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kafka-node
Advanced tools
The kafka-node package is a client library for Apache Kafka, a distributed streaming platform. It allows you to produce and consume messages, manage Kafka topics, and handle Kafka streams in Node.js applications.
Producer
This feature allows you to produce messages to a Kafka topic. The code sample demonstrates how to create a Kafka producer, connect to a Kafka broker, and send a message to a specified topic.
const kafka = require('kafka-node');
const client = new kafka.KafkaClient({kafkaHost: 'localhost:9092'});
const producer = new kafka.Producer(client);
const payloads = [
{ topic: 'topic1', messages: 'hello world', partition: 0 }
];
producer.on('ready', function () {
producer.send(payloads, function (err, data) {
console.log(data);
});
});
producer.on('error', function (err) {
console.error('Producer error:', err);
});
Consumer
This feature allows you to consume messages from a Kafka topic. The code sample demonstrates how to create a Kafka consumer, connect to a Kafka broker, and listen for messages on a specified topic.
const kafka = require('kafka-node');
const client = new kafka.KafkaClient({kafkaHost: 'localhost:9092'});
const consumer = new kafka.Consumer(
client,
[
{ topic: 'topic1', partition: 0 }
],
{
autoCommit: true
}
);
consumer.on('message', function (message) {
console.log(message);
});
consumer.on('error', function (err) {
console.error('Consumer error:', err);
});
Admin
This feature allows you to perform administrative tasks such as listing topics. The code sample demonstrates how to create an admin client and list all topics in the Kafka cluster.
const kafka = require('kafka-node');
const client = new kafka.KafkaClient({kafkaHost: 'localhost:9092'});
const admin = new kafka.Admin(client);
admin.listTopics((err, res) => {
console.log(res);
});
KafkaJS is a modern Apache Kafka client for Node.js. It is fully written in JavaScript and provides a more idiomatic and modern API compared to kafka-node. KafkaJS is known for its simplicity, better documentation, and active maintenance.
node-rdkafka is a high-performance Node.js client for Apache Kafka based on the C/C++ library librdkafka. It offers more advanced features and better performance compared to kafka-node, but it requires native module compilation.
Kafka-node is a Node.js client for Apache Kafka 0.9 and later.
Follow the instructions on the Kafka wiki to build Kafka and get a test broker up and running.
New KafkaClient connects directly to Kafka brokers.
kafkaHost
: A string of kafka broker/host combination delimited by comma for example: kafka-1.us-east-1.myapp.com:9093,kafka-2.us-east-1.myapp.com:9093,kafka-3.us-east-1.myapp.com:9093
default: localhost:9092
.connectTimeout
: in ms it takes to wait for a successful connection before moving to the next host default: 10000
requestTimeout
: in ms for a kafka request to timeout default: 30000
autoConnect
: automatically connect when KafkaClient is instantiated otherwise you need to manually call connect
default: true
connectRetryOptions
: object hash that applies to the initial connection. see retry module for these options.idleConnection
: allows the broker to disconnect an idle connection from a client (otherwise the clients continues to reconnect after being disconnected). The value is elapsed time in ms without any data written to the TCP socket. default: 5 minutesmaxAsyncRequests
: maximum async operations at a time toward the kafka cluster. default: 10sslOptions
: Object, options to be passed to the tls broker sockets, ex. { rejectUnauthorized: false }
(Kafka 0.9+)sasl
: Object, SASL authentication configuration (only SASL/PLAIN is currently supported), ex. { mechanism: 'plain', username: 'foo', password: 'bar' }
(Kafka 0.10+)const client = new kafka.KafkaClient({kafkaHost: '10.3.100.196:9092'});
client
: client which keeps a connection with the Kafka server.options
: options for producer,{
// Configuration for when to consider a message as acknowledged, default 1
requireAcks: 1,
// The amount of time in milliseconds to wait for all acks before considered, default 100ms
ackTimeoutMs: 100,
