diff --git a/vendor/github.com/Shopify/sarama/balance_strategy.go b/vendor/github.com/Shopify/sarama/balance_strategy.go
new file mode 100644
index 0000000..9855bf4
--- /dev/null
+++ b/vendor/github.com/Shopify/sarama/balance_strategy.go
@@ -0,0 +1,1136 @@
+package sarama
+
+import (
+	"container/heap"
+	"errors"
+	"fmt"
+	"math"
+	"sort"
+	"strings"
+)
+
+const (
+	// RangeBalanceStrategyName identifies strategies that use the range partition assignment strategy
+	RangeBalanceStrategyName = "range"
+
+	// RoundRobinBalanceStrategyName identifies strategies that use the round-robin partition assignment strategy
+	RoundRobinBalanceStrategyName = "roundrobin"
+
+	// StickyBalanceStrategyName identifies strategies that use the sticky-partition assignment strategy
+	StickyBalanceStrategyName = "sticky"
+
+	defaultGeneration = -1
+)
+
+// BalanceStrategyPlan is the results of any BalanceStrategy.Plan attempt.
+// It contains an allocation of topic/partitions by memberID in the form of
+// a `memberID -> topic -> partitions` map.
+type BalanceStrategyPlan map[string]map[string][]int32
+
+// Add assigns a topic with a number partitions to a member.
+func (p BalanceStrategyPlan) Add(memberID, topic string, partitions ...int32) {
+	if len(partitions) == 0 {
+		return
+	}
+	if _, ok := p[memberID]; !ok {
+		p[memberID] = make(map[string][]int32, 1)
+	}
+	p[memberID][topic] = append(p[memberID][topic], partitions...)
+}
+
+// --------------------------------------------------------------------
+
+// BalanceStrategy is used to balance topics and partitions
+// across members of a consumer group
+type BalanceStrategy interface {
+	// Name uniquely identifies the strategy.
+	Name() string
+
+	// Plan accepts a map of `memberID -> metadata` and a map of `topic -> partitions`
+	// and returns a distribution plan.
+	Plan(members map[string]ConsumerGroupMemberMetadata, topics map[string][]int32) (BalanceStrategyPlan, error)
+
+	// AssignmentData returns the serialized assignment data for the specified
+	// memberID
+	AssignmentData(memberID string, topics map[string][]int32, generationID int32) ([]byte, error)
+}
+
+// --------------------------------------------------------------------
+
+// BalanceStrategyRange is the default and assigns partitions as ranges to consumer group members.
+// Example with one topic T with six partitions (0..5) and two members (M1, M2):
+//   M1: {T: [0, 1, 2]}
+//   M2: {T: [3, 4, 5]}
+var BalanceStrategyRange = &balanceStrategy{
+	name: RangeBalanceStrategyName,
+	coreFn: func(plan BalanceStrategyPlan, memberIDs []string, topic string, partitions []int32) {
+		step := float64(len(partitions)) / float64(len(memberIDs))
+
+		for i, memberID := range memberIDs {
+			pos := float64(i)
+			min := int(math.Floor(pos*step + 0.5))
+			max := int(math.Floor((pos+1)*step + 0.5))
+			plan.Add(memberID, topic, partitions[min:max]...)
+		}
+	},
+}
+
+// BalanceStrategySticky assigns partitions to members with an attempt to preserve earlier assignments
+// while maintain a balanced partition distribution.
+// Example with topic T with six partitions (0..5) and two members (M1, M2):
+//   M1: {T: [0, 2, 4]}
+//   M2: {T: [1, 3, 5]}
+//
+// On reassignment with an additional consumer, you might get an assignment plan like:
+//   M1: {T: [0, 2]}
+//   M2: {T: [1, 3]}
+//   M3: {T: [4, 5]}
+//
+var BalanceStrategySticky = &stickyBalanceStrategy{}
+
+// --------------------------------------------------------------------
+
+type balanceStrategy struct {
+	name   string
+	coreFn func(plan BalanceStrategyPlan, memberIDs []string, topic string, partitions []int32)
+}
+
+// Name implements BalanceStrategy.
+func (s *balanceStrategy) Name() string { return s.name }
+
+// Plan implements BalanceStrategy.
+func (s *balanceStrategy) Plan(members map[string]ConsumerGroupMemberMetadata, topics map[string][]int32) (BalanceStrategyPlan, error) {
+	// Build members by topic map
+	mbt := make(map[string][]string)
+	for memberID, meta := range members {
+		for _, topic := range meta.Topics {
+			mbt[topic] = append(mbt[topic], memberID)
+		}
+	}
+
+	// Sort members for each topic
+	for topic, memberIDs := range mbt {
+		sort.Sort(&balanceStrategySortable{
+			topic:     topic,
+			memberIDs: memberIDs,
+		})
+	}
+
+	// Assemble plan
+	plan := make(BalanceStrategyPlan, len(members))
+	for topic, memberIDs := range mbt {
+		s.coreFn(plan, memberIDs, topic, topics[topic])
+	}
+	return plan, nil
+}
+
+// AssignmentData simple strategies do not require any shared assignment data
+func (s *balanceStrategy) AssignmentData(memberID string, topics map[string][]int32, generationID int32) ([]byte, error) {
+	return nil, nil
+}
+
+type balanceStrategySortable struct {
+	topic     string
+	memberIDs []string
+}
+
+func (p balanceStrategySortable) Len() int { return len(p.memberIDs) }
+func (p balanceStrategySortable) Swap(i, j int) {
+	p.memberIDs[i], p.memberIDs[j] = p.memberIDs[j], p.memberIDs[i]
+}
+
+func (p balanceStrategySortable) Less(i, j int) bool {
+	return balanceStrategyHashValue(p.topic, p.memberIDs[i]) < balanceStrategyHashValue(p.topic, p.memberIDs[j])
+}
+
+func balanceStrategyHashValue(vv ...string) uint32 {
+	h := uint32(2166136261)
+	for _, s := range vv {
+		for _, c := range s {
+			h ^= uint32(c)
+			h *= 16777619
+		}
+	}
+	return h
+}
+
+type stickyBalanceStrategy struct {
+	movements partitionMovements
+}
+
+// Name implements BalanceStrategy.
