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In this video we are discussing join pattern overview
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We know that in case of RDBMS we can join two tables. But in case of big data, in case of huge data set, joining is not a very easy thing and
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it is a very costly affairs. And also here the MapReduce takes key value pair one at a time
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So these are the several constraints are there. So that's why we require some separate technique to do the joining in case of big data
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So, let us discuss this join pattern overview. So, what is join pattern
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So in SQL, the joining of two tables can be done easily by using some commands and queries
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And there will be taking some attributes as common between the tables and against that we
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can do the joining. But in MapReduce task, it is complex. Why it is complex
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Because it uses a single key value pair at a time. So as the joining is not simple
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we need to follow some techniques to join records in our map reduce applications so different
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types of join pattern types so let us discuss what are the different types are there so in
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this section we shall discuss this four different joint pattern so first one is the reduce
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site join next one is the replicated join composite join and condition product we shall be
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discussing all this with some sample examples and practice demonstration in the next videos please watch all the videos for their
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implementation and running thanks for watching this video