// Partitioner type (default = 0, random = 1, cyclic = 2, keyed = 3, custom = 4), default 0
partitionerType: 2
}
var kafka = require('kafka-node'),
Producer = kafka.Producer,
client = new kafka.KafkaClient(),
producer = new Producer(client);
ready
: this event is emitted when producer is ready to send messages.error
: this is the error event propagates from internal client, producer should always listen it.payloads
: Array,array of ProduceRequest
, ProduceRequest
is a JSON object like:{
topic: 'topicName',
messages: ['message body'], // multi messages should be a array, single message can be just a string or a KeyedMessage instance
key: 'theKey', // string or buffer, only needed when using keyed partitioner
partition: 0, // default 0
attributes: 2, // default: 0
timestamp: Date.now() // <-- defaults to Date.now() (only available with kafka v0.10+)
}
cb
: Function, the callbackattributes
controls compression of the message set. It supports the following values:
0
: No compression1
: Compress using GZip2
: Compress using snappyExample:
var kafka = require('kafka-node'),
Producer = kafka.Producer,
KeyedMessage = kafka.KeyedMessage,
client = new kafka.KafkaClient(),
producer = new Producer(client),
km = new KeyedMessage('key', 'message'),
payloads = [
{ topic: 'topic1', messages: 'hi', partition: 0 },
{ topic: 'topic2', messages: ['hello', 'world', km] }
];
producer.on('ready', function () {
producer.send(payloads, function (err, data) {
console.log(data);
});
});
producer.on('error', function (err) {})
⚠️WARNING: Batch multiple messages of the same topic/partition together as an array on the
messages
attribute otherwise you may lose messages!
This method is used to create topics on the Kafka server. It requires Kafka 0.10+.
topics
: Array, array of topicscb
: Function, the callbackExample:
var kafka = require('kafka-node');
var client = new kafka.KafkaClient();
var topicsToCreate = [{
topic: 'topic1',
partitions: 1,
replicationFactor: 2
},
{
topic: 'topic2',
partitions: 5,
replicationFactor: 3,
// Optional set of config entries
configEntries: [
{
name: 'compression.type',
value: 'gzip'
},
{
name: 'min.compaction.lag.ms',
value: '50'
}
],
// Optional explicit partition / replica assignment
// When this property exists, partitions and replicationFactor properties are ignored
replicaAssignment: [
{
partition: 0,
replicas: [3, 4]
},
{
partition: 1,
replicas: [2, 1]
}
]
}];
client.createTopics(topicsToCreate, (error, result) => {
// result is an array of any errors if a given topic could not be created
});
client
: client which keeps a connection with the Kafka server. Round-robins produce requests to the available topic partitionsoptions
: options for producer,{
// Configuration for when to consider a message as acknowledged, default 1
requireAcks: 1,
// The amount of time in milliseconds to wait for all acks before considered, default 100ms
ackTimeoutMs: 100
}
var kafka = require('kafka-node'),
HighLevelProducer = kafka.HighLevelProducer,
client = new kafka.KafkaClient(),
producer = new HighLevelProducer(client);
ready
: this event is emitted when producer is ready to send messages.error
: this is the error event propagates from internal client, producer should always listen it.payloads
: Array,array of ProduceRequest
, ProduceRequest
is a JSON object like:{
topic: 'topicName',
messages: ['message body'], // multi messages should be a array, single message can be just a string,
key: 'theKey', // string or buffer, only needed when using keyed partitioner
attributes: 1,
timestamp: Date.now() // <-- defaults to Date.now() (only available with kafka v0.10 and KafkaClient only)
}
cb
: Function, the callbackExample:
var kafka = require('kafka-node'),
HighLevelProducer = kafka.HighLevelProducer,
client = new kafka.KafkaClient(),
producer = new HighLevelProducer(client),
payloads = [
{ topic: 'topic1', messages: 'hi' },
{ topic: 'topic2', messages: ['hello', 'world'] }
];
producer.on('ready', function () {
producer.send(payloads, function (err, data) {
console.log(data);
});
});
⚠️WARNING: Batch multiple messages of the same topic/partition together as an array on the
messages
attribute otherwise you may lose messages!