+func (s *stickyBalanceStrategy) Name() string { return StickyBalanceStrategyName }
+
+// Plan implements BalanceStrategy.
+func (s *stickyBalanceStrategy) Plan(members map[string]ConsumerGroupMemberMetadata, topics map[string][]int32) (BalanceStrategyPlan, error) {
+	// track partition movements during generation of the partition assignment plan
+	s.movements = partitionMovements{
+		Movements:                 make(map[topicPartitionAssignment]consumerPair),
+		PartitionMovementsByTopic: make(map[string]map[consumerPair]map[topicPartitionAssignment]bool),
+	}
+
+	// prepopulate the current assignment state from userdata on the consumer group members
+	currentAssignment, prevAssignment, err := prepopulateCurrentAssignments(members)
+	if err != nil {
+		return nil, err
+	}
+
+	// determine if we're dealing with a completely fresh assignment, or if there's existing assignment state
+	isFreshAssignment := false
+	if len(currentAssignment) == 0 {
+		isFreshAssignment = true
+	}
+
+	// create a mapping of all current topic partitions and the consumers that can be assigned to them
+	partition2AllPotentialConsumers := make(map[topicPartitionAssignment][]string)
+	for topic, partitions := range topics {
+		for _, partition := range partitions {
+			partition2AllPotentialConsumers[topicPartitionAssignment{Topic: topic, Partition: partition}] = []string{}
+		}
+	}
+
+	// create a mapping of all consumers to all potential topic partitions that can be assigned to them
+	// also, populate the mapping of partitions to potential consumers
+	consumer2AllPotentialPartitions := make(map[string][]topicPartitionAssignment, len(members))
+	for memberID, meta := range members {
+		consumer2AllPotentialPartitions[memberID] = make([]topicPartitionAssignment, 0)
+		for _, topicSubscription := range meta.Topics {
+			// only evaluate topic subscriptions that are present in the supplied topics map
+			if _, found := topics[topicSubscription]; found {
+				for _, partition := range topics[topicSubscription] {
+					topicPartition := topicPartitionAssignment{Topic: topicSubscription, Partition: partition}
+					consumer2AllPotentialPartitions[memberID] = append(consumer2AllPotentialPartitions[memberID], topicPartition)
+					partition2AllPotentialConsumers[topicPartition] = append(partition2AllPotentialConsumers[topicPartition], memberID)
+				}
+			}
+		}
+
+		// add this consumer to currentAssignment (with an empty topic partition assignment) if it does not already exist
+		if _, exists := currentAssignment[memberID]; !exists {
+			currentAssignment[memberID] = make([]topicPartitionAssignment, 0)
+		}
+	}
+
+	// create a mapping of each partition to its current consumer, where possible
+	currentPartitionConsumers := make(map[topicPartitionAssignment]string, len(currentAssignment))
+	unvisitedPartitions := make(map[topicPartitionAssignment]bool, len(partition2AllPotentialConsumers))
+	for partition := range partition2AllPotentialConsumers {
+		unvisitedPartitions[partition] = true
+	}
+	var unassignedPartitions []topicPartitionAssignment
+	for memberID, partitions := range currentAssignment {
+		var keepPartitions []topicPartitionAssignment
+		for _, partition := range partitions {
+			// If this partition no longer exists at all, likely due to the
+			// topic being deleted, we remove the partition from the member.
+			if _, exists := partition2AllPotentialConsumers[partition]; !exists {
+				continue
+			}
+			delete(unvisitedPartitions, partition)
+			currentPartitionConsumers[partition] = memberID
+
+			if !strsContains(members[memberID].Topics, partition.Topic) {
+				unassignedPartitions = append(unassignedPartitions, partition)
+				continue
+			}
+			keepPartitions = append(keepPartitions, partition)
+		}
+		currentAssignment[memberID] = keepPartitions
+	}
+	for unvisited := range unvisitedPartitions {
+		unassignedPartitions = append(unassignedPartitions, unvisited)
+	}
+
+	// sort the topic partitions in order of priority for reassignment
+	sortedPartitions := sortPartitions(currentAssignment, prevAssignment, isFreshAssignment, partition2AllPotentialConsumers, consumer2AllPotentialPartitions)
+
+	// at this point we have preserved all valid topic partition to consumer assignments and removed
+	// all invalid topic partitions and invalid consumers. Now we need to assign unassignedPartitions
+	// to consumers so that the topic partition assignments are as balanced as possible.
+
+	// an ascending sorted set of consumers based on how many topic partitions are already assigned to them
+	sortedCurrentSubscriptions := sortMemberIDsByPartitionAssignments(currentAssignment)
+	s.balance(currentAssignment, prevAssignment, sortedPartitions, unassignedPartitions, sortedCurrentSubscriptions, consumer2AllPotentialPartitions, partition2AllPotentialConsumers, currentPartitionConsumers)
+
+	// Assemble plan
+	plan := make(BalanceStrategyPlan, len(currentAssignment))
+	for memberID, assignments := range currentAssignment {
+		if len(assignments) == 0 {
+			plan[memberID] = make(map[string][]int32)
+		} else {
+			for _, assignment := range assignments {
+				plan.Add(memberID, assignment.Topic, assignment.Partition)
+			}
+		}
+	}
+	return plan, nil
+}
+
+// AssignmentData serializes the set of topics currently assigned to the
+// specified member as part of the supplied balance plan
+func (s *stickyBalanceStrategy) AssignmentData(memberID string, topics map[string][]int32, generationID int32) ([]byte, error) {
+	return encode(&StickyAssignorUserDataV1{
+		Topics:     topics,
+		Generation: generationID,
+	}, nil)
+}
+
+func strsContains(s []string, value string) bool {
+	for _, entry := range s {
+		if entry == value {
+			return true
+		}
+	}
+	return false
+}
+
+// Balance assignments across consumers for maximum fairness and stickiness.
