rust-rdkafka VS librdkafka

I use this library a lot and it's got some nice touches for how to handle wrapping a C library: https://github.com/fede1024/rust-rdkafka

For this example, we're using rdkafka to build producers and consumers, because it allows us to specify custom headers for each record.

kafka

You might find https://crates.io/crates/rdkafka helpful

I am playing with tokio and rust-rdkafka library, following the examples like this one: https://github.com/fede1024/rust-rdkafka/blob/6fb2c37/examples/asynchronous_processing.rs

The source for the current version of the library can be found on Github. I had to increase the major version because I needed to break the API in order to support all formats supported by the current Schema Registry version. I also added the possibility to set an API key, so it can be used with Confluent Cloud, the cloud offering from Confluent. As part of the latest major refactoring it's also supporting async. This might improve performance of your app, and is also the default for the major Kafka client, more information about why you would want to use async can be found in the async book. The schemas retrieved from the Schema Registry are cached. This way the schema is only retrieved once for each id, and reused for other messages with the same id.

What's wrong with rust-rdkafka?

This is a two-part series to help you get started with Rust and Kafka. We will be using the rust-rdkafka crate which itself is based on librdkafka (C library).

recent PR: https://github.com/confluentinc/librdkafka/pull/4275

# Kafka configuration # https://github.com/confluentinc/librdkafka/blob/master/CONFIGURATION.md bootstrap.servers= security.protocol=SASL_SSL sasl.mechanisms=PLAIN sasl.username= sasl.password= compression.type=gzip compression.level=9 statistics.interval.ms=1000

But what about Kafka producer clients in other languages? The excellent librdkafka project is a C/C++ implementation of Kafka clients and is widely used for non-JVM Kafka applications. Additionally, Kafka clients in other languages (Python, C#) build on top of it. The default partitioner for librdkafka uses the CRC32 hash function to get the correct partition for a key.

We could have made some changes at the librdkafka level (see this), but we didn’t really want to pursue this (at least not yet).

You want records with the same key to always land on the same partition, so you need all the clients to use the same hashing algorithm. The easiest way to do that is to make sure the librdkafka client uses the java compatible murmur2_random hash algorithm. See “Partitioner” section here: https://github.com/confluentinc/librdkafka/blob/master/CONFIGURATION.md

As my first "real world" (ish) project in Vlang, I'm trying to copy https://github.com/confluentinc/confluent-kafka-go, which is a Go wrapper for Kafka C client library, https://github.com/edenhill/librdkafka

If you're using Kafka in a Node.js app, it's likely that you'll need node-rdkafka. This is a library that wraps the librdkafka library and makes it available in Node.js. According to the project's README, "All the complexity of balancing writes across partitions and managing (possibly ever-changing) brokers should be encapsulated in the library."

# Parse the configuration. # See https://github.com/edenhill/librdkafka/blob/master/CONFIGURATION.md config_parser = ConfigParser() config_parser.read_file(args.config_file) config = dict(config_parser['default']) # Create Producer instance producer = Producer(config)

• git clone https://github.com/edenhill/librdkafka.git