This method is used to create topics on the Kafka server. It only work when auto.create.topics.enable
, on the Kafka server, is set to true. Our client simply sends a metadata request to the server which will auto create topics. When async
is set to false, this method does not return until all topics are created, otherwise it returns immediately.
topics
: Array,array of topicsasync
: Boolean,async or synccb
: Function,the callbackExample:
var kafka = require('kafka-node'),
HighLevelProducer = kafka.HighLevelProducer,
client = new kafka.KafkaClient(),
producer = new HighLevelProducer(client);
// Create topics sync
producer.createTopics(['t','t1'], false, function (err, data) {
console.log(data);
});
// Create topics async
producer.createTopics(['t'], true, function (err, data) {});
producer.createTopics(['t'], function (err, data) {});// Simply omit 2nd arg
highWaterMark
size of write buffer (Default: 100)kafkaClient
options see KafkaClientproducer
options for Producer see HighLevelProducerIn this example we demonstrate how to stream a source of data (from stdin
) to kafka (ExampleTopic
topic) for processing. Then in a separate instance (or worker process) we consume from that kafka topic and use a Transform
stream to update the data and stream the result to a different topic using a ProducerStream
.
Stream text from
stdin
and write that into a Kafka Topic
const Transform = require('stream').Transform;
const ProducerStream = require('./lib/producerStream');
const _ = require('lodash');
const producer = new ProducerStream();
const stdinTransform = new Transform({
objectMode: true,
decodeStrings: true,
transform (text, encoding, callback) {
text = _.trim(text);
console.log(`pushing message ${text} to ExampleTopic`);
callback(null, {
topic: 'ExampleTopic',
messages: text
});
}
});
process.stdin.setEncoding('utf8');
process.stdin.pipe(stdinTransform).pipe(producer);
Use
ConsumerGroupStream
to read from this topic and transform the data and feed the result of into theRebalanceTopic
Topic.
const ProducerStream = require('./lib/producerStream');
const ConsumerGroupStream = require('./lib/consumerGroupStream');
const resultProducer = new ProducerStream();
const consumerOptions = {
kafkaHost: '127.0.0.1:9092',
groupId: 'ExampleTestGroup',
sessionTimeout: 15000,
protocol: ['roundrobin'],
asyncPush: false,
id: 'consumer1',
fromOffset: 'latest'
};
const consumerGroup = new ConsumerGroupStream(consumerOptions, 'ExampleTopic');
const messageTransform = new Transform({
objectMode: true,
decodeStrings: true,
transform (message, encoding, callback) {
console.log(`Received message ${message.value} transforming input`);
callback(null, {
topic: 'RebalanceTopic',
messages: `You have been (${message.value}) made an example of`
});
}
});
consumerGroup.pipe(messageTransform).pipe(resultProducer);
client
: client which keeps a connection with the Kafka server. Note: it's recommend that create new client for different consumers.payloads
: Array,array of FetchRequest
, FetchRequest
is a JSON object like:{
topic: 'topicName',
offset: 0, //default 0
partition: 0 // default 0
}
options
: options for consumer,{
groupId: 'kafka-node-group',//consumer group id, default `kafka-node-group`
// Auto commit config
autoCommit: true,
autoCommitIntervalMs: 5000,
// The max wait time is the maximum amount of time in milliseconds to block waiting if insufficient data is available at the time the request is issued, default 100ms
fetchMaxWaitMs: 100,
// This is the minimum number of bytes of messages that must be available to give a response, default 1 byte
fetchMinBytes: 1,
// The maximum bytes to include in the message set for this partition. This helps bound the size of the response.
fetchMaxBytes: 1024 * 1024,
// If set true, consumer will fetch message from the given offset in the payloads
fromOffset: false,
// If set to 'buffer', values will be returned as raw buffer objects.