+func (s *stickyBalanceStrategy) balance(currentAssignment map[string][]topicPartitionAssignment, prevAssignment map[topicPartitionAssignment]consumerGenerationPair, sortedPartitions []topicPartitionAssignment, unassignedPartitions []topicPartitionAssignment, sortedCurrentSubscriptions []string, consumer2AllPotentialPartitions map[string][]topicPartitionAssignment, partition2AllPotentialConsumers map[topicPartitionAssignment][]string, currentPartitionConsumer map[topicPartitionAssignment]string) {
+	initializing := false
+	if len(sortedCurrentSubscriptions) == 0 || len(currentAssignment[sortedCurrentSubscriptions[0]]) == 0 {
+		initializing = true
+	}
+
+	// assign all unassigned partitions
+	for _, partition := range unassignedPartitions {
+		// skip if there is no potential consumer for the partition
+		if len(partition2AllPotentialConsumers[partition]) == 0 {
+			continue
+		}
+		sortedCurrentSubscriptions = assignPartition(partition, sortedCurrentSubscriptions, currentAssignment, consumer2AllPotentialPartitions, currentPartitionConsumer)
+	}
+
+	// narrow down the reassignment scope to only those partitions that can actually be reassigned
+	for partition := range partition2AllPotentialConsumers {
+		if !canTopicPartitionParticipateInReassignment(partition, partition2AllPotentialConsumers) {
+			sortedPartitions = removeTopicPartitionFromMemberAssignments(sortedPartitions, partition)
+		}
+	}
+
+	// narrow down the reassignment scope to only those consumers that are subject to reassignment
+	fixedAssignments := make(map[string][]topicPartitionAssignment)
+	for memberID := range consumer2AllPotentialPartitions {
+		if !canConsumerParticipateInReassignment(memberID, currentAssignment, consumer2AllPotentialPartitions, partition2AllPotentialConsumers) {
+			fixedAssignments[memberID] = currentAssignment[memberID]
+			delete(currentAssignment, memberID)
+			sortedCurrentSubscriptions = sortMemberIDsByPartitionAssignments(currentAssignment)
+		}
+	}
+
+	// create a deep copy of the current assignment so we can revert to it if we do not get a more balanced assignment later
+	preBalanceAssignment := deepCopyAssignment(currentAssignment)
+	preBalancePartitionConsumers := make(map[topicPartitionAssignment]string, len(currentPartitionConsumer))
+	for k, v := range currentPartitionConsumer {
+		preBalancePartitionConsumers[k] = v
+	}
+
+	reassignmentPerformed := s.performReassignments(sortedPartitions, currentAssignment, prevAssignment, sortedCurrentSubscriptions, consumer2AllPotentialPartitions, partition2AllPotentialConsumers, currentPartitionConsumer)
+
+	// if we are not preserving existing assignments and we have made changes to the current assignment
+	// make sure we are getting a more balanced assignment; otherwise, revert to previous assignment
+	if !initializing && reassignmentPerformed && getBalanceScore(currentAssignment) >= getBalanceScore(preBalanceAssignment) {
+		currentAssignment = deepCopyAssignment(preBalanceAssignment)
+		currentPartitionConsumer = make(map[topicPartitionAssignment]string, len(preBalancePartitionConsumers))
+		for k, v := range preBalancePartitionConsumers {
+			currentPartitionConsumer[k] = v
+		}
+	}
+
+	// add the fixed assignments (those that could not change) back
+	for consumer, assignments := range fixedAssignments {
+		currentAssignment[consumer] = assignments
+	}
+}
+
+// BalanceStrategyRoundRobin assigns partitions to members in alternating order.
+// For example, there are two topics (t0, t1) and two consumer (m0, m1), and each topic has three partitions (p0, p1, p2):
+// M0: [t0p0, t0p2, t1p1]
+// M1: [t0p1, t1p0, t1p2]
+var BalanceStrategyRoundRobin = new(roundRobinBalancer)
+
+type roundRobinBalancer struct{}
+
+func (b *roundRobinBalancer) Name() string {
+	return RoundRobinBalanceStrategyName
+}
+
+func (b *roundRobinBalancer) Plan(memberAndMetadata map[string]ConsumerGroupMemberMetadata, topics map[string][]int32) (BalanceStrategyPlan, error) {
+	if len(memberAndMetadata) == 0 || len(topics) == 0 {
+		return nil, errors.New("members and topics are not provided")
+	}
+	// sort partitions
+	var topicPartitions []topicAndPartition
+	for topic, partitions := range topics {
+		for _, partition := range partitions {
+			topicPartitions = append(topicPartitions, topicAndPartition{topic: topic, partition: partition})
+		}
+	}
+	sort.SliceStable(topicPartitions, func(i, j int) bool {
+		pi := topicPartitions[i]
+		pj := topicPartitions[j]
+		return pi.comparedValue() < pj.comparedValue()
+	})
+
+	// sort members
+	var members []memberAndTopic
+	for memberID, meta := range memberAndMetadata {
+		m := memberAndTopic{
+			memberID: memberID,
+			topics:   make(map[string]struct{}),
+		}
+		for _, t := range meta.Topics {
+			m.topics[t] = struct{}{}
+		}
+		members = append(members, m)
+	}
+	sort.SliceStable(members, func(i, j int) bool {
+		mi := members[i]
+		mj := members[j]
+		return mi.memberID < mj.memberID
+	})
+
+	// assign partitions
+	plan := make(BalanceStrategyPlan, len(members))
+	i := 0
+	n := len(members)
+	for _, tp := range topicPartitions {
+		m := members[i%n]
+		for !m.hasTopic(tp.topic) {
+			i++
+			m = members[i%n]
+		}
+		plan.Add(m.memberID, tp.topic, tp.partition)
+		i++
+	}
+	return plan, nil
+}
+
+func (b *roundRobinBalancer) AssignmentData(memberID string, topics map[string][]int32, generationID int32) ([]byte, error) {
+	return nil, nil // do nothing for now
+}
+
+type topicAndPartition struct {
+	topic     string
+	partition int32
+}
+
+func (tp *topicAndPartition) comparedValue() string {
+	return fmt.Sprintf("%s-%d", tp.topic, tp.partition)
+}
+
+type memberAndTopic struct {
+	memberID string
+	topics   map[string]struct{}
+}
+
+func (m *memberAndTopic) hasTopic(topic string) bool {
+	_, isExist := m.topics[topic]
+	return isExist
+}
+
+// Calculate the balance score of the given assignment, as the sum of assigned partitions size difference of all consumer pairs.
