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Auto Data Balancing

The confluent-rebalancer tool balances data so that the number of leaders and disk usage are even across brokers and racks on a per topic and cluster level while minimizing data movement. It also integrates closely with the replication quotas feature in Apache Kafka® to dynamically throttle data-balancing traffic.

The tool is part of Confluent Platform and can also be installed on its own using the confluent-rebalancer package.

Requirements

To compute the rebalance plan, the tool relies on metrics collected from the Apache Kafka® cluster. This data is published by the Confluent Metrics Reporter to a configurable Kafka topic (_confluent-metrics by default) in a configurable Kafka cluster.

To enable the Metrics Reporter, see the installation instructions.

Confluent Auto Data Balancer Quick Start

Start a Kafka cluster

Start a ZooKeeper server. In this example, assume services run on localhost.

# Start ZooKeeper.  Run this command in its own terminal.
./bin/zookeeper-server-start ./etc/kafka/zookeeper.properties

Tip

These instructions assume you are installing Confluent Platform by using ZIP or TAR archives. For more information, see On-Premises Deployments.

Copy the broker configuration file to a temporary location, enable the metrics reporter, and duplicate the config for additional brokers.

# Copy the configuration files to /tmp
cp ./etc/kafka/server.properties /tmp/server0.properties

# Add metrics reporter configurations (alternatively, you could uncomment the configurations)
echo "" >> /tmp/server0.properties
echo "metric.reporters=io.confluent.metrics.reporter.ConfluentMetricsReporter" >> /tmp/server0.properties
echo "confluent.metrics.reporter.bootstrap.servers=localhost:9092" >> /tmp/server0.properties
echo "confluent.metrics.reporter.topic.replicas=1" >> /tmp/server0.properties

# properties for broker.id=1
cp /tmp/server0.properties /tmp/server1.properties
sed -i'' -e "s/broker.id=0/broker.id=1/g" /tmp/server1.properties
sed -i'' -e "s/9092/9082/g" /tmp/server1.properties
sed -i'' -e "s/#listen/listen/g" /tmp/server1.properties
sed -i'' -e "s/kafka-logs/kafka-logs-1/g" /tmp/server1.properties

# properties for broker.id=2
cp /tmp/server0.properties /tmp/server2.properties
sed -i'' -e "s/broker.id=0/broker.id=2/g" /tmp/server2.properties
sed -i'' -e "s/9092/9072/g" /tmp/server2.properties
sed -i'' -e "s/#listen/listen/g" /tmp/server2.properties
sed -i'' -e "s/kafka-logs/kafka-logs-2/g" /tmp/server2.properties

# properties for broker.id=3
cp /tmp/server0.properties /tmp/server3.properties
sed -i'' -e "s/broker.id=0/broker.id=3/g" /tmp/server3.properties
sed -i'' -e "s/9092/9062/g" /tmp/server3.properties
sed -i'' -e "s/#listen/listen/g" /tmp/server3.properties
sed -i'' -e "s/kafka-logs/kafka-logs-3/g" /tmp/server3.properties

Start the Kafka brokers:

# Start Kafka.  Run these commands in a separate terminal:
./bin/kafka-server-start /tmp/server0.properties &
./bin/kafka-server-start /tmp/server1.properties &
./bin/kafka-server-start /tmp/server2.properties &
./bin/kafka-server-start /tmp/server3.properties &

For complete details on getting these services up and running see the quickstart for Confluent Platform.

Create topics and produce data

Create a couple of topics, each with 4 partitions and a replication factor of 2. We intentionally create an unbalanced assignment:

./bin/kafka-topics --create --topic topic-a --replica-assignment 0:1,0:1,0:1,0:1 --bootstrap-server localhost:9092
./bin/kafka-topics --create --topic topic-b --replica-assignment 1:0,2:1,1:2,2:1 --bootstrap-server localhost:9092

Examine how they look:

./bin/kafka-topics --describe --topic topic-a --bootstrap-server localhost:9092

Topic:topic-a        PartitionCount:4        ReplicationFactor:2     Configs:
   Topic: topic-a    Partition: 0    Leader: 0       Replicas: 0,1   Isr: 0,1
   Topic: topic-a    Partition: 1    Leader: 0       Replicas: 0,1   Isr: 0,1
   Topic: topic-a    Partition: 2    Leader: 0       Replicas: 0,1   Isr: 0,1
   Topic: topic-a    Partition: 3    Leader: 0       Replicas: 0,1   Isr: 0,1

