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.
kafka-go
is currently compatible with Kafka versions from 0.10.1.0 to 2.1.0. While latest versions will be working,
some features available from the Kafka API may not be implemented yet.
kafka-go
is currently compatible with golang version from 1.12+. To use with older versions of golang use release v0.2.5.
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, _ := kafka.DialLeader(context.Background(), "tcp", "localhost:9092", topic, partition)
conn.SetWriteDeadline(time.Now().Add(10*time.Second))
conn.WriteMessages(
kafka.Message{Value: []byte("one!")},
kafka.Message{Value: []byte("two!")},
kafka.Message{Value: []byte("three!")},
)
conn.Close()
// to consume messages
topic := "my-topic"
partition := 0
conn, _ := kafka.DialLeader(context.Background(), "tcp", "localhost:9092", topic, partition)
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 {
_, err := batch.Read(b)
if err != nil {
break
}
fmt.Println(string(b))
}
batch.Close()
conn.Close()
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.
// make a new reader that consumes from topic-A, partition 0, at offset 42
r := kafka.NewReader(kafka.ReaderConfig{
Brokers: []string{"localhost:9092"},
Topic: "topic-A",
Partition: 0,
MinBytes: 10e3, // 10KB
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))
}
r.Close()
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"},
GroupID: "consumer-group-id",
Topic: "topic-A",
MinBytes: 10e3, // 10KB
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))
}
r.Close()
There are a number of limitations when using consumer groups:
(*Reader).SetOffset
will return an error when GroupID is set(*Reader).Offset
will always return-1
when GroupID is set(*Reader).Lag
will always return-1
when GroupID is set(*Reader).ReadLag
will return an error when GroupID is set(*Reader).Stats
will return a partition of-1
when 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))
r.CommitMessages(ctx, m)
}
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"},
GroupID: "consumer-group-id",
Topic: "topic-A",
MinBytes: 10e3, // 10KB
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.
// make a writer that produces to topic-A, using the least-bytes distribution
w := kafka.NewWriter(kafka.WriterConfig{
Brokers: []string{"localhost:9092"},
Topic: "topic-A",
Balancer: &kafka.LeastBytes{},
})
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!"),
},
)
w.Close()
Note: Even though kafka.Message contain Topic
and Partition
fields, they MUST NOT be
set when writing messages. They are intended for read use only.
If you're switching from Sarama and need/want to use the same algorithm for message
partitioning, you can use the kafka.Hash
balancer. kafka.Hash
routes
messages to the same partitions that Sarama's default partitioner would route to.
w := kafka.NewWriter(kafka.WriterConfig{
Brokers: []string{"localhost:9092"},
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.NewWriter(kafka.WriterConfig{
Brokers: []string{"localhost:9092"},
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.NewWriter(kafka.WriterConfig{
Brokers: []string{"localhost:9092"},
Topic: "topic-A",
Balancer: kafka.Murmur2Balancer{},
})
Compression can be enabled on the Writer
by configuring the CompressionCodec
:
w := kafka.NewWriter(kafka.WriterConfig{
Brokers: []string{"localhost:9092"},
Topic: "topic-A",
CompressionCodec: snappy.NewCompressionCodec(),
})
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. For example, if you
are going to be receiving messages compressed with Snappy, add the following
import:
import _ "github.com/segmentio/kafka-go/snappy"
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.
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:9093"},
GroupID: "consumer-group-id",
Topic: "topic-A",
Dialer: dialer,
})
dialer := &kafka.Dialer{
Timeout: 10 * time.Second,
DualStack: true,
TLS: &tls.Config{...tls config...},
}
w := kafka.NewWriter(kafka.WriterConfig{
Brokers: []string{"localhost:9093"},
Topic: "topic-A",
Balancer: &kafka.Hash{},
Dialer: dialer,
})