序
本文主要研究一下storm nimbus的mkAssignments
Nimbus.mkAssignments
storm-2.0.0/storm-server/src/main/java/org/apache/storm/daemon/nimbus/Nimbus.java
void doRebalance(String topoId, StormBase stormBase) throws Exception {
RebalanceOptions rbo = stormBase.get_topology_action_options().get_rebalance_options();
StormBase updated = new StormBase();
updated.set_topology_action_options(null);
updated.set_component_debug(Collections.emptyMap());
if (rbo.is_set_num_executors()) {
updated.set_component_executors(rbo.get_num_executors());
}
if (rbo.is_set_num_workers()) {
updated.set_num_workers(rbo.get_num_workers());
}
stormClusterState.updateStorm(topoId, updated);
updateBlobStore(topoId, rbo, ServerUtils.principalNameToSubject(rbo.get_principal()));
idToExecutors.getAndUpdate(new Dissoc<>(topoId)); // remove the executors cache to let it recompute.
mkAssignments(topoId);
}
private void mkAssignments() throws Exception {
mkAssignments(null);
}- 这里调用stormClusterState.updateStorm(topoId, updated)更新zk数据
- 这里doRebalance以及mkAssignments都调用了mkAssignments(String scratchTopoId)方法
mkAssignments(String scratchTopoId)
storm-2.0.0/storm-server/src/main/java/org/apache/storm/daemon/nimbus/Nimbus.java
private void mkAssignments(String scratchTopoId) throws Exception {
try {
if (!isReadyForMKAssignments()) {
return;
}
// get existing assignment (just the topologyToExecutorToNodePort map) -> default to {}
// filter out ones which have a executor timeout
// figure out available slots on cluster. add to that the used valid slots to get total slots. figure out how many executors
// should be in each slot (e.g., 4, 4, 4, 5)
// only keep existing slots that satisfy one of those slots. for rest, reassign them across remaining slots
// edge case for slots with no executor timeout but with supervisor timeout... just treat these as valid slots that can be
// reassigned to. worst comes to worse the executor will timeout and won't assign here next time around
IStormClusterState state = stormClusterState;
//read all the topologies
Map<String, StormBase> bases;
Map<String, TopologyDetails> tds = new HashMap<>();
synchronized (submitLock) {
// should promote: only fetch storm bases of topologies that need scheduling.
bases = state.topologyBases();
for (Iterator<Entry<String, StormBase>> it = bases.entrySet().iterator(); it.hasNext(); ) {
Entry<String, StormBase> entry = it.next();
String id = entry.getKey();
try {
tds.put(id, readTopologyDetails(id, entry.getValue()));
} catch (KeyNotFoundException e) {
//A race happened and it is probably not running
it.remove();
}
}
}
List<String> assignedTopologyIds = state.assignments(null);
Map<String, Assignment> existingAssignments = new HashMap<>();
for (String id : assignedTopologyIds) {
//for the topology which wants rebalance (specified by the scratchTopoId)
// we exclude its assignment, meaning that all the slots occupied by its assignment
// will be treated as free slot in the scheduler code.
if (!id.equals(scratchTopoId)) {
Assignment currentAssignment = state.assignmentInfo(id, null);
if (!currentAssignment.is_set_owner()) {
TopologyDetails td = tds.get(id);
if (td != null) {
currentAssignment.set_owner(td.getTopologySubmitter());
state.setAssignment(id, currentAssignment, td.getConf());
}
}
existingAssignments.put(id, currentAssignment);
}
}
// make the new assignments for topologies
lockingMkAssignments(existingAssignments, bases, scratchTopoId, assignedTopologyIds, state, tds);
} catch (Exception e) {
this.mkAssignmentsErrors.mark();
throw e;
}
}- 通过readTopologyDetails读取topology对应的TopologyDetails信息
- 通过state.assignments(Runnable callback)以及state.assignmentInfo(String stormId, Runnable callback)获取已经存在的assignments
- 然后调用lockingMkAssignments为topologies分配新的assignments
lockingMkAssignments
storm-2.0.0/storm-server/src/main/java/org/apache/storm/daemon/nimbus/Nimbus.java
private void lockingMkAssignments(Map<String, Assignment> existingAssignments, Map<String, StormBase> bases,
String scratchTopoId, List<String> assignedTopologyIds, IStormClusterState state,
Map<String, TopologyDetails> tds) throws Exception {
Topologies topologies = new Topologies(tds);
synchronized (schedLock) {
Map<String, SchedulerAssignment> newSchedulerAssignments =
computeNewSchedulerAssignments(existingAssignments, topologies, bases, scratchTopoId);
Map<String, Map<List<Long>, List<Object>>> topologyToExecutorToNodePort =
computeTopoToExecToNodePort(newSchedulerAssignments, assignedTopologyIds);
Map<String, Map<WorkerSlot, WorkerResources>> newAssignedWorkerToResources =
computeTopoToNodePortToResources(newSchedulerAssignments);
int nowSecs = Time.currentTimeSecs();
Map<String, SupervisorDetails> basicSupervisorDetailsMap = basicSupervisorDetailsMap(state);
//construct the final Assignments by adding start-times etc into it
Map<String, Assignment> newAssignments = new HashMap<>();
//......
