Details
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Improvement
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Status: Resolved
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Major
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Resolution: Fixed
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2.7.0
Description
In KAFKA-9987, we did a great improvement for the case when all consumers were subscribed to same set of topics. The algorithm contains 4 phases:
- Reassign as many previously owned partitions as possible, up to the maxQuota
- Fill remaining members up to minQuota
- If we ran out of unassigned partitions before filling all consumers, we need to start stealing partitions from the over-full consumers at max capacity
- Otherwise we may have run out of unfilled consumers before assigning all partitions, in which case we should just distribute one partition each to all consumers at min capacity
Take an example for better understanding:
example:
Current status: 2 consumers (C0, C1), and 10 topic partitions: t1p0, t1p1, ... t1p9
Suppose, current assignment is:
C0: t1p0, t1p1, t1p2, t1p3, t1p4
C1: t1p5, t1p6, t1p7, t1p8, t1p9
Now, new consumer added: C2, so we'll do:
- Reassign as many previously owned partitions as possible, up to the maxQuota
After this phase, the assignment will be: (maxQuota will be 4)
C0: t1p0, t1p1, t1p2, t1p3
C1: t1p5, t1p6, t1p7, t1p8
- Fill remaining members up to minQuota
After this phase, the assignment will be:
C0: t1p0, t1p1, t1p2, t1p3
C1: t1p5, t1p6, t1p7, t1p8
C2: t1p4, t1p9
- If we ran out of unassigned partitions before filling all consumers, we need to start stealing partitions from the over-full consumers at max capacity
After this phase, the assignment will be:
C0: t1p0, t1p1, t1p2
C1: t1p5, t1p6, t1p7, t1p8
C2: t1p4, t1p9, t1p3
- Otherwise we may have run out of unfilled consumers before assigning all partitions, in which case we should just distribute one partition each to all consumers at min capacity
As we can see, we need 3 phases to complete the assignment. But we can actually completed with 2 phases. Here's the updated algorithm:
- Reassign as many previously owned partitions as possible, up to the maxQuota, and also considering the numMaxQuota by the remainder of (Partitions / Consumers)
- Fill remaining members up to maxQuota if current maxQuotaMember < numMaxQuota, otherwise, to minQuota
By considering the numMaxQuota, the original step 1 won't be too aggressive to assign too many partitions to consumers, and the step 2 won't be too conservative to assign not enough partitions to consumers, so that we don't need step 3 and step 4 to balance them.
So, the updated Pseudo-code sketch of the algorithm:
C_f := (P/N)_floor, the floor capacity
C_c := (P/N)_ceil, the ceiling capacity
C_r := (P%N) the allowed number of members with C_c partitions assigned
num_max_capacity_members := current number of members with C_c partitions assigned (default to 0)
members := the sorted set of all consumers
partitions := the set of all partitions
unassigned_partitions := the set of partitions not yet assigned, initialized to be all partitions
unfilled_members := the set of consumers not yet at capacity, initialized to empty
max_capacity_members := the set of members with exactly C_c partitions assigned, initialized to empty
member.owned_partitions := the set of previously owned partitions encoded in the Subscription
// Reassign as many previously owned partitions as possible, by considering the num_max_capacity_members
for member : members
remove any partitions that are no longer in the subscription from its owned partitions
remove all owned_partitions if the generation is old
if member.owned_partitions.size < C_f
assign all owned partitions to member and remove from unassigned_partitions
add member to unfilled_members
else if member.owned_partitions.size == C_f
assign first C_f owned_partitions to member and remove from unassigned_partitions
else if member.owned_partitions.size >= C_c && num_max_capacity_members < C_r
assign first C_c owned_partitions to member and remove from unassigned_partitions
num_max_capacity_members++
a-dd member to max_capacity_members-
else
assign first C_f owned_partitions to member and remove from unassigned_partitions
sort unassigned_partitions in partition order, ie t0_p0, t1_p0, t2_p0, t0_p1, t1_p0 .... (for data parallelism)
sort unfilled_members by memberId (for determinism)
// Fill remaining members up to the C_r numbers of C_c, otherwise, to C_f
for member : unfilled_members
compute the remaining capacity as C = C_f - num_assigned_partitions
if num_max_capacity_members < C_r:
C = C_c - num_assigned_partitions
num_max_capacity_members++
else
C = C_f - num_assigned_partitions
pop the first C partitions from unassigned_partitions and assign to member
// Steal partitions from members with max_capacity if necessary
if we run out of partitions before getting to the end of unfilled members:
for member : unfilled_members
poll for first member in max_capacity_members and remove one partition
assign this partition to the unfilled member
// Distribute remaining partitions, one per consumer, to fill some up to C_c if necessary