+// A perfectly balanced assignment (with all consumers getting the same number of partitions) has a balance score of 0.
+// Lower balance score indicates a more balanced assignment.
+func getBalanceScore(assignment map[string][]topicPartitionAssignment) int {
+	consumer2AssignmentSize := make(map[string]int, len(assignment))
+	for memberID, partitions := range assignment {
+		consumer2AssignmentSize[memberID] = len(partitions)
+	}
+
+	var score float64
+	for memberID, consumerAssignmentSize := range consumer2AssignmentSize {
+		delete(consumer2AssignmentSize, memberID)
+		for _, otherConsumerAssignmentSize := range consumer2AssignmentSize {
+			score += math.Abs(float64(consumerAssignmentSize - otherConsumerAssignmentSize))
+		}
+	}
+	return int(score)
+}
+
+// Determine whether the current assignment plan is balanced.
+func isBalanced(currentAssignment map[string][]topicPartitionAssignment, allSubscriptions map[string][]topicPartitionAssignment) bool {
+	sortedCurrentSubscriptions := sortMemberIDsByPartitionAssignments(currentAssignment)
+	min := len(currentAssignment[sortedCurrentSubscriptions[0]])
+	max := len(currentAssignment[sortedCurrentSubscriptions[len(sortedCurrentSubscriptions)-1]])
+	if min >= max-1 {
+		// if minimum and maximum numbers of partitions assigned to consumers differ by at most one return true
+		return true
+	}
+
+	// create a mapping from partitions to the consumer assigned to them
+	allPartitions := make(map[topicPartitionAssignment]string)
+	for memberID, partitions := range currentAssignment {
+		for _, partition := range partitions {
+			if _, exists := allPartitions[partition]; exists {
+				Logger.Printf("Topic %s Partition %d is assigned more than one consumer", partition.Topic, partition.Partition)
+			}
+			allPartitions[partition] = memberID
+		}
+	}
+
+	// for each consumer that does not have all the topic partitions it can get make sure none of the topic partitions it
+	// could but did not get cannot be moved to it (because that would break the balance)
+	for _, memberID := range sortedCurrentSubscriptions {
+		consumerPartitions := currentAssignment[memberID]
+		consumerPartitionCount := len(consumerPartitions)
+
+		// skip if this consumer already has all the topic partitions it can get
+		if consumerPartitionCount == len(allSubscriptions[memberID]) {
+			continue
+		}
+
+		// otherwise make sure it cannot get any more
+		potentialTopicPartitions := allSubscriptions[memberID]
+		for _, partition := range potentialTopicPartitions {
+			if !memberAssignmentsIncludeTopicPartition(currentAssignment[memberID], partition) {
+				otherConsumer := allPartitions[partition]
+				otherConsumerPartitionCount := len(currentAssignment[otherConsumer])
+				if consumerPartitionCount < otherConsumerPartitionCount {
+					return false
+				}
+			}
+		}
+	}
+	return true
+}
+
+// Reassign all topic partitions that need reassignment until balanced.
+func (s *stickyBalanceStrategy) performReassignments(reassignablePartitions []topicPartitionAssignment, currentAssignment map[string][]topicPartitionAssignment, prevAssignment map[topicPartitionAssignment]consumerGenerationPair, sortedCurrentSubscriptions []string, consumer2AllPotentialPartitions map[string][]topicPartitionAssignment, partition2AllPotentialConsumers map[topicPartitionAssignment][]string, currentPartitionConsumer map[topicPartitionAssignment]string) bool {
+	reassignmentPerformed := false
+	modified := false
+
+	// repeat reassignment until no partition can be moved to improve the balance
+	for {
+		modified = false
+		// reassign all reassignable partitions (starting from the partition with least potential consumers and if needed)
+		// until the full list is processed or a balance is achieved
+		for _, partition := range reassignablePartitions {
+			if isBalanced(currentAssignment, consumer2AllPotentialPartitions) {
+				break
+			}
+
+			// the partition must have at least two consumers
+			if len(partition2AllPotentialConsumers[partition]) <= 1 {
+				Logger.Printf("Expected more than one potential consumer for partition %s topic %d", partition.Topic, partition.Partition)
+			}
+
+			// the partition must have a consumer
+			consumer := currentPartitionConsumer[partition]
+			if consumer == "" {
+				Logger.Printf("Expected topic %s partition %d to be assigned to a consumer", partition.Topic, partition.Partition)
+			}
+
+			if _, exists := prevAssignment[partition]; exists {
+				if len(currentAssignment[consumer]) > (len(currentAssignment[prevAssignment[partition].MemberID]) + 1) {
+					sortedCurrentSubscriptions = s.reassignPartition(partition, currentAssignment, sortedCurrentSubscriptions, currentPartitionConsumer, prevAssignment[partition].MemberID)
+					reassignmentPerformed = true
+					modified = true
+					continue
+				}
+			}
+
+			// check if a better-suited consumer exists for the partition; if so, reassign it
+			for _, otherConsumer := range partition2AllPotentialConsumers[partition] {
+				if len(currentAssignment[consumer]) > (len(currentAssignment[otherConsumer]) + 1) {
+					sortedCurrentSubscriptions = s.reassignPartitionToNewConsumer(partition, currentAssignment, sortedCurrentSubscriptions, currentPartitionConsumer, consumer2AllPotentialPartitions)
+					reassignmentPerformed = true
+					modified = true
+					break
+				}
+			}
+		}
+		if !modified {
+			return reassignmentPerformed
+		}
+	}
+}
+
+// Identify a new consumer for a topic partition and reassign it.
