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Application Reset Tool¶
You can reset an application and force it to reprocess its data from scratch by using the application reset tool. This can be useful for development and testing, or when fixing bugs.
The application reset tool handles the Kafka Streams user topics (input, output, and intermediate topics) and internal topics differently when resetting the application.
Here’s what the application reset tool does for each topic type:
- Input topics: Reset offsets to specified position. By default they are reset to the beginning of the topic.
- Intermediate topics: Skip to the end of the topic, i.e., set the application’s committed consumer offsets for all partitions to each partition’s
logSize(for consumer groupapplication.id). - Internal topics: Delete the internal topic (this automatically deletes any committed offsets).
The application reset tool does not:
- Reset output topics of an application. If any output (or intermediate) topics are consumed by downstream applications, it is your responsibility to adjust those downstream applications as appropriate when you reset the upstream application.
- Reset the local environment of your application instances. It is your responsibility to delete the local state on any machine on which an application instance was run. See the instructions in section Step 2: Reset the local environments of your application instances on how to do this.
- Prerequisites
All instances of your application must be stopped. Otherwise, the application may enter an invalid state, crash, or produce incorrect results. You can verify whether the consumer group with ID
application.idis still active by usingbin/kafka-consumer-groups.Use this tool with care and double-check its parameters: If you provide wrong parameter values (e.g., typos in
application.id) or specify parameters inconsistently (e.g., specify the wrong input topics for the application), this tool might invalidate the application’s state or even impact other applications, consumer groups, or your Apache Kafka® topics.You should manually delete and re-create any intermediate topics before running the application reset tool. This will free up disk space in Kafka brokers.
You should delete and recreate intermediate topics before running the application reset tool, unless the following applies:
- You have external downstream consumers for the application’s intermediate topics.
- You are in a development environment where manually deleting and re-creating intermediate topics is unnecessary.
Step 1: Run the application reset tool¶
Invoke the application reset tool from the command line
<path-to-confluent>/bin/kafka-streams-application-reset
The tool accepts the following parameters:
Option (* = required) Description
--------------------- -----------
* --application-id <String: ID> The |kstreams| application ID
(application.id).
--bootstrap-servers <String: urls> Comma-separated list of broker urls with
format: HOST1:PORT1,HOST2:PORT2
(default: localhost:9092)
--by-duration <String: urls> Reset offsets to offset by duration from
current timestamp. Format: 'PnDTnHnMnS'
--config-file <String: file name> Property file containing configs to be
passed to admin clients and embedded
consumer.
--dry-run Display the actions that would be
performed without executing the reset
commands.
--from-file <String: urls> Reset offsets to values defined in CSV
file.
--input-topics <String: list> Comma-separated list of user input
topics. For these topics, the tool will
reset the offset to the earliest
available offset.
--intermediate-topics <String: list> Comma-separated list of intermediate user
topics (topics used in the through()
method). For these topics, the tool
will skip to the end.
--shift-by <Long: number-of-offsets> Reset offsets shifting current offset by
'n', where 'n' can be positive or
negative
--to-datetime <String> Reset offsets to offset from datetime.
Format: 'YYYY-MM-DDTHH:mm:SS.sss'
--to-earliest Reset offsets to earliest offset.
--to-latest Reset offsets to latest offset.
--to-offset <Long> Reset offsets to a specific offset.
--zookeeper Zookeeper option is deprecated by
bootstrap.servers, as the reset tool
would no longer access Zookeeper
directly.
Parameters can be combined as needed. For example, if you want to restart an application from an
empty internal state, but not reprocess previous data, simply omit the parameters --input-topics and
--intermediate-topics.
Step 2: Reset the local environments of your application instances¶
For a complete application reset, you must delete the application’s local state directory on any machines where the application instance was run. You must do this before restarting an application instance on the same machine. You can use either of these methods:
- The API method
KafkaStreams#cleanUp()in your application code. - Manually delete the corresponding local state directory (default location:
/var/lib/kafka-streams/<application.id>). For more information, see state.dir StreamsConfig class.
Example¶
In this example you are developing and testing an application locally and you want to iteratively improve your application via run-reset-modify cycles.
package io.confluent.examples.streams;
import ...;
public class ResetDemo {
public static void main(String[] args) throws Exception {
// Kafka Streams configuration
Properties props = new Properties();
props.put(StreamsConfig.APPLICATION_ID_CONFIG, "my-streams-app");
// ...and so on...
// Define the processing topology
StreamsBuilder builder = new StreamsBuilder();
builder.stream("my-input-topic")
.selectKey(...)
.through("rekeyed-topic")
.groupByKey()
.count("global-count")
.to("my-output-topic");
KafkaStreams app = new KafkaStreams(builder.build(), props);
// Delete the application's local state.
// Note: In real application you'd call `cleanUp()` only under
// certain conditions. See tip on `cleanUp()` below.
app.cleanUp();
app.start();
// Note: In real applications you would register a shutdown hook
// that would trigger the call to `app.close()` rather than
// using the sleep-then-close example we show here.
Thread.sleep(30 * 1000L);
app.close();
}
}
Tip: To avoid the corresponding recovery overhead, you should not call cleanUp() unconditionally and every time an
application instance is restarted or resumed. For exammple, in a production application you could use command line
arguments to enable or disable the cleanUp() call on an as-needed basis.
You can then perform run-reset-modify cycles as follows:
# Run your application
bin/kafka-run-class io.confluent.examples.streams.ResetDemo
# After stopping all application instances, reset the application
bin/kafka-streams-application-reset --application-id my-streams-app \
--input-topics my-input-topic \
--intermediate-topics rekeyed-topic
# Now you can modify/recompile as needed and then re-run the application again.
# You can also experiment, for example, with different input data without
# modifying the application.