shibuya-kafka-adapter-0.12.0.0: src/Shibuya/Adapter/Kafka/Internal.hs
-- | Internal implementation details for the Kafka adapter.
-- This module is not part of the public API and may change without notice.
module Shibuya.Adapter.Kafka.Internal
( -- * Adapter State
KafkaAdapterState (..),
KafkaAcknowledgementException (..),
newKafkaAdapterState,
markPartitionsAssigned,
markPartitionsRevoked,
withConsumerLock,
-- * Stream Construction
kafkaSource,
Polled (..),
gateRecords,
ingestedStream,
-- * Ingested Construction
mkIngested,
-- * AckHandle Construction
mkAckHandle,
)
where
import Control.Concurrent (threadDelay)
import Control.Concurrent.MVar (MVar, newMVar, putMVar, takeMVar)
import Control.Concurrent.STM (TVar, atomically, modifyTVar', newTVarIO, readTVar, readTVarIO, retry)
import Control.Exception qualified as IOExc
import Control.Monad (unless, when)
import Data.ByteString (ByteString)
import Data.Function ((&))
import Data.IORef (IORef, atomicModifyIORef', atomicWriteIORef, newIORef, readIORef)
import Data.Map.Strict (Map)
import Data.Map.Strict qualified as Map
import Data.Text qualified as Text
import Data.Time.Clock (NominalDiffTime)
import Data.Word (Word64)
import Effectful (Eff, IOE, (:>))
import Effectful qualified
import Effectful.Error.Static (Error, catchError, throwError)
import Effectful.Exception qualified as Exception
import Kafka.Consumer.Types (ConsumerRecord (..), Offset (..), PartitionOffset (..), TopicPartition (..))
import Kafka.Effectful.Consumer.Effect
( KafkaConsumer,
pausePartitions,
pollMessageBatch,
seekPartitions,
storeOffsetMessage,
)
import Kafka.Streamly.Stream (isFatal, skipNonFatal)
import Kafka.Types (KafkaError, PartitionId, Timeout (..), TopicName)
import Shibuya.Adapter.Kafka.Config (KafkaAdapterConfig (..))
import Shibuya.Adapter.Kafka.Convert (consumerRecordToEnvelope)
import Shibuya.Core.Ack (AckDecision (..), RetryDelay (..), renderDeadLetterReason)
import Shibuya.Core.AckHandle (AckHandle (..))
import Shibuya.Core.Ingested (Ingested)
import Shibuya.Core.Ingested qualified as Core
import Streamly.Data.Stream (Stream)
import Streamly.Data.Stream qualified as Stream
import System.IO (hPutStrLn, stderr)
type PartitionKey = (TopicName, PartitionId)
newtype DeliveryToken = DeliveryToken Word64
deriving stock (Eq, Ord, Show)
newtype AssignmentGeneration = AssignmentGeneration Word64
deriving stock (Eq, Show)
data RetryBarrier = RetryBarrier
{ offset :: !Offset,
retryToken :: !DeliveryToken,
replayed :: !Bool
}
data PartitionAckState = PartitionAckState
{ barrier :: !(Maybe RetryBarrier),
validFromToken :: !DeliveryToken,
assignmentGeneration :: !AssignmentGeneration,
assigned :: !Bool,
retryRequests :: !Word64,
seeksCompleted :: !Word64,
seekedAt :: !Word64,
halted :: !Bool
}
data AckState = AckState
{ nextDeliveryToken :: !Word64,
seekSerial :: !Word64,
partitions :: !(Map PartitionKey PartitionAckState)
}
data DeliveryAttempt = DeliveryAttempt
{ partition :: !PartitionKey,
recordOffset :: !Offset,
token :: !DeliveryToken,
generation :: !AssignmentGeneration
}
-- | A Kafka operation failed after the adapter's bounded retry budget. This is
-- a synchronous exception so Shibuya's finalizer boundary can retry it and,
-- when exhausted, retain a processor failure with the delivery identity.
newtype KafkaAcknowledgementException = KafkaAcknowledgementException KafkaError
deriving stock (Show)
instance Exception.Exception KafkaAcknowledgementException
initialPartitionAckState :: PartitionAckState
initialPartitionAckState =
PartitionAckState
{ barrier = Nothing,
validFromToken = DeliveryToken 0,
assignmentGeneration = AssignmentGeneration 0,
assigned = True,
retryRequests = 0,
seeksCompleted = 0,
seekedAt = 0,
halted = False
}
initialAckState :: AckState
initialAckState = AckState {nextDeliveryToken = 1, seekSerial = 0, partitions = Map.empty}
-- | Mutable state shared by the source stream and ack handles.
