Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Sign up for free
Menu
Search
Features
All features
Private URLs
Password Protection
Custom URLS
Scheduled publishing
Remove Branding
Restrict embedding
Deck Collections
Notes
Features
All features
Private URLs
Password Protection
Custom URLS
Scheduled publishing
Remove Branding
Restrict embedding
Deck Collections
Notes
Explore
Featured decks
Featured speakers
Programming
Technology
Storyboards
Explore
Featured decks
Featured speakers
Programming
Technology
Storyboards
Pricing
Search
Sign in
Sign up for free
[OracleCode NYC-2018] Apache Kafka A Streaming ...
Search
Sponsored
·
SiteGround - Reliable hosting with speed, security, and support you can count on.
→
Viktor Gamov
March 08, 2018
Technology
200
1
Share
Embed
Copy iframe code
Copy JS code
Copy link
Start on current slide
[OracleCode NYC-2018] Apache Kafka A Streaming Data Platform
Viktor Gamov
March 08, 2018
More Decks by Viktor Gamov
See All by Viktor Gamov
Processing Streaming Data with KSQL
vikgamov
4
490
[VirtualJUG] Apache Kafka — A Streaming Data Platform
vikgamov
3
460
[SF JUG] Apache Kafka — A Streaming Data Platform
vikgamov
4
130
[OracleCode NYC-2018] Rethinking Stream Processing with KStreams and KSQL
vikgamov
2
280
[JBreak-2018] Это кто там твитить про #jbreak?
vikgamov
0
250
[DevNexus-2018] Apache Kafka A Streaming Data Platform
vikgamov
2
340
[DataSciCon] Divide, Distribute and Conquer: Stream v. Batch
vikgamov
0
130
[Philly JUG] Divide, Distribute and Conquer: Stream v. Batch
vikgamov
0
530
[Atlanta JUG] Testing containers with TestContainers
vikgamov
0
1.3k
Other Decks in Technology
See All in Technology
二歩目のフロントエンド・ウェブアクセシビリティ
camiha
2
430
10年後、Engineering 行為を剥奪されるとして、わたしたちは、どう、何を創ればいいだろうか。 / If Engineering Is Taken Away in 10 Years, How and What Should We Create?
bitkey
PRO
1
130
事業活動を AI Ready にする攻めと守りのデータエンジニアリング / data-engineering-for-ai-ready-business
pei0804
7
2.7k
SREでアラート疲れを 解決しよう!
kairim0
1
230
大型犬好きによるPugの紹介
yamanoku
1
150
実践!Cloud Run ハンズオン!! / Cloud Run handson
y0hgi
1
250
不可逆な意思決定を避けながら10億超の顧客データを AI Ready にするデータ基盤設計
baseballyama
1
310
Running Kotlin + Quarkus with Lambda
nealle
1
460
[AWS 秋のクラウドオペレーション祭り 2026]AWS DevOps Agentで変わるリリースと運用対応 ~リリース管理機能と Directed actions のご紹介~
furuton
4
1.2k
Snapshot Testing in Practice: Predictable and Reliable SwiftUI Views
fespinoza
0
210
実体験から学ぶ分析エージェントの開発と運⽤
recruitengineers
PRO
8
2.2k
Getting Started with Google Antigravity
glaforge
0
230
Featured
See All Featured
How to audit for AI Accessibility on your Front & Back End
davetheseo
0
600
Build your cross-platform service in a week with App Engine
jlugia
234
19k
Building AI with AI
inesmontani
PRO
1
1.3k
Let's Do A Bunch of Simple Stuff to Make Websites Faster
chriscoyier
508
140k
Designing for Timeless Needs
cassininazir
1
520
AI in Enterprises - Java and Open Source to the Rescue
ivargrimstad
0
1.5k
Amusing Abliteration
ianozsvald
1
340
Breaking role norms: Why Content Design is so much more than writing copy - Taylor Woolridge
uxyall
1
450
[RailsConf 2023] Rails as a piece of cake
palkan
59
7.1k
Prompt Engineering for Job Search
mfonobong
0
500
実際に使うSQLの書き方 徹底解説 / pgcon21j-tutorial
soudai
PRO
203
77k
Scaling GitHub
holman
464
140k
Transcript
@ Apache Kafka A Streaming Data Platform
@ @gamussa @confluentinc Solutions Architect Developer Advocate @gamussa in internetz
Hey you, yes, you, go follow me in twitter © Who am I?
