GEODE-10010: Refine per-second Redis stats

[DonalEvans]

Code changes:

• Rather than a value that updates once per second, instantaneous
  operations per second and instantaneous kilobytes read per second now
  return a rolling average of those stats updated 16 times per second
• Change instantaneous operations per second type from double to int,
  since it's always a whole number
• Introduce RollingAverageStat nested class in RedisStats to handle
  calculating the rolling average value of a given stat

Test changes:

• Rename AbstractRedisInfoStatsIntegrationTest to match child classes
• Rather than measuring instantaneous per second stats after
  operations have finished, sample them while operations are ongoing
• Assert only that the stats have updated, not that they are close to a
  calculated expected value, as this proved too inconsistent and very
  flaky

Authored-by: Donal Evans doevans@vmware.com

For all changes:

• Is there a JIRA ticket associated with this PR? Is it referenced in the commit message?

• Has your PR been rebased against the latest commit within the target branch (typically develop)?

• Is your initial contribution a single, squashed commit?

• Does gradlew build run cleanly?

• Have you written or updated unit tests to verify your changes?

• If adding new dependencies to the code, are these dependencies licensed in a way that is compatible for inclusion under ASF 2.0?

[jdeppe-pivotal]

For fun I did some quick benchmarking and came up with this optimization:

    long currentTotal = 0;
    public long calculate2() {
      long currentValue;
      try {
        currentValue = statCallable.call();
      } catch (Exception e) {
        throw new RedisException("Error while calculating RollingAverage stats", e);
      }
      long delta = currentValue - valueReadLastTick;
      valueReadLastTick = currentValue;

      currentTotal = currentTotal + delta - valuesReadOverLastNSamples[tickNumber];
      valuesReadOverLastNSamples[tickNumber] = delta;
      // same as mod (%) but measurably faster...
      tickNumber = (tickNumber + 1) & (valuesReadOverLastNSamples.length - 1);

      return currentTotal;
    }

This runs more than an order of magnitude faster. Granted, the benchmark was hammering this as fast as possible so at only 16 times / second the optimization would probably be negligible in the real world. Your call if you want to do it.

[DonalEvans]

Faster is better!