data KafkaAdapterState = KafkaAdapterState
{ shutdownVar :: !(TVar Bool),
ackState :: !(IORef AckState),
ackSignal :: !(TVar Word64),
fatalError :: !(IORef (Maybe KafkaError)),
-- | Serializes every librdkafka consumer operation. Under
-- 'Shibuya.App.runApp' the consumer handle is shared between the ingester
-- thread (which polls) and the processor thread (which seeks, stores,
-- pauses, and commits during finalize). Running @rd_kafka_consume_batch_queue@
-- concurrently with a seek/store on the same handle corrupts librdkafka's
-- internal fetch queue and crashes with a native SIGSEGV, so every consumer
-- call is wrapped in this mutex. Each poll is additionally bounded (see
-- @maxPollHoldMillis@) so the lock is released frequently and finalize is
-- never starved.
consumerLock :: !(MVar ())
}
-- | Allocate mutable state shared by the Kafka source, ack handles, and
-- optional rebalance callback.
newKafkaAdapterState :: IO KafkaAdapterState
newKafkaAdapterState =
KafkaAdapterState
<$> newTVarIO False
<*> newIORef initialAckState
<*> newTVarIO 0
<*> newIORef Nothing
<*> newMVar ()
-- | Mark partitions assigned to this adapter generation. A revoke/assign cycle
-- advances the generation, so ack handles retained from the previous owner can
-- no longer store, seek, or pause the newly assigned partition.
markPartitionsAssigned :: KafkaAdapterState -> [PartitionKey] -> IO ()
markPartitionsAssigned state = setPartitionsAssigned state True
-- | Mark partitions revoked and discard only the local retry ledger. Kafka's
-- committed offset remains the durable recovery boundary; callbacks from the
-- old generation are fenced by the incremented assignment generation.
markPartitionsRevoked :: KafkaAdapterState -> [PartitionKey] -> IO ()
markPartitionsRevoked state = setPartitionsAssigned state False
setPartitionsAssigned :: KafkaAdapterState -> Bool -> [PartitionKey] -> IO ()
setPartitionsAssigned state isAssigned keys = IOExc.mask_ $ do
atomicModifyIORef' state.ackState $ \ackState' ->
let partitions' = foldr (Map.alter (Just . transition . maybe initialPartitionAckState id)) ackState'.partitions keys
in (ackState' {partitions = partitions'}, ())
signalAckState state
where
transition partitionState
| partitionState.assigned == isAssigned =
if isAssigned
then partitionState
else partitionState {barrier = Nothing}
| otherwise =
partitionState
{ barrier = Nothing,
validFromToken = DeliveryToken 0,
assignmentGeneration = nextGeneration partitionState.assignmentGeneration,
assigned = isAssigned,
seeksCompleted = partitionState.retryRequests,
halted = False
}
nextGeneration (AssignmentGeneration generation') = AssignmentGeneration (generation' + 1)
-- | Run a librdkafka consumer operation while holding the shared consumer
-- lock, guaranteeing no other consumer call runs concurrently on the same
-- handle. See 'consumerLock' for why this is mandatory. The lock is always
-- released, including when the action throws through the 'Error' @KafkaError@
-- effect.
withConsumerLock :: (IOE :> es) => KafkaAdapterState -> Eff es a -> Eff es a
withConsumerLock state =
Exception.bracket_
(Effectful.liftIO (takeMVar state.consumerLock))
(Effectful.liftIO (putMVar state.consumerLock ()))
-- | Upper bound (milliseconds) on how long any single blocking consumer call
-- may hold the consumer lock. Every consumer call runs under 'consumerLock' so
-- the poll never races a concurrent seek/store on the shared handle (see
-- 'consumerLock'). A call that blocks for its whole timeout — an empty poll, or a
-- seek that cannot complete — would then hold the lock for that long and starve
-- (and, under GHC's deadlock detector, wedge) the finalize path that must seek to
-- redeliver a retried message. Capping the poll and seek timeouts at this value
-- keeps the lock available roughly every @maxPollHoldMillis@ so finalize can
-- interleave and the ingester promptly re-polls to observe redelivered records.
