Franz-go is an all-encompassing Apache Kafka client fully written Go. This library aims to provide every Kafka feature from Apache Kafka v0.8.0 onward. It has support for transactions, regex topic consuming, the latest partitioning strategies, data loss detection, closest replica fetching, and more. If a client KIP exists, this library aims to support it.
This library attempts to provide an intuitive API while interacting with Kafka the way Kafka expects (timeouts, etc.).
Request functionkgo.ProducerBatchCompression(kgo.NoCompression).This repo contains multiple tags to allow separate features to be developed and
released independently. The main client is in franz-go. Plugins are released
from plugin/{plugin}. The raw-protocol package is released from pkg/kmsg,
and the admin package is released from pkg/kadm.
The main client is located in the package github.com/twmb/franz-go/pkg/kgo,
while the root of the project is at github.com/twmb/franz-go. There are
a few extra packages within the project, as well as a few sub-modules. To
use the main kgo package,
go get github.com/twmb/franz-go
To use a plugin,
go get github.com/twmb/franz-go/plugin/kzap
To use kadm,
go get github.com/twmb/franz-go/pkg/kadm
As an example, your require section in go.mod may look like this:
require (
github.com/twmb/franz-go v1.12.0
github.com/twmb/franz-go/pkg/kmsg v1.4.0
)
Here's a basic overview of producing and consuming:
seeds := []string{"localhost:9092"} // One client can both produce and consume! // Consuming can either be direct (no consumer group), or through a group. Below, we use a group. cl, err := kgo.NewClient( kgo.SeedBrokers(seeds...), kgo.ConsumerGroup("my-group-identifier"), kgo.ConsumeTopics("foo"), ) if err != nil { panic(err) } defer cl.Close() ctx := context.Background() // 1.) Producing a message // All record production goes through Produce, and the callback can be used // to allow for synchronous or asynchronous production. var wg sync.WaitGroup wg.Add(1) record := &kgo.Record{Topic: "foo", Value: []byte("bar")} cl.Produce(ctx, record, func(_ *kgo.Record, err error) { defer wg.Done() if err != nil { fmt.Printf("record had a produce error: %v\n", err) } }) wg.Wait() // Alternatively, ProduceSync exists to synchronously produce a batch of records. if err := cl.ProduceSync(ctx, record).FirstErr(); err != nil { fmt.Printf("record had a produce error while synchronously producing: %v\n", err) } // 2.) Consuming messages from a topic for { fetches := cl.PollFetches(ctx) if errs := fetches.Errors(); len(errs) > 0 { // All errors are retried internally when fetching, but non-retriable errors are // returned from polls so that users can notice and take action. panic(fmt.Sprint(errs)) } // We can iterate through a record iterator... iter := fetches.RecordIter() for !iter.Done() { record := iter.Next() fmt.Println(string(record.Value), "from an iterator!") } // or a callback function. fetches.EachPartition(func(p kgo.FetchTopicPartition) { for _, record := range p.Records { fmt.Println(string(record.Value), "from range inside a callback!") } // We can even use a second callback! p.EachRecord(func(record *kgo.Record) { fmt.Println(string(record.Value), "from a second callback!") }) }) }
This only shows producing and consuming in the most basic sense, and does not show the full list of options to customize how the client runs, nor does it show transactional producing / consuming. Check out the examples directory for more!
API reference documentation can be found on
.
Supplementary information can be found in the docs directory:
In alphabetical order,
If you use this library and want on the list above, please either open a PR or comment on #142!
By default, the client issues an ApiVersions request on connect to brokers and
defaults to using the maximum supported version for requests that each broker
supports. If you want to pin to an exact version, you can use the MaxVersions
option.
Kafka 0.10.0 introduced the ApiVersions request; if you are working with brokers older than that, you must use the kversions package. Use the MaxVersions option for the client if you do so.
Note there exists plug-in packages that allow you to easily add prometheus
metrics, go-metrics, zap logging, etc. to your client! See the plugin
directory for more information! These plugins are provided under dedicated
modules, e.g. github.com/twmb/franz-go/plugin/kprom@v1.0.0.
The franz-go client takes a neutral approach to metrics by providing hooks that you can use to plug in your own metrics.
All connections, disconnections, reads, writes, and throttles can be hooked into, as well as per-batch produce & consume metrics. If there is an aspect of the library that you wish you could have insight into, please open an issue and we can discuss adding another hook.
Hooks allow you to log in the event of specific errors, or to trace latencies, count bytes, etc., all with your favorite monitoring systems.
In addition to hooks, logging can be plugged in with a general Logger
interface. A basic logger is provided if you just want to write to a given
file in a simple format. All logs have a message and then key/value pairs of
supplementary information. It is recommended to always use a logger and to use
LogLevelInfo.
See this example for an expansive example of integrating with prometheus! Alternatively, see this example for how to use the plug-in prometheus package!
This client is quite fast; it is the fastest and most cpu and memory efficient client in Go.
For 100 byte messages,
This client is 4x faster at producing than confluent-kafka-go, and up to 10x-20x faster (at the expense of more memory usage) at consuming.
This client is 2.5x faster at producing than sarama, and 1.5x faster at consuming.
This client is 2.4x faster at producing than segment's kafka-go, and anywhere from 2x to 6x faster at consuming.
To check benchmarks yourself, see the bench example. This example lets you produce or consume to a cluster and see the byte / record rate. The compare subdirectory shows comparison code.
Theoretically, this library supports every (non-Java-specific) client facing KIP. Any KIP that simply adds or modifies a protocol is supported by code generation.
| KIP | Kafka release | Status |
|---|---|---|
| KIP-1 — Disallow acks > 1 | 0.8.3 | Supported & Enforced |
| KIP-4 — Request protocol changes | 0.9.0 through 0.10.1 | Supported |
| KIP-8 — Flush method on Producer | 0.8.3 | Supported |
| KIP-12 — SASL & SSL | 0.9.0 | Supported |
| KIP-13 — Throttling (on broker) | 0.9.0 | Supported |
| KIP-15 — Close with a timeout | 0.9.0 | Supported (via context) |
| KIP-19 — Request timeouts | 0.9.0 | Supported |
| KIP-22 — Custom partitioners | 0.9.0 | Supported |
| KIP-31 — Relative offsets in message sets | 0.10.0 | Supported |
| KIP-32 — Timestamps in message set v1 | 0.10.0 | Supported |
| KIP-35 — ApiVersion | 0.10.0 | Supported |
| KIP-40 — ListGroups and DescribeGroups | 0.9.0 | Supported |
| KIP-41 — max.poll.records | 0.10.0 | Supported (via PollRecords) |
| KIP-42 — Producer & consumer interceptors | 0.10.0 | Partial support (hooks) |
| KIP-43 — SASL PLAIN & handshake | 0.10.0 | Supported |
| KIP-48 — Delegation tokens | 1.1 | Supported |
| KIP-54 — Sticky partitioning | 0.11.0 | Supported |
| KIP-57 — Fix lz4 | 0.10.0 | Supported |
| KIP-62 — background heartbeats & improvements | 0.10.1 | Supported |
| KIP-70 — On{Assigned,Revoked} | 0.10.1 | Supported |
| KIP-74 — Fetch response size limits | 0.10.1 | Supported |
| KIP-78 — ClusterID in Metadata | 0.10.1 | Supported |
| KIP-79 — List offsets for times | 0.10.1 | Supported |
| KIP-81 — Bound fetch memory usage | WIP | Supported (through a combo of options) |


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