Examples with Assignment org.apache.kafka.connect.runtime.distributed.ConnectProtocol.Assignment used on opensource projects

Example 1 with Assignment

use of org.apache.kafka.connect.runtime.distributed.ConnectProtocol.Assignment in project kafka by apache.

the class IncrementalCooperativeAssignor method performTaskAssignment.

/**
 * Performs task assignment based on the incremental cooperative connect protocol.
 * Read more on the design and implementation in:
 * {@see https://cwiki.apache.org/confluence/display/KAFKA/KIP-415%3A+Incremental+Cooperative+Rebalancing+in+Kafka+Connect}
 *
 * @param leaderId the ID of the group leader
 * @param maxOffset the latest known offset of the configuration topic
 * @param memberConfigs the metadata of all the members of the group as gather in the current
 * round of rebalancing
 * @param coordinator the worker coordinator instance that provide the configuration snapshot
 * and get assigned the leader state during this assignment
 * @param protocolVersion the Connect subprotocol version
 * @return the serialized assignment of tasks to the whole group, including assigned or
 * revoked tasks
 */
protected Map<String, ByteBuffer> performTaskAssignment(String leaderId, long maxOffset, Map<String, ExtendedWorkerState> memberConfigs, WorkerCoordinator coordinator, short protocolVersion) {
    log.debug("Performing task assignment during generation: {} with memberId: {}", coordinator.generationId(), coordinator.memberId());
    // Base set: The previous assignment of connectors-and-tasks is a standalone snapshot that
    // can be used to calculate derived sets
    log.debug("Previous assignments: {}", previousAssignment);
    int lastCompletedGenerationId = coordinator.lastCompletedGenerationId();
    if (previousGenerationId != lastCompletedGenerationId) {
        log.debug("Clearing the view of previous assignments due to generation mismatch between " + "previous generation ID {} and last completed generation ID {}. This can " + "happen if the leader fails to sync the assignment within a rebalancing round. " + "The following view of previous assignments might be outdated and will be " + "ignored by the leader in the current computation of new assignments. " + "Possibly outdated previous assignments: {}", previousGenerationId, lastCompletedGenerationId, previousAssignment);
        this.previousAssignment = ConnectorsAndTasks.EMPTY;
    }
    ClusterConfigState snapshot = coordinator.configSnapshot();
    Set<String> configuredConnectors = new TreeSet<>(snapshot.connectors());
    Set<ConnectorTaskId> configuredTasks = configuredConnectors.stream().flatMap(c -> snapshot.tasks(c).stream()).collect(Collectors.toSet());
    // Base set: The set of configured connectors-and-tasks is a standalone snapshot that can
    // be used to calculate derived sets
    ConnectorsAndTasks configured = new ConnectorsAndTasks.Builder().with(configuredConnectors, configuredTasks).build();
    log.debug("Configured assignments: {}", configured);
    // Base set: The set of active connectors-and-tasks is a standalone snapshot that can be
    // used to calculate derived sets
    ConnectorsAndTasks activeAssignments = assignment(memberConfigs);
    log.debug("Active assignments: {}", activeAssignments);
    // appropriately and be ready to re-apply revocation of tasks
    if (!previousRevocation.isEmpty()) {
        if (previousRevocation.connectors().stream().anyMatch(c -> activeAssignments.connectors().contains(c)) || previousRevocation.tasks().stream().anyMatch(t -> activeAssignments.tasks().contains(t))) {
            previousAssignment = activeAssignments;
            canRevoke = true;
        }
        previousRevocation.connectors().clear();
        previousRevocation.tasks().clear();
    }
    // Derived set: The set of deleted connectors-and-tasks is a derived set from the set
    // difference of previous - configured
    ConnectorsAndTasks deleted = diff(previousAssignment, configured);
    log.debug("Deleted assignments: {}", deleted);
    // Derived set: The set of remaining active connectors-and-tasks is a derived set from the
    // set difference of active - deleted
    ConnectorsAndTasks remainingActive = diff(activeAssignments, deleted);
    log.debug("Remaining (excluding deleted) active assignments: {}", remainingActive);
    // Derived set: The set of lost or unaccounted connectors-and-tasks is a derived set from
    // the set difference of previous - active - deleted
    ConnectorsAndTasks lostAssignments = diff(previousAssignment, activeAssignments, deleted);
    log.debug("Lost assignments: {}", lostAssignments);
    // Derived set: The set of new connectors-and-tasks is a derived set from the set
    // difference of configured - previous - active
    ConnectorsAndTasks newSubmissions = diff(configured, previousAssignment, activeAssignments);
    log.debug("New assignments: {}", newSubmissions);
