Presentation: Stream processing with Apache Flink
Location:
- Abbey, 4th flr.
Duration
Day of week:
- Monday
Abstract
Data streaming is gaining popularity, as more and more organizations are realizing that the nature of their data production is continuous and unbounded, and can be better served with a streaming architecture. Streaming architectures promise decreased latency from signal to decision, a radically simplified data infrastructure architecture, and the ability to cope with new data that is generated continuously. Apache Flink is a full-featured true stream processing framework with:
- Easy to use Java- and Scala-embedded APIs that make stream analytics easy, yet provide powerful tools to deal with time and uncertainty
- Throughput close to a million of events per second per core
- Latencies as low as the millisecond range
- Full support for event time and out of order arrivals with flexible windows, watermarks, and triggers
- Exactly-once consistency guarantees, and the ability to realize distributed transactional data movement between systems (e.g., between Kafka and HDFS)
- Ease of configuration and separation between application logic and fault tolerance via a novel asynchronous checkpointing algorithm
- No single point of failure
- Integration with popular open source infrastructure (e.g., Hadoop, HBase, Kafka, Cascading, Elasticsearch, …)
- Batch processing as a special case of stream processing, including dedicated libraries for machine learning and graph processing, managed memory on-, and off-heap, and query optimization
Flink is used in several companies, including at ResearchGate, Bouygues Telecom, the Otto Group, and Capital One, and has a large and active developer community of well over 140 contributors. In this talk, we provide an overview of the system internals and its streaming-first philosophy, as well as the programming APIs.
Similar Talks
Tracks
Covering innovative topics
Monday, 7 March
-
Back to Java
What to expect in Java 9 and Spring 5
-
Stream Processing @ Scale
Big data, fast-moving data. Practical implementation lessons on Real-time Data
-
DevOps & CI/CD
Lessons/stories on optimizing the deployment pipeline
-
Head-to-Tail Functional Languages
Free-range Monads, Tackling immutability, tales from production, and more...
-
Architecting for Failure
Your system will fail. Take control before it takes you with it
-
21st Century Culture from Geeks on the Ground
New ways to organise technology companies and workplace culture
Tuesday, 8 March
-
Architectures You've Always Wondered about
In-depth technical case studies from giants like: Microsoft, Netflix, Google, Twitter, and more...
-
Close to the Metal
Get efficiency back into your code, concepts like: cache efficient algorithm and lock free data structures
-
Containers (in production)
Real-world lessons on scalability and reliability in production container deployments
-
Modern CS in the real world
Real-world Industry adoption of modern CS ideas
-
Security, Incident Response & Fraud Detection
Master-level classes on building security into your system and responding to incidents when things go wrong.
-
Optimizing You
Keeping life in balance is always a challenge. Learning lifehacks
Wednesday, 9 March
-
Disrupting Finance
Technology advances in finance (blockchain, P2P, Machine Learning, API's)
-
Modern Native Languages
Modern native languages: Safe efficiency with Go, Rust, Swift
-
Full Stack Javascript
Level up Javascript with topics like Angular, React/ReactNative, Node, Mongo/Couch/Other, Falcor, GraphQL, etc
-
Data Science & Machine Learning Methods
A developer's data science and machine learning toolkit
-
Microservices for Mega-Architectures
Practical lessons on Microservices success.
-
Modern Agile Development
Revisiting Agile today and tackling challenges we are seeing in the wild