encoding: 'utf8',
keyEncoding: 'utf8'
}
Example:
var kafka = require('kafka-node'),
Consumer = kafka.Consumer,
client = new kafka.KafkaClient(),
consumer = new Consumer(
client,
[
{ topic: 't', partition: 0 }, { topic: 't1', partition: 1 }
],
{
autoCommit: false
}
);
By default, we will consume messages from the last committed offset of the current group
onMessage
: Function, callback when new message comesExample:
consumer.on('message', function (message) {
console.log(message);
});
Add topics to current consumer, if any topic to be added not exists, return error
topics
: Array, array of topics to addcb
: Function,the callbackfromOffset
: Boolean, if true, the consumer will fetch message from the specified offset, otherwise it will fetch message from the last commited offset of the topic.Example:
consumer.addTopics(['t1', 't2'], function (err, added) {
});
or
consumer.addTopics([{ topic: 't1', offset: 10 }], function (err, added) {
}, true);
topics
: Array, array of topics to removecb
: Function, the callbackExample:
consumer.removeTopics(['t1', 't2'], function (err, removed) {
});
Commit offset of the current topics manually, this method should be called when a consumer leaves
cb
: Function, the callbackExample:
consumer.commit(function(err, data) {
});
Set offset of the given topic
topic
: String
partition
: Number
offset
: Number
Example:
consumer.setOffset('topic', 0, 0);
Pause the consumer. Calling pause
does not automatically stop messages from being emitted. This is because pause just stops the kafka consumer fetch loop. Each iteration of the fetch loop can obtain a batch of messages (limited by fetchMaxBytes
).
Resume the consumer. Resumes the fetch loop.
Pause specify topics
consumer.pauseTopics([
'topic1',
{ topic: 'topic2', partition: 0 }
]);
Resume specify topics
consumer.resumeTopics([
'topic1',
{ topic: 'topic2', partition: 0 }
]);
force
: Boolean, if set to true, it forces the consumer to commit the current offset before closing, default false
Example
consumer.close(true, cb);
consumer.close(cb); //force is disabled
Consumer
implemented using node's Readable
stream interface. Read more about streams here.
kafka-node
each chunk is a kafka message100
messages and can be changed through the highWaterMark
optionSimilar API as Consumer
with some exceptions. Methods like pause
and resume
in ConsumerStream
respects the toggling of flow mode in a Stream. In Consumer
calling pause()
just paused the fetch cycle and will continue to emit message
events. Pausing in a ConsumerStream
should immediately stop emitting data
events.
var options = {
kafkaHost: 'broker:9092', // connect directly to kafka broker (instantiates a KafkaClient)
batch: undefined, // put client batch settings if you need them
ssl: true, // optional (defaults to false) or tls options hash
groupId: 'ExampleTestGroup',
sessionTimeout: 15000,
// An array of partition assignment protocols ordered by preference.
// 'roundrobin' or 'range' string for built ins (see below to pass in custom assignment protocol)
protocol: ['roundrobin'],
encoding: 'utf8', // default is utf8, use 'buffer' for binary data
// Offsets to use for new groups other options could be 'earliest' or 'none' (none will emit an error if no offsets were saved)
// equivalent to Java client's auto.offset.reset
fromOffset: 'latest', // default
commitOffsetsOnFirstJoin: true, // on the very first time this consumer group subscribes to a topic, record the offset returned in fromOffset (latest/earliest)
// how to recover from OutOfRangeOffset error (where save offset is past server retention) accepts same value as fromOffset
outOfRangeOffset: 'earliest', // default
migrateHLC: false, // for details please see Migration section below
migrateRolling: true,
// Callback to allow consumers with autoCommit false a chance to commit before a rebalance finishes
// isAlreadyMember will be false on the first connection, and true on rebalances triggered after that
onRebalance: (isAlreadyMember, callback) => { callback(); } // or null
};
var consumerGroup = new ConsumerGroup(options, ['RebalanceTopic', 'RebalanceTest']);
// Or for a single topic pass in a string
var consumerGroup = new ConsumerGroup(options, 'RebalanceTopic');
You can pass a custom assignment strategy to the protocol
array with the interface:
topicPartition
{
"RebalanceTopic": [
"0",
"1",
"2"
],
