We rely on both Go and Kafka a lot at Segment. Unfortunately, the state of the Go client libraries for Kafka at the time of this writing was not ideal. The available options were:
-
sarama, which is by far the most popular but is quite difficult to work with. It is poorly documented, the API exposes low level concepts of the Kafka protocol, and it doesn't support recent Go features like contexts. It also passes all values as pointers which causes large numbers of dynamic memory allocations, more frequent garbage collections, and higher memory usage.
-
confluent-kafka-go is a cgo based wrapper around librdkafka, which means it introduces a dependency to a C library on all Go code that uses the package. It has much better documentation than sarama but still lacks support for Go contexts.
-
goka is a more recent Kafka client for Go which focuses on a specific usage pattern. It provides abstractions for using Kafka as a message passing bus between services rather than an ordered log of events, but this is not the typical use case of Kafka for us at Segment. The package also depends on sarama for all interactions with Kafka.
This is where kafka-go comes into play. It provides both low and high level
APIs for interacting with Kafka, mirroring concepts and implementing interfaces of
the Go standard library to make it easy to use and integrate with existing
software.
In order to better align with our newly adopted Code of Conduct, the kafka-go
project has renamed our default branch to main. For the full details of our
Code Of Conduct see this document.
kafka-go is currently tested with Kafka versions 0.10.1.0 to 2.7.1.
While it should also be compatible with later versions, newer features available
in the Kafka API may not yet be implemented in the client.
kafka-go requires Go version 1.15 or later.
The Conn type is the core of the kafka-go package. It wraps around a raw
network connection to expose a low-level API to a Kafka server.
Here are some examples showing typical use of a connection object:
// to produce messages
topic := "my-topic"
partition := 0
conn, err := kafka.DialLeader(context.Background(), "tcp", "localhost:9092", topic, partition)
if err != nil {
log.Fatal("failed to dial leader:", err)
}
conn.SetWriteDeadline(time.Now().Add(10*time.Second))
_, err = conn.WriteMessages(
kafka.Message{Value: []byte("one!")},
kafka.Message{Value: []byte("two!")},
kafka.Message{Value: []byte("three!")},
)
if err != nil {
log.Fatal("failed to write messages:", err)
}
if err := conn.Close(); err != nil {
log.Fatal("failed to close writer:", err)
}// to consume messages
topic := "my-topic"
partition := 0
conn, err := kafka.DialLeader(context.Background(), "tcp", "localhost:9092", topic, partition)
if err != nil {
log.Fatal("failed to dial leader:", err)
}
conn.SetReadDeadline(time.Now().Add(10*time.Second))
batch := conn.ReadBatch(10e3, 1e6) // fetch 10KB min, 1MB max
b := make([]byte, 10e3) // 10KB max per message
for {
n, err := batch.Read(b)
if err != nil {
break
}
fmt.Println(string(b[:n]))
}
if err := batch.Close(); err != nil {
log.Fatal("failed to close batch:", err)
}
if err := conn.Close(); err != nil {
log.Fatal("failed to close connection:", err)
}By default kafka has the auto.create.topics.enable='true' (KAFKA_CFG_AUTO_CREATE_TOPICS_ENABLE='true' in the bitnami/kafka kafka docker image). If this value is set to 'true' then topics will be created as a side effect of kafka.DialLeader like so:
// to create topics when auto.create.topics.enable='true'
conn, err := kafka.DialLeader(context.Background(), "tcp", "localhost:9092", "my-topic", 0)
if err != nil {
panic(err.Error())
}If auto.create.topics.enable='false' then you will need to create topics explicitly like so:
// to create topics when auto.create.topics.enable='false'
topic := "my-topic"
conn, err := kafka.Dial("tcp", "localhost:9092")
if err != nil {
panic(err.Error())
}
defer conn.Close()
controller, err := conn.Controller()
if err != nil {
panic(err.Error())
}
var controllerConn *kafka.Conn
controllerConn, err = kafka.Dial("tcp", net.JoinHostPort(controller.Host, strconv.Itoa(controller.Port)))
if err != nil {
panic(err.Error())
}
defer controllerConn.Close()
topicConfigs := []kafka.TopicConfig{
{
Topic: topic,
NumPartitions: 1,
ReplicationFactor: 1,
},
}
err = controllerConn.CreateTopics(topicConfigs...)