@ @gamussa @confluentinc A company is build on DATA FLOWS
but All we have is DATA STORES
@ @gamussa @confluentinc
@ @gamussa @confluentinc
@ @gamussa @confluentinc
@ @gamussa @confluentinc
@ @gamussa @confluentinc
@ @gamussa @confluentinc Streaming Platform 1. Pub/Sub 2. Store 3.
Process
@ @gamussa @confluentinc Streaming Platform 1. Pub/Sub 2. Store 3.
Process
@ @gamussa @confluentinc Core abstraction DB - table Hadoop -
file Messaging -?
@ @gamussa @confluentinc LOGS
@ @gamussa @confluentinc Producing to Kafka Time
@ @gamussa @confluentinc Producing to Kafka Time C C C
@ @gamussa @confluentinc Producing to Kafka - With Key Time
A B C D hash(key) % numPartitions = N
@ @gamussa @confluentinc Producing to Kafka - No Key Time
Messages will be produced in a round robin fashion
@ @gamussa @confluentinc Consuming From Kafka - Single Consumer C
@ @gamussa @confluentinc Consuming From Kafka - Grouped Consumers C
C C1 C C C2
@ @gamussa @confluentinc Consuming From Kafka - Grouped Consumers C
C C C
@ @gamussa @confluentinc Consuming From Kafka - Grouped Consumers 0
1 2 3
@ @gamussa @confluentinc Consuming From Kafka - Grouped Consumers 0
1 2 3
@ @gamussa @confluentinc Consuming From Kafka - Grouped Consumers 0,
3 1 2 3
@ @gamussa @confluentinc Producers Consumers
@ @gamussa @confluentinc
@ @gamussa @confluentinc
@ @gamussa @confluentinc
@ @gamussa @confluentinc Kafka Connect does hard work so you
don’t 1. Scale out
@ @gamussa @confluentinc
@ @gamussa @confluentinc
@ @gamussa @confluentinc
@ @gamussa @confluentinc
@ @gamussa @confluentinc Streaming Platform 1. Pub/Sub 2. Store 3.
Process
@ @gamussa @confluentinc Why Store?
@ @gamussa @confluentinc Scalability of a filesystem Throughput 100s mb/s
TBs per server Commodity Hardware O(1) writes
@ @gamussa @confluentinc Guarantees of a database Persistence Strict ordering
@ @gamussa @confluentinc Replication Fault Tolerance Partitioning Scale Distributed by
Design
@ @gamussa @confluentinc
@ @gamussa @confluentinc Partition Leadership and Replication Broker 1 Topic1
partition1 Broker 2 Broker 3 Broker 4 Topic1 partition1 Topic1 partition1 Leader Follower Topic1 partition2 Topic1 partition2 Topic1 partition2 Topic1 partition3 Topic1 partition4 Topic1 partition3 Topic1 partition3 Topic1 partition4 Topic1 partition4
@ @gamussa @confluentinc Partition Leadership and Replication - node failure
Broker 1 Topic1 partition1 Broker 2 Broker 3 Broker 4 Topic1 partition1 Topic1 partition1 Leader Follower Topic1 partition2 Topic1 partition2 Topic1 partition2 Topic1 partition3 Topic1 partition4 Topic1 partition3 Topic1 partition3 Topic1 partition4 Topic1 partition4
@ @gamussa @confluentinc Streaming Platform 1. Pub/Sub 2. Store 3.
Process
@ @gamussa @confluentinc What is Stream Processing? A machine for
combining streams of events
@ @gamussa @confluentinc
@ @gamussa @confluentinc
@ @gamussa @confluentinc https://www.confluent.io/download/
@ @gamussa @confluentinc We are hiring! https://www.confluent.io/careers/
@ @gamussa @confluentinc One more thing…
@ @gamussa @confluentinc
@ @gamussa @confluentinc
@ @gamussa @confluentinc A Major New Paradigm
@ @gamussa @confluentinc Thanks! questions? @gamussa
[email protected]
We are hiring!
https://www.confluent.io/careers/