38 Cummulative sales - PySpark Interview Question | Running Total sales

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  • Опубликовано: 17 окт 2024
  • #pyspark #interviewquestions #interview #pysparkinterview #dataengineer #aws #databricks #python
    Cummulative sales - PySpark Interview Question
    Cummulative sales Interview Question using pyspark
    Cummulative sales Interview Question using spark sql
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    dataset
    data = [ ['2024-01-01',20000], ['2024-01-02',10000],[ '2024-01-03',150000], ['2024-01-04',100000], ['2024-01-05',210000]]
    #define column names
    columns = ['date', 'sales']
    #create dataframe using data and column names
    df = spark.createDataFrame(data, columns)
    display(df)
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Комментарии • 6

  • @manikandanpanneer1650
    @manikandanpanneer1650 Месяц назад +1

    Thanks 🙏

  • @mohammedak-m8k
    @mohammedak-m8k 13 дней назад +1

    make one video on when to import sql function sql window function and sql types on which scenario based

  • @Anna_Tamil
    @Anna_Tamil Месяц назад +1

    Bro please make a video for aws step function bro

  • @ABQ06
    @ABQ06 Месяц назад +1

    Hi manish
    Can u make a video on facts and dimensional tables
    How we load data(full and incremental loading) based on those tables
    Especially SCD Type scenario
    By using azure adf

    • @learnbydoingit
      @learnbydoingit  Месяц назад

      Sure , few SCD video already in the channel

    • @ABQ06
      @ABQ06 Месяц назад

      @@learnbydoingit yah I have seen even I purchased ur udemy courses long back..petty straightforward and good
      .. but I'm looking for fact & dimensional tables ...how can we find out those in realtime
      And after finding how can we decide which one we need to load full and which is delta(incrementally) based on table data
      I'm totally getting confused by how to combine those three topics
      1.Fact and dimensional
      2.Full load and incremental (delta)load
      And 3. SCD`s implementation