+func (s *stickyBalanceStrategy) reassignPartitionToNewConsumer(partition topicPartitionAssignment, currentAssignment map[string][]topicPartitionAssignment, sortedCurrentSubscriptions []string, currentPartitionConsumer map[topicPartitionAssignment]string, consumer2AllPotentialPartitions map[string][]topicPartitionAssignment) []string {
+	for _, anotherConsumer := range sortedCurrentSubscriptions {
+		if memberAssignmentsIncludeTopicPartition(consumer2AllPotentialPartitions[anotherConsumer], partition) {
+			return s.reassignPartition(partition, currentAssignment, sortedCurrentSubscriptions, currentPartitionConsumer, anotherConsumer)
+		}
+	}
+	return sortedCurrentSubscriptions
+}
+
+// Reassign a specific partition to a new consumer
+func (s *stickyBalanceStrategy) reassignPartition(partition topicPartitionAssignment, currentAssignment map[string][]topicPartitionAssignment, sortedCurrentSubscriptions []string, currentPartitionConsumer map[topicPartitionAssignment]string, newConsumer string) []string {
+	consumer := currentPartitionConsumer[partition]
+	// find the correct partition movement considering the stickiness requirement
+	partitionToBeMoved := s.movements.getTheActualPartitionToBeMoved(partition, consumer, newConsumer)
+	return s.processPartitionMovement(partitionToBeMoved, newConsumer, currentAssignment, sortedCurrentSubscriptions, currentPartitionConsumer)
+}
+
+// Track the movement of a topic partition after assignment
+func (s *stickyBalanceStrategy) processPartitionMovement(partition topicPartitionAssignment, newConsumer string, currentAssignment map[string][]topicPartitionAssignment, sortedCurrentSubscriptions []string, currentPartitionConsumer map[topicPartitionAssignment]string) []string {
+	oldConsumer := currentPartitionConsumer[partition]
+	s.movements.movePartition(partition, oldConsumer, newConsumer)
+
+	currentAssignment[oldConsumer] = removeTopicPartitionFromMemberAssignments(currentAssignment[oldConsumer], partition)
+	currentAssignment[newConsumer] = append(currentAssignment[newConsumer], partition)
+	currentPartitionConsumer[partition] = newConsumer
+	return sortMemberIDsByPartitionAssignments(currentAssignment)
+}
+
+// Determine whether a specific consumer should be considered for topic partition assignment.
+func canConsumerParticipateInReassignment(memberID string, currentAssignment map[string][]topicPartitionAssignment, consumer2AllPotentialPartitions map[string][]topicPartitionAssignment, partition2AllPotentialConsumers map[topicPartitionAssignment][]string) bool {
+	currentPartitions := currentAssignment[memberID]
+	currentAssignmentSize := len(currentPartitions)
+	maxAssignmentSize := len(consumer2AllPotentialPartitions[memberID])
+	if currentAssignmentSize > maxAssignmentSize {
+		Logger.Printf("The consumer %s is assigned more partitions than the maximum possible", memberID)
+	}
+	if currentAssignmentSize < maxAssignmentSize {
+		// if a consumer is not assigned all its potential partitions it is subject to reassignment
+		return true
+	}
+	for _, partition := range currentPartitions {
+		if canTopicPartitionParticipateInReassignment(partition, partition2AllPotentialConsumers) {
+			return true
+		}
+	}
+	return false
+}
+
+// Only consider reassigning those topic partitions that have two or more potential consumers.
+func canTopicPartitionParticipateInReassignment(partition topicPartitionAssignment, partition2AllPotentialConsumers map[topicPartitionAssignment][]string) bool {
+	return len(partition2AllPotentialConsumers[partition]) >= 2
+}
+
+// The assignment should improve the overall balance of the partition assignments to consumers.
+func assignPartition(partition topicPartitionAssignment, sortedCurrentSubscriptions []string, currentAssignment map[string][]topicPartitionAssignment, consumer2AllPotentialPartitions map[string][]topicPartitionAssignment, currentPartitionConsumer map[topicPartitionAssignment]string) []string {
+	for _, memberID := range sortedCurrentSubscriptions {
+		if memberAssignmentsIncludeTopicPartition(consumer2AllPotentialPartitions[memberID], partition) {
+			currentAssignment[memberID] = append(currentAssignment[memberID], partition)
+			currentPartitionConsumer[partition] = memberID
+			break
+		}
+	}
+	return sortMemberIDsByPartitionAssignments(currentAssignment)
+}
+
+// Deserialize topic partition assignment data to aid with creation of a sticky assignment.
+func deserializeTopicPartitionAssignment(userDataBytes []byte) (StickyAssignorUserData, error) {
+	userDataV1 := &StickyAssignorUserDataV1{}
+	if err := decode(userDataBytes, userDataV1); err != nil {
+		userDataV0 := &StickyAssignorUserDataV0{}
+		if err := decode(userDataBytes, userDataV0); err != nil {
+			return nil, err
+		}
+		return userDataV0, nil
+	}
+	return userDataV1, nil
+}
+
+// filterAssignedPartitions returns a map of consumer group members to their list of previously-assigned topic partitions, limited
+// to those topic partitions currently reported by the Kafka cluster.
+func filterAssignedPartitions(currentAssignment map[string][]topicPartitionAssignment, partition2AllPotentialConsumers map[topicPartitionAssignment][]string) map[string][]topicPartitionAssignment {
+	assignments := deepCopyAssignment(currentAssignment)
+	for memberID, partitions := range assignments {
+		// perform in-place filtering
+		i := 0
+		for _, partition := range partitions {
+			if _, exists := partition2AllPotentialConsumers[partition]; exists {
+				partitions[i] = partition
+				i++
+			}
+		}
+		assignments[memberID] = partitions[:i]
+	}
+	return assignments
+}
+
+func removeTopicPartitionFromMemberAssignments(assignments []topicPartitionAssignment, topic topicPartitionAssignment) []topicPartitionAssignment {
+	for i, assignment := range assignments {
+		if assignment == topic {
+			return append(assignments[:i], assignments[i+1:]...)
