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1Confidential
Introducing ExactlyOnce
Semantics in Apache® KafkaTM
Jason Gustafson, Apurva Mehta, Guozhang Wang, and Sriram
Subramaniam
Matthias J. Sax | Software Engineer
matthias@confluent.io
@MatthiasJSax
2Confidential
Outline
• Kafka’sexisting delivery semantics.
• What’s new?
• How do you use it?
• Summary.
3Confidential
What Kafka offers today
• At-least-once,in-order delivery per partition.
• Producer retries can introduce duplicates.
4Confidential
Stream Processing with Apache Spark
Read-process-write pattern:
5Confidential
Example: duplicate write
Producer Broker
Topic Partition
6Confidential
Example: duplicate write
Producer Broker
Topic Partition
send (k,v)
7Confidential
Example: duplicate write
Producer Broker (k,v)
Topic Partition
append (k,v)
8Confidential
Example: duplicate write
Producer Broker (k,v)
Topic Partition
ack
9Confidential
Example: duplicate write
Producer Broker (k,v)
Topic Partition
send (k,v)
10Confidential
Example: duplicate write
Producer Broker (k,v) (k,v)
Topic Partition
append (k,v)
11Confidential
Example: duplicate write
Producer Broker (k,v) (k,v)
Topic Partition
ack
12Confidential
Why improve?
• Stream processing is becoming a bigger part of the data landscape.
• Apache Kafka is the foundation for such stream processing.
• Strengthening Kafka’ssemantics expands the universe of
streaming applications.
13Confidential
What’s new?
14Confidential
What’s new
• Idempotent producer:exactly-once writes.
• Transactionalproducer:Atomic writes across multiple partitions.
• Exactly-once stream processing: read-process-write.
15Confidential
What’s new
Idempotent Producer
16Confidential
Example: Idempotent Producer
Producer Broker
Topic Partition
17Confidential
Example: Idempotent Producer
Producer Broker
send (k,v)
seq = 0
pid = 73 Topic Partition
18Confidential
Example: Idempotent Producer
Producer Broker
append (k,v)
seq = 0
pid = 73 Topic Partition
(k,v)
seq = 0
pid = 73
19Confidential
Example: Idempotent Producer
Producer Broker
ack
Topic Partition
(k,v)
seq = 0
pid = 73
20Confidential
Example: Idempotent Producer
Producer Broker
send (k,v)
seq = 0
pid = 73 Topic Partition
(k,v)
seq = 0
pid = 73
21Confidential
Example: Idempotent Producer
Producer Broker
ack (dup)
Topic Partition
(k,v)
seq = 0
pid = 73
22Confidential
What’s new
Atomic Multi-Partition Writes
(aka “transactions”)
23Confidential
Atomic Multi-Partition Writes
Producer
Topic A, Partition 0
Topic B, Partition 0
Topic B, Partition 1
24Confidential
Atomic Multi-Partition Writes
Producer
Topic A, Partition 0 m1 m5
m3 m4 m6Topic B, Partition 0
m2Topic B, Partition 1
25Confidential
Atomic Multi-Partition Writes
Producer
Topic A, Partition 0 m1 m5 C
m3 m4 m6Topic B, Partition 0
m2Topic B, Partition 1
C
C
atomic commit
26Confidential
Atomic Multi-Partition Writes
Consumer
Topic A, Partition 0 m1 m5 C
m3 m4 m6Topic B, Partition 0
m2Topic B, Partition 1
C
C
read committed
27Confidential
TransactionalAPI
producer.initTransactions();
try {
producer.beginTransaction();
producer.send(record0);
producer.send(record1);
producer.sendOffsetsToTxn(…);
producer.commitTransaction();
} catch (ProducerFencedException e) {
producer.close();
} catch (KafkaException e) {
producer.abortTransaction();
}
28Confidential
How to use exactly-once capabilities:
• Streams API (the easiest way to use exactly-once semantics)
• Config parameter processing.mode = “exactly_once”
• Idempotent Producer
• Config parameter enable.idempotence = true
• Transactional Producer
• Config parameter transactional.id = “my-unique-tid”
• And Transactional API (hard to use!)
• Transactional Consumer
• Config parameter isolation.level = “read_committed”
(default: “read_uncommitted”)
29Confidential
Stream Processing with Kafka’s Streams API
Transactional read-process-write-commit pattern:
30Confidential
Stream Processing with Apache Spark
Transactional read-process-write-commit pattern:
31Confidential
When to use this?
Available in Kafka 0.11, June 2017. Try it out!
32Confidential
Putting it together
• We understood Kafka’sexisting delivery semantics.
• Learned how these have been strengthened.
• Learned how the new semantics work.
• Saw, it’s easy to use with higher levelAPIs like Kafka Streams or
Apache Spark.
33Confidential
Thank You
We are hiring!

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