    // A collection of the complete assignment
    List<WorkerLoad> completeWorkerAssignment = workerAssignment(memberConfigs, ConnectorsAndTasks.EMPTY);
    log.debug("Complete (ignoring deletions) worker assignments: {}", completeWorkerAssignment);
    // Per worker connector assignments without removing deleted connectors yet
    Map<String, Collection<String>> connectorAssignments = completeWorkerAssignment.stream().collect(Collectors.toMap(WorkerLoad::worker, WorkerLoad::connectors));
    log.debug("Complete (ignoring deletions) connector assignments: {}", connectorAssignments);
    // Per worker task assignments without removing deleted connectors yet
    Map<String, Collection<ConnectorTaskId>> taskAssignments = completeWorkerAssignment.stream().collect(Collectors.toMap(WorkerLoad::worker, WorkerLoad::tasks));
    log.debug("Complete (ignoring deletions) task assignments: {}", taskAssignments);
    // A collection of the current assignment excluding the connectors-and-tasks to be deleted
    List<WorkerLoad> currentWorkerAssignment = workerAssignment(memberConfigs, deleted);
    Map<String, ConnectorsAndTasks> toRevoke = computeDeleted(deleted, connectorAssignments, taskAssignments);
    log.debug("Connector and task to delete assignments: {}", toRevoke);
    // Revoking redundant connectors/tasks if the workers have duplicate assignments
    toRevoke.putAll(computeDuplicatedAssignments(memberConfigs, connectorAssignments, taskAssignments));
    log.debug("Connector and task to revoke assignments (include duplicated assignments): {}", toRevoke);
    // Recompute the complete assignment excluding the deleted connectors-and-tasks
    completeWorkerAssignment = workerAssignment(memberConfigs, deleted);
    connectorAssignments = completeWorkerAssignment.stream().collect(Collectors.toMap(WorkerLoad::worker, WorkerLoad::connectors));
    taskAssignments = completeWorkerAssignment.stream().collect(Collectors.toMap(WorkerLoad::worker, WorkerLoad::tasks));
    handleLostAssignments(lostAssignments, newSubmissions, completeWorkerAssignment, memberConfigs);
    // Do not revoke resources for re-assignment while a delayed rebalance is active
    // Also we do not revoke in two consecutive rebalances by the same leader
    canRevoke = delay == 0 && canRevoke;
    // Compute the connectors-and-tasks to be revoked for load balancing without taking into
    // account the deleted ones.
    log.debug("Can leader revoke tasks in this assignment? {} (delay: {})", canRevoke, delay);
    if (canRevoke) {
        Map<String, ConnectorsAndTasks> toExplicitlyRevoke = performTaskRevocation(activeAssignments, currentWorkerAssignment);
        log.debug("Connector and task to revoke assignments: {}", toRevoke);
        toExplicitlyRevoke.forEach((worker, assignment) -> {
            ConnectorsAndTasks existing = toRevoke.computeIfAbsent(worker, v -> new ConnectorsAndTasks.Builder().build());
            existing.connectors().addAll(assignment.connectors());
            existing.tasks().addAll(assignment.tasks());
        });
        canRevoke = toExplicitlyRevoke.size() == 0;
    } else {
        canRevoke = delay == 0;
    }
    assignConnectors(completeWorkerAssignment, newSubmissions.connectors());
    assignTasks(completeWorkerAssignment, newSubmissions.tasks());
    log.debug("Current complete assignments: {}", currentWorkerAssignment);
    log.debug("New complete assignments: {}", completeWorkerAssignment);
    Map<String, Collection<String>> currentConnectorAssignments = currentWorkerAssignment.stream().collect(Collectors.toMap(WorkerLoad::worker, WorkerLoad::connectors));
    Map<String, Collection<ConnectorTaskId>> currentTaskAssignments = currentWorkerAssignment.stream().collect(Collectors.toMap(WorkerLoad::worker, WorkerLoad::tasks));
    Map<String, Collection<String>> incrementalConnectorAssignments = diff(connectorAssignments, currentConnectorAssignments);
    Map<String, Collection<ConnectorTaskId>> incrementalTaskAssignments = diff(taskAssignments, currentTaskAssignments);
    log.debug("Incremental connector assignments: {}", incrementalConnectorAssignments);
    log.debug("Incremental task assignments: {}", incrementalTaskAssignments);
    coordinator.leaderState(new LeaderState(memberConfigs, connectorAssignments, taskAssignments));
    Map<String, ExtendedAssignment> assignments = fillAssignments(memberConfigs.keySet(), Assignment.NO_ERROR, leaderId, memberConfigs.get(leaderId).url(), maxOffset, incrementalConnectorAssignments, incrementalTaskAssignments, toRevoke, delay, protocolVersion);
    previousAssignment = computePreviousAssignment(toRevoke, connectorAssignments, taskAssignments, lostAssignments);
    previousGenerationId = coordinator.generationId();
    previousMembers = memberConfigs.keySet();
    log.debug("Actual assignments: {}", assignments);
    return serializeAssignments(assignments);
}

