hw-kafka-client
Kafka bindings for Haskell
https://github.com/haskell-works/hw-kafka-client
Version on this page: | 4.0.3 |
LTS Haskell 22.37: | 5.3.0 |
Stackage Nightly 2024-10-11: | 5.3.0 |
Latest on Hackage: | 5.3.0 |
hw-kafka-client-4.0.3@sha256:20e3614454d5afd2a6acfc0709b9bf00bd6ee9a9bc646c2e2e4ccec1d16831a1,4861
hw-kafka-client
Kafka bindings for Haskell backed by the librdkafka C module.
Ecosystem
HaskellWorks Kafka ecosystem is described here: https://github.com/haskell-works/hw-kafka
Consumer
High level consumers are supported by librdkafka
starting from version 0.9.
High-level consumers provide an abstraction for consuming messages from multiple
partitions and topics. They also address scalability (up to a number of partitions)
by providing automatic rebalancing functionality. When a new consumer joins a consumer
group the set of consumers attempts to “rebalance” the load to assign partitions to each consumer.
Consumer example
See Running integration tests locally to learn how to configure a local environment.
cabal build --flag examples
or
cabal run kafka-client-example --flag examples
A working consumer example can be found here: ConsumerExample.hs
To run an example please compile with the examples
flag.
import Control.Exception (bracket)
import Kafka.Consumer
-- Global consumer properties
consumerProps :: ConsumerProperties
consumerProps = brokersList ["localhost:9092"]
<> groupId "consumer_example_group"
<> noAutoCommit
<> logLevel KafkaLogInfo
-- Subscription to topics
consumerSub :: Subscription
consumerSub = topics ["kafka-client-example-topic"]
<> offsetReset Earliest
-- Running an example
runConsumerExample :: IO ()
runConsumerExample = do
res <- bracket mkConsumer clConsumer runHandler
print res
where
mkConsumer = newConsumer consumerProps consumerSub
clConsumer (Left err) = return (Left err)
clConsumer (Right kc) = maybe (Right ()) Left <$> closeConsumer kc
runHandler (Left err) = return (Left err)
runHandler (Right kc) = processMessages kc
-------------------------------------------------------------------
processMessages :: KafkaConsumer -> IO (Either KafkaError ())
processMessages kafka = do
replicateM_ 10 $ do
msg <- pollMessage kafka (Timeout 1000)
putStrLn $ "Message: " <> show msg
err <- commitAllOffsets OffsetCommit kafka
putStrLn $ "Offsets: " <> maybe "Committed." show err
return $ Right ()
Producer
kafka-client
producer supports sending messages to multiple topics.
Target topic name is a part of each message that is to be sent by produceMessage
.
A working producer example can be found here: ProducerExample.hs
Delivery reports
Kafka Producer maintains its own internal queue for outgoing messages. Calling produceMessage
does not mean that the message is actually written to Kafka, it only means that the message is put
to that outgoing queue and that the producer will (eventually) push it to Kafka.
However, it is not always possible for the producer to send messages to Kafka. Network problems or Kafka cluster being offline can prevent the producer from doing it.
When a message cannot be sent to Kafka for some time (see message.timeout.ms
configuration option),
the message is dropped from the outgoing queue and the delivery report indicating an error is raised.
It is possible to configure hw-kafka-client
to set an infinite message timeout so the message is
never dropped from the queue:
producerProps :: ProducerProperties
producerProps = brokersList ["localhost:9092"]
<> sendTimeout (Timeout 0) -- for librdkafka "0" means "infinite" (see https://github.com/edenhill/librdkafka/issues/2015)
Delivery reports provide the way to detect when producer experiences problems sending messages to Kafka.
Currently hw-kafka-client
only supports delivery error callbacks:
producerProps :: ProducerProperties
producerProps = brokersList ["localhost:9092"]
<> setCallback (deliveryCallback print)
In the example above when the producer cannot deliver the message to Kafka, the error will be printed (and the message will be dropped).
Producer example
{-# LANGUAGE OverloadedStrings #-}
import Control.Exception (bracket)
import Control.Monad (forM_)
import Data.ByteString (ByteString)
import Kafka.Producer
-- Global producer properties
producerProps :: ProducerProperties
producerProps = brokersList ["localhost:9092"]
<> logLevel KafkaLogDebug
-- Topic to send messages to
targetTopic :: TopicName
targetTopic = "kafka-client-example-topic"
-- Run an example
runProducerExample :: IO ()
runProducerExample =
bracket mkProducer clProducer runHandler >>= print
where
mkProducer = newProducer producerProps
clProducer (Left _) = return ()
clProducer (Right prod) = closeProducer prod
runHandler (Left err) = return $ Left err
runHandler (Right prod) = sendMessages prod
sendMessages :: KafkaProducer -> IO (Either KafkaError ())
sendMessages prod = do
err1 <- produceMessage prod (mkMessage Nothing (Just "test from producer") )
forM_ err1 print
err2 <- produceMessage prod (mkMessage (Just "key") (Just "test from producer (with key)"))
forM_ err2 print
return $ Right ()
mkMessage :: Maybe ByteString -> Maybe ByteString -> ProducerRecord
mkMessage k v = ProducerRecord
{ prTopic = targetTopic
, prPartition = UnassignedPartition
, prKey = k
, prValue = v
}
Synchronous sending of messages
Because of the asynchronous nature of librdkafka, there is no API to provide
synchronous production of messages. It is, however, possible to combine the
delivery reports feature with that of callbacks. This can be done using the
Kafka.Producer.produceMessage'
function.
produceMessage' :: MonadIO m
=> KafkaProducer
-> ProducerRecord
-> (DeliveryReport -> IO ())
-> m (Either ImmediateError ())
Using this function, you can provide a callback which will be invoked upon the
produced message’s delivery report. With a little help of MVar
s or similar,
you can in fact, create a synchronous-like interface.
sendMessageSync :: MonadIO m
=> KafkaProducer
-> ProducerRecord
-> m (Either KafkaError Offset)
sendMessageSync producer record = liftIO $ do
-- Create an empty MVar:
var <- newEmptyMVar
-- Produce the message and use the callback to put the delivery report in the
-- MVar:
res <- produceMessage' producer record (putMVar var)
case res of
Left (ImmediateError err) ->
pure (Left err)
Right () -> do
-- Flush producer queue to make sure you don't get stuck waiting for the
-- message to send:
flushProducer producer
-- Wait for the message's delivery report and map accordingly:
takeMVar var >>= return . \case
DeliverySuccess _ offset -> Right offset
DeliveryFailure _ err -> Left err
NoMessageError err -> Left err
Note: this is a semi-naive solution as this waits forever (or until librdkafka times out). You should make sure that your configuration reflects the behavior you want out of this functionality.
Running integration tests locally
shell.nix can be used to provide a working environment that is enough to build and test hw-kafka-client
.
To be able to run tests locally, $KAFKA_TEST_BROKER
environment variable is expected to be set (use shell.nix or export manually).
$KAFKA_TEST_BROKER
should contain an IP address of an accessible Kafka broker that will be used to run integration tests against.
With Docker Compose this variable is used to configure Kafka broker to listen on this address:
$ docker-compose up
After that, integration tests can switched on with using ‘it’ flag:
$ cabal test --test-show-details=direct --flag it
Credits
This project is inspired by Haskakafka which unfortunately doesn’t seem to be actively maintained.