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KSQL – Streaming SQL
for Apache Kafka
Matthias J. Sax | Software Engineer
matthias@confluent.io
@MatthiasJSax

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1.0 Enterprise
Ready
A Brief History of 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

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Why KSQL?
• Enable Stream Processing for Non-Engineers
• Everybody knows SQL
• Look Ma, no code!
• Declarative stream processing language
• Fast prototyping
• Streaming SQL engine for Apache Kafka
• Streaming ETL
• Ad-hoc topic inspection

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Trade-Offs
• subscribe()
• poll()
• send()
• flush()
Consumer,
Producer
• filter()
• join()
• aggregate()
Kafka Streams
• Select…from…
• Join…where…
• Group by..
KSQL
Flexibility Simplicity

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Core Concepts KSQL

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CREATE STREAM clickstream (
time BIGINT,
url VARCHAR,
status INTEGER,
bytes INTEGER,
user_id VARCHAR,
agent VARCHAR)
WITH (
value_format = 'JSON',
kafka_topic = 'my_clickstream_topic'
);
Creating a Stream

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Querying Streams
CREATE STREAM user_clicks AS
SELECT *
FROM clickstream
WHERE user_id = 'mjsax';

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CREATE TABLE clicks AS
SELECT user_id, COUNT(url)
FROM clickstream
WINDOW TUMBLING (size 30 seconds)
GROUP BY user_id
HAVING COUNT(url) > 20
WHERE bytes > 1024;
Windowed Aggregations

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Windowed Aggregations

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Core Concepts KSQL

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Do you think that’s a table you are querying ?

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CREATE TABLE users (
user_id INTEGER,
registered_at LONG,
username VARCHAR,
name VARCHAR,
city VARCHAR,
level VARCHAR)
WITH (
key = 'user_id',
kafka_topic = 'clickstream_users',
value_format = 'AVRO');
Creating a Table

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Confluent Schema Registry FTW!
CREATE TABLE users
WITH (
key = 'user_id',
kafka_topic = 'clickstream_users',
value_format = 'AVRO');
Creating a Table

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Using Tables

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CREATE STREAM vip_actions AS
SELECT c.user_id, fullname, url, status
FROM clickstream c
LEFT JOIN users u ON c.user_id = u.user_id
WHERE u.level = 'Platinum';
Joins for Enrichment

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Joins for Enrichment

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Stream-Table-Duality

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How to deploy and use KSQL

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How to run KSQL
JVM
KSQL Server
KSQL CLI
JVM
KSQL Server
JVM
KSQL Server
Kafka Cluster
#1 Client-server

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How to run KSQL
#1 Client-server
• Start any number of server nodes
bin/ksql-server-start
• Start one or more CLIs and point them to a server
bin/ksql https://myksqlserver:8090
• All servers share the processing load
Technically, instances of the same Kafka Streams Applications
Scale up/down without restart

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How to run KSQL
JVM
KSQL Server
JVM
KSQL Server
JVM
KSQL Server
#2 as a standalone Application
Kafka Cluster

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How to run KSQL
#2 as a standalone Application
• Start any number of server nodes
Pass a file of KSQL statement to execute
bin/ksql-node query-file=foo/bar.sql
• Ideal for streaming ETL application deployment
Version-control your queries and transformations as code
• All running engines share the processing load
Technically, instances of the same Kafka Streams Applications
Scale up/down without restart

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How to run KSQL
#3 EMBEDDED IN AN APPLICATION
JVM App Instance
KSQL Engine
Application Code
JVM App Instance
KSQL Engine
Application Code
JVM App Instance
KSQL Engine
Application Code
Kafka Cluster

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How to run KSQL
#3 EMBEDDED IN AN APPLICATION
• Embed directly in your Java application
• Generate and execute KSQL queries through the Java API
Version-control your queries and transformations as code
• All running application instances share the processing load
Technically, instances of the same Kafka Streams Applications
Scale up/down without restart

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Internals

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Internals
Read input from Kafka
Operator DAG:
• filter/map/aggregation/joins
• Operators can be stateful
Write result back to Kafka

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Internals

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Runtime: Kafka Streams

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Distributed State

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Scaling

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Take home
• Streaming SQL engine for Apache Kafka
• Leverages Kafka Streams
• Open Source: Apache 2.0
• https://github.com/confluentinc/ksql/
• Included in Confluent Platform 4.1
• https://www.confluent.io/product/ksql/
• https://docs.confluent.io/current/ksql/docs/index.html

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Thank You
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