Name: AWS ECS Fargate to Production & Deep dive on Apache Spark Encoders[_]
Start: 2021-12-14T18:30:00+01:00
End: 2021-12-14T20:00:00+01:00

Hello everyone! We are happy to announce a new meetup for Big Data & AI Torino. It will be held on December 14th at 18:30 CET. We will have two fantastic speakers with us, Faith Olapade and Antonio Murgia talking about AWS ECS Fargate and Apache Spark respectivelly, a great opportunity for big data and cloud enthusiasts. Feel free to come and ask questions.

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The event will last about 1,5 hours:

18:30-19:05 - Deep dive on Apache Spark Encoders[_] (35 mins)
19:05-19:15 - Q&A (10 mins)
19:15-19:50 - Amazon ECS Fargate to Production (35 mins)
19:50-20:00 - Q&A (10 mins)

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Deep dive on Apache Spark Encoders[_]

Abstract: Spark is the most used Big Data framework. Spark 0.x introduced RDDs where you could process in a distributed fashion large collections of Plain Old Java Objects. Then Spark 1.6 introduced Dataframes and Dataset, a faster and more powerful abstraction to work on distributed datasets that can be “seen” as tables. Datasets especially allowed developers to mix different programming models, declarative ones like SQL and functional ones like `map`, `flatMap` and so on. But all this power comes with a cost that Spark tries to hide to its users. In this talk I want to demystify how Dataset/Dataframe work and allow their hybrid programming model, I also want to share with you my opinion on the design choices that were taken and made Spark so easy for newcomers and so frustrating for power users. In the end I want to share how I think we can work on those limitations in “user-land” to make our Data Engineers life much better.

Speaker Bio Antonio Murgia (https://www.linkedin.com/in/antonio-murgia/): Big Data Architect @ AgileLab. I fell in love with Scala at first sight in 2014 and never stopped using it and learning new things. Mainly that was because of Apache Spark where I started to understand how much you can love or hate the language and also how much power it can give it to you. In the last years I contributed to Apache Spark and to Witboost DataStream an open source analytics streaming platform we build at AgileLab. Beside computers I love to hike with my small dog and travel.

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Amazon ECS Fargate to Production

Abstract: When choosing a container orchestration tool, companies and organizations will most likely go with Kubernetes by default.
Without the Kubernetes complexity , Amazon ECS Fargate solves about 90% of container orchestration needs taking advantage of the seamless integration with a robust pool of AWS services from CI/CD pipelines, load balancers, autoscaling, to service meshing.
Let's explore how Amazon ECS Fargate can be leveraged to deploy secure, scalable, and highly available workloads.

Speaker: Faith Olapade (https://www.linkedin.com/in/faithtosinolapade/) is an AWS certified Cloud/DevOps engineer. Extremely passionate about Software delivery automation, containerization technologies, and cloud-native technologies.

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Due to Covid the event will be held only online. The streaming platform is Teams, we will provide a link as direct access for attendees.
Desktop: you can access via browser or with the Teams app.
Mobile: you need to access with the Teams app, unless you set your mobile browser as "Desktop Website".

We hope you will join us!
Please, send your RSVP as soon as possible to help us organize the event!

See you all on Thursday 14th December!

dario amorosi

Big Data & AI Torino

Technology

Web Development

Programming Languages

Scala

Big Data

Computer Programming

Machine Learning

Scala Akka

Distributed Systems

Play Framework

Apache Spark

AWS ECS Fargate to Production & Deep dive on Apache Spark Encoders[_]

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AWS ECS Fargate to Production & Deep dive on Apache Spark Encoders[_]

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