peeeto / kafka-lag-based-assignor

Kafka partition assignor that distributes lag evenly across a consumer group

kafka-lag-based-assignor

Kafka partition assignor that distributes lag evenly across a consumer group.

Requires Kafka 0.10.0.0 or later.

To configure a Kafka consumer group to use lag-based partition assignment:

1. Add the following maven dependency to your Kafka consumer application:

   <dependency>
       <groupId>com.github.grantneale</groupId>
       <artifactId>kafka-lag-based-assignor</artifactId>
   </dependency>

2. Set the following in your Kafka consumer properties:

   partition.assignment.strategy = com.github.grantneale.kafka.LagBasedPartitionAssignor

Overview

The LagBasedPartitionAssignor operates on a per-topic basis, and attempts to assign partitions such that lag is distributed evenly across a consumer group.

For each topic, we first obtain the lag on all partitions. Lag on a given partition is the difference between the end offset and the last offset committed by the consumer group. If no offsets have been committed for a partition we determine the lag based on the code auto.offset.reset property. If auto.offset.reset=latest, we assign a lag of 0. If auto.offset.reset=earliest (or any other value) we assume assign lag equal to the total number of message currently available in that partition.

We then create a map storing the current total lag of all partitions assigned to each member of the consumer group. Partitions are assigned in decreasing order of lag, with each partition assigned to the consumer with least total number of assigned partitions, breaking ties by assigning to the consumer with the least total assigned lag.

Distributing partitions evenly across consumers (by count) ensures that the partition assignment is balanced when all partitions have a current lag of 0 or if the distribution of lags is heavily skewed. It also gives the consumer group the best possible chance of remaining balanced if the assignment is retained for a long period.

Example: LagBasedPartitionAssignor

For example, suppose there are two consumers C0 and C1, both subscribed to a topic t0 having 3 partitions with the following lags:

t0p0: 100,000
t0p1:  50,000
t0p2:  60,000

The assignment will be:

C0: [t0p0]
C1: [t0p1, t0p2]

The total lag or partitions assigned to each consumer will be:

C0: 100,000
C1: 110,000

Example: RangeAssignor (kafka default)

Compare this to the assignments made by Kafka's default org.apache.kafka.clients.consumer.RangeAssignor:

C0: [t0p0, t0p1]
C1: [t0p2]

The RangeAssignor results in a less balanced total lag for each consumer of:

C0: 160,000
C1:  50,000