-- It also bounds shutdown latency. The cap leaves ample headroom over a healthy
-- seek (which acknowledges in single-digit milliseconds), so it only bites when a
-- call is genuinely stuck — in which case surfacing it fast (via the ack path's
-- bounded retry and fatal slot) is the desired behavior.
maxPollHoldMillis :: Int
maxPollHoldMillis = 100
-- | Cap a caller-supplied timeout at 'maxPollHoldMillis' so a single blocking
-- consumer call cannot hold the consumer lock longer than that. Applied to both
-- the poll and the retry seek.
boundedLockTimeout :: Timeout -> Timeout
boundedLockTimeout t = Timeout (min (unTimeout t) maxPollHoldMillis)
-- | Poll records and stamp each successful record with the completed seek serial
-- under the consumer lock. Feed this stream through 'gateRecords'.
--
-- Calls 'pollMessageBatch' in a loop under 'consumerLock', preserving errors as
-- @Left@ values. Each poll uses a timeout capped at @maxPollHoldMillis@ so the
-- lock stays available to the finalize path (which seeks, stores, pauses, and
-- commits). Non-fatal errors (timeouts, partition EOF, etc.) are filtered out
-- via 'skipNonFatal' from hw-kafka-streamly. Fatal errors are preserved for
-- upstream handling; a fatal error recorded by the ack path (see 'fatalError')
-- terminates the stream.
kafkaSource ::
(KafkaConsumer :> es, Error KafkaError :> es, IOE :> es) =>
KafkaAdapterState ->
KafkaAdapterConfig ->
Stream (Eff es) (Either KafkaError Polled)
kafkaSource state config =
skipNonFatal $
Stream.unfoldrM step ()
& Stream.concatMap Stream.fromList
where
pollT = boundedLockTimeout config.pollTimeout
step () = do
mbFatal <- Effectful.liftIO $ readIORef state.fatalError
case mbFatal of
Just err -> throwError err
Nothing -> pure ()
isShutdown <- Effectful.liftIO $ readTVarIO state.shutdownVar
if isShutdown
then pure Nothing
else do
batch <- withConsumerLock state $ do
records <- pollMessageBatch pollT config.batchSize
serial <- Effectful.liftIO $ (.seekSerial) <$> readIORef state.ackState
pure (map (fmap (Polled serial)) records)
pure (Just (batch, ()))
-- | A record stamped under the consumer lock with the latest completed seek.
data Polled = Polled
{ pollSerial :: !Word64,
record :: !(ConsumerRecord (Maybe ByteString) (Maybe ByteString))
}
data Admission = Emit | EmitAfterGap !Offset | Drop | Hold
-- | Drop pre-seek records; retain post-seek successors until their replay resolves.
-- Holds are interruptible and never own the consumer lock. Missing offsets are
-- abandoned with a warning, fencing callbacks from before the gap.
gateRecords ::
(IOE :> es) =>
KafkaAdapterState ->
Stream (Eff es) (Either KafkaError Polled) ->
Stream (Eff es) (Either KafkaError (ConsumerRecord (Maybe ByteString) (Maybe ByteString)))
gateRecords state =
Stream.mapMaybeM $ \case
Left err -> pure (Just (Left err))
Right polled -> do
admitted <- Effectful.liftIO $ admitRecord state polled
pure $ if admitted then Just (Right polled.record) else Nothing
admitRecord :: KafkaAdapterState -> Polled -> IO Bool
admitRecord state polled = do
ackState' <- readIORef state.ackState
let partitionState = Map.findWithDefault initialPartitionAckState key ackState'.partitions
case (partitionState.barrier, isFresh partitionState) of
(Nothing, True) -> pure True
_ -> wait
where
cr = polled.record
key = partitionKey cr
isFresh partitionState =
partitionState.assigned
&& partitionState.retryRequests == partitionState.seeksCompleted
&& polled.pollSerial >= partitionState.seekedAt
wait = do
version <- readTVarIO state.ackSignal
admission <- atomicModifyIORef' state.ackState decide
case admission of
Emit -> pure True
EmitAfterGap missing -> do
hPutStrLn stderr $
"[shibuya-kafka-adapter] WARNING: retried record is no longer in the log; resuming after it: "
<> show (cr.crTopic, cr.crPartition, missing)
pure True
Drop -> pure False
Hold -> do
mbFatal <- readIORef state.fatalError
case mbFatal of
Just _ -> pure False
Nothing -> do
stop <- atomically $ do
isShutdown <- readTVar state.shutdownVar
current <- readTVar state.ackSignal
if isShutdown
then pure True
else if current /= version then pure False else retry
if stop then pure False else wait
decide ackState' =
let partitionState = Map.findWithDefault initialPartitionAckState key ackState'.partitions
update partitionState' = ackState' {partitions = Map.insert key partitionState' ackState'.partitions}
in if not (isFresh partitionState)
then (ackState', Drop)
else case partitionState.barrier of
Nothing -> (ackState', Emit)
Just retryBarrier
| cr.crOffset < retryBarrier.offset -> (ackState', Emit)
| cr.crOffset == retryBarrier.offset ->
(update partitionState {barrier = Just retryBarrier {replayed = True}}, Emit)
| partitionState.halted -> (ackState', Drop)
| retryBarrier.replayed -> (ackState', Hold)
| otherwise ->
( update
partitionState
{ barrier = Nothing,
validFromToken = max partitionState.validFromToken (DeliveryToken ackState'.nextDeliveryToken)
},
EmitAfterGap retryBarrier.offset
)
-- | Create an 'AckHandle' for a single 'ConsumerRecord'.