"RebalanceTest": [
"0",
"1",
"2"
]
}
groupMembers
[
{
"subscription": [
"RebalanceTopic",
"RebalanceTest"
],
"version": 0,
"id": "consumer1-8db1b117-61c6-4f91-867d-20ccd1ad8b3d"
},
{
"subscription": [
"RebalanceTopic",
"RebalanceTest"
],
"version": 0,
"id": "consumer3-bf2d11f4-1c73-4a39-b498-cfe76eb65bea"
},
{
"subscription": [
"RebalanceTopic",
"RebalanceTest"
],
"version": 0,
"id": "consumer2-9781058e-fad4-40e8-a69c-69afbae05184"
}
]
callback(error, result)
result
[
{
"memberId": "consumer3-bf2d11f4-1c73-4a39-b498-cfe76eb65bea",
"topicPartitions": {
"RebalanceTopic": [
"2"
],
"RebalanceTest": [
"2"
]
},
"version": 0
},
{
"memberId": "consumer2-9781058e-fad4-40e8-a69c-69afbae05184",
"topicPartitions": {
"RebalanceTopic": [
"1"
],
"RebalanceTest": [
"1"
]
},
"version": 0
},
{
"memberId": "consumer1-8db1b117-61c6-4f91-867d-20ccd1ad8b3d",
"topicPartitions": {
"RebalanceTopic": [
"0"
],
"RebalanceTest": [
"0"
]
},
"version": 0
}
]
By default, we will consume messages from the last committed offset of the current group
onMessage
: Function, callback when new message comesExample:
consumer.on('message', function (message) {
console.log(message);
});
Commit offset of the current topics manually, this method should be called when a consumer leaves
force
: Boolean, force a commit even if there's a pending commit, default false (optional)cb
: Function, the callbackExample:
consumer.commit(function(err, data) {
});
Pause the consumer. Calling pause
does not automatically stop messages from being emitted. This is because pause just stops the kafka consumer fetch loop. Each iteration of the fetch loop can obtain a batch of messages (limited by fetchMaxBytes
).
Resume the consumer. Resumes the fetch loop.
force
: Boolean, if set to true, it forces the consumer to commit the current offset before closing, default false
Example:
consumer.close(true, cb);
consumer.close(cb); //force is disabled
The ConsumerGroup
wrapped with a Readable
stream interface. Read more about consuming Readable
streams here.
Same notes in the Notes section of ConsumerStream applies to this stream.
ConsumerGroupStream
manages auto commits differently than ConsumerGroup
. Whereas the ConsumerGroup
would automatically commit offsets of fetched messages the ConsumerGroupStream
will only commit offsets of consumed messages from the stream buffer. This will be better for most users since it more accurately represents what was actually "Consumed". The interval at which auto commit fires off is still controlled by the autoCommitIntervalMs
option and this feature can be disabled by setting autoCommit
to false
.
consumerGroupOptions
same options to initialize a ConsumerGroup
topics
a single or array of topics to subscribe toThis method can be used to commit manually when autoCommit
is set to false
.
message
the original message or an object with {topic, partition, offset}
force
a commit even if there's a pending commitcallback
(optional)Closes the ConsumerGroup
. Calls callback
when complete. If autoCommit
is enabled calling close will also commit offsets consumed from the buffer.
client
: client which keeps a connection with the Kafka server.ready
: when all brokers are discoveredconnect
when broker is readyFetch the available offset of a specific topic-partition
payloads
: Array,array of OffsetRequest
, OffsetRequest
is a JSON object like:{
topic: 'topicName',
partition: 0, //default 0
// time:
// Used to ask for all messages before a certain time (ms), default Date.now(),
// Specify -1 to receive the latest offsets and -2 to receive the earliest available offset.
time: Date.now(),
maxNum: 1 //default 1
}
cb
: Function, the callbackExample
var kafka = require('kafka-node'),
client = new kafka.KafkaClient(),
offset = new kafka.Offset(client);
offset.fetch([
{ topic: 't', partition: 0, time: Date.now(), maxNum: 1 }
], function (err, data) {
// data
// { 't': { '0': [999] } }
});
Fetch the last committed offset in a topic of a specific consumer group
groupId
: consumer grouppayloads
: Array,array of OffsetFetchRequest
, OffsetFetchRequest
is a JSON object like:{
topic: 'topicName',
partition: 0 //default 0
}
Example
var kafka = require('kafka-node'),
client = new kafka.KafkaClient(),
offset = new kafka.Offset(client);
offset.fetchCommitsV1('groupId', [
{ topic: 't', partition: 0 }
], function (err, data) {
});
Alias of fetchCommits
.
