Examples of org.apache.hadoop.hbase.util.ByteBloomFilter$MetaWriter

org.apache.hadoop.hbase.util.ByteBloomFilter
ne-lab.org">European Commission One-Lab Project 034819. Bloom filters are very sensitive to the number of elements inserted into them. For HBase, the number of entries depends on the size of the data stored in the column. Currently the default region size is 256MB, so entry count ~= 256MB / (average value size for column). Despite this rule of thumb, there is no efficient way to calculate the entry count after compactions. Therefore, it is often easier to use a dynamic bloom filter that will add extra space instead of allowing the error rate to grow. ( http://www.eecs.harvard.edu/~michaelm/NEWWORK/postscripts/BloomFilterSurvey .pdf ) m denotes the number of bits in the Bloom filter (bitSize) n denotes the number of elements inserted into the Bloom filter (maxKeys) k represents the number of hash functions used (nbHash) e represents the desired false positive rate for the bloom (err) If we fix the error rate (e) and know the number of entries, then the optimal bloom size m = -(n * ln(err) / (ln(2)^2) ~= n * ln(err) / ln(0.6185) The probability of false positives is minimized when k = m/n ln(2). @see BloomFilter The general behavior of a filter @see Space/Time Trade-Offs in Hash Coding with Allowable Errors

          if (bloomFilterType == BloomType.NONE) {
            throw new IOException("valid bloom filter type not found in FileInfo");
          }




          this.bloomFilter = new ByteBloomFilter(b);
          LOG.info("Loaded " + (bloomFilterType== BloomType.ROW? "row":"col")
                 + " bloom filter metadata for " + reader.getName());
        }
      } catch (IOException e) {
        LOG.error("Error reading bloom filter meta -- proceeding without", e);

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          }


          //Printing bloom information
          ByteBuffer b = reader.getMetaBlock("BLOOM_FILTER_META", false);
          if (b!= null) {
            BloomFilter bloomFilter = new ByteBloomFilter(b);
            System.out.println("BloomSize: " + bloomFilter.getByteSize());
            System.out.println("No of Keys in bloom: " +
                bloomFilter.getKeyCount());
            System.out.println("Max Keys for bloom: " +
                bloomFilter.getMaxKeys());
          } else {
            System.out.println("Could not get bloom data from meta block");
          }
        }
        reader.close();

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          }


          //Printing bloom information
          ByteBuffer b = reader.getMetaBlock("BLOOM_FILTER_META", false);
          if (b!= null) {
            BloomFilter bloomFilter = new ByteBloomFilter(b);
            System.out.println("BloomSize: " + bloomFilter.getByteSize());
            System.out.println("No of Keys in bloom: " +
                bloomFilter.getKeyCount());
            System.out.println("Max Keys for bloom: " +
                bloomFilter.getMaxKeys());
          } else {
            System.out.println("Could not get bloom data from meta block");
          }
        }
        reader.close();

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      if (bloomType != BloomType.NONE && conf != null) {
        float err = conf.getFloat(IO_STOREFILE_BLOOM_ERROR_RATE, (float)0.01);
        int maxFold = conf.getInt(IO_STOREFILE_BLOOM_MAX_FOLD, 7);


        this.bloomFilter = new ByteBloomFilter(maxKeys, err,
            Hash.getHashType(conf), maxFold);
        this.bloomFilter.allocBloom();
        this.bloomType = bloomType;
      } else {
        this.bloomFilter = null;

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          if (bloomFilterType == BloomType.NONE) {
            throw new IOException("valid bloom filter type not found in FileInfo");
          }




          this.bloomFilter = new ByteBloomFilter(b);
          LOG.info("Loaded " + (bloomFilterType== BloomType.ROW? "row":"col")
                 + " bloom filter metadata for " + reader.getName());
        }
      } catch (IOException e) {
        LOG.error("Error reading bloom filter meta -- proceeding without", e);

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