private final OutputStream collector;


        public CacheStream ( OutputStream stream, OutputStream collector ) {
            this.stream = stream;
            this.collector = collector;
        }


        @Override
        public void close () throws IOException {
            this.stream.close();
            this.collector.close();
        }


        @Override

        private final OutputStream stream;

        private final OutputStream collector;

        public CacheStream(OutputStream stream, OutputStream collector) {
            this.stream = stream;
            this.collector = collector;
        }

        public void close() throws IOException {
            stream.close();
            collector.close();
        }

        public void flush() throws IOException {

        new LineProcessor<List<String>>() {
          List<String> collector = new ArrayList<>();

          @Override
          public boolean processLine(String line) {
            collector.add(line);
            return true;
          }

          @Override
          public List<String> getResult() {
            return collector;
          }
        };

// to collect the metrics.
//
// It implements the prometheus.Collector interface for metric groups without a
// bucket dimension. For metric groups with a bucket dimension, use the
// `GetBucketCollector` method to get a `BucketCollector` that implements the
// prometheus.Collector interface.
type MetricsGroup struct {
	// Path (relative to the Metrics v3 base endpoint) at which this group of

        ProblemCollector collector = ProblemCollectorFactory.newInstance(null);
        problems.forEach(p -> collector.add(
                Problem.Severity.valueOf(p.getSeverity().name()),
                p.getMessage(),
                p.getLineNumber(),
                p.getColumnNumber(),
                p.getException()));
        return collector.getProblems();
    }

        new LineProcessor<List<String>>() {
          List<String> collector = new ArrayList<>();

          @Override
          public boolean processLine(String line) {
            collector.add(whitespace().trimFrom(line));
            return true;
          }

          @Override
          public List<String> getResult() {
            return collector;
          }
        };

    implements Serializable {

  /**
   * Returns a {@code Collector} that accumulates elements into an {@code ImmutableTable}. Each
   * input element is mapped to one cell in the returned table, with the rows, columns, and values
   * generated by applying the specified functions.
   *
   * <p>The returned {@code Collector} will throw a {@code NullPointerException} at collection time

  // This gives minimal coverage to the forwarding functions
  public void testToImmutableTableSanityTest() {
    Collector<Cell<String, String, Integer>, ?, ImmutableTable<String, String, Integer>> collector =
        toImmutableTable(Cell::getRowKey, Cell::getColumnKey, Cell::getValue);
    CollectorTester.of(collector)
        .expectCollects(ImmutableTable.of())

    checkArgument(fpp < 1.0, "False positive probability (%s) must be < 1.0", fpp);
    return Collector.of(
        () -> BloomFilter.create(funnel, expectedInsertions, fpp),
        BloomFilter::put,
        (bf1, bf2) -> {
          bf1.putAll(bf2);
          return bf1;
        },
        Collector.Characteristics.UNORDERED,
        Collector.Characteristics.CONCURRENT);
  }

  /**

   *
   * <p><b>Note:</b> the values of the metrics are undefined in case of overflow (though it is
   * guaranteed not to throw an exception). If you require specific handling, we recommend
   * implementing your own stats collector.
   */
  public long requestCount() {
    return saturatedAdd(hitCount, missCount);
  }

  /** Returns the number of times {@link Cache} lookup methods have returned a cached value. */