Example
var partition = 0;
var topic = 't';
offset.fetchLatestOffsets([topic], function (error, offsets) {
if (error)
return handleError(error);
console.log(offsets[topic][partition]);
});
Example
var partition = 0;
var topic = 't';
offset.fetchEarliestOffsets([topic], function (error, offsets) {
if (error)
return handleError(error);
console.log(offsets[topic][partition]);
});
This class provides administrative APIs can be used to monitor and administer the Kafka cluster.
kafkaClient
: client which keeps a connection with the Kafka server.List the consumer groups managed by the kafka cluster.
cb
: Function, the callbackExample:
const client = new kafka.KafkaClient();
const admin = new kafka.Admin(client); // client must be KafkaClient
admin.listGroups((err, res) => {
console.log('consumerGroups', res);
});
Result:
consumerGroups { 'console-consumer-87148': 'consumer',
'console-consumer-2690': 'consumer',
'console-consumer-7439': 'consumer'
}
Fetch consumer group information from the cluster. See result for detailed information.
consumerGroups
: Array, array of consumer groups (which can be gathered from listGroups
)cb
: Function, the callbackExample:
admin.describeGroups(['console-consumer-2690'], (err, res) => {
console.log(JSON.stringify(res,null,1));
})
Result:
{
"console-consumer-2690": {
"members": [
{
"memberId": "consumer-1-20195e12-cb3b-4ba4-9076-e7da8ed0d57a",
"clientId": "consumer-1",
"clientHost": "/192.168.61.1",
"memberMetadata": {
"subscription": [
"twice-tt"
],
"version": 0,
"userData": "JSON parse error",
"id": "consumer-1-20195e12-cb3b-4ba4-9076-e7da8ed0d57a"
},
"memberAssignment": {
"partitions": {
"twice-tt": [
0,
1
]
},
"version": 0,
"userData": "JSON Parse error"
}
}
],
"error": null,
"groupId": "console-consumer-2690",
"state": "Stable",
"protocolType": "consumer",
"protocol": "range",
"brokerId": "4"
}
}
List the topics managed by the kafka cluster.
cb
: Function, the callbackExample:
const client = new kafka.KafkaClient();
const admin = new kafka.Admin(client);
admin.listTopics((err, res) => {
console.log('topics', res);
});
Result:
[
{
"1001": {
"nodeId": 1001,
"host": "127.0.0.1",
"port": 9092
}
},
{
"metadata": {
"my-test-topic": {
"0": {
"topic": "my-test-topic",
"partition": 0,
"leader": 1001,
"replicas": [
1001
],
"isr": [
1001
]
},
"1": {
"topic": "my-test-topic",
"partition": 1,
"leader": 1001,
"replicas": [
1001
],
"isr": [
1001
]
}
}
},
"clusterMetadata": {
"controllerId": 1001
}
}
]
var topics = [{
topic: 'topic1',
partitions: 1,
replicationFactor: 2
}];
admin.createTopics(topics, (err, res) => {
// result is an array of any errors if a given topic could not be created
})
See createTopics
Fetch the configuration for the specified resources. It requires Kafka 0.11+.
payload
: Array, array of resourcescb
: Function, the callbackExample:
const resource = {
resourceType: admin.RESOURCE_TYPES.topic, // 'broker' or 'topic'
resourceName: 'my-topic-name',
configNames: [] // specific config names, or empty array to return all,
}
const payload = {
resources: [resource],
includeSynonyms: false // requires kafka 2.0+
};
admin.describeConfigs(payload, (err, res) => {
console.log(JSON.stringify(res,null,1));
})
Result:
[
{
"configEntries": [
{
"synonyms": [],
"configName": "compression.type",
"configValue": "producer",
"readOnly": false,
"configSource": 5,
"isSensitive": false
},
{
"synonyms": [],
"configName": "message.format.version",
"configValue": "0.10.2-IV0",
"readOnly": false,
"configSource": 4,
"isSensitive": false
},
{
"synonyms": [],
"configName": "file.delete.delay.ms",
"configValue": "60000",
"readOnly": false,
"configSource": 5,
"isSensitive": false
},
{
"synonyms": [],
"configName": "leader.replication.throttled.replicas",
"configValue": "",
"readOnly": false,
"configSource": 5,
"isSensitive": false
},
{
"synonyms": [],
"configName": "max.message.bytes",
"configValue": "1000012",
"readOnly": false,
"configSource": 5,
"isSensitive": false
},
...