Example 2 with Assignment

use of org.apache.kafka.connect.runtime.distributed.ConnectProtocol.Assignment in project kafka by apache.

the class IncrementalCooperativeAssignor method performTaskRevocation.

/**
 * Task revocation is based on an rough estimation of the lower average number of tasks before
 * and after new workers join the group. If no new workers join, no revocation takes place.
 * Based on this estimation, tasks are revoked until the new floor average is reached for
 * each existing worker. The revoked tasks, once assigned to the new workers will maintain
 * a balanced load among the group.
 *
 * @param activeAssignments
 * @param completeWorkerAssignment
 * @return
 */
private Map<String, ConnectorsAndTasks> performTaskRevocation(ConnectorsAndTasks activeAssignments, Collection<WorkerLoad> completeWorkerAssignment) {
    int totalActiveConnectorsNum = activeAssignments.connectors().size();
    int totalActiveTasksNum = activeAssignments.tasks().size();
    Collection<WorkerLoad> existingWorkers = completeWorkerAssignment.stream().filter(wl -> wl.size() > 0).collect(Collectors.toList());
    int existingWorkersNum = existingWorkers.size();
    int totalWorkersNum = completeWorkerAssignment.size();
    int newWorkersNum = totalWorkersNum - existingWorkersNum;
    if (log.isDebugEnabled()) {
        completeWorkerAssignment.forEach(wl -> log.debug("Per worker current load size; worker: {} connectors: {} tasks: {}", wl.worker(), wl.connectorsSize(), wl.tasksSize()));
    }
    Map<String, ConnectorsAndTasks> revoking = new HashMap<>();
    // after logging the status
    if (!(newWorkersNum > 0 && existingWorkersNum > 0)) {
        log.debug("No task revocation required; workers with existing load: {} workers with " + "no load {} total workers {}", existingWorkersNum, newWorkersNum, totalWorkersNum);
        // connectors and tasks as well
        return revoking;
    }
    log.debug("Task revocation is required; workers with existing load: {} workers with " + "no load {} total workers {}", existingWorkersNum, newWorkersNum, totalWorkersNum);
    // We have at least one worker assignment (the leader itself) so totalWorkersNum can't be 0
    log.debug("Previous rounded down (floor) average number of connectors per worker {}", totalActiveConnectorsNum / existingWorkersNum);
    int floorConnectors = totalActiveConnectorsNum / totalWorkersNum;
    int ceilConnectors = floorConnectors + ((totalActiveConnectorsNum % totalWorkersNum == 0) ? 0 : 1);
    log.debug("New average number of connectors per worker rounded down (floor) {} and rounded up (ceil) {}", floorConnectors, ceilConnectors);
    log.debug("Previous rounded down (floor) average number of tasks per worker {}", totalActiveTasksNum / existingWorkersNum);
    int floorTasks = totalActiveTasksNum / totalWorkersNum;
    int ceilTasks = floorTasks + ((totalActiveTasksNum % totalWorkersNum == 0) ? 0 : 1);
    log.debug("New average number of tasks per worker rounded down (floor) {} and rounded up (ceil) {}", floorTasks, ceilTasks);
    int numToRevoke;
    for (WorkerLoad existing : existingWorkers) {
        Iterator<String> connectors = existing.connectors().iterator();
        numToRevoke = existing.connectorsSize() - ceilConnectors;
        for (int i = existing.connectorsSize(); i > floorConnectors && numToRevoke > 0; --i, --numToRevoke) {
            ConnectorsAndTasks resources = revoking.computeIfAbsent(existing.worker(), w -> new ConnectorsAndTasks.Builder().build());
            resources.connectors().add(connectors.next());
        }
    }
    for (WorkerLoad existing : existingWorkers) {
        Iterator<ConnectorTaskId> tasks = existing.tasks().iterator();
        numToRevoke = existing.tasksSize() - ceilTasks;
        log.debug("Tasks on worker {} is higher than ceiling, so revoking {} tasks", existing, numToRevoke);
        for (int i = existing.tasksSize(); i > floorTasks && numToRevoke > 0; --i, --numToRevoke) {
            ConnectorsAndTasks resources = revoking.computeIfAbsent(existing.worker(), w -> new ConnectorsAndTasks.Builder().build());
            resources.tasks().add(tasks.next());
        }
    }
    return revoking;
}