if we run out of unfilled_members before assigning all partitions:
for partition : unassigned_partitions
assign to next member in members that is not in max_capacity_members (then add member to max_capacity_members)
C_f := (P/N)_floor, the floor capacity C_c := (P/N)_ceil, the ceiling capacity C_r := (P%N) the allowed number of members with C_c partitions assigned num_max_capacity_members := current number of members with C_c partitions assigned (default to 0) members := the sorted set of all consumers partitions := the set of all partitions unassigned_partitions := the set of partitions not yet assigned, initialized to be all partitions unfilled_members := the set of consumers not yet at capacity, initialized to empty member.owned_partitions := the set of previously owned partitions encoded in the Subscription // Reassign as many previously owned partitions as possible, by considering the num_max_capacity_members for member : members remove any partitions that are no longer in the subscription from its owned partitions remove all owned_partitions if the generation is old if member.owned_partitions.size < C_f assign all owned partitions to member and remove from unassigned_partitions add member to unfilled_members else if member.owned_partitions.size >= C_c && num_max_capacity_members < C_r assign first C_c owned_partitions to member and remove from unassigned_partitions num_max_capacity_members++ else assign first C_f owned_partitions to member and remove from unassigned_partitions sort unassigned_partitions in partition order, ie t0_p0, t1_p0, t2_p0, t0_p1, t1_p0 .... (for data parallelism) sort unfilled_members by memberId (for determinism) // Fill remaining members up to the C_r numbers of C_c, otherwise, to C_f for member : unfilled_members compute the remaining capacity as: if num_max_capacity_members < C_r: C = C_c - num_assigned_partitions num_max_capacity_members++ else C = C_f - num_assigned_partitions pop the first C partitions from unassigned_partitions and assign to member
So, adopting the updated algorithm, the previous example will be:
example:
Current status: 2 consumers (C0, C1), and 10 topic partitions: t1p0, t1p1, ... t1p9
Suppose, current assignment is:
C0: t1p0, t1p1, t1p2, t1p3, t1p4
C1: t1p5, t1p6, t1p7, t1p8, t1p9
Now, new consumer added: C2, so we'll do:
- Reassign as many previously owned partitions as possible, up to the maxQuota
After this phase, the assignment will be: (maxQuota will be 4, and numAllowedWithMaxQuota will be 1)
C0: t1p0, t1p1, t1p2, t1p3
C1: t1p5, t1p6, t1p7
- Fill remaining members up to maxQuota if current maxQuotaMember < numMaxQuota, otherwise, to minQuota
After this phase, the assignment will be:
C0: t1p0, t1p1, t1p2, t1p3
C1: t1p5, t1p6, t1p7
C2: t1p4, t1p8, t1p9
Another enhancement:
Currently, in phase 1, we loop through all consumerToOwnedPartitions 1 by 1, to do partition assignment or partition remove. However, we doesn't care each partition info, what we only care, is the partition number assigned. So, we can just use List.subList() to get the expected number of subList from the consumerToOwnedPartitions. It'll also improve the performance of the algorithm.
That is:
// Reassign as many previously owned partitions as possible for (Map.Entry<String, List<TopicPartition>> consumerEntry : consumerToOwnedPartitions.entrySet()) { String consumer = consumerEntry.getKey(); List<TopicPartition> ownedPartitions = consumerEntry.getValue(); List<TopicPartition> consumerAssignment = assignment.get(consumer); int i = 0; // assign the first N partitions up to the max quota, and mark the remaining as being revoked // originally, we loop through the partitions 1 by 1 /* for (TopicPartition tp : ownedPartitions) { if (i < maxQuota) { consumerAssignment.add(tp); unassignedPartitions.remove(tp); } else { allRevokedPartitions.add(tp); } ++i; } */ // Enhancement: since we only care the number of partitions assigned, we can use subList to assign the expected number, so no need to loop through them all if (ownedPartitions.size() < minQuota) { // the expected assignment size is more than consumer have now, so keep all the owned partitions // and put this member into unfilled member list consumerAssignment.addAll(ownedPartitions); unassignedPartitions.removeAll(ownedPartitions); unfilledMembers.add(consumer); } else if (ownedPartitions.size() >= maxQuota && numMaxCapacityMembers++ <= numExpectedMaxCapacityMembers) { // consumer owned the "maxQuota" of partitions or more, and we still under the number of expected max capacity members // so keep "maxQuota" of the owned partitions, and revoke the rest of the partitions consumerAssignment.addAll(ownedPartitions.subList(0, maxQuota)); unassignedPartitions.removeAll(ownedPartitions.subList(0, maxQuota)); allRevokedPartitions.addAll(ownedPartitions.subList(maxQuota, ownedPartitions.size())); } else { // consumer owned the "minQuota" of partitions or more // so keep "minQuota" of the owned partitions, and revoke the rest of the partitions consumerAssignment.addAll(ownedPartitions.subList(0, minQuota)); unassignedPartitions.removeAll(ownedPartitions.subList(0, minQuota)); allRevokedPartitions.addAll(ownedPartitions.subList(minQuota, ownedPartitions.size())); } .....