],
"resourceType": "2",
"resourceName": "my-topic-name"
}
]
Error:
BrokerNotAvailableError: Could not find the leader
Call client.refreshMetadata()
before sending the first message. Reference issue #354
This module uses the debug module so you can just run below before starting your app.
export DEBUG=kafka-node:*
If you are using the new ConsumerGroup
simply set 'latest'
to fromOffset
option.
Otherwise:
offset.fetchLatestOffsets
to get fetch the latest offsetReference issue #342
Your partition will be stuck if the fetchMaxBytes
is smaller than the message produced. Increase fetchMaxBytes
value should resolve this issue.
Reference to issue #339
async.queue
with message processor and concurrency of one (the message processor itself is wrapped with setImmediate
so it will not freeze up the event loop)queue.drain
to resume the consumermessage
event pauses the consumer and pushes the message to the queue.In the consumer set the encoding
option to buffer
.
Set the messages
attribute in the payload
to a Buffer
. TypedArrays
such as Uint8Array
are not supported and need to be converted to a Buffer
.
{
messages: Buffer.from(data.buffer)
}
Snappy is a optional compression library. Windows users have reported issues with installing it while running npm install
. It's optional in kafka-node and can be skipped by using the --no-optional
flag (though errors from it should not fail the install).
npm install kafka-node --no-optional --save
Keep in mind if you try to use snappy without installing it kafka-node
will throw a runtime exception.
By default, kafka-node
uses debug to log important information. To integrate kafka-node
's log output into an application, it is possible to set a logger provider. This enables filtering of log levels and easy redirection of output streams.
A logger provider is a function which takes the name of a logger and returns a logger implementation. For instance, the following code snippet shows how a logger provider for the global console
object could be written:
function consoleLoggerProvider (name) {
// do something with the name
return {
debug: console.debug.bind(console),
info: console.info.bind(console),
warn: console.warn.bind(console),
error: console.error.bind(console)
};
}
The logger interface with its debug
, info
, warn
and error
methods expects format string support as seen in debug
or the JavaScript console
object. Many commonly used logging implementations cover this API, e.g. bunyan, pino or winston.
For performance reasons, initialization of the kafka-node
module creates all necessary loggers. This means that custom logger providers need to be set before requiring the kafka-node
module. The following example shows how this can be done:
// first configure the logger provider
const kafkaLogging = require('kafka-node/logging');
kafkaLogging.setLoggerProvider(consoleLoggerProvider);
// then require kafka-node and continue as normal
const kafka = require('kafka-node');
If you are receiving this error in your consumer double check the fetchMaxBytes
configuration. If set too low the broker could start sending fetch responses in RecordBatch format instead of MessageSet.
On the Mac install Docker for Mac.
npm test
Achieved using the KAFKA_VERSION
environment variable.
# Runs "latest" kafka on docker hub*
npm test
# Runs test against other versions:
KAFKA_VERSION=0.9 npm test
KAFKA_VERSION=0.10 npm test
KAFKA_VERSION=0.11 npm test
KAFKA_VERSION=1.0 npm test
KAFKA_VERSION=1.1 npm test
KAFKA_VERSION=2.0 npm test
*See Docker hub tags entry for which version is considered latest
.
npm run stopDocker
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FAQs
Client for Apache Kafka v0.9.x, v0.10.x and v0.11.x
The npm package kafka-node receives a total of 133,078 weekly downloads. As such, kafka-node popularity was classified as popular.
We found that kafka-node demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 3 open source maintainers collaborating on the project.
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