Example 3 with Assignment

use of org.apache.kafka.connect.runtime.distributed.ConnectProtocol.Assignment in project kafka by apache.

the class EagerAssignor method fillAssignmentsAndSerialize.

private Map<String, ByteBuffer> fillAssignmentsAndSerialize(Collection<String> members, short error, String leaderId, String leaderUrl, long maxOffset, Map<String, Collection<String>> connectorAssignments, Map<String, Collection<ConnectorTaskId>> taskAssignments) {
    Map<String, ByteBuffer> groupAssignment = new HashMap<>();
    for (String member : members) {
        Collection<String> connectors = connectorAssignments.get(member);
        if (connectors == null) {
            connectors = Collections.emptyList();
        }
        Collection<ConnectorTaskId> tasks = taskAssignments.get(member);
        if (tasks == null) {
            tasks = Collections.emptyList();
        }
        Assignment assignment = new Assignment(error, leaderId, leaderUrl, maxOffset, connectors, tasks);
        log.debug("Assignment: {} -> {}", member, assignment);
        groupAssignment.put(member, ConnectProtocol.serializeAssignment(assignment));
    }
    log.debug("Finished assignment");
    return groupAssignment;
}

Example 4 with Assignment

use of org.apache.kafka.connect.runtime.distributed.ConnectProtocol.Assignment in project kafka by apache.

the class IncrementalCooperativeAssignor method performAssignment.

@Override
public Map<String, ByteBuffer> performAssignment(String leaderId, String protocol, List<JoinGroupResponseMember> allMemberMetadata, WorkerCoordinator coordinator) {
    log.debug("Performing task assignment");
    Map<String, ExtendedWorkerState> memberConfigs = new HashMap<>();
    for (JoinGroupResponseMember member : allMemberMetadata) {
        memberConfigs.put(member.memberId(), IncrementalCooperativeConnectProtocol.deserializeMetadata(ByteBuffer.wrap(member.metadata())));
    }
    log.debug("Member configs: {}", memberConfigs);
    // The new config offset is the maximum seen by any member. We always perform assignment using this offset,
    // even if some members have fallen behind. The config offset used to generate the assignment is included in
    // the response so members that have fallen behind will not use the assignment until they have caught up.
    long maxOffset = memberConfigs.values().stream().map(ExtendedWorkerState::offset).max(Long::compare).get();
    log.debug("Max config offset root: {}, local snapshot config offsets root: {}", maxOffset, coordinator.configSnapshot().offset());
    short protocolVersion = memberConfigs.values().stream().allMatch(state -> state.assignment().version() == CONNECT_PROTOCOL_V2) ? CONNECT_PROTOCOL_V2 : CONNECT_PROTOCOL_V1;
    Long leaderOffset = ensureLeaderConfig(maxOffset, coordinator);
    if (leaderOffset == null) {
        Map<String, ExtendedAssignment> assignments = fillAssignments(memberConfigs.keySet(), Assignment.CONFIG_MISMATCH, leaderId, memberConfigs.get(leaderId).url(), maxOffset, Collections.emptyMap(), Collections.emptyMap(), Collections.emptyMap(), 0, protocolVersion);
        return serializeAssignments(assignments);
    }
    return performTaskAssignment(leaderId, leaderOffset, memberConfigs, coordinator, protocolVersion);
}