@heroku/no-kafka
v2.4.1
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Apache Kafka 0.9 client for Node.JS
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no-kafka
no-kafka is Apache Kafka 0.9 client for Node.js with new unified consumer API support.
Supports sync and async Gzip and Snappy compression, producer batching and controllable retries, offers few predefined group assignment strategies and producer partitioner option.
All methods will return a promise
- Using
- Producer
- Simple Consumer
- Group Consumer
- Group Admin
- Compression
- Connection
- Logging
- Topic Creation
- License
Using
- download and install Kafka
- create your test topic:
kafka-topics.sh --zookeeper 127.0.0.1:2181 --create --topic kafka-test-topic --partitions 3 --replication-factor 1
- install no-kafka
npm install no-kafka
Producer
Example:
var Kafka = require('no-kafka');
var producer = new Kafka.Producer();
return producer.init().then(function(){
return producer.send({
topic: 'kafka-test-topic',
partition: 0,
message: {
value: 'Hello!'
}
});
})
.then(function (result) {
/*
[ { topic: 'kafka-test-topic', partition: 0, offset: 353 } ]
*/
});
Send and retry if failed 2 times with 100ms delay:
return producer.send(messages, {
retries: {
attempts: 2,
delay: 100
}
});
Batching (grouping) produce requests
Accumulate messages into single batch until their total size is >= 1024 bytes or 100ms timeout expires (overwrite Producer constructor options):
producer.send(messages, {
batch: {
size: 1024,
maxWait: 100
}
});
producer.send(messages, {
batch: {
size: 1024,
maxWait: 100
}
});
Please note, that if you pass different options to the send()
method then these messages will be grouped into separate batches:
// will be sent in batch 1
producer.send(messages, {
batch: {
size: 1024,
maxWait: 100
},
codec: Kafka.COMPRESSION_GZIP
});
// will be sent in batch 2
producer.send(messages, {
batch: {
size: 1024,
maxWait: 100
},
codec: Kafka.COMPRESSION_SNAPPY
});
Keyed Messages
Send a message with the key:
producer.send({
topic: 'kafka-test-topic',
partition: 0,
message: {
key: 'some-key'
value: 'Hello!'
}
});
Producer options:
requiredAcks
- require acknoledgments for produce request. If it is 0 the server will not send any response. If it is 1 (default), the server will wait the data is written to the local log before sending a response. If it is -1 the server will block until the message is committed by all in sync replicas before sending a response. For any number > 1 the server will block waiting for this number of acknowledgements to occur (but the server will never wait for more acknowledgements than there are in-sync replicas).timeout
- timeout in ms for produce requestclientId
- ID of this client, defaults to 'no-kafka-client'connectionString
- comma delimited list of initial brokers list, defaults to '127.0.0.1:9092'partitioner
- function used to determine topic partition for message. If message already specifies a partition, the partitioner won't be used. The partitioner function receives 3 arguments: the topic name, an array with topic partitions, and the message (useful to partition by key, etc.).partitioner
can be sync or async (return a Promise).retries
- controls number of attempts at delay between them when produce request failsattempts
- number of total attempts to send the message, defaults to 3delay
- delay in ms between retries, defaults to 1000
codec
- compression codec, one of Kafka.COMPRESSION_NONE, Kafka.COMPRESSION_SNAPPY, Kafka.COMPRESSION_GZIPbatch
- control batching (grouping) of requestssize
- group messages together into single batch until their total size exceeds this value, defaults to 16384 bytes. Set to 0 to disable batching.maxWait
- send grouped messages after this amount of milliseconds expire even if their total size doesn't exceedbatch.size
yet, defaults to 10ms. Set to 0 to disable batching.
asyncCompression
- boolean, use asynchronouse compression instead of synchronous, defaults tofalse
SimpleConsumer
Manually specify topic, partition and offset when subscribing. Suitable for simple use cases.