if err != nil {
panic(err.Error())
}// to connect to the kafka leader via an existing non-leader connection rather than using DialLeader
conn, err := kafka.Dial("tcp", "localhost:9092")
if err != nil {
panic(err.Error())
}
defer conn.Close()
controller, err := conn.Controller()
if err != nil {
panic(err.Error())
}
var connLeader *kafka.Conn
connLeader, err = kafka.Dial("tcp", net.JoinHostPort(controller.Host, strconv.Itoa(controller.Port)))
if err != nil {
panic(err.Error())
}
defer connLeader.Close()conn, err := kafka.Dial("tcp", "localhost:9092")
if err != nil {
panic(err.Error())
}
defer conn.Close()
partitions, err := conn.ReadPartitions()
if err != nil {
panic(err.Error())
}
m := map[string]struct{}{}
for _, p := range partitions {
m[p.Topic] = struct{}{}
}
for k := range m {
fmt.Println(k)
}Because it is low level, the Conn type turns out to be a great building block
for higher level abstractions, like the Reader for example.
A Reader is another concept exposed by the kafka-go package, which intends
to make it simpler to implement the typical use case of consuming from a single
topic-partition pair.
A Reader also automatically handles reconnections and offset management, and
exposes an API that supports asynchronous cancellations and timeouts using Go
contexts.
Note that it is important to call Close() on a Reader when a process exits.
The kafka server needs a graceful disconnect to stop it from continuing to
attempt to send messages to the connected clients. The given example will not
call Close() if the process is terminated with SIGINT (ctrl-c at the shell) or
SIGTERM (as docker stop or a kubernetes restart does). This can result in a
delay when a new reader on the same topic connects (e.g. new process started
or new container running). Use a signal.Notify handler to close the reader on
process shutdown.
// make a new reader that consumes from topic-A, partition 0, at offset 42
r := kafka.NewReader(kafka.ReaderConfig{
Brokers: []string{"localhost:9092","localhost:9093", "localhost:9094"},
Topic: "topic-A",
Partition: 0,
MaxBytes: 10e6, // 10MB
})
r.SetOffset(42)
for {
m, err := r.ReadMessage(context.Background())
if err != nil {
break
}
fmt.Printf("message at offset %d: %s = %s\n", m.Offset, string(m.Key), string(m.Value))
}
if err := r.Close(); err != nil {
log.Fatal("failed to close reader:", err)
}kafka-go also supports Kafka consumer groups including broker managed offsets.
To enable consumer groups, simply specify the GroupID in the ReaderConfig.
ReadMessage automatically commits offsets when using consumer groups.
// make a new reader that consumes from topic-A
r := kafka.NewReader(kafka.ReaderConfig{
Brokers: []string{"localhost:9092", "localhost:9093", "localhost:9094"},
GroupID: "consumer-group-id",
Topic: "topic-A",
MaxBytes: 10e6, // 10MB
})
for {
m, err := r.ReadMessage(context.Background())
if err != nil {
break
}
fmt.Printf("message at topic/partition/offset %v/%v/%v: %s = %s\n", m.Topic, m.Partition, m.Offset, string(m.Key), string(m.Value))
}
if err := r.Close(); err != nil {
log.Fatal("failed to close reader:", err)
}There are a number of limitations when using consumer groups:
(*Reader).SetOffsetwill return an error when GroupID is set(*Reader).Offsetwill always return-1when GroupID is set(*Reader).Lagwill always return-1when GroupID is set(*Reader).ReadLagwill return an error when GroupID is set(*Reader).Statswill return a partition of-1when GroupID is set
kafka-go also supports explicit commits. Instead of calling ReadMessage,
call FetchMessage followed by CommitMessages.
ctx := context.Background()
for {
m, err := r.FetchMessage(ctx)
if err != nil {
break
}
fmt.Printf("message at topic/partition/offset %v/%v/%v: %s = %s\n", m.Topic, m.Partition, m.Offset, string(m.Key), string(m.Value))
if err := r.CommitMessages(ctx, m); err != nil {
log.Fatal("failed to commit messages:", err)
}
}When committing messages in consumer groups, the message with the highest offset
for a given topic/partition determines the value of the committed offset for
that partition. For example, if messages at offset 1, 2, and 3 of a single
partition were retrieved by call to FetchMessage, calling CommitMessages
with message offset 3 will also result in committing the messages at offsets 1
and 2 for that partition.
