Skip to content

[SPARK-55725][K8S][DOCS] Make AbstractPodsAllocator docs up-to-date #54526

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
dongjoon-hyun wants to merge 1 commit into from
Closed

[SPARK-55725][K8S][DOCS] Make AbstractPodsAllocator docs up-to-date #54526

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
49 changes: 37 additions & 12 deletions ...es/core/src/main/scala/org/apache/spark/scheduler/cluster/k8s/AbstractPodsAllocator.scala
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -18,55 +18,80 @@ package org.apache.spark.scheduler.cluster.k8s

import io.fabric8.kubernetes.api.model.Pod

import org.apache.spark.annotation.DeveloperApi
import org.apache.spark.annotation.{DeveloperApi, Since}
import org.apache.spark.resource.ResourceProfile


/**
* :: DeveloperApi ::
* A abstract interface for allowing different types of pods allocation.
*
* The internal Spark implementations are [[StatefulSetPodsAllocator]]
* and [[ExecutorPodsAllocator]]. This may be useful for folks integrating with custom schedulers.
*
* This API may change or be removed at anytime.
* The internal Spark implementations are [[StatefulSetPodsAllocator]],
* [[DeploymentPodsAllocator]], and [[ExecutorPodsAllocator]].
* This may be useful for folks integrating with custom schedulers.
*
* @since 3.3.0
*/
@DeveloperApi
@Since("3.3.0")
abstract class AbstractPodsAllocator {
/*
/**
Copy link
Member Author

@dongjoon-hyun dongjoon-hyun Feb 27, 2026

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Apache Spark uses Javadoc style instead of Scaladoc.

* Optional lifecycle manager for tracking executor pod lifecycle events.
* Set via setExecutorPodsLifecycleManager for backward compatibility.
*
* @since 4.2.0
*/
@Since("4.2.0")
protected var executorPodsLifecycleManager: Option[ExecutorPodsLifecycleManager] = None

/*
/**
* Set the lifecycle manager for tracking executor pod lifecycle events.
* This method is optional and may not exist in custom implementations based on older versions.
*
* @since 4.2.0
*/
@Since("4.2.0")
def setExecutorPodsLifecycleManager(manager: ExecutorPodsLifecycleManager): Unit = {
executorPodsLifecycleManager = Some(manager)
}

/*
/**
* Set the total expected executors for an application
*
* @since 3.3.0
*/
@Since("3.3.0")
def setTotalExpectedExecutors(resourceProfileToTotalExecs: Map[ResourceProfile, Int]): Unit
/*

/**
* Reference to driver pod.
*
* @since 3.3.0
*/
@Since("3.3.0")
def driverPod: Option[Pod]
/*

/**
* If the pod for a given exec id is deleted.
*
* @since 3.3.0
*/
@Since("3.3.0")
def isDeleted(executorId: String): Boolean
/*

/**
* Start hook.
*
* @since 3.3.0
*/
@Since("3.3.0")
def start(applicationId: String, schedulerBackend: KubernetesClusterSchedulerBackend): Unit
/*

/**
* Stop hook
*
* @since 3.3.0
*/
@Since("3.3.0")
def stop(applicationId: String): Unit
}