mapreduce tutorial | what is mapreduce | hadoop tutorial | mapreduce with example | Trendytech

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Пікірлер: 9

  • @sumitmittal07
    @sumitmittal07 Жыл бұрын

    Checkout the Big Data course details here: trendytech.in/?referrer=youtube_bd3

  • @uma_kumar2396
    @uma_kumar23964 жыл бұрын

    Very well explained sir.... Clearly understood how a mapreduce works.... Thank u

  • @sumitmittal07

    @sumitmittal07

    4 жыл бұрын

    Glad to hear that

  • @subbuk8889
    @subbuk88893 жыл бұрын

    awesome explanation sir...

  • @1234abcd2139
    @1234abcd21392 жыл бұрын

    thanks a lot sir. However one question, when you have 1 separate node for reducer and 4 nodes for mapper, is not the cluster should be called 5 node cluster instead of 4 node cluster ? And in case reducer is one among the 4 nodes, then how overhead of having reducer on one of the existing mapper node gets handled by Map- Reduce or Hadoop ?

  • @shivarajhalageri2513
    @shivarajhalageri2513 Жыл бұрын

    Loved the session 🙌🪄

  • @kameswari11
    @kameswari11 Жыл бұрын

    is bigdata is in demand now?

  • @tonystarc9567
    @tonystarc9567 Жыл бұрын

    How come data from Map phase fit into single reducer machine? There should be 4 reducers right? It would have been better if you would have taken this example with multiple reducer machines. Now it is clear until the map phase but Reducer is still confusing. As if there are multiple reducers and let's say data is skewed then let's say the key value pair ("Hello",1) occurs so many times that it does not fit in one Reducer machine how will be take care of that?

  • @maabkhan70

    @maabkhan70

    10 ай бұрын

    @tonystarc9567 My understanding is following - - we can have multiple reducer machine and that depends on following - 1- no of available cores 2- shuffled data partition 3- key on which data is partitioned. If data is skewed and we have only one key then there will be only partition of data , and it will be processed sequentially by one core only. The tasks will be queued up on single core and will be processed one after the other.