Copyright (c) 2016 Blizzard Entertainment.
https://github.com/blizzard/node-rdkafka
I am looking for your help to make this project even better! If you're interested, check this out
The node-rdkafka
library is a high-performance NodeJS client for Apache Kafka that wraps the native librdkafka library. All the complexity of balancing writes across partitions and managing (possibly ever-changing) brokers should be encapsulated in the library.
This library currently uses librdkafka
version 2.6.1
.
To view the reference docs for the current version, go here
For guidelines on contributing please see CONTRIBUTING.md
Play nice; Play fair.
- Apache Kafka >=0.9
- Node.js >=16
- Linux/Mac
- Windows?! See below
- OpenSSL
OpenSSL has been upgraded in High Sierra and homebrew does not overwrite default system libraries. That means when building node-rdkafka, because you are using openssl, you need to tell the linker where to find it:
export CPPFLAGS=-I/usr/local/opt/openssl/include
export LDFLAGS=-L/usr/local/opt/openssl/lib
Then you can run npm install
on your application to get it to build correctly.
NOTE: From the librdkafka
docs
WARNING: Due to a bug in Apache Kafka 0.9.0.x, the ApiVersionRequest (as sent by the client when connecting to the broker) will be silently ignored by the broker causing the request to time out after 10 seconds. This causes client-broker connections to stall for 10 seconds during connection-setup before librdkafka falls back on the
broker.version.fallback
protocol features. The workaround is to explicitly configureapi.version.request
tofalse
on clients communicating with <=0.9.0.x brokers.
Using Alpine Linux? Check out the docs.
Windows build is not compiled from librdkafka
source but it is rather linked against the appropriate version of NuGet librdkafka.redist static binary that gets downloaded from https://globalcdn.nuget.org/packages/librdkafka.redist.2.6.1.nupkg
during installation. This download link can be changed using the environment variable NODE_RDKAFKA_NUGET_BASE_URL
that defaults to https://globalcdn.nuget.org/packages/
when it's no set.
Requirements:
Note: I still do not recommend using node-rdkafka
in production on Windows. This feature was in high demand and is provided to help develop, but we do not test against Windows, and windows support may lag behind Linux/Mac support because those platforms are the ones used to develop this library. Contributors are welcome if any Windows issues are found :)
This project includes two types of unit tests in this project:
- end-to-end integration tests
- unit tests
You can run both types of tests by using Makefile
. Doing so calls mocha
in your locally installed node_modules
directory.
- Before you run the tests, be sure to init and update the submodules:
git submodule init
git submodule update
- To run the unit tests, you can run
make lint
ormake test
. - To run the integration tests, you must have a running Kafka installation available. By default, the test tries to connect to
localhost:9092
; however, you can supply theKAFKA_HOST
environment variable to override this default behavior. Runmake e2e
.
You can install the node-rdkafka
module like any other module:
npm install node-rdkafka
To use the module, you must require
it.
const Kafka = require('node-rdkafka');
You can pass many configuration options to librdkafka
. A full list can be found in librdkafka
's Configuration.md
Configuration keys that have the suffix _cb
are designated as callbacks. Some
of these keys are informational and you can choose to opt-in (for example, dr_cb
). Others are callbacks designed to
return a value, such as partitioner_cb
.
Not all of these options are supported. The library will throw an error if the value you send in is invalid.
The library currently supports the following callbacks:
partitioner_cb
dr_cb
ordr_msg_cb
event_cb
rebalance_cb
(see Rebalancing)offset_commit_cb
(see Commits)
This library includes two utility functions for detecting the status of your installation. Please try to include these when making issue reports where applicable.
You can get the features supported by your compile of librdkafka
by reading the variable "features" on the root of the node-rdkafka
object.
const Kafka = require('node-rdkafka');
console.log(Kafka.features);
// #=> [ 'gzip', 'snappy', 'ssl', 'sasl', 'regex', 'lz4' ]
You can also get the version of librdkafka
const Kafka = require('node-rdkafka');
console.log(Kafka.librdkafkaVersion);
// #=> 2.6.1
A Producer
sends messages to Kafka. The Producer
constructor takes a configuration object, as shown in the following example:
const producer = new Kafka.Producer({
'metadata.broker.list': 'kafka-host1:9092,kafka-host2:9092'
});
A Producer
requires only metadata.broker.list
(the Kafka brokers) to be created. The values in this list are separated by commas. For other configuration options, see the Configuration.md file described previously.
