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:
- Add the following maven dependency to your Kafka consumer application:
<dependency> <groupId>com.github.grantneale</groupId> <artifactId>kafka-lag-based-assignor</artifactId> </dependency>
- Set the following in your Kafka consumer properties:
partition.assignment.strategy = com.github.grantneale.kafka.LagBasedPartitionAssignor
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 lag.
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
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