./bin/kafka-topics --describe --topic topic-b --bootstrap-server localhost:9092

Topic:topic-b        PartitionCount:4        ReplicationFactor:2     Configs:
  Topic: topic-b     Partition: 0    Leader: 1       Replicas: 1,0   Isr: 1,0
  Topic: topic-b     Partition: 1    Leader: 2       Replicas: 2,1   Isr: 2,1
  Topic: topic-b     Partition: 2    Leader: 1       Replicas: 1,2   Isr: 1,2
  Topic: topic-b     Partition: 3    Leader: 2       Replicas: 2,1   Isr: 2,1

Now produce some data:

./bin/kafka-producer-perf-test --topic topic-a --num-records 200000 --record-size 1000 --throughput 10000000 --producer-props bootstrap.servers=localhost:9092
./bin/kafka-producer-perf-test --topic topic-b --num-records 800000 --record-size 1000 --throughput 10000000 --producer-props bootstrap.servers=localhost:9092

And finally, force the creation of the offsets topic by running a consumer:

./bin/kafka-consumer-perf-test --topic topic-a --broker-list localhost:9092 --messages 10

Execute the rebalancer

Before starting, it’s worth mentioning that if you run ./bin/confluent-rebalancer with no arguments, it will output a list of supported commands along with a description.

Begin with the execute command. Specify the bootstrap servers for the Kafka cluster containing the metrics topic and the maximum bandwidth (in bytes per second) allocated to moving replicas. The verbose flag includes per broker statistics in the CLI output, which is useful unless the number of brokers is very high.

./bin/confluent-rebalancer execute --bootstrap-server localhost:9092 --metrics-bootstrap-server localhost:9092 --throttle 10000000 --verbose

You are presented with a rebalancing plan, which will be slightly different depending on whether the Kafka brokers are configured to use a single log directory (as shown in our example) or multiple log directories. In the former case, the rebalancer ensures that the volume containing the log directory has at least the specified percentage of free space during and after the rebalance (20% is the default).

Computing the rebalance plan (this may take a while) ...
You are about to move 17 replica(s) for 14 partitions to 4 broker(s) with total size 827.2 MB.
The preferred leader for 14 partition(s) will be changed.
In total, the assignment for 15 partitions will be changed.
The minimum free volume space is set to 20.0%.

The following brokers will have less than 40% of free volume space during the rebalance:
      Broker     Current Size (MB)  Size During Rebalance (MB)   Free % During Rebalance      Size After Rebalance (MB)    Free % After Rebalance
      0          413.6              620.4                        30.1                         519.6                        30.5
      2          620.4              723.8                        30.1                         520.8                        30.5
      3          0                  517                          30.1                         520.8                        30.5
      1          1,034              1,034                        30.1                         519.6                        30.5

Min/max stats for brokers (before -> after):
      Type  Leader Count                 Replica Count                Size (MB)
      Min   12 (id: 3) -> 17 (id: 0)     37 (id: 3) -> 43 (id: 3)     0 (id: 3) -> 517 (id: 1)
      Max   21 (id: 0) -> 17 (id: 0)     51 (id: 1) -> 45 (id: 0)     1,034 (id: 1) -> 517 (id: 3)
No racks are defined.

Broker stats (before -> after):
  Broker     Leader Count    Replica Count   Size (MB)            Free Space (%)
      0          21 -> 17        48 -> 45        413.6 -> 517       30.5 -> 30.5
      1          20 -> 17        51 -> 44        1,034 -> 517       30.5 -> 30.5
      2          15 -> 17        40 -> 44        620.4 -> 517       30.5 -> 30.5
      3          12 -> 17        37 -> 43        0 -> 517           30.5 -> 30.5

Would you like to continue? (y/n):

Because we are running all brokers in the same volume, the free space numbers don’t change after the rebalance. If configuring multiple log directories, pay close attention to the additional disk space requirements during and after the rebalance to ensure that it won’t cause a broker to run out of disk space.