The following example illustrates a list with several librdkafka
options set.
const producer = new Kafka.Producer({
'client.id': 'kafka',
'metadata.broker.list': 'localhost:9092',
'compression.codec': 'gzip',
'retry.backoff.ms': 200,
'message.send.max.retries': 10,
'socket.keepalive.enable': true,
'queue.buffering.max.messages': 100000,
'queue.buffering.max.ms': 1000,
'batch.num.messages': 1000000,
'dr_cb': true
});
You can easily use the Producer
as a writable stream immediately after creation (as shown in the following example):
// Our producer with its Kafka brokers
// This call returns a new writable stream to our topic 'topic-name'
const stream = Kafka.Producer.createWriteStream({
'metadata.broker.list': 'kafka-host1:9092,kafka-host2:9092'
}, {}, {
topic: 'topic-name'
});
// Writes a message to the stream
const queuedSuccess = stream.write(Buffer.from('Awesome message'));
if (queuedSuccess) {
console.log('We queued our message!');
} else {
// Note that this only tells us if the stream's queue is full,
// it does NOT tell us if the message got to Kafka! See below...
console.log('Too many messages in our queue already');
}
// NOTE: MAKE SURE TO LISTEN TO THIS IF YOU WANT THE STREAM TO BE DURABLE
// Otherwise, any error will bubble up as an uncaught exception.
stream.on('error', (err) => {
// Here's where we'll know if something went wrong sending to Kafka
console.error('Error in our kafka stream');
console.error(err);
})
If you do not want your code to crash when an error happens, ensure you have an error
listener on the stream. Most errors are not necessarily fatal, but the ones that are will immediately destroy the stream. If you use autoClose
, the stream will close itself at the first sign of a problem.
The Standard API is more performant, particularly when handling high volumes of messages. However, it requires more manual setup to use. The following example illustrates its use:
const producer = new Kafka.Producer({
'metadata.broker.list': 'localhost:9092',
'dr_cb': true
});
// Connect to the broker manually
producer.connect();
// Wait for the ready event before proceeding
producer.on('ready', () => {
try {
producer.produce(
// Topic to send the message to
'topic',
// optionally we can manually specify a partition for the message
// this defaults to -1 - which will use librdkafka's default partitioner (consistent random for keyed messages, random for unkeyed messages)
null,
// Message to send. Must be a buffer
Buffer.from('Awesome message'),
// for keyed messages, we also specify the key - note that this field is optional
'Stormwind',
// you can send a timestamp here. If your broker version supports it,
// it will get added. Otherwise, we default to 0
Date.now(),
// you can send an opaque token here, which gets passed along
// to your delivery reports
);
} catch (err) {
console.error('A problem occurred when sending our message');
console.error(err);
}
});
// Any errors we encounter, including connection errors
producer.on('event.error', (err) => {
console.error('Error from producer');
console.error(err);
})
// We must either call .poll() manually after sending messages
// or set the producer to poll on an interval (.setPollInterval).
// Without this, we do not get delivery events and the queue
// will eventually fill up.
producer.setPollInterval(100);
To see the configuration options available to you, see the Configuration section.
Method | Description |
---|---|
producer.connect() |
Connects to the broker. The connect() method emits the ready event when it connects successfully. If it does not, the error will be passed through the callback. |
producer.disconnect() |
Disconnects from the broker. The disconnect() method emits the disconnected event when it has disconnected. If it does not, the error will be passed through the callback. |
producer.poll() |
Polls the producer for delivery reports or other events to be transmitted via the emitter. In order to get the events in librdkafka 's queue to emit, you must call this regularly. |
producer.setPollInterval(interval) |
Polls the producer on this interval, handling disconnections and reconnection. Set it to 0 to turn it off. |
producer.produce(topic, partition, msg, key, timestamp, opaque) |
Sends a message. The produce() method throws when produce would return an error. Ordinarily, this is just if the queue is full. |
producer.flush(timeout, callback) |
Flush the librdkafka internal queue, sending all messages. Default timeout is 500ms |
producer.initTransactions(timeout, callback) |
Initializes the transactional producer. |
producer.beginTransaction(callback) |
Starts a new transaction. |
producer.sendOffsetsToTransaction(offsets, consumer, timeout, callback) |
Sends consumed topic-partition-offsets to the broker, which will get committed along with the transaction. |
producer.abortTransaction(timeout, callback) |
Aborts the ongoing transaction. |
producer.commitTransaction(timeout, callback) |
Commits the ongoing transaction. |
Some configuration properties that end in _cb
indicate that an event should be generated for that option. You can either:
- provide a value of
true
and react to the event - provide a callback function directly
The following example illustrates an event:
const producer = new Kafka.Producer({
'client.id': 'my-client', // Specifies an identifier to use to help trace activity in Kafka
'metadata.broker.list': 'localhost:9092', // Connect to a Kafka instance on localhost
'dr_cb': true // Specifies that we want a delivery-report event to be generated
});
// Poll for events every 100 ms
producer.setPollInterval(100);
producer.on('delivery-report', (err, report) => {
// Report of delivery statistics here:
//
console.log(report);
});
The following table describes types of events.
