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/*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you 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 org.apache.cassandra.concurrent;
import java.util.List;
import java.util.Map;
import java.util.concurrent.ConcurrentSkipListMap;
import java.util.concurrent.CopyOnWriteArrayList;
import java.util.concurrent.atomic.AtomicInteger;
import java.util.concurrent.atomic.AtomicLong;
import static org.apache.cassandra.concurrent.SEPWorker.Work;
/**
* A pool of worker threads that are shared between all Executors created with it. Each executor is treated as a distinct
* unit, with its own concurrency and task queue limits, but the threads that service the tasks on each executor are
* free to hop between executors at will.
*
* To keep producers from incurring unnecessary delays, once an executor is "spun up" (i.e. is processing tasks at a steady
* rate), adding tasks to the executor often involves only placing the task on the work queue and updating the
* task permits (which imposes our max queue length constraints). Only when it cannot be guaranteed the task will be serviced
* promptly, and the maximum concurrency has not been reached, does the producer have to schedule a thread itself to perform
* the work ('promptly' in this context means we already have a worker spinning for work, as described next).
*
* Otherwise the worker threads schedule themselves: when they are assigned a task, they will attempt to spawn
* a partner worker to service any other work outstanding on the queue (if any); once they have finished the task they
* will either take another (if any remaining) and repeat this, or they will attempt to assign themselves to another executor
* that does have tasks remaining. If both fail, it will enter a non-busy-spinning phase, where it will sleep for a short
* random interval (based upon the number of threads in this mode, so that the total amount of non-sleeping time remains
* approximately fixed regardless of the number of spinning threads), and upon waking will again try to assign itself to
* an executor with outstanding tasks to perform. As a result of always scheduling a partner before committing to performing
* any work, with a steady state of task arrival we should generally have either one spinning worker ready to promptly respond
* to incoming work, or all possible workers actively committed to tasks.
*
* In order to prevent this executor pool acting like a noisy neighbour to other processes on the system, workers also deschedule
* themselves when it is detected that there are too many for the current rate of operation arrival. This is decided as a function
* of the total time spent spinning by all workers in an interval; as more workers spin, workers are descheduled more rapidly.
*/
public class SharedExecutorPool
{
public static final SharedExecutorPool SHARED = new SharedExecutorPool("SharedPool");
// the name assigned to workers in the pool, and the id suffix
final String poolName;
final AtomicLong workerId = new AtomicLong();
// the collection of executors serviced by this pool; periodically ordered by traffic volume
final List executors = new CopyOnWriteArrayList<>();
// the number of workers currently in a spinning state
final AtomicInteger spinningCount = new AtomicInteger();
// see SEPWorker.maybeStop() - used to self coordinate stopping of threads
final AtomicLong stopCheck = new AtomicLong();
// the collection of threads that are (most likely) in a spinning state - new workers are scheduled from here first
// TODO: consider using a queue partially-ordered by scheduled wake-up time
// (a full-fledged correctly ordered SkipList is overkill)
final ConcurrentSkipListMap spinning = new ConcurrentSkipListMap<>();
// the collection of threads that have been asked to stop/deschedule - new workers are scheduled from here last
final ConcurrentSkipListMap descheduled = new ConcurrentSkipListMap<>();
public SharedExecutorPool(String poolName)
{
this.poolName = poolName;
}
void schedule(Work work)
{
// we try to hand-off our work to the spinning queue before the descheduled queue, even though we expect it to be empty
// all we're doing here is hoping to find a worker without work to do, but it doesn't matter too much what we find;
// we atomically set the task so even if this were a collection of all workers it would be safe, and if they are both
// empty we schedule a new thread
Map.Entry e;
while (null != (e = spinning.pollFirstEntry()) || null != (e = descheduled.pollFirstEntry()))
if (e.getValue().assign(work, false))
return;
if (!work.isStop())
new SEPWorker(workerId.incrementAndGet(), work, this);
}
void maybeStartSpinningWorker()
{
// in general the workers manage spinningCount directly; however if it is zero, we increment it atomically
// ourselves to avoid starting a worker unless we have to
int current = spinningCount.get();
if (current == 0 && spinningCount.compareAndSet(0, 1))
schedule(Work.SPINNING);
}
public LocalAwareExecutorService newExecutor(int maxConcurrency, int maxQueuedTasks, String jmxPath, String name)
{
SEPExecutor executor = new SEPExecutor(this, maxConcurrency, maxQueuedTasks, jmxPath, name);
executors.add(executor);
return executor;
}
}