+		}
+	}
+	return assignments
+}
+
+func memberAssignmentsIncludeTopicPartition(assignments []topicPartitionAssignment, topic topicPartitionAssignment) bool {
+	for _, assignment := range assignments {
+		if assignment == topic {
+			return true
+		}
+	}
+	return false
+}
+
+func sortPartitions(currentAssignment map[string][]topicPartitionAssignment, partitionsWithADifferentPreviousAssignment map[topicPartitionAssignment]consumerGenerationPair, isFreshAssignment bool, partition2AllPotentialConsumers map[topicPartitionAssignment][]string, consumer2AllPotentialPartitions map[string][]topicPartitionAssignment) []topicPartitionAssignment {
+	unassignedPartitions := make(map[topicPartitionAssignment]bool, len(partition2AllPotentialConsumers))
+	for partition := range partition2AllPotentialConsumers {
+		unassignedPartitions[partition] = true
+	}
+
+	sortedPartitions := make([]topicPartitionAssignment, 0)
+	if !isFreshAssignment && areSubscriptionsIdentical(partition2AllPotentialConsumers, consumer2AllPotentialPartitions) {
+		// if this is a reassignment and the subscriptions are identical (all consumers can consumer from all topics)
+		// then we just need to simply list partitions in a round robin fashion (from consumers with
+		// most assigned partitions to those with least)
+		assignments := filterAssignedPartitions(currentAssignment, partition2AllPotentialConsumers)
+
+		// use priority-queue to evaluate consumer group members in descending-order based on
+		// the number of topic partition assignments (i.e. consumers with most assignments first)
+		pq := make(assignmentPriorityQueue, len(assignments))
+		i := 0
+		for consumerID, consumerAssignments := range assignments {
+			pq[i] = &consumerGroupMember{
+				id:          consumerID,
+				assignments: consumerAssignments,
+			}
+			i++
+		}
+		heap.Init(&pq)
+
+		for {
+			// loop until no consumer-group members remain
+			if pq.Len() == 0 {
+				break
+			}
+			member := pq[0]
+
+			// partitions that were assigned to a different consumer last time
+			var prevPartitionIndex int
+			for i, partition := range member.assignments {
+				if _, exists := partitionsWithADifferentPreviousAssignment[partition]; exists {
+					prevPartitionIndex = i
+					break
+				}
+			}
+
+			if len(member.assignments) > 0 {
+				partition := member.assignments[prevPartitionIndex]
+				sortedPartitions = append(sortedPartitions, partition)
+				delete(unassignedPartitions, partition)
+				if prevPartitionIndex == 0 {
+					member.assignments = member.assignments[1:]
+				} else {
+					member.assignments = append(member.assignments[:prevPartitionIndex], member.assignments[prevPartitionIndex+1:]...)
+				}
+				heap.Fix(&pq, 0)
+			} else {
+				heap.Pop(&pq)
+			}
+		}
+
+		for partition := range unassignedPartitions {
+			sortedPartitions = append(sortedPartitions, partition)
+		}
+	} else {
+		// an ascending sorted set of topic partitions based on how many consumers can potentially use them
+		sortedPartitions = sortPartitionsByPotentialConsumerAssignments(partition2AllPotentialConsumers)
+	}
+	return sortedPartitions
+}
+
+func sortMemberIDsByPartitionAssignments(assignments map[string][]topicPartitionAssignment) []string {
+	// sort the members by the number of partition assignments in ascending order
+	sortedMemberIDs := make([]string, 0, len(assignments))
+	for memberID := range assignments {
+		sortedMemberIDs = append(sortedMemberIDs, memberID)
+	}
+	sort.SliceStable(sortedMemberIDs, func(i, j int) bool {
+		ret := len(assignments[sortedMemberIDs[i]]) - len(assignments[sortedMemberIDs[j]])
+		if ret == 0 {
+			return sortedMemberIDs[i] < sortedMemberIDs[j]
+		}
+		return len(assignments[sortedMemberIDs[i]]) < len(assignments[sortedMemberIDs[j]])
+	})
+	return sortedMemberIDs
+}
+
+func sortPartitionsByPotentialConsumerAssignments(partition2AllPotentialConsumers map[topicPartitionAssignment][]string) []topicPartitionAssignment {
+	// sort the members by the number of partition assignments in descending order
+	sortedPartionIDs := make([]topicPartitionAssignment, len(partition2AllPotentialConsumers))
+	i := 0
+	for partition := range partition2AllPotentialConsumers {
+		sortedPartionIDs[i] = partition
+		i++
+	}
+	sort.Slice(sortedPartionIDs, func(i, j int) bool {
+		if len(partition2AllPotentialConsumers[sortedPartionIDs[i]]) == len(partition2AllPotentialConsumers[sortedPartionIDs[j]]) {
+			ret := strings.Compare(sortedPartionIDs[i].Topic, sortedPartionIDs[j].Topic)
+			if ret == 0 {
+				return sortedPartionIDs[i].Partition < sortedPartionIDs[j].Partition
+			}
+			return ret < 0
+		}
+		return len(partition2AllPotentialConsumers[sortedPartionIDs[i]]) < len(partition2AllPotentialConsumers[sortedPartionIDs[j]])
+	})
+	return sortedPartionIDs
+}
+
+func deepCopyAssignment(assignment map[string][]topicPartitionAssignment) map[string][]topicPartitionAssignment {
+	m := make(map[string][]topicPartitionAssignment, len(assignment))
+	for memberID, subscriptions := range assignment {
+		m[memberID] = append(subscriptions[:0:0], subscriptions...)
