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Apache Spark:Intro to Spark(Lightning-fast cluster computing)

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A Brief History Spark Deconstructed Spark Essential Simple Spark Demo Spark SQL
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Intro to Spar rk Lightning-fast cluster computing

Intro to Spark Lightning-fast cluster computing

What is Spark? Spark Overview a fast and general-purpose cluster computing system Soak

What is Spark? Spark Overview: A fast and general-purpose cluster computing system

What is Spark? Spark Overview a fast and general-purpose cluster computing system It provides high-level APls in java, Scala and python, and an optimized engine that supports general execution graphs Soak

What is Spark? Spark Overview: A fast and general-purpose cluster computing system. It provides high-level APIs in Java, Scala and Python, and an optimized engine that supports general execution graphs

What is Spark? Spark Overview a fast and general-purpose cluster computing system It provides high-level APls in java, Scala and python, and an optimized engine that supports general execution graphs It supports a rich set of higher-level tools including Spark sQL for SQL and structured data processing MLlib for machine learning GraphX for graph processing Spark Streaming for streaming processing Soak

What is Spark? Spark Overview: A fast and general-purpose cluster computing system. It provides high-level APIs in Java, Scala and Python, and an optimized engine that supports general execution graphs. It supports a rich set of higher-level tools including: Spark SQL for SQL and structured data processing MLlib for machine learning GraphX for graph processing Spark Streaming for streaming processing

Apache spark A Brief History

Apache Spark A Brief History

A Brief History: MapReduce circa 2004-Google MapReduce: Simplified Data Processing on Large clusters Jeffrey dean and sanjay ghemawat researchgoogle.com/archive/mapreduce.html MapReduce is a programming model and an associated implementation for processing and generating large data sets

A Brief History: MapReduce circa 2004 – Google MapReduce: Simplified Data Processing on Large Clusters Jeffrey Dean and Sanjay Ghemawat MapReduce is a programming model and an associated implementation for processing and generating large data sets. research.google.com/archive/mapreduce.html

A Brief History: MapReduce circa 2004-Google M Program jeff resel Master (2) reduce worker plit O (6)w Worker (5) remote read file o split 2A(3)read worker (4)local write ork file I plit 4 worker ntermediate files Reduce Output files phase (on local disks) phase files

A Brief History: MapReduce circa 2004 – Google MapReduce: Simplified Data Processing on Large Clusters Jeffrey Dean and Sanjay Ghemawat MapReduce is a programming model and an associated implementation for processing and generating large data sets. research.google.com/archive/mapreduce.html

A Brief History: MapReduce MapReduce use cases showed two major limitations. difficultly of programming directly in MR 2. performance bottlenecks, or batch not fitting the e use cases In short, Mr doesnt compose well for large applications

A Brief History: MapReduce MapReduce use cases showed two major limitations: 1. difficultly of programming directly in MR 2. performance bottlenecks, or batch not fitting the use cases In short, MR doesn’t compose well for large applications

A Brief History: Spark Developed in 2009 at Uc berkeley amPlab then open sourced in 2010, Spark has since become one of the largest oss communities in big data with over 200 contributors in 50+ organiZations Unlike the various specialized systems, Sparks goal was to generalize mapreduce to support new apps within same engine Q Lightning-fast cluster computing

A Brief History: Spark Developed in 2009 at UC Berkeley AMPLab, then open sourced in 2010, Spark has since become one of the largest OSS communities in big data, with over 200 contributors in 50+ organizations Unlike the various specialized systems, Spark’s goal was to generalize MapReduce to support new apps within same engine Lightning-fast cluster computing

A Brief History: Special Member Lately Ive been working on the Databricks Cloud and Spark. Ive been responsible for the architecture, design, and implementation of many Spark components Recently led an effort to scale spark and built a ystem based on Spark that set a new world record for sorting 100TB of data(in 23 mins) @Reynold Xin

A Brief History: Special Member Lately I've been working on the Databricks Cloud and Spark. I've been responsible for the architecture, design, and implementation of many Spark components. Recently, I led an effort to scale Spark and built a system based on Spark that set a new world record for sorting 100TB of data (in 23 mins). @Reynold Xin

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