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Meet up

Redis Streams + Spark Structured Streaming: Scale-out Your Continuous Apps

Tuesday, 30th July at CodeNode, London

This meetup was organised by Redis London in July 2019

Join Redis London and learn to Scale-out your Continuous Apps!

Lightening talk: Redis Modules

Pieter Cailliau

Pieter is part of the Solutions Architect team of RedisLabs based in London. He holds a MSc in Computer Science from Ghent University, where he wrote a distinguished thesis on time-based graph models. Prior to joining RedisLabs, Pieter used to work for Neo4j and was an instanceof Software Engineer at TomTom, the world’s leader in location and navigation software.

Redis Streams + Spark Structured Streaming: Scale-out Your Continuous Apps

Continuous applications face many challenges as they grow to production. Often, due to the rapid increase in the number of devices or end-users or other data sources, the size of their data set grows exponentially. This results in a backlog of data to be processed. The data will no longer be processed in near-real-time. Redis Streams enables you to collect both binary and text data in the time series format. The consumer groups of Redis Stream help you match the data processing rate of your continuous application with the rate of data arrival from various sources. Apache Spark’s Structured Streaming API enables real-time decision making for Continuous Applications. In this session, Roshan will perform a live demonstration of how to integrate open source Redis Streams with Apache Spark’s Structured Streaming API using Spark-Redis library. He will also walk through the code and demo a live continuous application.

Talk Description: Continuous applications have 3 things in common:

1) They collect data from sources (ex: IoT devices)

2) process them in real-time (example: ETL)

3) deliver them to machine learning serving layer for decision making

Roshan Kumar

Rosham Kumar is a Senior Product Manager at Redis Labs

Thanks to our sponsors

Attending Members

Overview

Join Redis London and learn to Scale-out your Continuous Apps!

Lightening talk: Redis Modules

Pieter Cailliau

Pieter is part of the Solutions Architect team of RedisLabs based in London. He holds a MSc in Computer Science from Ghent University, where he wrote a distinguished thesis on time-based graph models. Prior to joining RedisLabs, Pieter used to work for Neo4j and was an instanceof Software Engineer at TomTom, the world’s leader in location and navigation software.

Redis Streams + Spark Structured Streaming: Scale-out Your Continuous Apps

Continuous applications face many challenges as they grow to production. Often, due to the rapid increase in the number of devices or end-users or other data sources, the size of their data set grows exponentially. This results in a backlog of data to be processed. The data will no longer be processed in near-real-time. Redis Streams enables you to collect both binary and text data in the time series format. The consumer groups of Redis Stream help you match the data processing rate of your continuous application with the rate of data arrival from various sources. Apache Spark’s Structured Streaming API enables real-time decision making for Continuous Applications. In this session, Roshan will perform a live demonstration of how to integrate open source Redis Streams with Apache Spark’s Structured Streaming API using Spark-Redis library. He will also walk through the code and demo a live continuous application.

Talk Description: Continuous applications have 3 things in common:

1) They collect data from sources (ex: IoT devices)

2) process them in real-time (example: ETL)

3) deliver them to machine learning serving layer for decision making

Roshan Kumar

Rosham Kumar is a Senior Product Manager at Redis Labs

Thanks to our sponsors

Who's coming?

Attending Members