//tasks figure out what tasks to talk to by looking at topology at runtime
// only log/set when there's been a change to the assignment
for (Entry<String, Assignment> entry : newAssignments.entrySet()) {
String topoId = entry.getKey();
Assignment assignment = entry.getValue();
Assignment existingAssignment = existingAssignments.get(topoId);
TopologyDetails td = topologies.getById(topoId);
if (assignment.equals(existingAssignment)) {
LOG.debug("Assignment for {} hasn't changed", topoId);
} else {
LOG.info("Setting new assignment for topology id {}: {}", topoId, assignment);
state.setAssignment(topoId, assignment, td.getConf());
}
}
//grouping assignment by node to see the nodes diff, then notify nodes/supervisors to synchronize its owned assignment
//because the number of existing assignments is small for every scheduling round,
//we expect to notify supervisors at almost the same time
Map<String, String> totalAssignmentsChangedNodes = new HashMap<>();
for (Entry<String, Assignment> entry : newAssignments.entrySet()) {
String topoId = entry.getKey();
Assignment assignment = entry.getValue();
Assignment existingAssignment = existingAssignments.get(topoId);
totalAssignmentsChangedNodes.putAll(assignmentChangedNodes(existingAssignment, assignment));
}
notifySupervisorsAssignments(newAssignments, assignmentsDistributer, totalAssignmentsChangedNodes,
basicSupervisorDetailsMap);
Map<String, Collection<WorkerSlot>> addedSlots = new HashMap<>();
for (Entry<String, Assignment> entry : newAssignments.entrySet()) {
String topoId = entry.getKey();
Assignment assignment = entry.getValue();
Assignment existingAssignment = existingAssignments.get(topoId);
if (existingAssignment == null) {
existingAssignment = new Assignment();
existingAssignment.set_executor_node_port(new HashMap<>());
existingAssignment.set_executor_start_time_secs(new HashMap<>());
}
Set<WorkerSlot> newSlots = newlyAddedSlots(existingAssignment, assignment);
addedSlots.put(topoId, newSlots);
}
inimbus.assignSlots(topologies, addedSlots);
}
}- 这里首先调用computeNewSchedulerAssignments方法计算newSchedulerAssignments
- 对newAssignments进行遍历，如果assignment有变动，则调用state.setAssignment(topoId, assignment, td.getConf())将分配信息写到zk
- 然后计算totalAssignmentsChangedNodes调用notifySupervisorsAssignments，借助AssignmentDistributionService通知到supervisors
computeNewSchedulerAssignments
storm-2.0.0/storm-server/src/main/java/org/apache/storm/daemon/nimbus/Nimbus.java
private Map<String, SchedulerAssignment> computeNewSchedulerAssignments(Map<String, Assignment> existingAssignments,
Topologies topologies, Map<String, StormBase> bases,
String scratchTopologyId)
throws KeyNotFoundException, AuthorizationException, InvalidTopologyException, IOException {
Map<String, Set<List<Integer>>> topoToExec = computeTopologyToExecutors(bases);
Set<String> zkHeartbeatTopologies = topologies.getTopologies().stream()
.filter(topo -> !supportRpcHeartbeat(topo))
.map(TopologyDetails::getId)
.collect(Collectors.toSet());
updateAllHeartbeats(existingAssignments, topoToExec, zkHeartbeatTopologies);
Map<String, Set<List<Integer>>> topoToAliveExecutors = computeTopologyToAliveExecutors(existingAssignments, topologies,
topoToExec, scratchTopologyId);
Map<String, Set<Long>> supervisorToDeadPorts = computeSupervisorToDeadPorts(existingAssignments, topoToExec,
topoToAliveExecutors);
Map<String, SchedulerAssignmentImpl> topoToSchedAssignment = computeTopologyToSchedulerAssignment(existingAssignments,
topoToAliveExecutors);
Set<String> missingAssignmentTopologies = new HashSet<>();
for (TopologyDetails topo : topologies.getTopologies()) {
String id = topo.getId();
Set<List<Integer>> allExecs = topoToExec.get(id);
Set<List<Integer>> aliveExecs = topoToAliveExecutors.get(id);
int numDesiredWorkers = topo.getNumWorkers();
int numAssignedWorkers = numUsedWorkers(topoToSchedAssignment.get(id));
if (allExecs == null || allExecs.isEmpty() || !allExecs.equals(aliveExecs) || numDesiredWorkers > numAssignedWorkers) {
//We have something to schedule...
