add more db views

queries.R

@@ -21,7 +21,7 @@ con <- dbConnect(
   password = config$db_password
 )
 
-# lazy load DB tables
+# DB TABLES
 
 econ.normalized_landfalls <- tbl(con, I("econ.normalized_landfalls"))
 econ.storm_base_loss <- tbl(con, I("econ.storm_base_loss"))
@@ -43,8 +43,16 @@ metrics.pop_and_housing <- tbl(con, I("metrics.pop_and_housing"))
 
 public.counties <- tbl(con, I("public.counties"))
 
+# DB VIEWS
+view.all_normalized_losses <- tbl(con, "all_normalized_losses")
+view.hurdat_track <- tbl(con, "hurdat_track")
+view.all_loss_storms <- tbl(con, "all_loss_storms")
+view.all_loss_landfalls <- tbl(con, "all_loss_landfalls")
+view.yearly_normalized_losses <- tbl(con, "yearly_normalized_losses")
+view.county_population_housing <- tbl(con, "county_population_housing")
+
 # test storm
-test_storm <- list(
+storm <- list(
   storm_basin = "AL",
   storm_year = 2005,
   storm_name = "KATRINA",
@@ -66,35 +74,32 @@ split_full_lf_id <- function(full_lf_id) {
 
 # returns a list of loss storms we have data on
 get_all_loss_storms <- function() {
-  query <- "SELECT * FROM all_loss_storms"
+  query <- view.all_loss_storms
   
-  result <- dbGetQuery(con, query)
+  result <- query %>% collect()
   
   return(result)
 }
 
 # returns a list of latest normalized losses
 get_latest_aggregate_losses <- function() {
-  query <- "SELECT * FROM all_normalized_losses"
+  query <- view.all_normalized_losses
   
-  result <- dbGetQuery(con, query)
+  result <- query %>% collect()
   
   return(result)
 }
 
 # returns unique lf ids for a storm
 get_unique_lf_ids <- function(storm) {
-  query <- econ.storm_base_loss %>% 
+  query <- view.all_loss_landfalls %>% 
     filter(
       storm_basin == storm$storm_basin,
       storm_year == storm$storm_year,
       storm_name == storm$storm_name
     ) %>% 
-    mutate(
-      full_lf_id = paste0(lf_type, lf_id)
-    ) %>% 
     distinct(
-      full_lf_id, 
+      full_lf_id,
       .keep_all = T
     ) %>% 
     arrange(
@@ -113,7 +118,7 @@ get_unique_lf_ids <- function(storm) {
 get_normalized_cost_index <- function(storm, full_lf_id) {
   lf_id_parts <- split_full_lf_id(full_lf_id)
   
-  query <- econ.normalized_landfalls %>% 
+  query <- view.yearly_normalized_losses %>% 
     filter(
       storm_basin == storm$storm_basin,
       storm_year == storm$storm_year,
@@ -121,28 +126,9 @@ get_normalized_cost_index <- function(storm, full_lf_id) {
       lf_type == lf_id_parts$lf_type,
       lf_id == lf_id_parts$lf_id
     ) %>% 
-    left_join(econ.storm_base_loss %>% 
-                filter(!is.na(base_loss)) %>% 
-                mutate(
-                  ncei_priority = case_when(
-                    str_like(base_loss_source, "%ncei%") ~ 1,
-                    str_like(base_loss_source, "%mwr%") ~ 2,
-                    TRUE ~ 3
-                  )
-                ) %>% 
-                group_by(storm_basin, storm_year, storm_name, lf_type, lf_id) %>% 
-                slice_min(ncei_priority, n = 1, with_ties = F) %>% 
-                ungroup(),
-              by = c("storm_basin", "storm_year", "storm_name", "lf_type", "lf_id")) %>% 
-      mutate(
-        mmh_index = (gdp_deflator * rwhu * affected_housing),
-        mmp_index = (gdp_deflator * rwpc * affected_population),
-        mmh = (base_loss * mmh_index),
-        mmp = (base_loss * mmp_index)
-      ) %>% 
-      select(
-        normalization_year, mmh, mmp
-      )
+    select(
+      normalization_year, mmh, mmp
+    )
   
   result <- query %>% collect()
   
@@ -151,19 +137,15 @@ get_normalized_cost_index <- function(storm, full_lf_id) {
 
 # returns landfalls and data at landfall from HURDAT
 get_hurdat_landfalls <- function(storm) {
-  query <- hurdat.best_track %>% 
+  query <- view.hurdat_track %>% 
     filter(
       storm_basin == storm$storm_basin,
       storm_year == storm$storm_year,
       storm_name == storm$storm_name,
       record_identifier == "L"
     ) %>% 
-    mutate(
-      lon = sql("ST_X(ST_Transform(location::geometry, 4326))"),
-      lat = sql("ST_Y(ST_Transform(location::geometry, 4326))")
-    ) %>% 
     select(
-      datetime,
+      datetime, 
       lon,
       lat,
       rmw,
@@ -187,17 +169,12 @@ get_hurdat_landfalls <- function(storm) {
 
 # returns storm track from HURDAT
 get_hurdat_track <- function(storm) {
-  query <- hurdat.best_track %>% 
+  query <- view.hurdat_track %>% 
     filter(
       storm_basin == storm$storm_basin,
       storm_year == storm$storm_year,
       storm_name == storm$storm_name
-    ) %>% 
-    mutate(
-      lon = sql("ST_X(ST_Transform(location::geometry, 4326))"),
-      lat = sql("ST_Y(ST_Transform(location::geometry, 4326))"),
-      rmw_meters = (rmw * 1852) # convert nautical miles to meters
-    ) %>% 
+    ) %>%
     select(
       datetime,
       lon,
@@ -281,56 +258,4 @@ get_normalized_metric_growth <- function(storm, full_lf_id) {
   result <- query %>% collect()
   
   return(result)
-}
-
-async_db_query <- function(query_func, ...) {
-  args <- list(...)
-  
-  mirai_call <- mirai({
-    linuxdir <- "/home/dylan/Personal/Projects/Hurricane Normalization/"
-    macdir <- "~/Desktop/Personal/Projects/Hurricane Normalization/"
-    #baseDir <- macdir
-    baseDir <- linuxdir
-    
-    config <- config::get(file = paste0(baseDir, "R/dataScripts/restructured/app/config.yml"))
-    
-    source(file = paste0(baseDir, "R/dataScripts/restructured/app/queries.R"))
-    
-    if(length(args) == 0) {
-      query_func()
-    }else{
-      do.call(query_func, args)
-    }
-  },
-  environment()
-  )
-  
-  return(mirai_call)
-}
-
-# test functions
-
-#storm <- list(storm_basin = "AL", storm_name = "KATRINA", storm_year = 2005)
-#full_lf_id <- "LF1"
-
-#a <- get_all_loss_storms()
-
-#b <- get_latest_aggregate_losses()
-
-#c <- get_unique_lf_ids(storm)
-
-#d <- get_normalized_cost_index(storm, full_lf_id)
-
-#e <- get_hurdat_landfalls(storm)
-
-#f <- get_hurdat_track(storm)
-
-#g <- get_normalized_metric_growth(storm, full_lf_id)
-#g_2 <- g %>% 
-#  st_as_sf(wkt = "geom_wkt")
-
-
-
-
-
-
+}