+	}
+	return m
+}
+
+func areSubscriptionsIdentical(partition2AllPotentialConsumers map[topicPartitionAssignment][]string, consumer2AllPotentialPartitions map[string][]topicPartitionAssignment) bool {
+	curMembers := make(map[string]int)
+	for _, cur := range partition2AllPotentialConsumers {
+		if len(curMembers) == 0 {
+			for _, curMembersElem := range cur {
+				curMembers[curMembersElem]++
+			}
+			continue
+		}
+
+		if len(curMembers) != len(cur) {
+			return false
+		}
+
+		yMap := make(map[string]int)
+		for _, yElem := range cur {
+			yMap[yElem]++
+		}
+
+		for curMembersMapKey, curMembersMapVal := range curMembers {
+			if yMap[curMembersMapKey] != curMembersMapVal {
+				return false
+			}
+		}
+	}
+
+	curPartitions := make(map[topicPartitionAssignment]int)
+	for _, cur := range consumer2AllPotentialPartitions {
+		if len(curPartitions) == 0 {
+			for _, curPartitionElem := range cur {
+				curPartitions[curPartitionElem]++
+			}
+			continue
+		}
+
+		if len(curPartitions) != len(cur) {
+			return false
+		}
+
+		yMap := make(map[topicPartitionAssignment]int)
+		for _, yElem := range cur {
+			yMap[yElem]++
+		}
+
+		for curMembersMapKey, curMembersMapVal := range curPartitions {
+			if yMap[curMembersMapKey] != curMembersMapVal {
+				return false
+			}
+		}
+	}
+	return true
+}
+
+// We need to process subscriptions' user data with each consumer's reported generation in mind
+// higher generations overwrite lower generations in case of a conflict
+// note that a conflict could exist only if user data is for different generations
+func prepopulateCurrentAssignments(members map[string]ConsumerGroupMemberMetadata) (map[string][]topicPartitionAssignment, map[topicPartitionAssignment]consumerGenerationPair, error) {
+	currentAssignment := make(map[string][]topicPartitionAssignment)
+	prevAssignment := make(map[topicPartitionAssignment]consumerGenerationPair)
+
+	// for each partition we create a sorted map of its consumers by generation
+	sortedPartitionConsumersByGeneration := make(map[topicPartitionAssignment]map[int]string)
+	for memberID, meta := range members {
+		consumerUserData, err := deserializeTopicPartitionAssignment(meta.UserData)
+		if err != nil {
+			return nil, nil, err
+		}
+		for _, partition := range consumerUserData.partitions() {
+			if consumers, exists := sortedPartitionConsumersByGeneration[partition]; exists {
+				if consumerUserData.hasGeneration() {
+					if _, generationExists := consumers[consumerUserData.generation()]; generationExists {
+						// same partition is assigned to two consumers during the same rebalance.
+						// log a warning and skip this record
+						Logger.Printf("Topic %s Partition %d is assigned to multiple consumers following sticky assignment generation %d", partition.Topic, partition.Partition, consumerUserData.generation())
+						continue
+					} else {
+						consumers[consumerUserData.generation()] = memberID
+					}
+				} else {
+					consumers[defaultGeneration] = memberID
+				}
+			} else {
+				generation := defaultGeneration
+				if consumerUserData.hasGeneration() {
+					generation = consumerUserData.generation()
+				}
+				sortedPartitionConsumersByGeneration[partition] = map[int]string{generation: memberID}
+			}
+		}
+	}
+
+	// prevAssignment holds the prior ConsumerGenerationPair (before current) of each partition
+	// current and previous consumers are the last two consumers of each partition in the above sorted map
+	for partition, consumers := range sortedPartitionConsumersByGeneration {
+		// sort consumers by generation in decreasing order
+		var generations []int
+		for generation := range consumers {
+			generations = append(generations, generation)
+		}
+		sort.Sort(sort.Reverse(sort.IntSlice(generations)))
+
+		consumer := consumers[generations[0]]
+		if _, exists := currentAssignment[consumer]; !exists {
+			currentAssignment[consumer] = []topicPartitionAssignment{partition}
+		} else {
+			currentAssignment[consumer] = append(currentAssignment[consumer], partition)
+		}
+
+		// check for previous assignment, if any
+		if len(generations) > 1 {
+			prevAssignment[partition] = consumerGenerationPair{
+				MemberID:   consumers[generations[1]],
+				Generation: generations[1],
+			}
+		}
+	}
+	return currentAssignment, prevAssignment, nil
+}
+
+type consumerGenerationPair struct {
+	MemberID   string
+	Generation int
+}
+
+// consumerPair represents a pair of Kafka consumer ids involved in a partition reassignment.
+type consumerPair struct {
+	SrcMemberID string
+	DstMemberID string
+}
+
+// partitionMovements maintains some data structures to simplify lookup of partition movements among consumers.
+type partitionMovements struct {
+	PartitionMovementsByTopic map[string]map[consumerPair]map[topicPartitionAssignment]bool
+	Movements                 map[topicPartitionAssignment]consumerPair
+}
+
+func (p *partitionMovements) removeMovementRecordOfPartition(partition topicPartitionAssignment) consumerPair {
+	pair := p.Movements[partition]
+	delete(p.Movements, partition)
+
+	partitionMovementsForThisTopic := p.PartitionMovementsByTopic[partition.Topic]
+	delete(partitionMovementsForThisTopic[pair], partition)
+	if len(partitionMovementsForThisTopic[pair]) == 0 {
+		delete(partitionMovementsForThisTopic, pair)
+	}
+	if len(p.PartitionMovementsByTopic[partition.Topic]) == 0 {
+		delete(p.PartitionMovementsByTopic, partition.Topic)
+	}
+	return pair
+}
+
+func (p *partitionMovements) addPartitionMovementRecord(partition topicPartitionAssignment, pair consumerPair) {
+	p.Movements[partition] = pair
+	if _, exists := p.PartitionMovementsByTopic[partition.Topic]; !exists {
+		p.PartitionMovementsByTopic[partition.Topic] = make(map[consumerPair]map[topicPartitionAssignment]bool)
+	}
+	partitionMovementsForThisTopic := p.PartitionMovementsByTopic[partition.Topic]
+	if _, exists := partitionMovementsForThisTopic[pair]; !exists {
+		partitionMovementsForThisTopic[pair] = make(map[topicPartitionAssignment]bool)
+	}
+	partitionMovementsForThisTopic[pair][partition] = true
+}
+
+func (p *partitionMovements) movePartition(partition topicPartitionAssignment, oldConsumer, newConsumer string) {
+	pair := consumerPair{
