[GitHub] [arrow] cgostic commented on issue #15056: [R][R Shiny] Deployed/published Rshiny app using arrow to query an AWS-hosted dataset causes intermittent "stack imbalance", "segfault", "memory not mapped" errors.

[GitBox <gi...@apache.org>]

cgostic commented on issue #15056:
URL: https://github.com/apache/arrow/issues/15056#issuecomment-1363055765

   @boshek Thanks so much for the reply! I appreciate your time!
   
   I've worked out a reprex I can share that still yields the error. 
   
   **Attached Materials:**
   
   - data subset -- attached as a zipped .csv
   - renv.lockfile -- (uploaded as renv_lock_txt.txt) has been converted to a text file for upload. You'll need to change the file format to use it.
   - Error logs for RStudio Connect and shinyapps.io.
   
   
   Steps to recreate:
   
   **1. Write ozone data to a private AWS bucket**
   
   ```
   library(arrow)
   library(aws.s3)
   
   # Using attached dataset
   ozone <- read.csv(unz('ozone_data_2022.zip', 'ozone_data_2022.csv'))
   
   bname <- '<your-bucket>'
   db_uri <- paste0('s3://',bname)
   
   write_dataset(ozone, 
                 path = db_uri, 
                 format = 'arrow', 
                 partitioning = c('aqs_sitecode', 'sample_duration', 
                                  'parameter', 'poc'))
   ```
   
   **2. Deploy app**
   
   This app should run fine locally. 
   
   After deployment ( to shinyapps.io or RStudio Connect) I've observed the following:
     
   ```
   # See attached lockfile for package versions
   library(shiny)
   library(dplyr)
   library(ggplot2)
   library(htmltools)
   library(arrow)
   library(aws.s3)
   
   bname <- 'bucket'
   db_uri <- paste0('s3://',bname)
   ds <- arrow::open_dataset(db_uri, format = 'arrow', unify_schemas = F)
   
   ui <- fluidPage(
     fluidRow(column(3,
                     selectInput('sitecode',
                                 label = 'Select Site',
                                 choices = unique(metadata$aqs_sitecode),
                                 selected = NULL)),
              column(2,
                     div(style = 'padding-top:26px',
                         actionButton('go', 'Create Plot', width = '100%')))),
     fluidRow(plotOutput('TS')),
     fluidRow(textOutput('connstr'))
     
   )
   
   server <- function(input, output, session) {
     selected_site <- reactiveValues(sitecode = NULL)
     observeEvent(input$go, {
       selected_site$sitecode <- input$sitecode
     })
     
     plot_data <- reactive({
       req(selected_site$sitecode)
       
       s <- as.integer(selected_site$sitecode)
       
       ds %>%
         filter(aqs_sitecode == s,
                parameter == 'Ozone',
                sample_duration == '1 HOUR',
                poc == 1) %>%
         select(date_time2, sample_measurement) %>%
         collect()
     })
     
     output$TS <- renderPlot({
       req(selected_site$sitecode, 
           is.data.frame(plot_data()))
       
       ggplot(plot_data()) +
         geom_line(aes(date_time2, sample_measurement)) +
         scale_x_datetime() +
         labs(x = 'DateTime', y = 'Ozone in ppb', main = selected_site$sitecode)
     })
     
     log_db <- reactivePoll(30000, session, #reactivePoll inside the server
                            # Check for maximum month
                            checkFunc = function() {
                              r_num <- ds %>%
                                      filter(aqs_sitecode == 500070007,
                                             sample_duration == '24 HOUR',
                                             parameter == 'WD',
                                             poc == 1) %>%
                                      collect() %>%
                                      nrow()
                              print(r_num)
                              return(as.character(r_num))
   
                            },
                            valueFunc = function() {
                              print('pinged')
                              return(" ")
                            }
     )
   
     output$connstr <- renderText(log_db())
   }
   
   shinyApp(ui = ui, server = server)
   
   ```
   
   **3. In-app workflow to create error**
   
   - Constant update of the plot every few seconds (select new sitecode, click "Create Plot") **will not yield an error.**
   - Letting the app site idle for **~1 min and 30 seconds** will yield an error when the plot is updated after this wait-time, even with the reactivepoll collecting from the dataset every 30 seconds 
   
   [shinyappsio_logs.txt](https://github.com/apache/arrow/files/10288428/shinyappsio_logs.txt)
   
   [rstudio_connect.log](https://github.com/apache/arrow/files/10288468/rstudio_connect.log)
   
   [ozone_data_2022.zip](https://github.com/apache/arrow/files/10288323/ozone_data_2022.zip)
   
   [renv_lock_txt.txt](https://github.com/apache/arrow/files/10288492/renv_lock_txt.txt)
   
   


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