In addition, the min/max stats provide a quick summary of the data balance improvement after the rebalance completes. The goal should be for the min and max values to be closer to each other after the rebalance. In this case, we achieve near optimal balance so the numbers are virtually identical.

If you proceed, you will see the following (don’t ignore the warning):

Rebalance started, its status can be checked via the status command.

Warning: You must run the status or finish command periodically, until the rebalance completes, to ensure the throttle is removed. You can also alter the throttle by re-running the execute command passing a new value.

At this point, the tool will exit and the rebalance will take place in the background (driven by the Kafka Controller).

Check status, finish and cancel

Check the status of the rebalance:

./bin/confluent-rebalancer status --bootstrap-server localhost:9092

Partitions being rebalanced:
        Topic topic-a: 1,2
        Topic topic-b: 0

Eventually, the rebalance will complete (finish and status are similar; the latter has more concise output and returns a 0 exit status code when the rebalance is finished):

./bin/confluent-rebalancer finish --bootstrap-server localhost:9092                             ⏎

The rebalance has completed and throttling has been disabled

Verify that the replica assignment is balanced:

./bin/kafka-topics --describe --topic topic-a --bootstrap-server localhost:9092

Topic:topic-a        PartitionCount:4        ReplicationFactor:2     Configs:
        Topic: topic-a       Partition: 0    Leader: 3       Replicas: 3,2   Isr: 2,3
        Topic: topic-a       Partition: 1    Leader: 2       Replicas: 2,3   Isr: 2,3
        Topic: topic-a       Partition: 2    Leader: 0       Replicas: 1,0   Isr: 0,1
        Topic: topic-a       Partition: 3    Leader: 0       Replicas: 0,1   Isr: 0,1

./bin/kafka-topics --describe --topic topic-b --bootstrap-server localhost:9092

Topic:topic-b        PartitionCount:4        ReplicationFactor:2     Configs:
        Topic: topic-b       Partition: 0    Leader: 3       Replicas: 3,0   Isr: 0,3
        Topic: topic-b       Partition: 1    Leader: 0       Replicas: 0,3   Isr: 0,3
        Topic: topic-b       Partition: 2    Leader: 1       Replicas: 1,2   Isr: 1,2
        Topic: topic-b       Partition: 3    Leader: 2       Replicas: 2,1   Isr: 2,1

Partition sizes are communicated asynchronously (every 15 seconds by default and configurable using the confluent.metrics.reporter.publish.ms configuration), so there may be a delay before the tool reports the correct information after a rebalance completes, which is particularly noticeable when conducting local tests such as this.

You can use the cancel command to stop any reassignment currently in progress.

./bin/confluent-rebalancer cancel --bootstrap-server localhost:9092

Leader balance

If auto.leader.rebalance.enable is disabled on your brokers, run the preferred leader election tool after the rebalance completes. This will ensure that the actual leaders are balanced (not just the preferred leaders).

./bin/kafka-preferred-replica-election --bootstrap-server localhost:9092

Created preferred replica election path with _confluent-metrics-7,_confluent-metrics-2,_confluent-metrics-5,_confluent-metrics-11,_confluent-metrics-10,topic-b-2,topic-a-1,_confluent-metrics-1,topic-a-3,__confluent.support.metrics-0,topic-a-0,_confluent-metrics-9,_confluent-metrics-0,topic-a-2,topic-b-3,_confluent-metrics-3,_confluent-metrics-4,_confluent-metrics-6,topic-b-1,_confluent-metrics-8,topic-b-0
Successfully started preferred replica election for partitions Set(_confluent-metrics-7, _confluent-metrics-2, _confluent-metrics-5, _confluent-metrics-11, _confluent-metrics-10, topic-b-2, topic-a-1, _confluent-metrics-1, topic-a-3, __confluent.support.metrics-0, topic-a-0, _confluent-metrics-9, _confluent-metrics-0, topic-a-2, topic-b-3, _confluent-metrics-3, _confluent-metrics-4, _confluent-metrics-6, topic-b-1, _confluent-metrics-8, topic-b-0)
# run again to see the completion
./bin/kafka-preferred-replica-election --bootstrap-server localhost:9092

Successfully completed preferred replica election for partitions topic-b-3, topic-b-0, _confluent-metrics-1, _confluent-metrics-5, _confluent-metrics-9, topic-a-1, _confluent-metrics-2, topic-b-1, _confluent-metrics-6, __confluent.support.metrics-0, _confluent-metrics-10, topic-a-2, _confluent-metrics-3, topic-b-2, topic-a-3, _confluent-metrics-7, _confluent-metrics-4, _confluent-metrics-11, _confluent-metrics-8, _confluent-metrics-0, topic-a-0

Decommissioning brokers

The confluent-rebalancer tool automatically generates a rebalance plan for decommissioning brokers using the --remove-broker-ids option. The cluster is balanced in the same execution.

