导入方法依赖的package包/类
private void parseColumnFamilyOptions(CommandLine cmd) {
  String dataBlockEncodingStr = cmd.getOptionValue(OPT_DATA_BLOCK_ENCODING);
  dataBlockEncodingAlgo = dataBlockEncodingStr == null ? null :
      DataBlockEncoding.valueOf(dataBlockEncodingStr);

  String compressStr = cmd.getOptionValue(OPT_COMPRESSION);
  compressAlgo = compressStr == null ? Compression.Algorithm.NONE :
      Compression.Algorithm.valueOf(compressStr);

  String bloomStr = cmd.getOptionValue(OPT_BLOOM);
  bloomType = bloomStr == null ? BloomType.ROW :
      BloomType.valueOf(bloomStr);

  inMemoryCF = cmd.hasOption(OPT_INMEMORY);
  if (cmd.hasOption(OPT_ENCRYPTION)) {
    cipher = Encryption.getCipher(conf, cmd.getOptionValue(OPT_ENCRYPTION));
  }

}
 

import org.apache.hadoop.hbase.io.encoding.DataBlockEncoding; //导入方法依赖的package包/类
private void createTable() throws Exception {
  deleteTable();
  LOG.info("Creating table");
  Configuration conf = util.getConfiguration();
  String encodingKey = String.format(ENCODING_KEY, this.getClass().getSimpleName());
  DataBlockEncoding blockEncoding = DataBlockEncoding.valueOf(conf.get(encodingKey, "FAST_DIFF"));
  HTableDescriptor htd = new HTableDescriptor(TABLE_NAME);
  for (byte[] cf : dataGen.getColumnFamilies()) {
    HColumnDescriptor hcd = new HColumnDescriptor(cf);
    hcd.setDataBlockEncoding(blockEncoding);
    htd.addFamily(hcd);
  }
  int serverCount = util.getHBaseClusterInterface().getClusterStatus().getServersSize();
  byte[][] splits = new RegionSplitter.HexStringSplit().split(serverCount * REGIONS_PER_SERVER);
  util.getHBaseAdmin().createTable(htd, splits);
  LOG.info("Created table");
}
 

import org.apache.hadoop.hbase.io.encoding.DataBlockEncoding; //导入方法依赖的package包/类
protected void parseColumnFamilyOptions(CommandLine cmd) {
  String dataBlockEncodingStr = cmd.getOptionValue(OPT_DATA_BLOCK_ENCODING);
  dataBlockEncodingAlgo = dataBlockEncodingStr == null ? null :
      DataBlockEncoding.valueOf(dataBlockEncodingStr);
  if (dataBlockEncodingAlgo == DataBlockEncoding.NONE && encodeInCacheOnly) {
    throw new IllegalArgumentException("-" + OPT_ENCODE_IN_CACHE_ONLY + " " +
        "does not make sense when data block encoding is not used");
  }

  String compressStr = cmd.getOptionValue(OPT_COMPRESSION);
  compressAlgo = compressStr == null ? Compression.Algorithm.NONE :
      Compression.Algorithm.valueOf(compressStr);

  String bloomStr = cmd.getOptionValue(OPT_BLOOM);
  bloomType = bloomStr == null ? null :
      StoreFile.BloomType.valueOf(bloomStr);

  inMemoryCF = cmd.hasOption(OPT_INMEMORY);
}
 

import org.apache.hadoop.hbase.io.encoding.DataBlockEncoding; //导入方法依赖的package包/类
private void parseColumnFamilyOptions(CommandLine cmd) {
  String dataBlockEncodingStr = cmd.getOptionValue(OPT_DATA_BLOCK_ENCODING);
  dataBlockEncodingAlgo = dataBlockEncodingStr == null ? null :
      DataBlockEncoding.valueOf(dataBlockEncodingStr);

  String compressStr = cmd.getOptionValue(OPT_COMPRESSION);
  compressAlgo = compressStr == null ? Compression.Algorithm.NONE :
      Compression.Algorithm.valueOf(compressStr);

  String bloomStr = cmd.getOptionValue(OPT_BLOOM);
  bloomType = bloomStr == null ? null :
      BloomType.valueOf(bloomStr);

  inMemoryCF = cmd.hasOption(OPT_INMEMORY);
  if (cmd.hasOption(OPT_ENCRYPTION)) {
    cipher = Encryption.getCipher(conf, cmd.getOptionValue(OPT_ENCRYPTION));
  }
}
 

import org.apache.hadoop.hbase.io.encoding.DataBlockEncoding; //导入方法依赖的package包/类
/**
 * Command line interface:
 * @param args
 * @throws IOException if there is a bug while reading from disk
 */
public static void main(final String[] args) throws Exception {
  Option encodingOption = new Option("e", "blockEncoding", true,
    "Data block encoding; Default: FAST_DIFF");
  encodingOption.setRequired(false);
  options.addOption(encodingOption);
  
  Option ratioOption = new Option("r", "selectionRatio", true,
    "Ratio of selected rows using essential column family");
  ratioOption.setRequired(false);
  options.addOption(ratioOption);
  
  Option widthOption = new Option("w", "valueWidth", true,
    "Width of value for non-essential column family");
  widthOption.setRequired(false);
  options.addOption(widthOption);
  
