io.datakernel.rpc.client.sender.RpcStrategyRandomSampling Maven / Gradle / Ivy

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High-performance and fault-tolerant remote procedure call module for building distributed applications. Provides a high-performance asynchronous binary RPC streaming protocol.
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/*
 * Copyright (C) 2015 SoftIndex LLC.
 *
 * 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.
 */

package io.datakernel.rpc.client.sender;

import io.datakernel.async.callback.Callback;
import io.datakernel.rpc.client.RpcClientConnectionPool;
import org.jetbrains.annotations.NotNull;

import java.net.InetSocketAddress;
import java.util.*;

import static io.datakernel.common.Preconditions.checkArgument;

public class RpcStrategyRandomSampling implements RpcStrategy {
	private final Random random = new Random();
	private final Map strategyToWeight = new HashMap<>();

	private RpcStrategyRandomSampling() {}

	public static RpcStrategyRandomSampling create() {return new RpcStrategyRandomSampling();}

	public RpcStrategyRandomSampling add(int weight, RpcStrategy strategy) {
		checkArgument(weight >= 0, "weight cannot be negative");
		checkArgument(!strategyToWeight.containsKey(strategy), "withStrategy is already added");

		strategyToWeight.put(strategy, weight);

		return this;
	}

	@Override
	public Set getAddresses() {
		HashSet result = new HashSet<>();
		for (RpcStrategy strategy : strategyToWeight.keySet()) {
			result.addAll(strategy.getAddresses());
		}
		return result;
	}

	@Override
	public RpcSender createSender(RpcClientConnectionPool pool) {
		Map senderToWeight = new HashMap<>();
		int totalWeight = 0;
		for (RpcStrategy rpcStrategy : strategyToWeight.keySet()) {
			RpcSender sender = rpcStrategy.createSender(pool);
			if (sender != null) {
				int weight = strategyToWeight.get(rpcStrategy);
				senderToWeight.put(sender, weight);
				totalWeight += weight;
			}
		}

		if (totalWeight == 0) {
			return null;
		}

		long randomLong = random.nextLong();
		long seed = randomLong != 0L ? randomLong : 2347230858016798896L;

		return new RandomSamplingSender(senderToWeight, seed);
	}

	static final class RandomSamplingSender implements RpcSender {
		private final List senders;
		private final int[] cumulativeWeights;
		private final int totalWeight;

		private long lastRandomLong;

		RandomSamplingSender(Map senderToWeight, long seed) {
			checkArgument(!senderToWeight.containsKey(null), "sender cannot be null");

			senders = new ArrayList<>(senderToWeight.size());
			cumulativeWeights = new int[senderToWeight.size()];
			int currentCumulativeWeight = 0;
			int currentSender = 0;
			for (RpcSender rpcSender : senderToWeight.keySet()) {
				currentCumulativeWeight += senderToWeight.get(rpcSender);
				senders.add(rpcSender);
				cumulativeWeights[currentSender++] = currentCumulativeWeight;
			}
			totalWeight = currentCumulativeWeight;

			lastRandomLong = seed;
		}

		@Override
		public  void sendRequest(I request, int timeout, @NotNull Callback cb) {
			lastRandomLong ^= (lastRandomLong << 21);
			lastRandomLong ^= (lastRandomLong >>> 35);
			lastRandomLong ^= (lastRandomLong << 4);
			int currentRandomValue = (int) ((lastRandomLong & Long.MAX_VALUE) % totalWeight);
			int lowerIndex = 0;
			int upperIndex = cumulativeWeights.length;
			while (lowerIndex != upperIndex) {
				int middle = (lowerIndex + upperIndex) / 2;
				if (currentRandomValue >= cumulativeWeights[middle]) {
					lowerIndex = middle + 1;
				} else {
					upperIndex = middle;
				}
			}
			senders.get(lowerIndex).sendRequest(request, timeout, cb);
		}
	}

}