By default, CommitMessages will synchronously commit offsets to Kafka. For improved performance, you can instead periodically commit offsets to Kafka by setting CommitInterval on the ReaderConfig.
// make a new reader that consumes from topic-A
r := kafka.NewReader(kafka.ReaderConfig{
Brokers: []string{"localhost:9092", "localhost:9093", "localhost:9094"},
GroupID: "consumer-group-id",
Topic: "topic-A",
MaxBytes: 10e6, // 10MB
CommitInterval: time.Second, // flushes commits to Kafka every second
})To produce messages to Kafka, a program may use the low-level Conn API, but
the package also provides a higher level Writer type which is more appropriate
to use in most cases as it provides additional features:
- Automatic retries and reconnections on errors.
- Configurable distribution of messages across available partitions.
- Synchronous or asynchronous writes of messages to Kafka.
- Asynchronous cancellation using contexts.
- Flushing of pending messages on close to support graceful shutdowns.
- Creation of a missing topic before publishing a message. Note! it was the default behaviour up to the version
v0.4.30.
// make a writer that produces to topic-A, using the least-bytes distribution
w := &kafka.Writer{
Addr: kafka.TCP("localhost:9092", "localhost:9093", "localhost:9094"),
Topic: "topic-A",
Balancer: &kafka.LeastBytes{},
}
err := w.WriteMessages(context.Background(),
kafka.Message{
Key: []byte("Key-A"),
Value: []byte("Hello World!"),
},
kafka.Message{
Key: []byte("Key-B"),
Value: []byte("One!"),
},
kafka.Message{
Key: []byte("Key-C"),
Value: []byte("Two!"),
},
)
if err != nil {
log.Fatal("failed to write messages:", err)
}
if err := w.Close(); err != nil {
log.Fatal("failed to close writer:", err)
}// Make a writer that publishes messages to topic-A.
// The topic will be created if it is missing.
w := &Writer{
Addr: kafka.TCP("localhost:9092", "localhost:9093", "localhost:9094"),
Topic: "topic-A",
AllowAutoTopicCreation: true,
}
messages := []kafka.Message{
{
Key: []byte("Key-A"),
Value: []byte("Hello World!"),
},
{
Key: []byte("Key-B"),
Value: []byte("One!"),
},
{
Key: []byte("Key-C"),
Value: []byte("Two!"),
},
}
var err error
const retries = 3
for i := 0; i < retries; i++ {
ctx, cancel := context.WithTimeout(context.Background(), 10*time.Second)
defer cancel()
// attempt to create topic prior to publishing the message
err = w.WriteMessages(ctx, messages...)
if errors.Is(err, kafka.LeaderNotAvailable) || errors.Is(err, context.DeadlineExceeded) {
time.Sleep(time.Millisecond * 250)
continue
}
if err != nil {
log.Fatalf("unexpected error %v", err)
}
break
}
if err := w.Close(); err != nil {
log.Fatal("failed to close writer:", err)
}Normally, the WriterConfig.Topic is used to initialize a single-topic writer.
By excluding that particular configuration, you are given the ability to define
the topic on a per-message basis by setting Message.Topic.
w := &kafka.Writer{
Addr: kafka.TCP("localhost:9092", "localhost:9093", "localhost:9094"),
// NOTE: When Topic is not defined here, each Message must define it instead.
Balancer: &kafka.LeastBytes{},
}
err := w.WriteMessages(context.Background(),
// NOTE: Each Message has Topic defined, otherwise an error is returned.
kafka.Message{
Topic: "topic-A",
Key: []byte("Key-A"),
Value: []byte("Hello World!"),
},
kafka.Message{
Topic: "topic-B",
Key: []byte("Key-B"),
Value: []byte("One!"),
},
kafka.Message{
Topic: "topic-C",
Key: []byte("Key-C"),
Value: []byte("Two!"),
},
)
if err != nil {
log.Fatal("failed to write messages:", err)
}
if err := w.Close(); err != nil {
log.Fatal("failed to close writer:", err)
}NOTE: These 2 patterns are mutually exclusive, if you set Writer.Topic,
you must not also explicitly define Message.Topic on the messages you are
writing. The opposite applies when you do not define a topic for the writer.
