Copyright 2016 Netflix, Inc.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
/**
 * Copyright 2016 Netflix, Inc.
 * <p/>
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 * <p/>
 * http://www.apache.org/licenses/LICENSE-2.0
 * <p/>
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
package com.netflix.hystrix.metric.consumer;

import com.netflix.hystrix.HystrixCommandProperties;
import com.netflix.hystrix.metric.HystrixCommandExecutionStarted;
import com.netflix.hystrix.metric.HystrixEventStream;
import rx.Observable;
import rx.Subscription;
import rx.functions.Func0;
import rx.functions.Func1;
import rx.functions.Func2;
import rx.subjects.BehaviorSubject;

import java.util.ArrayList;
import java.util.List;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.atomic.AtomicReference;

Maintains a stream of max-concurrency This gets calculated using a rolling window of t1 milliseconds. This window has b buckets. Therefore, a new rolling-max is produced every t2 (=t1/b) milliseconds t1 = HystrixCommandProperties.metricsRollingStatisticalWindowInMilliseconds() b = HystrixCommandProperties.metricsRollingStatisticalWindowBuckets() This value gets cached in this class. It may be queried using getLatestRollingMax() This is a stable value - there's no peeking into a bucket until it is emitted /**
 * Maintains a stream of max-concurrency
 *
 * This gets calculated using a rolling window of t1 milliseconds.  This window has b buckets.
 * Therefore, a new rolling-max is produced every t2 (=t1/b) milliseconds
 * t1 = {@link HystrixCommandProperties#metricsRollingStatisticalWindowInMilliseconds()}
 * b = {@link HystrixCommandProperties#metricsRollingStatisticalWindowBuckets()}
 *
 * This value gets cached in this class.  It may be queried using {@link #getLatestRollingMax()}
 *
 * This is a stable value - there's no peeking into a bucket until it is emitted
 */
public abstract class RollingConcurrencyStream {
    private AtomicReference<Subscription> rollingMaxSubscription = new AtomicReference<Subscription>(null);
    private final BehaviorSubject<Integer> rollingMax = BehaviorSubject.create(0);
    private final Observable<Integer> rollingMaxStream;

    private static final Func2<Integer, Integer, Integer> reduceToMax = new Func2<Integer, Integer, Integer>() {
        @Override
        public Integer call(Integer a, Integer b) {
            return Math.max(a, b);
        }
    };

    private static final Func1<Observable<Integer>, Observable<Integer>> reduceStreamToMax = new Func1<Observable<Integer>, Observable<Integer>>() {
        @Override
        public Observable<Integer> call(Observable<Integer> observedConcurrency) {
            return observedConcurrency.reduce(0, reduceToMax);
        }
    };

    private static final Func1<HystrixCommandExecutionStarted, Integer> getConcurrencyCountFromEvent = new Func1<HystrixCommandExecutionStarted, Integer>() {
        @Override
        public Integer call(HystrixCommandExecutionStarted event) {
            return event.getCurrentConcurrency();
        }
    };

    protected RollingConcurrencyStream(final HystrixEventStream<HystrixCommandExecutionStarted> inputEventStream, final int numBuckets, final int bucketSizeInMs) {
        final List<Integer> emptyRollingMaxBuckets = new ArrayList<Integer>();
        for (int i = 0; i < numBuckets; i++) {
            emptyRollingMaxBuckets.add(0);
        }

        rollingMaxStream = inputEventStream
                .observe()
                .map(getConcurrencyCountFromEvent)
                .window(bucketSizeInMs, TimeUnit.MILLISECONDS)
                .flatMap(reduceStreamToMax)
                .startWith(emptyRollingMaxBuckets)
                .window(numBuckets, 1)
                .flatMap(reduceStreamToMax)
                .share()
                .onBackpressureDrop();
    }

    public void startCachingStreamValuesIfUnstarted() {
        if (rollingMaxSubscription.get() == null) {
            //the stream is not yet started
            Subscription candidateSubscription = observe().subscribe(rollingMax);
            if (rollingMaxSubscription.compareAndSet(null, candidateSubscription)) {
                //won the race to set the subscription
            } else {
                //lost the race to set the subscription, so we need to cancel this one
                candidateSubscription.unsubscribe();
            }
        }
    }

    public long getLatestRollingMax() {
        startCachingStreamValuesIfUnstarted();
        if (rollingMax.hasValue()) {
            return rollingMax.getValue();
        } else {
            return 0L;
        }
    }

    public Observable<Integer> observe() {
        return rollingMaxStream;
    }

    public void unsubscribe() {
        Subscription s = rollingMaxSubscription.get();
        if (s != null) {
            s.unsubscribe();
            rollingMaxSubscription.compareAndSet(s, null);
        }
    }
}