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© 2020 Ververica
1
© 2020 Ververica
2
2
● Caito Scherr
Introduction
© 2020 Ververica
3
3
● Caito Scherr
Introduction
3
● Caito Scherr
● Developer Advocate
© 2020 Ververica
4
● Caito Scherr
● Developer Advocate
● Ververica, GmbH
Introduction
© 2020 Ververica
5
● Caito Scherr
● Developer Advocate
● Ververica, GmbH
● Portland, OR, USA
Introduction
© 2020 Ververica
6
Introduction
© 2020 Ververica
7
Introduction
© 2020 Ververica
8
● Quick Flink Intro
● Why Flink SQL?
● Getting Started
Agenda
© 2020 Ververica
9
Agenda
● Quick Flink Intro
● Why Flink SQL?
● Getting Started
© 2020 Ververica
10
Agenda
● Quick Flink Intro
● Why Flink SQL?
● Getting Started
© 2020 Ververica
11
Flink Intro
● Stateful, distributed
● Stream processing engine
● Unified batch & streaming
>> High Level
© 2020 Ververica
12
Flink Intro
● Stateful, distributed
● Stream processing engine
● Unified batch & streaming
● Scalable
● Highly configurable
● “Deploy anywhere”
>> High Level
© 2020 Ververica
13
>> Flink’s APIs
Flink Intro
© 2020 Ververica
14
>> Flink: Unified Processing
● Reuse code and logic
● Consistent semantics
● Mix historic and real-time
● Simplify operations
Flink Intro
© 2020 Ververica
15
>> Architecture
Flink Intro
© 2020 Ververica
16
>> Basic Example
Flink Intro
© 2020 Ververica
17
Flink Intro >> Basic Example
© 2020 Ververica
18
Flink Intro >> Basic Example
© 2020 Ververica
19
Flink Intro >> Basic Example
© 2020 Ververica
20
Flink Intro >> Basic Example
© 2020 Ververica
21
Flink Runtime
Stateful Computations over Data Streams
Stateful
Stream Processing
Streams, State, Time
Event-Driven
Applications
Stateful Functions
Streaming
Analytics & ML
SQL, PyFlink, Tables
Why Flink SQL?
Image Credit: Marta Paes
© 2020 Ververica
22
>> Benefits / Use Cases
● Unified, distributed
● Less implementation overhead
● Developer autonomy
Why Flink SQL?
© 2020 Ververica
23
user cnt
Mary 2
Bob 1
SELECT user_id,
COUNT(url) AS cnt
FROM clicks
GROUP BY user_id;
Take a snapshot when the
query starts
A final result is
produced
A row that was added after the query
was started is not considered
user cTime url
Mary 12:00:00 https://…
Bob 12:00:00 https://…
Mary 12:00:02 https://…
Liz 12:00:03 https://…
The query
terminates
Why Flink SQL? >> Compare: Regular SQL Engine
Image Credit: Marta Paes
© 2020 Ververica
24
user cTime url
user cnt
SELECT user_id,
COUNT(url) AS cnt
FROM clicks
GROUP BY user_id;
Mary 12:00:00 https://…
Bob 12:00:00 https://…
Mary 12:00:02 https://…
Liz 12:00:03 https://…
Bob 1
Liz 1
Mary 1
Mary 2
Ingest all changes as
they happen
Continuously update the
result
The result is identical to the one-time query (at this point)
>> A Streaming SQL Engine
Why Flink SQL?
Image Credit: Marta Paes
© 2020 Ververica
25
>> Simpler with SQL
Why Flink SQL?
© 2020 Ververica
26
● Standard SQL syntax and semantics (i.e. not a “SQL-flavor”)
● Unified APIs for batch and streaming
● Support for advanced time handling and operations (e.g. CDC, pattern matching)
UDF Support
Python
Java
Scala
Execution
TPC-DS Coverage
Batch
Streaming
+
Formats
Native Connectors
Apache Kafka
Elasticsearch
FileSystems
JDBC HBase
+
Kinesis
Metastore Postgres (JDBC)
Data Catalogs
Debezium
>> Flink SQL In A Nutshell
Why Flink SQL?
Image Credit: Marta Paes
© 2020 Ververica
27
>> Simple Pre-Requisites
1. Check Java version
2. Download Flink snapshot
3. Un-tar it
Getting Started
© 2020 Ververica
28
What Next? >> Flink SQL Cookbook
© 2020 Ververica
29
© 2020 Ververica
30
© 2020 Ververica
31
© 2020 Ververica
32
© 2020 Ververica
33
© 2020 Ververica
34
What Next? >> Flink SQL Cookbook
Image Credit: Marta Paes
© 2020 Ververica
35
What Next? >> Flink SQL Cookbook
© 2020 Ververica
36
Find Me Here
Twitter
Caito_200_OK
Content
https://medium.com/@caito
http://caito-200-ok.com/
Email
Caito@ververica.com
© 2020 Ververica
37
Credits + Resources
● Flink Ahead: What Comes After Batch & Streaming: https://youtu.be/h5OYmy9Yx7Y
● Flink Table API & SQL:
https://ci.apache.org/projects/flink/flink-docs-master/dev/table/sql/queries.html#operatio
ns
● Flink SQL Cookbook: https://github.com/ververica/flink-sql-cookbook
● Flink logos:
https://wints.github.io/flink-web//community.html
● Powered by Flink: https://flink.apache.org/poweredby.html
● Flink SQL Connectors:
https://ci.apache.org/projects/flink/flink-docs-master/docs/connectors/table/formats/over
view/
© 2020 Ververica
● Nina & the Berlin Buzzwords
Conference staff!!
● Marta Paes
38
Thank You!
Scan here for links
& resources

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