missingAssignmentTopologies.add(id);
}
}
Map<String, SupervisorDetails> supervisors =
readAllSupervisorDetails(supervisorToDeadPorts, topologies, missingAssignmentTopologies);
Cluster cluster = new Cluster(inimbus, resourceMetrics, supervisors, topoToSchedAssignment, topologies, conf);
cluster.setStatusMap(idToSchedStatus.get());
schedulingStartTimeNs.set(Time.nanoTime());
scheduler.schedule(topologies, cluster);
//Get and set the start time before getting current time in order to avoid potential race with the longest-scheduling-time-ms gauge
//......
return cluster.getAssignments();
}- computeTopologyToExecutors返回的是Map<String, Set<List<Integer>>> topoToExec，key为topologyId，value为Set<List<Integer>>，Integer为executorId
- computeTopologyToAliveExecutors返回的是Map<String, Set<List<Integer>>> topoToAliveExecutors，key为topologyId，value为Set<List<Integer>>，Integer为executorId
- computeSupervisorToDeadPorts返回的是Map<String, Set<Long>> supervisorToDeadPorts，key为supervisorId，value为Set<Long>，Long为port端口
- computeTopologyToSchedulerAssignment返回的是Map<String, SchedulerAssignmentImpl> topoToSchedAssignment，key为topologyId，value为SchedulerAssignmentImpl
- 之后根据topology配置要求的woker数量及executor数量跟现有的assignment进行对比，计算出missingAssignmentTopologies
- readAllSupervisorDetails返回Map<String, SupervisorDetails> supervisors，即存活的可以分配的supervisor信息
- 最后这里创建Cluster，然后调用scheduler.schedule(topologies, cluster);进行调度
DefaultScheduler.schedule
storm-2.0.0/storm-server/src/main/java/org/apache/storm/scheduler/DefaultScheduler.java
public void schedule(Topologies topologies, Cluster cluster) {
defaultSchedule(topologies, cluster);
}
public static void defaultSchedule(Topologies topologies, Cluster cluster) {
for (TopologyDetails topology : cluster.needsSchedulingTopologies()) {
List<WorkerSlot> availableSlots = cluster.getAvailableSlots();
Set<ExecutorDetails> allExecutors = topology.getExecutors();
Map<WorkerSlot, List<ExecutorDetails>> aliveAssigned =
EvenScheduler.getAliveAssignedWorkerSlotExecutors(cluster, topology.getId());
Set<ExecutorDetails> aliveExecutors = new HashSet<ExecutorDetails>();
for (List<ExecutorDetails> list : aliveAssigned.values()) {
aliveExecutors.addAll(list);
}
Set<WorkerSlot> canReassignSlots = slotsCanReassign(cluster, aliveAssigned.keySet());
int totalSlotsToUse = Math.min(topology.getNumWorkers(), canReassignSlots.size() + availableSlots.size());
Set<WorkerSlot> badSlots = null;
if (totalSlotsToUse > aliveAssigned.size() || !allExecutors.equals(aliveExecutors)) {
badSlots = badSlots(aliveAssigned, allExecutors.size(), totalSlotsToUse);
}
if (badSlots != null) {
cluster.freeSlots(badSlots);
}
EvenScheduler.scheduleTopologiesEvenly(new Topologies(topology), cluster);
}
}- 通过cluster.needsSchedulingTopologies()遍历需要调度的TopologyDetails进行处理
- 通过cluster.getAvailableSlots()获取可用的slots
- 通过EvenScheduler.getAliveAssignedWorkerSlotExecutors获取aliveAssigned，根据aliveAssigned调用slotsCanReassign获取canReassignSlots
- Math.min(topology.getNumWorkers(), canReassignSlots.size() + availableSlots.size())计算totalSlotsToUse，对badSlots进行释放
- 最后通过EvenScheduler.scheduleTopologiesEvenly(new Topologies(topology), cluster)进行分配
EvenScheduler.scheduleTopologiesEvenly