--
-- Maps 'AckDecision' to Kafka operations:
--
-- * 'AckOk' -> 'storeOffsetMessage' (mark offset ready for commit)
-- * 'AckRetry' -> record seek barrier and seek partition back to the failed offset
-- * 'AckDeadLetter' -> warn to stderr, then 'storeOffsetMessage' (DLQ deferred)
-- * 'AckHalt' -> 'pausePartitions' (do NOT store offset; message will be re-consumed)
mkAckHandle ::
(KafkaConsumer :> es, Error KafkaError :> es, IOE :> es) =>
KafkaAdapterState ->
KafkaAdapterConfig ->
ConsumerRecord (Maybe ByteString) (Maybe ByteString) ->
Eff es (AckHandle es)
mkAckHandle state config cr = do
attempt <- Effectful.liftIO $ registerDelivery state cr
ackHandleFor state config attempt cr
ackHandleFor ::
(KafkaConsumer :> es, Error KafkaError :> es, IOE :> es) =>
KafkaAdapterState ->
KafkaAdapterConfig ->
DeliveryAttempt ->
ConsumerRecord (Maybe ByteString) (Maybe ByteString) ->
Eff es (AckHandle es)
ackHandleFor state config attempt cr = do
finalizerLock <- Effectful.liftIO $ newMVar ()
completed <- Effectful.liftIO $ newIORef False
pure $ AckHandle $ \decision ->
Exception.bracket_
(Effectful.liftIO (takeMVar finalizerLock))
(Effectful.liftIO (putMVar finalizerLock ()))
$ do
isCompleted <- Effectful.liftIO $ readIORef completed
unless isCompleted $ do
finalizeAttempt state config attempt cr decision
Effectful.liftIO $ atomicWriteIORef completed True
registerDelivery :: KafkaAdapterState -> ConsumerRecord k v -> IO DeliveryAttempt
registerDelivery state cr =
atomicModifyIORef' state.ackState $ \ackState' ->
let partition = partitionKey cr
partitionState = Map.findWithDefault initialPartitionAckState partition ackState'.partitions
token = DeliveryToken ackState'.nextDeliveryToken
attempt =
DeliveryAttempt
{ partition,
recordOffset = cr.crOffset,
token,
generation = partitionState.assignmentGeneration
}
ackState'' =
ackState'
{ nextDeliveryToken = ackState'.nextDeliveryToken + 1,
partitions = Map.insert partition partitionState ackState'.partitions
}
in (ackState'', attempt)
finalizeAttempt ::
(KafkaConsumer :> es, Error KafkaError :> es, IOE :> es) =>
KafkaAdapterState ->
KafkaAdapterConfig ->
DeliveryAttempt ->
ConsumerRecord (Maybe ByteString) (Maybe ByteString) ->
AckDecision ->
Eff es ()
finalizeAttempt state config attempt cr = \case
AckOk -> storeGuarded state attempt cr (pure ())
AckRetry (RetryDelay delay) -> do
Effectful.liftIO $ delayRetry delay
mbTarget <- Effectful.liftIO $ recordRetry state attempt
case mbTarget of
Nothing -> pure ()
Just (target, request) ->
ackAttempt state $
withConsumerLock state $ do
seekPartitions
[ TopicPartition
{ tpTopicName = cr.crTopic,
tpPartition = cr.crPartition,
tpOffset = PartitionOffset (unOffset target)
}
]
(boundedLockTimeout config.pollTimeout)
Effectful.liftIO $ markSeekCompleted state attempt.partition request
AckDeadLetter reason ->
storeGuarded state attempt cr $
Effectful.liftIO $
hPutStrLn stderr $
"[shibuya-kafka-adapter] WARNING: dead-lettered message DROPPED (no DLQ producer): "
<> show (cr.crTopic, cr.crPartition, cr.crOffset)
<> " reason="
<> Text.unpack (renderDeadLetterReason reason)
AckHalt _ -> do
isAccepted <- Effectful.liftIO $ markHalted state attempt
when isAccepted $
ackAttempt state (withConsumerLock state (pausePartitions [(cr.crTopic, cr.crPartition)]))
ackAttempt ::
(Error KafkaError :> es, IOE :> es) =>
KafkaAdapterState ->
Eff es () ->
Eff es ()
ackAttempt state action = go (1 :: Int)
where
maxAttempts = 3
retryDelayMicros = 50000
go attempt =
