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The article discusses the challenge of supplanting entrenched software such as Hadoop. I am actually a bit more optimistic about the ability to swap out Hadoop
by mikegagnon 13y ago
The article discusses the challenge of supplanting entrenched software such as Hadoop. I am actually a bit more optimistic about the ability to swap out Hadoop with technologies like Spark.
At Twitter we don't program using Hadoop directly; we mostly use either Scalding or Pig, languages that compile down to Hadoop code.
https://dev.twitter.com/blog/scalding https://dev.twitter.com/blog/scalding
http://www.slideshare.net/kevinweil/hadoop-pig-and-twitter-nosql-east-2009 http://www.slideshare.net/kevinweil/hadoop-pig-and-twitter-n...
I believe this is how many other companies use Hadoop as well.
The benefit here is that it's possible to write new backends for Pig and Scalding that compile down to Spark or anything else. And then you have backwards compatibility with all your old big-data code.
- shazzdeeds 13y agoOne of the Cloudera devs told me 80% of all Hadoop users run Hive. This suggests most devs secretly want to continue using SQL, but want more scalable relational solutions. Thus why Cloudera is backing Impala, and Facebook is about to open source Presto. I worked on an entire team of developers where I was the only one who understood the raw Java MapReduce API. Almost everyone else on my team got by with learning HiveQL, and a very minimal understand of MapReduce design flow. Your belief is absolutely correct.