storm-2.0.0/storm-server/src/main/java/org/apache/storm/scheduler/EvenScheduler.java
public static void scheduleTopologiesEvenly(Topologies topologies, Cluster cluster) {
for (TopologyDetails topology : cluster.needsSchedulingTopologies()) {
String topologyId = topology.getId();
Map<ExecutorDetails, WorkerSlot> newAssignment = scheduleTopology(topology, cluster);
Map<WorkerSlot, List<ExecutorDetails>> nodePortToExecutors = Utils.reverseMap(newAssignment);
for (Map.Entry<WorkerSlot, List<ExecutorDetails>> entry : nodePortToExecutors.entrySet()) {
WorkerSlot nodePort = entry.getKey();
List<ExecutorDetails> executors = entry.getValue();
cluster.assign(nodePort, topologyId, executors);
}
}
}- 通过scheduleTopology(topology, cluster)计算newAssignment，转换为Map<WorkerSlot, List<ExecutorDetails>> nodePortToExecutors
- 通过cluster.assign(nodePort, topologyId, executors)进行分配
EvenScheduler.scheduleTopology
storm-2.0.0/storm-server/src/main/java/org/apache/storm/scheduler/EvenScheduler.java
private static Map<ExecutorDetails, WorkerSlot> scheduleTopology(TopologyDetails topology, Cluster cluster) {
List<WorkerSlot> availableSlots = cluster.getAvailableSlots();
Set<ExecutorDetails> allExecutors = topology.getExecutors();
Map<WorkerSlot, List<ExecutorDetails>> aliveAssigned = getAliveAssignedWorkerSlotExecutors(cluster, topology.getId());
int totalSlotsToUse = Math.min(topology.getNumWorkers(), availableSlots.size() + aliveAssigned.size());
List<WorkerSlot> sortedList = sortSlots(availableSlots);
if (sortedList == null) {
LOG.error("No available slots for topology: {}", topology.getName());
return new HashMap<ExecutorDetails, WorkerSlot>();
}
//allow requesting slots number bigger than available slots
int toIndex = (totalSlotsToUse - aliveAssigned.size())
> sortedList.size() ? sortedList.size() : (totalSlotsToUse - aliveAssigned.size());
List<WorkerSlot> reassignSlots = sortedList.subList(0, toIndex);
Set<ExecutorDetails> aliveExecutors = new HashSet<ExecutorDetails>();
for (List<ExecutorDetails> list : aliveAssigned.values()) {
aliveExecutors.addAll(list);
}
Set<ExecutorDetails> reassignExecutors = Sets.difference(allExecutors, aliveExecutors);
Map<ExecutorDetails, WorkerSlot> reassignment = new HashMap<ExecutorDetails, WorkerSlot>();
if (reassignSlots.size() == 0) {
return reassignment;
}
List<ExecutorDetails> executors = new ArrayList<ExecutorDetails>(reassignExecutors);
Collections.sort(executors, new Comparator<ExecutorDetails>() {
@Override
public int compare(ExecutorDetails o1, ExecutorDetails o2) {
return o1.getStartTask() - o2.getStartTask();
}
});
for (int i = 0; i < executors.size(); i++) {
reassignment.put(executors.get(i), reassignSlots.get(i % reassignSlots.size()));
}
if (reassignment.size() != 0) {
LOG.info("Available slots: {}", availableSlots.toString());
}
return reassignment;
}- 根据availableSlots计算出List<WorkerSlot> reassignSlots
- 通过Sets.difference(allExecutors, aliveExecutors)计算reassignExecutors，并按startTask进行排序
- 最后遍历reassignExecutors，分配slots，slot按reassignSlots.get(i % reassignSlots.size())分配
ExecutorDetails
storm-2.0.0/storm-server/src/main/java/org/apache/storm/scheduler/ExecutorDetails.java
public class ExecutorDetails {
public final int startTask;
public final int endTask;
//......