action `catchError` \_ err ->
if isFatal err || attempt >= maxAttempts
then do
Effectful.liftIO $ recordFatalError state err
Exception.throwIO (KafkaAcknowledgementException err)
else do
Effectful.liftIO $ threadDelay retryDelayMicros
go (attempt + 1)
recordFatalError :: KafkaAdapterState -> KafkaError -> IO ()
recordFatalError state err = IOExc.mask_ $ do
atomicModifyIORef' state.fatalError $ \case
Just existing -> (Just existing, ())
Nothing -> (Just err, ())
signalAckState state
storeGuarded ::
(KafkaConsumer :> es, Error KafkaError :> es, IOE :> es) =>
KafkaAdapterState ->
DeliveryAttempt ->
ConsumerRecord (Maybe ByteString) (Maybe ByteString) ->
Eff es () ->
Eff es ()
storeGuarded state attempt cr beforeStore = do
shouldStore <- Effectful.liftIO $ claimStore state attempt
when shouldStore $ do
beforeStore
ackAttempt state (withConsumerLock state (storeOffsetMessage cr))
recordRetry :: KafkaAdapterState -> DeliveryAttempt -> IO (Maybe (Offset, Word64))
recordRetry state attempt = IOExc.mask_ $ do
result <- atomicModifyIORef' state.ackState $ \ackState' ->
let partitionState = Map.findWithDefault initialPartitionAckState attempt.partition ackState'.partitions
in if not (attemptIsAccepted partitionState attempt)
then (ackState', Nothing)
else
let retryBarrier = case partitionState.barrier of
Nothing -> RetryBarrier attempt.recordOffset attempt.token False
Just existing
| attempt.recordOffset < existing.offset -> RetryBarrier attempt.recordOffset attempt.token False
| attempt.recordOffset == existing.offset && attempt.token > existing.retryToken ->
existing {retryToken = attempt.token}
| otherwise -> existing
partitionState' = partitionState {barrier = Just retryBarrier {replayed = False}, retryRequests = partitionState.retryRequests + 1}
ackState'' = ackState' {partitions = Map.insert attempt.partition partitionState' ackState'.partitions}
in (ackState'', Just (retryBarrier.offset, partitionState'.retryRequests))
case result of
Nothing -> pure ()
Just _ -> signalAckState state
pure result
claimStore :: KafkaAdapterState -> DeliveryAttempt -> IO Bool
claimStore state attempt = IOExc.mask_ $ do
(accepted, cleared) <- atomicModifyIORef' state.ackState $ \ackState' ->
let partitionState = Map.findWithDefault initialPartitionAckState attempt.partition ackState'.partitions
in if not (attemptIsAccepted partitionState attempt)
then (ackState', (False, False))
else case partitionState.barrier of
Nothing -> (ackState', (True, False))
Just retryBarrier
| attempt.recordOffset > retryBarrier.offset -> (ackState', (False, False))
| attempt.recordOffset < retryBarrier.offset -> (ackState', (True, False))
| attempt.token <= retryBarrier.retryToken -> (ackState', (False, False))
| otherwise ->
let partitionState' =
partitionState
{ barrier = Nothing,
validFromToken = max partitionState.validFromToken attempt.token
}
ackState'' = ackState' {partitions = Map.insert attempt.partition partitionState' ackState'.partitions}
in (ackState'', (True, True))
when cleared $ signalAckState state
pure accepted
signalAckState :: KafkaAdapterState -> IO ()
signalAckState state = atomically $ modifyTVar' state.ackSignal (+ 1)
markSeekCompleted :: KafkaAdapterState -> PartitionKey -> Word64 -> IO ()
markSeekCompleted state key request = IOExc.mask_ $ do
atomicModifyIORef' state.ackState $ \ledger ->
let serial = ledger.seekSerial + 1
partition = Map.findWithDefault initialPartitionAckState key ledger.partitions
updated = partition {seekedAt = serial, seeksCompleted = max partition.seeksCompleted request}
