---
title: "Kafka consumer group: how partitions split across members"
description: "A two-member Kafka consumer group splits a four-partition topic with the range assignor: c1 owns p0-p1, c2 owns p2-p3, and each partition has exactly one owner."
url: https://monedula.dev/kafka-simulator/scenarios/partitions-split-across-members/
---

# Kafka consumer group: how partitions split across members

Scenario 02.2.1 · Partitions split across members. Consumer groups · Intermediate · about 2 min · Apache Kafka 4.3.

A consumer group shares a topic by splitting its partitions - each partition is owned by exactly one member.

Run it: https://monedula.dev/kafka-simulator/playground/?scenario=02.2.1

## What you start with

A consumer group scales reads by dividing a topic's partitions among its members, with the assignor (run by the group's leader consumer in the classic protocol) guaranteeing each partition is owned by exactly one member at a time. Here a two-member group splits a four-partition topic and each member polls only its own partitions.

## Step by step

1. **Group ready - 2 members, 4 partitions** (t+0.000s): The group g1 has two members on the 4-partition topic orders. The range assignor immediately splits the partitions into contiguous blocks: c1 owns p0-p1 and c2 owns p2-p3. Every partition has exactly one owner, so each record is processed by just one member of the group. [Open at this step](https://monedula.dev/kafka-simulator/playground/?scenario=02.2.1&t=0)
2. **Each member reads only its own partitions** (t+1.700s): One record was produced to each partition. c1 polls and reads p0 and p1; c2 polls and reads p2 and p3 - in parallel. The group's per-partition positions have all advanced to 1 and lag is 0. Splitting partitions across members is how a consumer group scales read throughput without ever double-processing a record. [Open at this step](https://monedula.dev/kafka-simulator/playground/?scenario=02.2.1&t=1)

## The takeaway

Parallelism within a group is bounded by partition count - each partition has a single owner, so a record is processed once per group and consumers beyond the partition count sit idle.

## Further reading

- [Apache Kafka documentation](https://kafka.apache.org/43/getting-started/introduction/)