* There is no need for a blocking lock; when the lock is not
   * available, threads try other slots (or the base).  During these
   * retries, there is increased contention and reduced locality,
   * which is still better than alternatives.
   *
   * Per-thread hash codes are initialized to random values.
   * Contention and/or table collisions are indicated by failed

### Allowed values for REDUCED_REDUNDANCY storage class

`REDUCED_REDUNDANCY` implies lesser parity than `STANDARD` class. So,`REDUCED_REDUNDANCY` parity drives should be

- Less than N/2, if `STANDARD` parity is not set.
- Less than `STANDARD` Parity, if it is set.

Default value for `REDUCED_REDUNDANCY` storage class is `1`.

## Get started with Storage Class

	}
	return target.isActive()
}

func (target *NSQTarget) isActive() (bool, error) {
	if target.producer == nil {
		producer, err := nsq.NewProducer(target.args.NSQDAddress.String(), target.config)
		if err != nil {
			return false, err
		}
		target.producer = producer
	}

	if err := target.producer.Ping(); err != nil {
		// To treat "connection refused" errors as errNotConnected.
		if xnet.IsConnRefusedErr(err) {

   * There is no need for a blocking lock; when the lock is not
   * available, threads try other slots (or the base).  During these
   * retries, there is increased contention and reduced locality,
   * which is still better than alternatives.
   *
   * Per-thread hash codes are initialized to random values.
   * Contention and/or table collisions are indicated by failed

   * There is no need for a blocking lock; when the lock is not
   * available, threads try other slots (or the base).  During these
   * retries, there is increased contention and reduced locality,
   * which is still better than alternatives.
   *
   * Per-thread hash codes are initialized to random values.
   * Contention and/or table collisions are indicated by failed

  // many clusters. Larger clusters may need more attempts to find a node
  // that suits all pending resources. This may get increased in the
  // future, but not reduced.
  //
  // +listType=set
  // +optional
  repeated string potentialNodes = 2;
}

// PodSchedulingContextStatus describes where resources for the Pod can be allocated.
message PodSchedulingContextStatus {

        stream(tags).of(stream -> stream.sorted().reduce((l, r) -> l + r).ifPresent(v -> buf.append(v)));
        buf.append(CACHE_KEY_SPLITTER);
        stream(roles).of(stream -> stream.sorted().reduce((l, r) -> l + r).ifPresent(v -> buf.append(v)));
        buf.append(CACHE_KEY_SPLITTER);
        stream(fields).of(stream -> stream.sorted().reduce((l, r) -> l + r).ifPresent(v -> buf.append(v)));

Doing this provides the following specific benefits:
- **Reduce the API surface** - We no longer need to maintain two methods.
- **Consistency** - All languages have consistent access to the same APIs and ergonomics in the DSL.
- **Reduce the size of the Gradle distribution** - We no longer need to carry multiple standard libraries for different languages.

## Decision

        .sort(s => -(s.additions + s.deletions));

    let totalAdditions = Object.values(preppedStatistics).reduce((acc, summary) => acc + summary.additions, 0);
    let totalDeletions = Object.values(preppedStatistics).reduce((acc, summary) => acc + summary.deletions, 0);
    let newRatio = totalAdditions / (totalAdditions + totalDeletions) * 100;

      assertEquals(0, Queues.drain(q, ImmutableList.of(), 1, 10, MILLISECONDS));

      Producer producer = new Producer(q, 1);
      // producing one, will ask for two
      Future<?> producerThread = threadPool.submit(producer);
      producer.beganProducing.await();

      // make sure we time out
      Stopwatch timer = Stopwatch.createStarted();