@Override
public boolean equals(Object other) {
if (!(other instanceof ExecutorDetails)) {
return false;
}
ExecutorDetails executor = (ExecutorDetails) other;
return (this.startTask == executor.startTask) && (this.endTask == executor.endTask);
}
}- ExecutorDetails虽然起名为executor，但是里头封装的是startTask及endTask信息
- schedule的过程，其实是将标记staskTask及endTask的任务分配给slot去处理
- 注意这里重写了equals方法，根据startTask及endTask来对比，主要是前面的集合对比操作需要
Cluster.assign
storm-2.0.0/storm-server/src/main/java/org/apache/storm/scheduler/Cluster.java
/**
* Assign the slot to the executors for this topology.
*
* @throws RuntimeException if the specified slot is already occupied.
*/
public void assign(WorkerSlot slot, String topologyId, Collection<ExecutorDetails> executors) {
assertValidTopologyForModification(topologyId);
if (isSlotOccupied(slot)) {
throw new RuntimeException(
"slot: [" + slot.getNodeId() + ", " + slot.getPort() + "] is already occupied.");
}
TopologyDetails td = topologies.getById(topologyId);
if (td == null) {
throw new IllegalArgumentException(
"Trying to schedule for topo "
+ topologyId
+ " but that is not a known topology "
+ topologies.getAllIds());
}
WorkerResources resources = calculateWorkerResources(td, executors);
SchedulerAssignmentImpl assignment = assignments.get(topologyId);
if (assignment == null) {
assignment = new SchedulerAssignmentImpl(topologyId);
assignments.put(topologyId, assignment);
} else {
for (ExecutorDetails executor : executors) {
if (assignment.isExecutorAssigned(executor)) {
throw new RuntimeException(
"Attempting to assign executor: "
+ executor
+ " of topology: "
+ topologyId
+ " to workerslot: "
+ slot
+ ". The executor is already assigned to workerslot: "
+ assignment.getExecutorToSlot().get(executor)
+ ". The executor must unassigned before it can be assigned to another slot!");
}
}
}
assignment.assign(slot, executors, resources);
String nodeId = slot.getNodeId();
double sharedOffHeapMemory = calculateSharedOffHeapMemory(nodeId, assignment);
assignment.setTotalSharedOffHeapMemory(nodeId, sharedOffHeapMemory);
updateCachesForWorkerSlot(slot, resources, sharedOffHeapMemory);
totalResourcesPerNodeCache.remove(slot.getNodeId());
}- 这里主要是委托给assignment.assign(slot, executors, resources)
SchedulerAssignmentImpl.assign
storm-2.0.0/storm-server/src/main/java/org/apache/storm/scheduler/SchedulerAssignmentImpl.java
/**
* Assign the slot to executors.
*/
public void assign(WorkerSlot slot, Collection<ExecutorDetails> executors, WorkerResources slotResources) {
assert slot != null;
for (ExecutorDetails executor : executors) {
this.executorToSlot.put(executor, slot);
}
slotToExecutors.computeIfAbsent(slot, MAKE_LIST)
.addAll(executors);
if (slotResources != null) {
resources.put(slot, slotResources);
} else {
resources.remove(slot);
}
}- 给executorDetail(
startTask及endTask)分配slot
小结
- Nimbus.mkAssignments承担着调度分配的任务，主要计算newSchedulerAssignments(
Map<String, SchedulerAssignmentImpl>，key为topologyId)，期间通过scheduler.schedule(topologies, cluster);进行调度 - EvenScheduler.scheduleTopology方法是调度的核心操作，主要是对需要分配的ExecutorDetails分配slots，EvenScheduler采用的是robbin round的策略，对每个reassignExecutor，按reassignSlots.get(i % reassignSlots.size())分配slot
- ExecutorDetail里头有两个属性，一个是startTask，一个是endTask，分配的过程其实是对这些task分配slot
- 分配完之后，lockingMkAssignments里头有两个操作，一个是state.setAssignment(topoId, assignment, td.getConf())将变动的assignment存储到zk；另外一个是调用notifySupervisorsAssignments方法，通知到supervisor，supervisor接收到之后更新本地内存
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