Apache Spark Evolution: From Hadoop Origins to Spark 4.0 π
Discover the fascinating journey of Apache Spark, from its beginnings in 2009 as a response to Hadoop MapReduce frustrations to its latest Spark 4.0 release. Learn how Spark transformed big data processing!
DataFlint
122 views β’ Aug 11, 2025
About this video
Curious about the history of ππ©πππ‘π ππ©ππ«π€?
Did you know Apache Spark was born out of frustration with Hadoop MapReduce back in 2009?
Since then, itβs evolved into a powerhouse. From caching in-memory RDDs to structured streaming, adaptive query execution, and now declarative pipelines in Spark 4.0.
And this is where DataFlint comes in: helping you optimize, debug, and control your Spark pipelines so you can make the most of every version.
Watch the journey in under a minute π#apachespark #bigdata #dataengineering #sparkoptimization #DataFlint#AIcopilot
Did you know Apache Spark was born out of frustration with Hadoop MapReduce back in 2009?
Since then, itβs evolved into a powerhouse. From caching in-memory RDDs to structured streaming, adaptive query execution, and now declarative pipelines in Spark 4.0.
And this is where DataFlint comes in: helping you optimize, debug, and control your Spark pipelines so you can make the most of every version.
Watch the journey in under a minute π#apachespark #bigdata #dataengineering #sparkoptimization #DataFlint#AIcopilot
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Views
122
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1
Duration
1:10
Published
Aug 11, 2025
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