./bin/confluent-rebalancer execute --bootstrap-server localhost:9092 --metrics-bootstrap-server localhost:9092 --throttle 100000 --remove-broker-ids 1

Computing the rebalance plan (this may take a while) ...
You are about to move 48 replica(s) for 48 partitions to 3 broker(s) with total size 775.5 MB.
The preferred leader for 20 partition(s) will be changed.
In total, the assignment for 49 partitions will be changed.

You have requested all replicas to be moved out of 1 broker(s) with ID(s): 1.
After the rebalance, these broker(s) will have no replicas.

The following brokers will require more disk space during the rebalance and, in some cases, after the rebalance:
     Broker     Current (MB)    During Rebalance (MB)  After Rebalance (MB)
     0          517             775.5                  568.7
     2          517             775.5                  723.8
     3          517             775.5                  775.5

Min/max stats for brokers (before -> after):
     Type  Leader Count                 Replica Count                Size (MB)
     Min   17 (id: 0) -> 0 (id: 1)      43 (id: 3) -> 0 (id: 1)      517 (id: 2) -> 0 (id: 1)
     Max   17 (id: 0) -> 23 (id: 0)     45 (id: 0) -> 59 (id: 0)     517 (id: 1) -> 775.5 (id: 3)
No racks are defined.

Would you like to continue? (y/n):

Given that we have 8 partitions with roughly the same amount of data, it’s not possible for the 3 remaining brokers to have the same amount of data. Broker 2 would have 2 partitions after the rebalance and therefore, less data.

Limiting bandwidth usage during data migration

Use the --throttle option to limit the amount of bandwidth used for replication. It is possible to update the value while a rebalance is in progress by simply rerunning the tool.

./bin/confluent-rebalancer execute --bootstrap-server localhost:9092 --metrics-bootstrap-server localhost:9092 --throttle 100000

The throttle rate was updated to 100000 bytes/sec.
A rebalance is currently in progress for:
        Topic topic-b: 0,1

See Throttling for more details.

Limiting the scope of the reassignment

You can use the --topics and --exclude-internal-topics flags to limit the set of topics that are eligible for reassignment. You can use --replica-placement-only to perform reassignment only on partitions that do not satisfy the replica placement constraints. Assuming that topic topic-c was configured to use replica placement constraints, the following command makes the necessary reassignment to satisfy the constraints.

./bin/confluent-rebalancer execute --bootstrap-server localhost:9092 --metrics-bootstrap-server localhost:9092 --throttle 100000 --topics topic-c --replica-placement-only

For more details on replica placement constraints, see Replica Placement.

Incremental reassignment

For Kafka clusters with a large number of topic partitions, performing a reassignment in one batch can result in degraded performance or availability. To limit the maximum number of reassignments per leader, use the flag --incremental and the configuration parameter max.concurrent.moves.per.leader`.

./bin/confluent-rebalancer execute --incremental --bootstrap-server localhost:9092 --metrics-bootstrap-server localhost:9092 --throttle 100000

Use JMX for monitoring

Authentication is disabled for Java Management Extensions (JMX) by default in Kafka. You must use environment variables to override these defaults.

Use KAFKA_JMX_OPTS for processes started using the CLI or set the appropriate Java system properties.

For each platform component, the options to override the JMX defaults take the form <component-name>_JMX_OPTS.

For the confluent-rebalancer, use the environment variable REBALANCER_JMX_OPTS for processes started using the CLI or set the appropriate Java system properties.

Licensing

A license was not specified as part of the quick start. If you have a Confluent license, you can specify it using the confluent.license configuration. For more details about licenses, see Managing Confluent Platform Licenses.