Big Data - Let's SMACK
Language
English
Level
Intermediate
Length
53 minutes
Type
webinar
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About
Big Data • October 2017
Big Data - Let's SMACK
For many use cases such as fraud detection or reacting on sensor data the response times of traditional batch processing are simply to slow. In order to be able to react to such events close to real-time, we need to go beyond the classical batch processing and utilize stream processing systems such as Apache Spark Streaming, Apache Flink, or Apache Storm. But these systems are not sufficient by itself. One common example for such fast data pipelines is the SMACK stack using Apache Spark, Mesos, Kafka, Akka, Cassandra, Kafka
About speaker
Jörg Schad
Head of Machine LearningArangoDB
Jörg Schad is Head of Machine Learning at ArangoDB. In a previous life, he has worked on or built machine learning pipelines in healthcare, distributed systems at Mesosphere, and in-memory databases. He received his Ph.D. for research around distributed databases and data analytics. He’s a frequent speaker at meetups, international conferences, and lecture halls.
Details
Language
English
Level
Intermediate
Length
53 minutes
Type
webinar
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