[FLINK-12981][metrics] ignore NaNs in percentile implementation

[NicoK]

What is the purpose of the change

Histogram metrics report long values and therefore, there is no Double.NaN in DescriptiveStatistics' data and there is no need to cleanse it while working with it.

Please note that this PR is based on #8877.
-> follow-up PR: #8887

Brief change log

• set a percentile implementation with ' NaNStrategy.FIXED'

Verifying this change

This change is already covered by existing tests, such as derivatives of AbstractHistogramTest.

Does this pull request potentially affect one of the following parts:

• Dependencies (does it add or upgrade a dependency): no
• The public API, i.e., is any changed class annotated with @Public(Evolving): no
• The serializers: no
• The runtime per-record code paths (performance sensitive): no
• Anything that affects deployment or recovery: JobManager (and its components), Checkpointing, Yarn/Mesos, ZooKeeper: no
• The S3 file system connector: no

Documentation

• Does this pull request introduce a new feature? no
• If yes, how is the feature documented? JavaDocs

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Last check on commit e5fbad0 (Fri Aug 23 10:23:00 UTC 2019)

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[zentol]

What is the benefit here?

[flinkbot]

CI report:

• f1465ce : FAILURE Build
• be4d8cf : FAILURE Build
• e5fbad0 : FAILURE Build

[NicoK]

You get reduced overhead during percentile calculation, see this code from Percentile#getWorkArray:

    protected double[] getWorkArray(final double[] values, final int begin, final int length) {
            final double[] work;
            if (values == getDataRef()) {
                work = getDataRef();
            } else {
                switch (nanStrategy) {
                case MAXIMAL:// Replace NaNs with +INFs
                    work = replaceAndSlice(values, begin, length, Double.NaN, Double.POSITIVE_INFINITY);
                    break;
                case MINIMAL:// Replace NaNs with -INFs
                    work = replaceAndSlice(values, begin, length, Double.NaN, Double.NEGATIVE_INFINITY);
                    break;
                case REMOVED:// Drop NaNs from data
                    work = removeAndSlice(values, begin, length, Double.NaN);
                    break;
                case FAILED:// just throw exception as NaN is un-acceptable
                    work = copyOf(values, begin, length);
                    MathArrays.checkNotNaN(work);
                    break;
                default: //FIXED
                    work = copyOf(values,begin,length);
                    break;
                }
            }
            return work;
    }

[zentol]

+1