The rapidly expanding world of stream processing can be daunting. KSQL is an open-source, Apache 2.0 licensed streaming SQL engine on top of Apache Kafka which aims to make stream processing available to everyone. This session introduces the concepts, architecture, use cases and benefits of KSQL. A live demo shows how to setup and use KSQL quickly and easily on top of your Kafka ecosystem.

1. KSQL
The Streaming SQL Engine for Apache Kafka
Kai Waehner
Technology Evangelist
kontakt@kai-waehner.de
LinkedIn
@KaiWaehner
www.confluent.io
www.kai-waehner.de

2. 2Confidential
1.0 Enterprise
Ready J
A Brief History of Apache Kafka and Confluent
0.11 Exactly-once
semantics
0.10 Data processing
(Streams API)
0.9 Data integration
(Connect API)
Intra-cluster
replication
0.8
2012 2014
Cluster mirroring0.7
2015 2016 20172013 2018
CP 4.1
KSQL GA

3. 3Confidential
KSQL – A Streaming SQL Engine for Apache Kafka

4. 4Confidential
Independent Dev / Test / Prod of independent Apps

5. 5Confidential
No Matter Where it Runs

6. 6KSQL- Streaming SQL for Apache Kafka
Why KSQL?
Population
CodingSophistication
Realm of Stream Processing
New, Expanded Realm
BI
Analysts
Core
Developers
Data
Engineers
Core Developers
who don’t like
Java
Kafka
Streams
KSQL

7. 7KSQL- Streaming SQL for Apache Kafka
Shoulders of Streaming Giants
subscribe(), poll(), send(),
flush(), beginTransaction(), …
KStream, KTable, filter(), map(), flatMap(), join(),
aggregate(), transform(), …
CREATE STREAM, CREATE TABLE,
SELECT, JOIN, GROUP BY, SUM, …
KSQL UDFs

8. 8KSQL- Streaming SQL for Apache Kafka
KSQL for Data Exploration
An easy way to inspect your data in Kafka
SHOW TOPICS;
SELECT page, user_id, status, bytes
FROM clickstream
WHERE user_agent LIKE 'Mozilla/5.0%';
PRINT 'my-topic' FROM BEGINNING;

9. 9KSQL- Streaming SQL for Apache Kafka
KSQL for Data Transformation
Quickly make derivations of existing data in Kafka
CREATE STREAM clicks_by_user_id
WITH (PARTITIONS=6,
TIMESTAMP='view_time’
VALUE_FORMAT='JSON') AS
SELECT * FROM clickstream
PARTITION BY user_id;
Change number of partitions1
Convert data to JSON2
Repartition the data3

10. 10KSQL- Streaming SQL for Apache Kafka
KSQL for Real-Time, Streaming ETL
Filter, cleanse, process data while it is in motion
CREATE STREAM clicks_from_vip_users AS
SELECT user_id, u.country, page, action
FROM clickstream c
LEFT JOIN users u ON c.user_id = u.user_id
WHERE u.level ='Platinum'; Pick only VIP users1

11. 11KSQL- Streaming SQL for Apache Kafka
Example: CDC from DB via Kafka to Elastic

12. 12KSQL- Streaming SQL for Apache Kafka
KSQL for Real-time Data Enrichment
Join data from a variety of sources to see the full picture
CREATE STREAM enriched_payments AS
SELECT payment_id, c.country, total
FROM payments_stream p
LEFT JOIN customers_table c
ON p.user_id = c.user_id;
Stream-Table Join1

13. 13KSQL- Streaming SQL for Apache Kafka
Example: Retail

14. 14KSQL- Streaming SQL for Apache Kafka
KSQL for Real-Time Monitoring
Derive insights from events (IoT, sensors, etc.) and turn them into actions
CREATE TABLE failing_vehicles AS
SELECT vehicle, COUNT(*)
FROM vehicle_monitoring_stream
WINDOW TUMBLING (SIZE 1 MINUTE)
WHERE event_type = 'ERROR’
GROUP BY vehicle
HAVING COUNT(*) >= 5; Now we know to alert, and whom1

15. 15KSQL- Streaming SQL for Apache Kafka
Example: IoT, Automotive, Connected Cars
streams

16. 16KSQL- Streaming SQL for Apache Kafka
KSQL for Anomaly Detection
Aggregate data to identify patterns and anomalies in real-time
CREATE TABLE possible_fraud AS
SELECT card_number, COUNT(*)
FROM authorization_attempts
WINDOW TUMBLING (SIZE 30 SECONDS)
GROUP BY card_number
HAVING COUNT(*) > 3;
Aggregate data1
… per 30-sec windows2

17. 17KSQL- Streaming SQL for Apache Kafka
KSQL Concepts
● No need for source code
• Zero, none at all, not even one line.
• No SerDes, no generics, no lambdas, ...
● All the Kafka Streams “magic” out-of-the-box
• Exactly Once Semantics
• Windowing
• Event-time aggregation
• Late-arriving data
• Distributed, fault-tolerant, scalable, ...

