import org.gradle.api.tasks.PathSensitivity
import org.gradle.api.tasks.TaskAction
// Using star import to workaround https://youtrack.jetbrains.com/issue/KTIJ-24390
import org.gradle.kotlin.dsl.*
import org.gradle.workers.WorkerExecutor
import javax.inject.Inject


@CacheableTask
abstract class IncubatingApiAggregateReportTask : DefaultTask() {

    @get:InputFiles
    @get:PathSensitive(PathSensitivity.RELATIVE)

		config.HelpKV{
			Key:         apiReplicationMaxWorkers,
			Description: `set the maximum number of replication workers` + defaultHelpPostfix(apiReplicationMaxWorkers),
			Optional:    true,
			Type:        "number",
		},
		config.HelpKV{
			Key:         apiTransitionWorkers,
			Description: `set the number of transition workers` + defaultHelpPostfix(apiTransitionWorkers),
			Optional:    true,
			Type:        "number",
		},

			Optional:    true,
			Type:        "int",
		},
		config.HelpKV{
			Key:         DriveWorkers,
			Description: `the number of workers per drive to heal a new disk replacement` + defaultHelpPostfix(DriveWorkers),
			Optional:    true,
			Type:        "int",
		},
	}

      "coverage" : {
        "per_day" : [ "linux", "macOs", "windows" ]
      }
    } ]
  }, {
    "testId" : "org.gradle.performance.experiment.java.ParallelBuildPerformanceTest.clean assemble with 4 parallel workers",
    "groups" : [ {
      "testProject" : "largeJavaMultiProject",
      "coverage" : {
        "per_week" : [ "linux" ]
      }
    }, {
      "testProject" : "largeMonolithicJavaProject",
      "coverage" : {

  "durations" : [ {
    "testProject" : "nativeMonolithic",
    "linux" : 885
  }, {
    "testProject" : "nativeMonolithicOverlapping",
    "linux" : 999
  } ]
}, {
  "scenario" : "org.gradle.performance.regression.nativeplatform.RealWorldNativePluginPerformanceTest.build with 12 parallel workers",
  "durations" : [ {
    "testProject" : "nativeMonolithic",

</component>...

	current      [][]string       // current block of results to be returned
	recordsRead  int              // number of records read in current slice
	input        chan *queueItem  // input for workers
	queue        chan *queueItem  // output from workers in order
	err          error            // global error state, only touched by Reader.Read
	bufferPool   sync.Pool        // pool of []byte objects for input

// newBatchJobPool creates a pool of job manifest workers of specified size
func newBatchJobPool(ctx context.Context, o ObjectLayer, workers int) *BatchJobPool {
	jpool := &BatchJobPool{
		ctx:          ctx,
		objLayer:     o,
		jobCh:        make(chan *BatchJobRequest, 10000),
		workerKillCh: make(chan struct{}, workers),
		jobCancelers: make(map[string]context.CancelFunc),
	}

	if err != nil {
		rebalanceLogIf(ctx, fmt.Errorf("invalid workers value err: %v, defaulting to %d", err, len(pool.sets)))
		workerSize = len(pool.sets)
	}

	// Each decom worker needs one List() goroutine/worker
	// add that many extra workers.
	workerSize += len(pool.sets)

	wk, err := workers.New(workerSize)
	if err != nil {
		return err
	}

可以通过多种方法来实现这一目标，我将在接下来的章节中向您详细介绍具体策略，例如在谈论 Docker 和容器时。

要考虑的主要限制是必须有一个**单个**组件来处理**公共IP**中的**端口**。 然后它必须有一种方法将通信**传输**到复制的**进程/worker**。

以下是一些可能的组合和策略：

* **Gunicorn** 管理 **Uvicorn workers**
     * Gunicorn 将是监听 **IP** 和 **端口** 的 **进程管理器**，复制将通过 **多个 Uvicorn 工作进程** 进行
* **Uvicorn** 管理 **Uvicorn workers**
     * 一个 Uvicorn **进程管理器** 将监听 **IP** 和 **端口**，并且它将启动 **多个 Uvicorn 工作进程**
* **Kubernetes** 和其他分布式 **容器系统**