The Writer will return an error if it detects this ambiguity.
If you're switching from Sarama and need/want to use the same algorithm for message partitioning, you can either use
the kafka.Hash balancer or the kafka.ReferenceHash balancer:
kafka.Hash=sarama.NewHashPartitionerkafka.ReferenceHash=sarama.NewReferenceHashPartitioner
The kafka.Hash and kafka.ReferenceHash balancers would route messages to the same partitions that the two
aforementioned Sarama partitioners would route them to.
w := &kafka.Writer{
Addr: kafka.TCP("localhost:9092", "localhost:9093", "localhost:9094"),
Topic: "topic-A",
Balancer: &kafka.Hash{},
}Use the kafka.CRC32Balancer balancer to get the same behaviour as librdkafka's
default consistent_random partition strategy.
w := &kafka.Writer{
Addr: kafka.TCP("localhost:9092", "localhost:9093", "localhost:9094"),
Topic: "topic-A",
Balancer: kafka.CRC32Balancer{},
}Use the kafka.Murmur2Balancer balancer to get the same behaviour as the canonical
Java client's default partitioner. Note: the Java class allows you to directly specify
the partition which is not permitted.
w := &kafka.Writer{
Addr: kafka.TCP("localhost:9092", "localhost:9093", "localhost:9094"),
Topic: "topic-A",
Balancer: kafka.Murmur2Balancer{},
}Compression can be enabled on the Writer by setting the Compression field:
w := &kafka.Writer{
Addr: kafka.TCP("localhost:9092", "localhost:9093", "localhost:9094"),
Topic: "topic-A",
Compression: kafka.Snappy,
}The Reader will by determine if the consumed messages are compressed by
examining the message attributes. However, the package(s) for all expected
codecs must be imported so that they get loaded correctly.
Note: in versions prior to 0.4 programs had to import compression packages to install codecs and support reading compressed messages from kafka. This is no longer the case and import of the compression packages are now no-ops.
For a bare bones Conn type or in the Reader/Writer configs you can specify a dialer option for TLS support. If the TLS field is nil, it will not connect with TLS. Note: Connecting to a Kafka cluster with TLS enabled without configuring TLS on the Conn/Reader/Writer can manifest in opaque io.ErrUnexpectedEOF errors.
dialer := &kafka.Dialer{
Timeout: 10 * time.Second,
DualStack: true,
TLS: &tls.Config{...tls config...},
}
conn, err := dialer.DialContext(ctx, "tcp", "localhost:9093")dialer := &kafka.Dialer{
Timeout: 10 * time.Second,
DualStack: true,
TLS: &tls.Config{...tls config...},
}
r := kafka.NewReader(kafka.ReaderConfig{
Brokers: []string{"localhost:9092", "localhost:9093", "localhost:9094"},
GroupID: "consumer-group-id",
Topic: "topic-A",
Dialer: dialer,
})Direct Writer creation
w := kafka.Writer{
Addr: kafka.TCP("localhost:9092", "localhost:9093", "localhost:9094"),
Topic: "topic-A",
Balancer: &kafka.Hash{},
Transport: &kafka.Transport{
TLS: &tls.Config{},
},
}Using kafka.NewWriter
dialer := &kafka.Dialer{
Timeout: 10 * time.Second,
DualStack: true,
TLS: &tls.Config{...tls config...},
}
w := kafka.NewWriter(kafka.WriterConfig{
Brokers: []string{"localhost:9092", "localhost:9093", "localhost:9094"},
Topic: "topic-A",
Balancer: &kafka.Hash{},
Dialer: dialer,
})Note that kafka.NewWriter and kafka.WriterConfig are deprecated and will be removed in a future release.
