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Composable Data Processing with Apache Spark - Scaling Development and Error Handling

Offered By: Databricks via YouTube

Tags

Apache Spark Courses Big Data Courses Data Processing Courses Software Architecture Courses Data Engineering Courses Scalability Courses Data Pipelines Courses

Course Description

Overview

Explore a 28-minute conference talk on composable data processing with Apache Spark, presented by Databricks. Learn about the challenges of scaling Spark development and the consequences of isolated Spark apps. Discover SIP, an extensible plugin framework used in Adobe's Experience Platform for data processing, which addresses issues of resiliency, scalability, monitoring, and error handling. Dive deep into SIP's detailed error reporting and its improved user experience. Gain insights into parsing errors, conversions, and implementation challenges in the Adobe Data Platform context.

Syllabus

Intro
Adobe Data Platform
Implementation Challenges
Parsing Errors
Conversions


Taught by

Databricks

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