Example:
var consumer = new Kafka.SimpleConsumer();
// data handler function can return a Promise
var dataHandler = function (messageSet, topic, partition) {
messageSet.forEach(function (m) {
console.log(topic, partition, m.offset, m.message.value.toString('utf8'));
});
};
return consumer.init().then(function () {
// Subscribe partitons 0 and 1 in a topic:
return consumer.subscribe('kafka-test-topic', [0, 1], dataHandler);
});
Subscribe (or change subscription) to specific offset and limit maximum received MessageSet size:
consumer.subscribe('kafka-test-topic', 0, {offset: 20, maxBytes: 30}, dataHandler)
Subscribe to latest or earliest offsets in the topic/parition:
consumer.subscribe('kafka-test-topic', 0, {time: Kafka.LATEST_OFFSET}, dataHandler)
consumer.subscribe('kafka-test-topic', 0, {time: Kafka.EARLIEST_OFFSET}, dataHandler)
Subscribe to all partitions in a topic:
consumer.subscribe('kafka-test-topic', dataHandler)
Commit offset(s) (V0, Kafka saves these commits to Zookeeper)
consumer.commitOffset([
{
topic: 'kafka-test-topic',
partition: 0,
offset: 1
},
{
topic: 'kafka-test-topic',
partition: 1,
offset: 2
}
])
Fetch commited offset(s)
consumer.fetchOffset([
{
topic: 'kafka-test-topic',
partition: 0
},
{
topic: 'kafka-test-topic',
partition: 1
}
]).then(function (result) {
/*
[ { topic: 'kafka-test-topic',
partition: 1,
offset: 2,
metadata: null,
error: null },
{ topic: 'kafka-test-topic',
partition: 0,
offset: 1,
metadata: null,
error: null } ]
*/
});
SimpleConsumer options
groupId
- group ID for comitting and fetching offsets. Defaults to 'no-kafka-group-v0'maxWaitTime
- maximum amount of time in milliseconds to block waiting if insufficient data is available at the time the fetch request is issued, defaults to 100msidleTimeout
- timeout between fetch calls, defaults to 1000msminBytes
- minimum number of bytes to wait from Kafka before returning the fetch call, defaults to 1 bytemaxBytes
- maximum size of messages in a fetch responseclientId
- ID of this client, defaults to 'no-kafka-client'connectionString
- comma delimited list of initial brokers list, defaults to '127.0.0.1:9092'recoveryOffset
- recovery position (time) which will used to recover subscription in case of OffsetOutOfRange error, defaults to Kafka.LATEST_OFFSETasyncCompression
- boolean, use asynchronouse decompression instead of synchronous, defaults tofalse
handlerConcurrency
- specify concurrency level for the consumer handler function, defaults to 10
GroupConsumer (new unified consumer API)
Specify an assignment strategy (or use no-kafka built-in consistent or round robin assignment strategy) and subscribe by specifying only topics. Elected group leader will automatically assign partitions between all group members.
Example:
var Promise = require('bluebird');
var consumer = new Kafka.GroupConsumer();
var dataHandler = function (messageSet, topic, partition) {
return Promise.each(messageSet, function (m){
console.log(topic, partition, m.offset, m.message.value.toString('utf8'));
// commit offset
return consumer.commitOffset({topic: topic, partition: partition, offset: m.offset, metadata: 'optional'});
});
};
var strategies = [{
strategy: 'TestStrategy',
subscriptions: ['kafka-test-topic'],
handler: dataHandler
}];
consumer.init(strategies); // all done, now wait for messages in dataHandler
Assignment strategies
no-kafka provides three built-in strategies:
Kafka.WeightedRoundRobinAssignment
weighted round robin assignment (based on wrr-pool).Kafka.ConsistentAssignment
which is based on a consistent hash ring and so provides consistent assignment across consumers in a group based on suppliedmetadata.id
andmetadata.weight
options.Kafka.RoundRobinAssignment
simple assignment strategy (default).
Using Kafka.WeightedRoundRobinAssignment
:
var strategies = {
strategy: 'TestStrategy',
subscriptions: ['kafka-test-topic'],
metadata: {
weight: 4
},
fn: Kafka.WeightedRoundRobinAssignment,
handler: dataHandler
};
// consumer.init(strategies)....
Using Kafka.ConsistentAssignment
:
var strategies = {
strategy: 'TestStrategy',
subscriptions: ['kafka-test-topic'],
metadata: {
id: process.argv[2] || 'consumer_1',
weight: 50
},
fn: Kafka.ConsistentAssignment,
handler: dataHandler
};
// consumer.init(strategies)....
Note that each consumer in a group should have its own and consistent metadata.id.
Using Kafka.RoundRobinAssignment
(default in no-kafka):
var strategies = {
strategy: 'TestStrategy',
subscriptions: ['kafka-test-topic'],
handler: dataHandler
};
// consumer.init(strategies)....
You can also write your own assignment strategy function and provide it as fn
option of the strategy item.
