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Summarization Patterns - Intro to Hadoop and MapReduce

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    The next design patterns we're going to discuss, are
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    summarization patterns. And, these are patterns that give you, some
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    quick easy high level understanding of your data. And we're
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    going to make a distinction here. We're going to talk about making
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    what's called an inverted index. And this is very similar
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    to the index you'd find in a back of a
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    book, or the indexing that Google does when it crawls
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    the web. And, we're also going to talk about numerical summarizations.
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    And, these are things like finding counts, how many of a certain record type, or
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    min and max. And min and max of course, can be used to calculate first
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    or last. Or calculate statistics like, mean
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    and median, and basically any other high level
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    numerical value that you can use to summarize
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    your data set. In this section of summarization
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    patterns, we'll also talk about some
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    interesting additional [INAUDIBLE] functionality, something that
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    can exist between [INAUDIBLE] reducers, known
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    as combiners. So, let's keep going.
Tytuł:
Summarization Patterns - Intro to Hadoop and MapReduce
Opis:

07-06 Summarization Patterns

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Video Language:
English
Team:
Udacity
Projekt:
ud617 - Intro to Hadoop and Mapreduce
Duration:
01:05

English subtitles

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