rust-rdkafka provides a safe Rust interface to librdkafka. The master branch is currently based on librdkafka 0.11.6.
The main features provided at the moment are:
- Support for all Kafka versions since 0.8.x. For more information about broker compatibility options, check the librdkafka documentation.
- Consume from single or multiple topics.
- Automatic consumer rebalancing.
- Customizable rebalance, with pre and post rebalance callbacks.
- Synchronous or asynchronous message production.
- Customizable offset commit.
- Access to cluster metadata (list of topic-partitions, replicas, active brokers etc).
- Access to group metadata (list groups, list members of groups, hostnames etc).
- Access to producer and consumer metrics, errors and callbacks.
rust-rdkafka is designed to be easy and safe to use thanks to the abstraction layer written in Rust, while at the same time being extremely fast thanks to the librdkafka C library.
Here are some benchmark results using the rust-rdkafka
BaseProducer, sending data to a single Kafka 0.11 process running in localhost (default configuration, 3 partitions). Hardware: Dell laptop, with Intel Core i7-4712HQ @ 2.30GHz.
Scenario: produce 5 million messages, 10 bytes each, wait for all of them to be acked
- 1045413 messages/s, 9.970 MB/s (average over 5 runs)
Scenario: produce 100000 messages, 10 KB each, wait for all of them to be acked
- 24623 messages/s, 234.826 MB/s (average over 5 runs)
For more numbers, check out the kafka-benchmark project.
rust-rdkafka provides low level and high level consumers and producers. Low level:
BaseConsumer: simple wrapper around the librdkafka consumer. It requires to be periodically
poll()ed in order to execute callbacks, rebalances and to receive messages.
BaseProducer: simple wrapper around the librdkafka producer. As in the consumer case, the user must call
poll()periodically to execute delivery callbacks.
BaseProducerwith a separate thread dedicated to polling the producer.
StreamConsumer: it returns a
streamof messages and takes care of polling the consumer internally.
FutureProducer: it returns a
futurethat will be completed once the message is delivered to Kafka (or failed).
For more information about consumers and producers, refer to their module-level documentation.
Warning: the library is under active development and the APIs are likely to change.
tokio-rs is a platform for fast processing of asynchronous events in Rust. The interfaces exposed by the
StreamConsumer and the
FutureProducer allow rust-rdkafka users to easily integrate Kafka consumers and producers within the tokio-rs platform, and write asynchronous message processing code. Note that rust-rdkafka can be used without tokio-rs.
To see rust-rdkafka in action with tokio-rs, check out the asynchronous processing example in the examples folder.
At-least-once delivery semantic is common in many streaming applications: every message is guaranteed to be processed at least once; in case of temporary failure, the message can be re-processed and/or re-delivered, but no message will be lost.
In order to implement at-least-once delivery the stream processing application has to carefully commit the offset only once the message has been processed. Committing the offset too early, instead, might cause message loss, since upon recovery the consumer will start from the next message, skipping the one where the failure occurred.
To see how to implement at-least-once delivery with
rdkafka, check out the at-least-once delivery example in the examples folder. To know more about delivery semantics, check the message delivery semantics chapter in the Kafka documentation.
Here are some of the projects using rust-rdkafka:
- timely-dataflow: a modular implementation of timely dataflow in Rust (you can also check the blog post).
- kafka-view: a web interface for Kafka clusters.
- kafka-benchmark: a high performance benchmarking tool for Kafka.
If you are using rust-rdkafka, please let me know!
Add this to your
[dependencies] rdkafka = "~0.21"
This crate will compile librdkafka from sources and link it statically to your executable. To compile librdkafka you'll need:
- the GNU toolchain
libssl-dev: optional, not included by default (feature:
libsasl2-dev: optional, not included by default (feature:
To enable ssl and sasl, use the
features field in
[dependencies.rdkafka] version = "~0.21" features = ["ssl", "sasl"]
By default a submodule with the librdkafka sources pinned to a specific commit will be used to compile and statically link the library.
dynamic_linking feature can be used to link rdkafka to a locally installed
version of librdkafka: if the feature is enabled, the build script will use
to check the version of the library installed in the system, and it will configure the
compiler to use dynamic linking.
To compile from sources, you'll have to update the submodule containing librdkafka:
git submodule update --init
and then compile using
cargo, selecting the features that you want. Example:
cargo build --features "ssl sasl"
You can find examples in the
examples folder. To run them:
cargo run --example <example_name> -- <example_args>
The unit tests can run without a Kafka broker present:
cargo test --lib
rust-rdkafka contains a suite of tests which is automatically executed by travis in docker-compose. Given the interaction with C code that rust-rdkafka has to do, tests are executed in valgrind to check eventual memory errors and leaks.
To run the full suite using docker-compose:
To run locally, instead:
KAFKA_HOST="kafka_server:9092" cargo test
In this case there is a broker expected to be running on
The broker must be configured with default partition number 3 and topic autocreation in order
for the tests to succeed.
rust-rdkafka uses the
env_logger crates to handle logging. Logging can be enabled
RUST_LOG environment variable, for example:
RUST_LOG="librdkafka=trace,rdkafka::client=debug" cargo test
This will configure the logging level of librdkafka to trace, and the level of the client
module of the Rust client to debug. To actually receive logs from librdkafka, you also have to
debug option in the producer or consumer configuration (see librdkafka
To enable debugging in your project, make sure you initialize the logger with
env_logger::init() or equivalent.
Common client functionalities.
Producer and consumer configuration.
Base trait and common functionality for all consumers.
Group membership API.
Store and manipulate Kafka messages.
Low level and high level rdkafka producers.
A data structure representing topic, partitions and offsets, compatible with the
This module contains type aliases for types defined in the auto-generated bindings.