  CommandLineParser parser = new GnuParser();
  CommandLine cmd = parser.parse(options, args);
  if (args.length < 1) {
    HelpFormatter formatter = new HelpFormatter();
    formatter.printHelp("TestJoinedScanners", options, true);
  }
  
  if (cmd.hasOption("e")) {
    blockEncoding = DataBlockEncoding.valueOf(cmd.getOptionValue("e"));
  }
  if (cmd.hasOption("r")) {
    selectionRatio = Integer.parseInt(cmd.getOptionValue("r"));
  }
  if (cmd.hasOption("w")) {
    valueWidth = Integer.parseInt(cmd.getOptionValue("w"));
  }
  // run the test
  TestJoinedScanners test = new TestJoinedScanners();
  test.testJoinedScanners();
}
 

import org.apache.hadoop.hbase.io.encoding.DataBlockEncoding; //导入方法依赖的package包/类
/**
 * @return the data block encoding algorithm used in block cache and
 *         optionally on disk
 */
public DataBlockEncoding getDataBlockEncoding() {
  String type = getValue(DATA_BLOCK_ENCODING);
  if (type == null) {
    type = DEFAULT_DATA_BLOCK_ENCODING;
  }
  return DataBlockEncoding.valueOf(type);
}
 

import org.apache.hadoop.hbase.io.encoding.DataBlockEncoding; //导入方法依赖的package包/类
public static HFileDataBlockEncoder createFromFileInfo(
    FileInfo fileInfo, DataBlockEncoding preferredEncodingInCache)
    throws IOException {
  
  boolean hasPreferredCacheEncoding = preferredEncodingInCache != null
      && preferredEncodingInCache != DataBlockEncoding.NONE;

  byte[] dataBlockEncodingType = fileInfo.get(DATA_BLOCK_ENCODING);
  if (dataBlockEncodingType == null && !hasPreferredCacheEncoding) {
    return NoOpDataBlockEncoder.INSTANCE;
  }

  DataBlockEncoding onDisk;
  if (dataBlockEncodingType == null) {
    onDisk = DataBlockEncoding.NONE;
  }else {
    String dataBlockEncodingStr = Bytes.toString(dataBlockEncodingType);
    try {
      onDisk = DataBlockEncoding.valueOf(dataBlockEncodingStr);
    } catch (IllegalArgumentException ex) {
      throw new IOException("Invalid data block encoding type in file info: "
          + dataBlockEncodingStr, ex);
    }
  }

  DataBlockEncoding inCache;
  if (onDisk == DataBlockEncoding.NONE) {
    // This is an "in-cache-only" encoding or fully-unencoded scenario.
    // Either way, we use the given encoding (possibly NONE) specified by
    // the column family in cache.
    inCache = preferredEncodingInCache;
  } else {
    // Leave blocks in cache encoded the same way as they are on disk.
    // If we switch encoding type for the CF or the in-cache-only encoding
    // flag, old files will keep their encoding both on disk and in cache,
    // but new files will be generated with the new encoding.
    inCache = onDisk;
  }
  return new HFileDataBlockEncoderImpl(onDisk, inCache);
}
 

import org.apache.hadoop.hbase.io.encoding.DataBlockEncoding; //导入方法依赖的package包/类
public static HColumnDescriptor createColumnFamily(KylinConfig kylinConfig, String cfName, boolean isMemoryHungry) {
    HColumnDescriptor cf = new HColumnDescriptor(cfName);
    cf.setMaxVersions(1);

    if (isMemoryHungry) {
        cf.setBlocksize(kylinConfig.getHbaseDefaultBlockSize());
    } else {
        cf.setBlocksize(kylinConfig.getHbaseSmallFamilyBlockSize());
    }

    String hbaseDefaultCC = kylinConfig.getHbaseDefaultCompressionCodec().toLowerCase();
    switch (hbaseDefaultCC) {
    case "snappy": {
        logger.info("hbase will use snappy to compress data");
        cf.setCompressionType(Algorithm.SNAPPY);
        break;
    }
    case "lzo": {
        logger.info("hbase will use lzo to compress data");
        cf.setCompressionType(Algorithm.LZO);
        break;
    }
    case "gz":
    case "gzip": {
        logger.info("hbase will use gzip to compress data");
        cf.setCompressionType(Algorithm.GZ);
        break;
    }
    case "lz4": {
        logger.info("hbase will use lz4 to compress data");
        cf.setCompressionType(Algorithm.LZ4);
        break;
    }
    case "none":
    default: {
        logger.info("hbase will not use any compression algorithm to compress data");
        cf.setCompressionType(Algorithm.NONE);
    }
    }

    try {
        String encodingStr = kylinConfig.getHbaseDefaultEncoding();
        DataBlockEncoding encoding = DataBlockEncoding.valueOf(encodingStr);
        cf.setDataBlockEncoding(encoding);
    } catch (Exception e) {
        logger.info("hbase will not use any encoding", e);
        cf.setDataBlockEncoding(DataBlockEncoding.NONE);
    }

    cf.setInMemory(false);
    cf.setBloomFilterType(BloomType.NONE);
    return cf;
}