Event | Description |
---|---|
disconnected |
The disconnected event is emitted when the broker has disconnected. This event is emitted only when .disconnect is called. The wrapper will always try to reconnect otherwise. |
ready |
The ready event is emitted when the Producer is ready to send messages. |
event |
The event event is emitted when librdkafka reports an event (if you opted in via the event_cb option). |
event.log |
The event.log event is emitted when logging events come in (if you opted into logging via the event_cb option). You will need to set a value for debug if you want to send information. |
event.stats |
The event.stats event is emitted when librdkafka reports stats (if you opted in by setting the statistics.interval.ms to a non-zero value). |
event.error |
The event.error event is emitted when librdkafka reports an error |
event.throttle |
The event.throttle event emitted when librdkafka reports throttling. |
delivery-report |
The delivery-report event is emitted when a delivery report has been found via polling. To use this event, you must set request.required.acks to 1 or -1 in topic configuration and dr_cb (or dr_msg_cb if you want the report to contain the message payload) to true in the Producer constructor options. |
The higher level producer is a variant of the producer which can propagate callbacks to you upon message delivery.
const producer = new Kafka.HighLevelProducer({
'metadata.broker.list': 'localhost:9092',
});
This will enrich the produce call so it will have a callback to tell you when the message has been delivered. You lose the ability to specify opaque tokens.
producer.produce(topicName, null, Buffer.from('alliance4ever'), null, Date.now(), (err, offset) => {
// The offset if our acknowledgement level allows us to receive delivery offsets
console.log(offset);
});
Additionally you can add serializers to modify the value of a produce for a key or value before it is sent over to Kafka.
producer.setValueSerializer((value) => {
return Buffer.from(JSON.stringify(value));
});
Otherwise the behavior of the class should be exactly the same.
To read messages from Kafka, you use a KafkaConsumer
. You instantiate a KafkaConsumer
object as follows:
const consumer = new Kafka.KafkaConsumer({
'group.id': 'kafka',
'metadata.broker.list': 'localhost:9092',
}, {});
The first parameter is the global config, while the second parameter is the topic config that gets applied to all subscribed topics. To view a list of all supported configuration properties, see the Configuration.md file described previously. Look for the C
and *
keys.
The group.id
and metadata.broker.list
properties are required for a consumer.
Rebalancing is managed internally by librdkafka
by default. If you would like to override this functionality, you may provide your own logic as a rebalance callback.
const consumer = new Kafka.KafkaConsumer({
'group.id': 'kafka',
'metadata.broker.list': 'localhost:9092',
'rebalance_cb': (err, assignment) => {
if (err.code === Kafka.CODES.ERRORS.ERR__ASSIGN_PARTITIONS) {
// Note: this can throw when you are disconnected. Take care and wrap it in
// a try catch if that matters to you
this.assign(assignment);
} else if (err.code == Kafka.CODES.ERRORS.ERR__REVOKE_PARTITIONS){
// Same as above
this.unassign();
} else {
// We had a real error
console.error(err);
}
}
})
this
is bound to the KafkaConsumer
you have created. By specifying a rebalance_cb
you can also listen to the rebalance
event as an emitted event. This event is not emitted when using the internal librdkafka
rebalancer.