GroupConsumer options
groupId
- group ID for comitting and fetching offsets. Defaults to 'no-kafka-group-v0.9'maxWaitTime
- maximum amount of time in milliseconds to block waiting if insufficient data is available at the time the fetch request is issued, defaults to 100msidleTimeout
- timeout between fetch calls, defaults to 1000msminBytes
- minimum number of bytes to wait from Kafka before returning the fetch call, defaults to 1 bytemaxBytes
- maximum size of messages in a fetch responseclientId
- ID of this client, defaults to 'no-kafka-client'connectionString
- comma delimited list of initial brokers list, defaults to '127.0.0.1:9092'sessionTimeout
- session timeout in ms, min 6000, max 30000, defaults to15000
heartbeatTimeout
- delay between heartbeat requests in ms, defaults to1000
retentionTime
- offset retention time in ms, defaults to 1 day (24 * 3600 * 1000)startingOffset
- starting position (time) when there is no commited offset, defaults toKafka.LATEST_OFFSET
recoveryOffset
- recovery position (time) which will used to recover subscription in case of OffsetOutOfRange error, defaults to Kafka.LATEST_OFFSETasyncCompression
- boolean, use asynchronouse decompression instead of synchronous, defaults tofalse
handlerConcurrency
- specify concurrency level for the consumer handler function, defaults to 10
GroupAdmin (consumer groups API)
Offes two methods:
listGroups
- list existing consumer groupsdescribeGroup
- describe existing group by its id
Example:
var admin = new Kafka.GroupAdmin();
return admin.init().then(function(){
return admin.listGroups().then(function(groups){
// [ { groupId: 'no-kafka-admin-test-group', protocolType: 'consumer' } ]
return admin.describeGroup('no-kafka-admin-test-group').then(function(group){
/*
{ error: null,
groupId: 'no-kafka-admin-test-group',
state: 'Stable',
protocolType: 'consumer',
protocol: 'TestStrategy',
members:
[ { memberId: 'group-consumer-82646843-b4b8-4e91-94c9-b4708c8b05e8',
clientId: 'group-consumer',
clientHost: '/192.168.1.4',
version: 0,
subscriptions: [ 'kafka-test-topic'],
metadata: <Buffer 63 6f 6e 73 75 6d 65 72 2d 6d 65 74 61 64 61 74 61>,
memberAssignment:
{ _blength: 44,
version: 0,
partitionAssignment:
[ { topic: 'kafka-test-topic',
partitions: [ 0, 1, 2 ] },
],
metadata: null } },
] }
*/
})
});
});
Compression
no-kafka supports both SNAPPY and Gzip compression.
Enable compression in Producer:
var Kafka = require('no-kafka');
var producer = new Kafka.Producer({
clientId: 'producer',
codec: Kafka.COMPRESSION_SNAPPY // Kafka.COMPRESSION_NONE, Kafka.COMPRESSION_SNAPPY, Kafka.COMPRESSION_GZIP
});
Alternatively just send some messages with specified compression codec (overwrites codec set in contructor):
return producer.send({
topic: 'kafka-test-topic',
partition: 0,
message: { value: 'p00' }
}, { codec: Kafka.COMPRESSION_SNAPPY })
By default no-kafka will use synchronous compression and decompression (synchronous Gzip is not availble in node < 0.11).
Enable async compression/decompression with asyncCompression
options:
Producer:
var producer = new Kafka.Producer({
clientId: 'producer',
asyncCompression: true,
codec: Kafka.COMPRESSION_SNAPPY
});
Consumer:
var consumer = new Kafka.SimpleConsumer({
idleTimeout: 100,
clientId: 'simple-consumer',
asyncCompression: true
});
Connection
no-kafka will connect to the hosts specified in connectionString
constructor option unless it is omitted. In this case it will use KAFKA_URL environment variable or fallback to default kafka://127.0.0.1:9092
. For better availability always specify several initial brokers: 10.0.1.1:9092,10.0.1.2:9092,10.0.1.3:9092
. The kafka://
prefix is optional.
All network errors are handled by the library: producer will retry sending failed messages for configured amount of times, simple consumer and group consumer will try to reconnect to failed host, update metadata as needed as so on.
SSL
Kafka 0.9 supports encryption and authentication using SSL.
To connect over SSL, include an ssl
Object alongside your connectionString
which contains two properties:
clientCert
and clientCertKey
.
If not specified,
these will populate from the KAFKA_CLIENT_CERT
and KAFKA_CLIENT_CERT_KEY
environment variables.
The ssl option defaults to false
if no cert options or environment variables are found.
Logging
You can differentiate messages from several instances of producer/consumer by providing unique clientId
in options:
var consumer1 = new Kafka.GroupConsumer({
clientId: 'group-consumer-1'
});
var consumer2 = new Kafka.GroupConsumer({
clientId: 'group-consumer-2'
});
=>
2016-01-12T07:41:57.884Z INFO group-consumer-1 ....
2016-01-12T07:41:57.884Z INFO group-consumer-2 ....
Change the logging level:
var consumer = new Kafka.GroupConsumer({
clientId: 'group-consumer',
logger: {
logLevel: 1 // 0 - nothing, 1 - just errors, 2 - +warnings, 3 - +info, 4 - +debug, 5 - +trace
}
});
Send log messages to Logstash server(s) via UDP:
var consumer = new Kafka.GroupConsumer({
clientId: 'group-consumer',
logger: {
logstash: {
enabled: true,
connectionString: '10.0.1.1:9999,10.0.1.2:9999',
app: 'myApp-kafka-consumer'
}
}
});
You can overwrite the function that outputs messages to stdout/stderr:
var consumer = new Kafka.GroupConsumer({
clientId: 'group-consumer',
logger: {
logFunction: console.log
}
});
Topic Creation
There is no Kafka API call to create a topic. Kafka supports auto creating of topics when their metadata is first requested (auto.create.topic
option) but the topic is created with all default parameters, which is useless. There is no way to be notified when the topic has been created, so the library will need to ping the server with some interval. There is also no way to be notified of any error for this operation. For this reason, having no guarantees, no-kafka won't provide topic creation method until there will be a specific Kafka API call to create/manage topics.