+		SrcMemberID: oldConsumer,
+		DstMemberID: newConsumer,
+	}
+	if _, exists := p.Movements[partition]; exists {
+		// this partition has previously moved
+		existingPair := p.removeMovementRecordOfPartition(partition)
+		if existingPair.DstMemberID != oldConsumer {
+			Logger.Printf("Existing pair DstMemberID %s was not equal to the oldConsumer ID %s", existingPair.DstMemberID, oldConsumer)
+		}
+		if existingPair.SrcMemberID != newConsumer {
+			// the partition is not moving back to its previous consumer
+			p.addPartitionMovementRecord(partition, consumerPair{
+				SrcMemberID: existingPair.SrcMemberID,
+				DstMemberID: newConsumer,
+			})
+		}
+	} else {
+		p.addPartitionMovementRecord(partition, pair)
+	}
+}
+
+func (p *partitionMovements) getTheActualPartitionToBeMoved(partition topicPartitionAssignment, oldConsumer, newConsumer string) topicPartitionAssignment {
+	if _, exists := p.PartitionMovementsByTopic[partition.Topic]; !exists {
+		return partition
+	}
+	if _, exists := p.Movements[partition]; exists {
+		// this partition has previously moved
+		if oldConsumer != p.Movements[partition].DstMemberID {
+			Logger.Printf("Partition movement DstMemberID %s was not equal to the oldConsumer ID %s", p.Movements[partition].DstMemberID, oldConsumer)
+		}
+		oldConsumer = p.Movements[partition].SrcMemberID
+	}
+
+	partitionMovementsForThisTopic := p.PartitionMovementsByTopic[partition.Topic]
+	reversePair := consumerPair{
+		SrcMemberID: newConsumer,
+		DstMemberID: oldConsumer,
+	}
+	if _, exists := partitionMovementsForThisTopic[reversePair]; !exists {
+		return partition
+	}
+	var reversePairPartition topicPartitionAssignment
+	for otherPartition := range partitionMovementsForThisTopic[reversePair] {
+		reversePairPartition = otherPartition
+	}
+	return reversePairPartition
+}
+
+func (p *partitionMovements) isLinked(src, dst string, pairs []consumerPair, currentPath []string) ([]string, bool) {
+	if src == dst {
+		return currentPath, false
+	}
+	if len(pairs) == 0 {
+		return currentPath, false
+	}
+	for _, pair := range pairs {
+		if src == pair.SrcMemberID && dst == pair.DstMemberID {
+			currentPath = append(currentPath, src, dst)
+			return currentPath, true
+		}
+	}
+
+	for _, pair := range pairs {
+		if pair.SrcMemberID == src {
+			// create a deep copy of the pairs, excluding the current pair
+			reducedSet := make([]consumerPair, len(pairs)-1)
+			i := 0
+			for _, p := range pairs {
+				if p != pair {
+					reducedSet[i] = pair
+					i++
+				}
+			}
+
+			currentPath = append(currentPath, pair.SrcMemberID)
+			return p.isLinked(pair.DstMemberID, dst, reducedSet, currentPath)
+		}
+	}
+	return currentPath, false
+}
+
+func (p *partitionMovements) in(cycle []string, cycles [][]string) bool {
+	superCycle := make([]string, len(cycle)-1)
+	for i := 0; i < len(cycle)-1; i++ {
+		superCycle[i] = cycle[i]
+	}
+	superCycle = append(superCycle, cycle...)
+	for _, foundCycle := range cycles {
+		if len(foundCycle) == len(cycle) && indexOfSubList(superCycle, foundCycle) != -1 {
+			return true
+		}
+	}
+	return false
+}
+
+func (p *partitionMovements) hasCycles(pairs []consumerPair) bool {
+	cycles := make([][]string, 0)
+	for _, pair := range pairs {
+		// create a deep copy of the pairs, excluding the current pair
+		reducedPairs := make([]consumerPair, len(pairs)-1)
+		i := 0
+		for _, p := range pairs {
+			if p != pair {
+				reducedPairs[i] = pair
+				i++
+			}
+		}
+		if path, linked := p.isLinked(pair.DstMemberID, pair.SrcMemberID, reducedPairs, []string{pair.SrcMemberID}); linked {
+			if !p.in(path, cycles) {
+				cycles = append(cycles, path)
+				Logger.Printf("A cycle of length %d was found: %v", len(path)-1, path)
+			}
+		}
+	}
+
+	// for now we want to make sure there is no partition movements of the same topic between a pair of consumers.
+	// the odds of finding a cycle among more than two consumers seem to be very low (according to various randomized
+	// tests with the given sticky algorithm) that it should not worth the added complexity of handling those cases.
+	for _, cycle := range cycles {
+		if len(cycle) == 3 {
+			return true
+		}
+	}
+	return false
+}
+
+func (p *partitionMovements) isSticky() bool {
+	for topic, movements := range p.PartitionMovementsByTopic {
+		movementPairs := make([]consumerPair, len(movements))
+		i := 0
+		for pair := range movements {
+			movementPairs[i] = pair
+			i++
+		}
+		if p.hasCycles(movementPairs) {
+			Logger.Printf("Stickiness is violated for topic %s", topic)
+			Logger.Printf("Partition movements for this topic occurred among the following consumer pairs: %v", movements)
+			return false
+		}
+	}
+	return true
+}
+
+func indexOfSubList(source []string, target []string) int {
+	targetSize := len(target)
+	maxCandidate := len(source) - targetSize
+nextCand:
+	for candidate := 0; candidate <= maxCandidate; candidate++ {
+		j := candidate
+		for i := 0; i < targetSize; i++ {
+			if target[i] != source[j] {
+				// Element mismatch, try next cand
+				continue nextCand
+			}
+			j++
+		}
+		// All elements of candidate matched target
+		return candidate
+	}
+	return -1
+}
+
+type consumerGroupMember struct {
+	id          string
+	assignments []topicPartitionAssignment
+}
+
+// assignmentPriorityQueue is a priority-queue of consumer group members that is sorted
+// in descending order (most assignments to least assignments).
+type assignmentPriorityQueue []*consumerGroupMember
+
+func (pq assignmentPriorityQueue) Len() int { return len(pq) }
+
+func (pq assignmentPriorityQueue) Less(i, j int) bool {
+	// order asssignment priority queue in descending order using assignment-count/member-id
+	if len(pq[i].assignments) == len(pq[j].assignments) {
+		return strings.Compare(pq[i].id, pq[j].id) > 0
+	}
+	return len(pq[i].assignments) > len(pq[j].assignments)
+}
+
+func (pq assignmentPriorityQueue) Swap(i, j int) {
+	pq[i], pq[j] = pq[j], pq[i]
+}
+
+func (pq *assignmentPriorityQueue) Push(x interface{}) {
+	member := x.(*consumerGroupMember)
+	*pq = append(*pq, member)
+}
+
+func (pq *assignmentPriorityQueue) Pop() interface{} {
+	old := *pq
+	n := len(old)
+	member := old[n-1]
+	*pq = old[0 : n-1]
+	return member
+}