When you commit in node-rdkafka
, the standard way is to queue the commit request up with the next librdkafka
request to the broker. When doing this, there isn't a way to know the result of the commit. Luckily there is another callback you can listen to to get this information
const consumer = new Kafka.KafkaConsumer({
'group.id': 'kafka',
'metadata.broker.list': 'localhost:9092',
'offset_commit_cb': (err, topicPartitions) => {
if (err) {
// There was an error committing
console.error(err);
} else {
// Commit went through. Let's log the topic partitions
console.log(topicPartitions);
}
}
})
this
is bound to the KafkaConsumer
you have created. By specifying an offset_commit_cb
you can also listen to the offset.commit
event as an emitted event. It receives an error and the list of topic partitions as argument. This is not emitted unless opted in.
Messages that are returned by the KafkaConsumer
have the following structure.
{
value: Buffer.from('hi'), // message contents as a Buffer
size: 2, // size of the message, in bytes
topic: 'librdtesting-01', // topic the message comes from
offset: 1337, // offset the message was read from
partition: 1, // partition the message was on
key: 'someKey', // key of the message if present
timestamp: 1510325354780 // timestamp of message creation
}
The stream API is the easiest way to consume messages. The following example illustrates the use of the stream API:
// Read from the librdtesting-01 topic... note that this creates a new stream on each call!
const stream = KafkaConsumer.createReadStream(globalConfig, topicConfig, {
topics: ['librdtesting-01']
});
stream.on('data', (message) => {
console.log('Got message');
console.log(message.value.toString());
});
You can also get the consumer
from the streamConsumer, for using consumer methods. The following example illustrates that:
stream.consumer.commit(); // Commits all locally stored offsets
You can also use the Standard API and manage callbacks and events yourself. You can choose different modes for consuming messages:
- Flowing mode. This mode flows all of the messages it can read by maintaining an infinite loop in the event loop. It only stops when it detects the consumer has issued the
unsubscribe
ordisconnect
method. - Non-flowing mode. This mode reads a single message from Kafka at a time manually.
The following example illustrates flowing mode:
// Flowing mode
consumer.connect();
consumer
.on('ready', () => {
consumer.subscribe(['librdtesting-01']);
// Consume from the librdtesting-01 topic. This is what determines
// the mode we are running in. By not specifying a callback (or specifying
// only a callback) we get messages as soon as they are available.
consumer.consume();
})
.on('data', (data) => {
// Output the actual message contents
console.log(data.value.toString());
});
The following example illustrates non-flowing mode:
// Non-flowing mode
consumer.connect();
consumer
.on('ready', () => {
// Subscribe to the librdtesting-01 topic
// This makes subsequent consumes read from that topic.
consumer.subscribe(['librdtesting-01']);
// Read one message every 1000 milliseconds
setInterval(() => {
consumer.consume(1);
}, 1000);
})
.on('data', (data) => {
console.log('Message found! Contents below.');
console.log(data.value.toString());
});
The following table lists important methods for this API.
Method | Description |
---|---|
consumer.connect() |
Connects to the broker. The connect() emits the event ready when it has successfully connected. If it does not, the error will be passed through the callback. |
consumer.disconnect() |
Disconnects from the broker. The disconnect() method emits disconnected when it has disconnected. If it does not, the error will be passed through the callback. |
consumer.subscribe(topics) |
Subscribes to an array of topics. |
consumer.unsubscribe() |
Unsubscribes from the currently subscribed topics. You cannot subscribe to different topics without calling the unsubscribe() method first. |
consumer.consume(cb) |
Gets messages from the existing subscription as quickly as possible. If cb is specified, invokes cb(err, message) . This method keeps a background thread running to do the work. Note that the number of threads in nodejs process is limited by UV_THREADPOOL_SIZE (default value is 4) and using up all of them blocks other parts of the application that need threads. If you need multiple consumers then consider increasing UV_THREADPOOL_SIZE or using consumer.consume(number, cb) instead. |
consumer.consume(number, cb) |
Gets number of messages from the existing subscription. If cb is specified, invokes cb(err, message) . |
consumer.commit() |
Commits all locally stored offsets |
consumer.commit(topicPartition) |
Commits offsets specified by the topic partition |
consumer.commitMessage(message) |
Commits the offsets specified by the message |
The following table lists events for this API.
