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Structural Patterns - Intro to Hadoop and MapReduce

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    Finally, we're going to talk about structural patterns.
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    And this is a very pragmatic pattern to discuss
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    honestly because it's a pattern you use if you're
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    ever migrating data, from relational data base management systems,
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    to a Hadoop system. And what you do
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    with this pattern, is taking advantage of the fact
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    that Hadoop, doesn't care what format your data is
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    in, which means you can take advantage of hierarchical
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    data, which will allow you to avoid doing
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    live joins and several data sets at the time
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    of analysis. So if you know a kind of
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    information you're going to want to get later you can
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    save a lot of time by reformatting your data. Now in order to
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    use this pattern, your data sources must be linked by some
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    foreign keys, and the data must be structured and row based,
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    and in fact this pattern in the book of [INAUDIBLE]
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    design pattern is actually they refer to as structured hierarchical pattern.
タイトル:
Structural Patterns - Intro to Hadoop and MapReduce
概説:

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Video Language:
English
Team:
Udacity
プロジェクト:
ud617 - Intro to Hadoop and Mapreduce
Duration:
0:59

English subtitles

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