update queries to use pool, new indices, and materialized views for performance gain

app/global.R

@@ -47,7 +47,7 @@ all_conus_landfalls <- get_all_conus_landfalls()
 all_lf_type_storms <- get_all_lf_type_landfalls()
 
 onStop(function() {
-  disconnect_db()
+  poolClose(con)
 })
 
 storm_selection <- reactiveValues(

app/queries.R

@@ -4,12 +4,13 @@ library(tidyverse)
 library(dplyr)
 library(DBI)
 library(xts)
+library(pool)
 
 
 config <- config::get(file = "config.yml")
 
 # SUPABASE CON
-con <- dbConnect(
+con <- dbPool(
   RPostgres::Postgres(),
   host = config$db_host,
   port = config$db_port,
@@ -18,6 +19,14 @@ con <- dbConnect(
   password = config$db_password
 )
 
+#con <- dbConnect(
+#  RPostgres::Postgres(),
+#  host = config$db_host,
+#  port = config$db_port,
+#  dbname = config$db_dbname,
+#  user = config$db_user,
+#  password = config$db_password
+#)
 
 #qry <- econ.storm_base_loss %>%
 #  left_join(view.hurdat_track, by = c("storm_basin", "storm_year", "storm_name"))
@@ -41,11 +50,11 @@ con <- dbConnect(
 #  lf_id = 1
 #)
 
-agnes <- list(
-  storm_basin = "AL",
-  storm_year = 1972,
-  storm_name = "AGNES"
-)
+#agnes <- list(
+#  storm_basin = "AL",
+#  storm_year = 1972,
+#  storm_name = "AGNES"
+#)
 
 # helper functions
 
@@ -73,14 +82,14 @@ get_yearly_economics <- function(yr) {
   return(result)
 }
 
-get_latest_normalization_year <- function() {
-  query <- tbl(con, "all_yearly_normalized_losses") %>%
-    summarize(latest_year = max(normalization_year))
-
-  result <- query %>% collect()
-
-  return(result)
-}
+#get_latest_normalization_year <- function() {
+#  query <- tbl(con, "all_yearly_normalized_losses") %>%
+#    summarize(latest_year = max(normalization_year))
+#
+#  result <- query %>% collect()
+#
+#  return(result)
+#}
 
 get_storm_data_coverage <- function() {
   query <- tbl(con, "storm_data_coverage")
@@ -366,11 +375,6 @@ get_normalized_metric_growth <- function(storm, full_lf_id) {
         tbl(con, I("public.counties")),
         by = c("state_fips" = "statefp", "county_fips" = "countyfp")
       ) %>%
-      mutate(
-        geom_wkt = sql(
-          "ST_AsText(ST_SimplifyPreserveTopology(ST_Transform(geom, 4326), .001))"
-        )
-      ) %>%
       select(
         state_fips,
         county_fips,
@@ -416,7 +420,7 @@ get_normalized_metric_growth <- function(storm, full_lf_id) {
         state_fips
       )
 
-    baseline_metrics <- tbl(con, "yearly_state_metrics") %>%
+    baseline_metrics <- tbl(con, I("metrics.yearly_state_metrics")) %>%
       filter(year == storm$storm_year) %>%
       inner_join(affected_state, by = "state_fips") %>%
       select(
@@ -425,7 +429,7 @@ get_normalized_metric_growth <- function(storm, full_lf_id) {
         baseline_housing = state_housing_units
       )
 
-    normalized_metrics <- tbl(con, "yearly_state_metrics") %>%
+    normalized_metrics <- tbl(con, I("metrics.yearly_state_metrics")) %>%
       filter(
         year >= storm$storm_year
       ) %>%
@@ -452,11 +456,6 @@ get_normalized_metric_growth <- function(storm, full_lf_id) {
           rename(state_fips = statefp),
         by = "state_fips"
       ) %>%
-      mutate(
-        geom_wkt = sql(
-          "ST_AsText(ST_SimplifyPreserveTopology(ST_Transform(wkb_geometry, 4326), .001))"
-        )
-      ) %>%
       select(
         state_fips,
         year,