Event | Description |
---|---|
data |
When using the Standard API consumed messages are emitted in this event. |
partition.eof |
When using Standard API and the configuration option enable.partition.eof is set, partition.eof events are emitted in this event. The event contains topic , partition and offset properties. |
warning |
The event is emitted in case of UNKNOWN_TOPIC_OR_PART or TOPIC_AUTHORIZATION_FAILED errors when consuming in Flowing mode. Since the consumer will continue working if the error is still happening, the warning event should reappear after the next metadata refresh. To control the metadata refresh rate set topic.metadata.refresh.interval.ms property. Once you resolve the error, you can manually call getMetadata to speed up consumer recovery. |
rebalance |
The rebalance event is emitted when the consumer group is rebalanced. This event is only emitted if the rebalance_cb configuration is set to a function or set to true |
disconnected |
The disconnected event is emitted when the broker disconnects. This event is only emitted when .disconnect is called. The wrapper will always try to reconnect otherwise. |
ready |
The ready event is emitted when the Consumer is ready to read messages. |
event |
The event event is emitted when librdkafka reports an event (if you opted in via the event_cb option). |
event.log |
The event.log event is emitted when logging events occur (if you opted in for logging via the event_cb option).You will need to set a value for debug if you want information to send. |
event.stats |
The event.stats event is emitted when librdkafka reports stats (if you opted in by setting the statistics.interval.ms to a non-zero value). |
event.error |
The event.error event is emitted when librdkafka reports an error |
event.throttle |
The event.throttle event is emitted when librdkafka reports throttling. |
Some times you find yourself in the situation where you need to know the latest (and earliest) offset for one of your topics. Connected producers and consumers both allow you to query for these through queryWaterMarkOffsets
like follows:
const timeout = 5000, partition = 0;
consumer.queryWatermarkOffsets('my-topic', partition, timeout, (err, offsets) => {
const high = offsets.highOffset;
const low = offsets.lowOffset;
});
producer.queryWatermarkOffsets('my-topic', partition, timeout, (err, offsets) => {
const high = offsets.highOffset;
const low = offsets.lowOffset;
});
An error will be returned if the client was not connected or the request timed out within the specified interval.
Both Kafka.Producer
and Kafka.KafkaConsumer
include a getMetadata
method to retrieve metadata from Kafka.
Getting metadata on any connection returns the following data structure:
{
orig_broker_id: 1,
orig_broker_name: "broker_name",
brokers: [
{
id: 1,
host: 'localhost',
port: 40
}
],
topics: [
{
name: 'awesome-topic',
partitions: [
{
id: 1,
leader: 20,
replicas: [1, 2],
isrs: [1, 2]
}
]
}
]
}
The following example illustrates how to use the getMetadata
method.
When fetching metadata for a specific topic, if a topic reference does not exist, one is created using the default config.
Please see the documentation on Client.getMetadata
if you want to set configuration parameters, e.g. acks
, on a topic to produce messages to.
const opts = {
topic: 'librdtesting-01',
timeout: 10000
};
producer.getMetadata(opts, (err, metadata) => {
if (err) {
console.error('Error getting metadata');
console.error(err);
} else {
console.log('Got metadata');
console.log(metadata);
}
});
node-rdkafka
now supports the admin client for creating, deleting, and scaling out topics. The librdkafka
APIs also support altering configuration of topics and broker, but that is not currently implemented.
To create an Admin client, you can do as follows:
const Kafka = require('node-rdkafka');
const client = Kafka.AdminClient.create({
'client.id': 'kafka-admin',
'metadata.broker.list': 'broker01'
});
This will instantiate the AdminClient
, which will allow the calling of the admin methods.
client.createTopic({
topic: topicName,
num_partitions: 1,
replication_factor: 1
}, (err) => {
// Done!
});
All of the admin api methods can have an optional timeout as their penultimate parameter.
The following table lists important methods for this API.
Method | Description |
---|---|
client.disconnect() |
Destroy the admin client, making it invalid for further use. |
client.createTopic(topic, timeout, cb) |
Create a topic on the broker with the given configuration. See JS doc for more on structure of the topic object |
client.deleteTopic(topicName, timeout, cb) |
Delete a topic of the given name |
client.createPartitions(topicName, desiredPartitions, timeout, cb) |
Create partitions until the topic has the desired number of partitions. |
Check the tests for an example of how to use this API!