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This Meetup is cancelled

Using Hive for ETL

  • inome Inc.

    500 108th AVE NE, 16th Floor, Bellevue, WA (map)

    47.615040 -122.196167

  • This talk will be given by Ryan Harris. More details will be provided as the date approaches.

    Big Data Bellevue Meetup takes place at inome headquarters in Bellevue. inome provides the only centralized service for delivering comprehensive information about people, places, organizations, and their connection to each other. Our state-of-the-art big data technology platform is utilized across a wide range of industries to implement specific solutions.

    At each meetup, we invite an industry leader in Big Data to give a presentation followed by a lively discussion on big data technology and its impact on business world. Past speakers include researchers from the University of Washington, as well as senior members of various companies, such as Microsoft, Amazon, eBay, and inome.

    Bring your questions, ideas, suggestions, and afterwards join us for big pizza!

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  • Hakan K.

    Cancellation Notice for December Meetup

    Dear All,

    It has been a great year for the Big Data Bellevue meetup group. We organized 11 meetups and had many great speakers from both academia and industry. We had 60 attendees on average. We would like to thank you all for being part of this group. We are looking for your suggestions and comments for our future events.

    Due to the upcoming holiday season, we are canceling this month's meetup. We will have our next meetup in January 2014. We will again have great speakers and hope to see all of you in our upcoming meetups. Please stay tuned!!!

    Merry Christmas and Happy New Year.

    December 8, 2013

  • Richard A.

    Why is Hive better for ETL than other tools available?

    November 16, 2013

    • Ryan H.

      Hive isn't necessarily "better" than other tools, but in our case the end-goal was to have all data stored/normalized/organi­zed into Hive managed tables. Therefore it was simplest to use a single tool to parse and transform the data in essentially one step. Using the Hive transform function we allow users to do the actual transformation work in a scripting/programming language of their choice (perl, ruby, python, java, awk, sed, bash, etc). Hive serves as the framework for standardizing the ETL process. Pig is certainly more flexible overall than Hive, but until the recent HCatalog integration, Hive was the only tool out there with a reasonable meta-data store, which is one of the reasons we chose to store data in Hive.

      November 16, 2013

  • Ryan H.

    Unfortunately I've realized that I have a conflict on Dec 18th and will therefore not be able to present at this particular meeting, but I'd be up for a later date if there is interest.

    November 16, 2013

  • Gurmit S.


    November 15, 2013


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