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6/27/2014
10:09 AM
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Google I/O: Hello Dataflow, Goodbye MapReduce

Google introduces Dataflow to handle streams and batches of big data, replacing MapReduce and challenging other public cloud services.

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senorcarbone
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senorcarbone,
User Rank: Apprentice
7/3/2014 | 9:56:10 AM
Re: Dataflow implications for Hadoop community?
You can take a look on the following Apache incubator projects as the open source equivalents on parallel dataflow processing

- Apache Tez (https://tez.incubator.apache.org/)

- Apache Flink (former Stratosphere) (https://github.com/apache/incubator-flink
Charlie Babcock
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Charlie Babcock,
User Rank: Author
6/27/2014 | 8:15:00 PM
Google's goal: a competitive service
Agreed, many implications for Hadoop and other open source communities, Doug. There was no discussion on those issues that I got to witness at Google I/O. The thing I see is Google using its data handling expertise to build a competitive cloud service, let the chips fall where they may.
D. Henschen
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D. Henschen,
User Rank: Author
6/27/2014 | 11:38:02 AM
Dataflow implications for Hadoop community?
Charlie, this Dataflow announcement would seem to have huge implications for the Hadoop community, given that that platform was inspired by Google's technologies and white papers. With the introduction of YARN, the Hadoop community, too, has been moving away from MapReduce, but what's the Hadoop world's equivalent of Dataflow? Was anybody drawing parallels/similarities to Apache Spark or Apache Storm, for example?
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