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R Shiny - cache big dataframe

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I'm quite new to Shiny, so my apologizes if my question is an easy one. I tried to check on google and stackoverflow but couldn't locate a simple and helpful answer so far. What's my goal/issue: I'm coding a Shiny page that displays a table with hundreds of thousands of rows. Data is sourced from different databases, manipulated, cleaned, and displayed to all the users upon request. Problem 1: in order to load all the data, the script takes almost 5minutes Problem 2: if at 8:00am user1 requests this data and at 8:05am user2 requests the same data, two different queries are launched and also two different spaces in memory are used to show exactly the same data to two different users. So the question is: shall I use a cache system to enhance this process? if not, what else shall I use? I found a lot of official Shiny documentation on caching plots but nothing related to caching data (and I found this quite surprising). Other useful information: data in cache should be deleted every evening around 10pm since new data will be available the next day / early morning.

Code:

ui <- dashboardPage(  # https://rstudio.github.io/shinydashboard/structure.html
    title = "Dashboard",  
    dashboardHeader(title = "Angelo's Board"),
    dashboardSidebar(   # inside here everything that is displayed on the left hand side
      includeCSS("www/styles.css"),    

      sidebarMenu(      

        menuItem('menu 1', tabName = "menu1", icon = icon("th"),
                 menuItem('Data 1', tabName = 'tab_data1'))

      )),


    dashboardBody( 

      tabItems(

        tabItem(tabName = 'tab_data1')),
      h3("Page with big table"),
      fluidRow(dataTableOutput("main_table"))
    ))


  server <- function(input, output, session) {

    output$main_tabl <- renderDataTable({ 
      df <- data.frame(names = c("Mark","George","Mary"), age = c(30,40,35))
    })

  }

  cat("\nLaunching   'shinyApp' ....")
  shinyApp(ui, server)

Resources I used to check for potential solution:

Any help would be much appreciated. Thanks


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