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MapReduce as a paradigm and technology was popular about a decade ago and then died shortly after in favour of Hive, Spark etc. Pretty confident that not a sin
by threeseed 7y ago
MapReduce as a paradigm and technology was popular about a decade ago and then died shortly after in favour of Hive, Spark etc.
Pretty confident that not a single developer anywhere in this world would be first thinking of MapReduce. Just like they wouldn't jump straight to Cobol.
- wbl 7y agoBack in high school I did a map reduce job using split, sort, and a handwritten transformation and accumulation tool. It worked!
- jbergens 7y agoSome places still seem to go for large Kafka clusters just to calc some stats and forward some messages. I am sure some of their solutions are MapReduce below.
- threeseed 7y agoVery curious to understand more about these mythical developers who are recommending a technology/paradigm that stopped being used a decade ago. You've seen people writing pages and pages of Java code to do ETL ?
- doteka 7y agoI worked for a large multinational last year that had multiple teams rolling out terrible Hadoop solutions. The rest of the world does not particularly care about SV fashion trends.
- artimaeis 7y agoI'm on a team of a Fortune500 who uses a combination of Java and C# to do ETL. AMA. Edit: We're also a fairly greenfield team, with a product in beta that's less than 4 years old. So like, the leaders of the team knowingly crafted us in this particular direction.
- vonmoltke 7y agoI'm very curious to know where you got this strange notion that MapReduce is "a technology/paradigm that stopped being used a decade ago". I barely knew what MapReduce was in 2010, and didn't touch my first Hadoop cluster until late 2012. Every place I have worked since has had a Hadoop cluster or two.
- commandlinefan 7y ago> in favour of Hive, Spark Well, Hive and Spark create MapReduce jobs to satisfy your queries: it's still in the background, but you don't have to think about it (as much).