18. 18KSQL- Streaming SQL for Apache Kafka
KSQL is Equally viable for S / M / L / XL / XXL use cases
Ok. Ok. Ok.
… and KSQL is ready for production, including 24/7 support!

19. 19KSQL- Streaming SQL for Apache Kafka
Fault-Tolerance, powered by Kafka

20. 20KSQL- Streaming SQL for Apache Kafka
STREAM and TABLE as first-class citizens

21. 21KSQL- Streaming SQL for Apache Kafka
WINDOWing
● Not ANSI SQL ! à Continuous Queries
• TUMBLING
• SELECT appname, ip, COUNT(appname) AS problem_count FROM
logstream WINDOW TUMBLING (size 1 minute) WHERE loglevel='ERROR'
GROUP BY appname, ip;
• HOPPING
• SELECT itemid, SUM(arraycol[0]) FROM orders WINDOW HOPPING
(size 20 second, advance by 5 second) GROUP BY itemid;
• SESSION
• SELECT itemid, SUM(sales_price) FROM orders WINDOW SESSION
(20 second) GROUP BY itemid;

22. 22KSQL- Streaming SQL for Apache Kafka
KSQL - Components
KSQL has 3 main components:
1. The Engine which actually runs the Kafka Streams topologies
2. The REST server interface enables an Engine to receive instructions from the CLI
or any other client
3. The CLI, designed to be familiar to users of MySQL, Postgres etc.
(Note that you also need a Kafka Cluster… KSQL is deployed independently)

23. 23KSQL- Streaming SQL for Apache Kafka
KSQL can be used interactively + programmatically
ksql> POST /query
1UI
2CLI
3REST
4Headless

24. 24KSQL- Streaming SQL for Apache Kafka
Architecture (Client – Server Mode)
JVM
KSQL Server
KSQL CLI or any REST Client
JVM
KSQL Server
JVM
KSQL Server
Kafka Cluster

25. 25KSQL- Streaming SQL for Apache Kafka
Architecture (Headless Mode)
JVM
KSQL Server
JVM
KSQL Server
JVM
KSQL Server
Kafka Cluster

26. 26KSQL- Streaming SQL for Apache Kafka
Dedicating resources
Join Engines to the same
‘service pool’ by means of the
ksql.service.id property

27. 27KSQL- Streaming SQL for Apache Kafka
User Defined Functions (UDF, UDAF)
Write UDF code in Java, mark with annotations @UdfDescription, @Udf.
SELECT address, STRINGLENGTH(address->street) FROM orders;
Make UDF available to KSQL (next slides), then use it like any other KSQL function in your queries:
The UDF name in KSQL queries is
whatever you define in the `name` field in
the annotation (here: “stringLength”).

28. 28KSQL- Streaming SQL for Apache Kafka
KSQL Quick Start – Getting Started in Minutes!
https://docs.confluent.io/
current/quickstart/index.html
Local runtime
or
Docker container

29. 29KSQL- Streaming SQL for Apache Kafka
Demo - Clickstream Analysis
• https://docs.confluent.io/current/ksql/docs/tutorials/clickstream-docker.html#ksql-clickstream-
docker
• Leverages Apache Kafka, Kafka Connect, KSQL, Elasticsearch and Grafana
• 5min screencast: https://www.youtube.com/watch?v=A45uRzJiv7I
• Setup in 5 minutes (with or without Docker)
SELECT STREAM
CEIL(timestamp TO HOUR) AS timeWindow, productId,
COUNT(*) AS hourlyOrders, SUM(units) AS units
FROM Orders GROUP BY CEIL(timestamp TO HOUR),
productId;
timeWindow | productId | hourlyOrders | units
------------+-----------+--------------+-------
08:00:00 | 10 | 2 | 5
08:00:00 | 20 | 1 | 8
09:00:00 | 10 | 4 | 22
09:00:00 | 40 | 1 | 45
... | ... | ... | ...

30. 30KSQL- Streaming SQL for Apache Kafka
KSQL Recipes
https://www.confluent.io/stream-processing-cookbook

31. 31KSQL- Streaming SQL for Apache Kafka
Resources and Next Steps
Get Involved
• Try the Quickstart on GitHub
• Check out the code
• Play with the examples
KSQL is GA… You can already use it for production deployments!
https://github.com/confluentinc/ksql
http://confluent.io/ksql
https://slackpass.io/confluentcommunity #ksql

32. KSQLis the
Streaming
SQL Engine
for
Apache Kafka

33. Questions?
Kai Waehner
Technology Evangelist
kontakt@kai-waehner.de
LinkedIn
@KaiWaehner
www.confluent.io
www.kai-waehner.de