You can specify an option on the Dialer to use SASL authentication. The Dialer can be used directly to open a Conn or it can be passed to a Reader or Writer via their respective configs. If the SASLMechanism field is nil, it will not authenticate with SASL.
mechanism := plain.Mechanism{
Username: "username",
Password: "password",
}mechanism, err := scram.Mechanism(scram.SHA512, "username", "password")
if err != nil {
panic(err)
}mechanism, err := scram.Mechanism(scram.SHA512, "username", "password")
if err != nil {
panic(err)
}
dialer := &kafka.Dialer{
Timeout: 10 * time.Second,
DualStack: true,
SASLMechanism: mechanism,
}
conn, err := dialer.DialContext(ctx, "tcp", "localhost:9093")mechanism, err := scram.Mechanism(scram.SHA512, "username", "password")
if err != nil {
panic(err)
}
dialer := &kafka.Dialer{
Timeout: 10 * time.Second,
DualStack: true,
SASLMechanism: mechanism,
}
r := kafka.NewReader(kafka.ReaderConfig{
Brokers: []string{"localhost:9092","localhost:9093", "localhost:9094"},
GroupID: "consumer-group-id",
Topic: "topic-A",
Dialer: dialer,
})mechanism, err := scram.Mechanism(scram.SHA512, "username", "password")
if err != nil {
panic(err)
}
// Transports are responsible for managing connection pools and other resources,
// it's generally best to create a few of these and share them across your
// application.
sharedTransport := &kafka.Transport{
SASL: mechanism,
}
w := kafka.Writer{
Addr: kafka.TCP("localhost:9092", "localhost:9093", "localhost:9094"),
Topic: "topic-A",
Balancer: &kafka.Hash{},
Transport: sharedTransport,
}mechanism, err := scram.Mechanism(scram.SHA512, "username", "password")
if err != nil {
panic(err)
}
// Transports are responsible for managing connection pools and other resources,
// it's generally best to create a few of these and share them across your
// application.
sharedTransport := &kafka.Transport{
SASL: mechanism,
}
client := &kafka.Client{
Addr: kafka.TCP("localhost:9092", "localhost:9093", "localhost:9094"),
Timeout: 10 * time.Second,
Transport: sharedTransport,
}startTime := time.Now().Add(-time.Hour)
endTime := time.Now()
batchSize := int(10e6) // 10MB
r := kafka.NewReader(kafka.ReaderConfig{
Brokers: []string{"localhost:9092", "localhost:9093", "localhost:9094"},
Topic: "my-topic1",
Partition: 0,
MaxBytes: batchSize,
})
r.SetOffsetAt(context.Background(), startTime)
for {
m, err := r.ReadMessage(context.Background())
if err != nil {
break
}
if m.Time.After(endTime) {
break
}
// TODO: process message
fmt.Printf("message at offset %d: %s = %s\n", m.Offset, string(m.Key), string(m.Value))
}
if err := r.Close(); err != nil {
log.Fatal("failed to close reader:", err)
}For visiblity into the operations of the Reader/Writer types, configure a logger on creation.
func logf(msg string, a ...interface{}) {
fmt.Printf(msg, a...)
fmt.Println()
}
r := kafka.NewReader(kafka.ReaderConfig{
Brokers: []string{"localhost:9092", "localhost:9093", "localhost:9094"},
Topic: "my-topic1",
Partition: 0,
Logger: kafka.LoggerFunc(logf),
ErrorLogger: kafka.LoggerFunc(logf),
})func logf(msg string, a ...interface{}) {
fmt.Printf(msg, a...)
fmt.Println()
}
w := &kafka.Writer{
Addr: kafka.TCP("localhost:9092"),
Topic: "topic",
Logger: kafka.LoggerFunc(logf),
ErrorLogger: kafka.LoggerFunc(logf),
}Subtle behavior changes in later Kafka versions have caused some historical tests to break, if you are running against Kafka 2.3.1 or later, exporting the KAFKA_SKIP_NETTEST=1 environment variables will skip those tests.
Run Kafka locally in docker
docker-compose up -dRun tests
KAFKA_VERSION=2.3.1 \
KAFKA_SKIP_NETTEST=1 \
go test -race ./...(or) to clean up the cached test results and run tests:
go clean -cache && make test
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