Gates 412 curriculum vit im an assistant professor at stanford cs, where i work on computer systems and machine learning as part of stanford dawn. While the first big data systems made a new class of applications possible, organizations must now compete on the speed and sophistication with which they can draw value from data. I started the spark project during my phd and have also worked closely with other open source projects in largescale computing, including apache hadoop and mesos. Others recognize spark as a powerful complement to hadoop and other. An architecture for fast and general data processing on. Matei zaharia chief technologist databricks linkedin. Im also cofounder and chief technologist of databricks, a data and ai platform startup. Franklin, scott shenker, ion stoica university of california, berkeley abstract mapreduce and its variants have been highly successful in implementing largescale dataintensive applications on commodity clusters. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific. Bill chambers, matei zaharia learn how to use, deploy, and maintain apache spark with this comprehensive guide, written by the creators of the opensource clustercomputing framework. Some see the popular newcomer apache spark as a more accessible and more powerful replacement for hadoop, big datas original technology of choice. Matei zaharia is a computer scientist and the creator of apache spark zaharia was an undergraduate at the university of waterloo. Use features like bookmarks, note taking and highlighting while reading spark. He started the spark project at uc berkeley in 2009, where he was a phd student, and he continues to serve as its vice president at apache.
How companies are using spark, and where the edge in big data will be. This book introduces apache spark, the open source cluster computing system that makes data analytics fast to write and fast to run. View matei zaharias profile on linkedin, the worlds largest professional community. He is also a committer on apache hadoop and apache mesos. Lowlevel apis mapreduce separate systems for each task. Fast and expressive cluster computing system interoperable with apache hadoop improves efficiency through. Download it once and read it on your kindle device, pc, phones or tablets.
Description learn how to use, deploy, and maintain apache spark with this comprehensive guide, written by the creators of the opensource clustercomputing framework. Thomas, anil shanbhagy, deepak narayanan, holger pirky, malte schwarzkopfy, saman amarasinghey, matei zaharia stanford infolab ymit csail abstract modern analytics applications combine multiple functions from different libraries and frameworks to build. It was donated to apache software foundation in 20, and now apache spark has become a top level apache project from feb2014. Fast and interactive analytics over hadoop data with spark shark. Spark sql is a new module in apache spark that integrates relational processing with sparks functional programming api.
Written by the developers of spark, this book will have data scientists and engineers up and running in no time. This is the central repository for all materials related to spark. Download for offline reading, highlight, bookmark or take notes while you read learning spark. Fast and expressive big data analytics with python matei. Apache spark is a fast and general engine for big data processing. Matei zaharia is an assistant professor of computer science at stanford university and chief technologist at databricks. Pdf spark the definitive guide by visit amazons bill. The core abstraction of spark is the resilient distributed dataset rdd, a working set of data that sits in memory for fast, iterative processing.
How companies are using spark, and where the edge in big. Rdds in the open source spark system, which we evaluate using both synthetic 1. Cluster computing with working sets matei zaharia, mosharaf chowdhury, michael j. Im an assistant professor at stanford cs, where i work on computer systems and machine learning as part of stanford dawn. What is apache spark a new name has entered many of the conversations around big data recently. Matei zaharia is a romaniancanadian computer scientist specializing in big data, distributed systems, and cloud computing. Spark is the first to make this a declarative api integrates with other data science libraries. With spark, you can tackle big datasets quickly through simple apis in python, java, and scala. Running these applications at everlarger scales requires parallel platforms that automatically handle faults and stragglers.
Simplifying big data applications with apache spark 2. Logistic regression 0 500 1500 2000 2500 3000 3500 4000 1 5 10 20 30. Sql and rich analytics at scale discretized streams. Welcome to spark summit europe our largest european summit yet 102talks 1200attendees 11tracks. Semantic scholar profile for matei zaharia, with 3536 highly influential citations and 125 scientific research papers. Features of apache spark apache spark has following features. Spark 110 s iteration first iteration 80 s further iterations 1 s credits. Learning spark by matei zaharia, patrick wendell, andy konwinski, holden karau get learning spark now with oreilly online learning. We propose adding this to spark sql dataframes first, using a new api in the spark engine that lets libraries run dags adaptively.
He created the apache spark project and cocreated the apache mesos project during his phd at uc berkeley, and also designed the core. Im matei zaharia, creator of spark and cto at databricks. Lightningfast big data analysis kindle edition by karau, holden, konwinski, andy, wendell, patrick, zaharia, matei. Matei zaharia electrical engineering and computer sciences. Proceedings of the 2015 acm sigmod international conference on management of. A common runtime for high performance data analytics. While at university of california, berkeley s amplab in 2009, he created apache spark as a faster alternative to mapreduce. Im now an assistant professor at mit as well as cto of databricks, the startup company created by the spark team. An efficient and faulttolerant model for stream processing on large clusters. Apache spark is a system for processing large data sets in parallel. Matei zaharia created spark, and is the cofounder of databricks, a company using spark to power data science. He received the 2015 acm doctoral dissertation award for his phd research on largescale computing.
He is a cofounder and cto of databricks, and an assistant professor of computer science at the massachusetts institute of technology. See the complete profile on linkedin and discover mateis. Matei zaharia fast and expressive big data analytics with python uc berkeley uc berkeley mit. Background big data systems became a popular research topic nearly 10 years ago. Getting started with apache spark big data toronto 2020. This jira proposes to add adaptive query execution, so that the engine can change the plan for each query as it sees what data earlier stages produced. Big data processing made simple kindle edition by chambers, bill, zaharia, matei. Built on our experience with shark, spark sql lets spark programmers. An introduction to advanced spark features such as controllable partitioning, caching formats, and serialization. Matei also costarted the apache mesos project and is a committer on apache hadoop.
Spark helps to run an application in hadoop cluster, up to 100 times faster. Use features like bookmarks, note taking and highlighting while reading learning spark. Learn how to use, deploy, and maintain apache spark with this comprehensive guide, written by the creators of the opensource clustercomputing framework. First edition revision history for the first edition 20150126. Ill talk about how changes in the api have made it easier to write batch, streaming and. Apache spark creator matei zaharia interview software. We thank the first spark users, including timothy hunter, lester mackey, dilip joseph, jibin zhan, and teodor moldovan, for trying out. Relational data processing in spark m armbrust, rs xin, c lian, y huai, d liu, jk bradley, x meng, t kaftan. I plan to continue doing research and open source work in big data, so ask me anything on the topic. With an emphasis on improvements and new features in spark 2.
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