in (ledger {seekSerial = serial, partitions = Map.insert key updated ledger.partitions}, ())
signalAckState state
markHalted :: KafkaAdapterState -> DeliveryAttempt -> IO Bool
markHalted state attempt = IOExc.mask_ $ do
accepted <- atomicModifyIORef' state.ackState $ \ledger ->
let partition = Map.findWithDefault initialPartitionAckState attempt.partition ledger.partitions
in if attemptIsAccepted partition attempt
then (ledger {partitions = Map.insert attempt.partition partition {halted = True} ledger.partitions}, True)
else (ledger, False)
when accepted $ signalAckState state
pure accepted
attemptIsAccepted :: PartitionAckState -> DeliveryAttempt -> Bool
attemptIsAccepted partitionState attempt =
partitionState.assigned
&& partitionState.assignmentGeneration == attempt.generation
&& attempt.token >= partitionState.validFromToken
partitionKey :: ConsumerRecord k v -> PartitionKey
partitionKey cr = (cr.crTopic, cr.crPartition)
delayRetry :: NominalDiffTime -> IO ()
delayRetry delay
| delay <= 0 = pure ()
| otherwise = threadDelay (floor (realToFrac delay * (1000000 :: Double)))
-- | Combine conversion and ack handle to produce an 'Ingested'.
--
-- Lease is always 'Nothing' for Kafka (no visibility timeout mechanism).
mkIngested ::
(KafkaConsumer :> es, Error KafkaError :> es, IOE :> es) =>
KafkaAdapterState ->
KafkaAdapterConfig ->
ConsumerRecord (Maybe ByteString) (Maybe ByteString) ->
Eff es (Ingested es (Maybe ByteString))
mkIngested state config cr = do
attempt <- Effectful.liftIO $ registerDelivery state cr
ackHandle <- ackHandleFor state config attempt cr
pure
(Core.mkIngested (consumerRecordToEnvelope cr) ackHandle)
{ Core.deliveryStatus = Effectful.liftIO (deliveryStatusOf state attempt)
}
-- Admission is a single ledger read, independent of consumer-lock ownership.
-- A current answer cannot cancel a later revoke or concurrent retry.
deliveryStatusOf :: KafkaAdapterState -> DeliveryAttempt -> IO Core.DeliveryStatus
deliveryStatusOf state attempt = do
ledger <- readIORef state.ackState
let partition = Map.findWithDefault initialPartitionAckState attempt.partition ledger.partitions
current =
attemptIsAccepted partition attempt && case partition.barrier of
Nothing -> True
Just barrier ->
attempt.recordOffset < barrier.offset
|| (attempt.recordOffset == barrier.offset && attempt.token > barrier.retryToken)
pure $ if current then Core.DeliveryCurrent else Core.DeliverySuperseded
-- | Transform a poll stream of @Either KafkaError ConsumerRecord@ into a
-- stream of 'Ingested'.
--
-- A @Right cr@ is wrapped via the supplied builder (in production,
-- 'mkIngested'). A @Left err@ that reaches this stage is fatal by construction
-- — 'Kafka.Streamly.Stream.skipNonFatal' has already dropped non-fatal errors
-- — and is thrown via the 'Error' @KafkaError@ effect, terminating the stream.
--
-- Parameterizing over the builder function keeps this helper free of the
-- 'KafkaConsumer' constraint, so it can be exercised in a unit test that
-- injects a synthetic @Left@ without standing up a real consumer.
ingestedStream ::
(Error KafkaError :> es) =>
(ConsumerRecord (Maybe ByteString) (Maybe ByteString) -> Eff es (Ingested es (Maybe ByteString))) ->
Stream (Eff es) (Either KafkaError (ConsumerRecord (Maybe ByteString) (Maybe ByteString))) ->
Stream (Eff es) (Ingested es (Maybe ByteString))
ingestedStream mkI =
Stream.mapMaybeM $ \case
Right cr -> Just <$> mkI cr
Left err -> throwError err