Is it possible to parallelize all the operations with in separate code chunks. For example, I have 3 code chunks that query separate tables in a database. I then perform some data cleaning. Is it possible to have each code chunk be broken into its own process to be ran on a core at the same time as other code chunks? Essentially have process 1+2+3 going at the same time on separate cores instead of sequentially.

Process 1

q_flighthistory <- "SELECT *
                    FROM CT_FLIGHT_HISTORY;" # WHERE FLIGHT_DATE BETWEEN '2024-07-01' AND '2024-07-02';"

dbGetQuery(q_flighthistory, "view_flighthistory")


# Unique flight history for that date
clean_flighthistory <- view_flighthistory %>%
  filter(SEGMENT_STATUS == "A") %>% 
  select(c(2:10), (12:13), (55:59),EQUIPMENT) %>% 
  #filter(!duplicated(UNIQUE_ID)) %>% 
  rename(SCHED_DEPARTURE_TIME = SCHED_DEPARTURE_TIME_RAW)%>% 
  mutate(updated_dt = paste(UPDATE_DATE, UPDATE_TIME, sep= " ")) %>% 
  group_by(FLIGHT_NO, FLIGHT_DATE, DEPARTING_CITY, ARRIVAL_CITY, SCHED_DEPARTURE_TIME) %>% 
  filter(updated_dt == max(updated_dt)) %>% 
  mutate(temp_id = cur_group_id()) %>% 
  filter(!duplicated(temp_id)) %>% 
  select(!c(12:16)) %>% 
  select(!c(5:7)) %>% 
  select(!c(10:11))

rm(view_flighthistory)
gc()

Process 2

q_flightleg <- "SELECT *
                FROM CT_FLIGHT_LEG;" # WHERE PAIRING_DATE BETWEEN '2024-06-28' AND '2024-07-02';"

dbGetQuery(q_flightleg, "view_flightleg")


flight_leg_join <-  view_flightleg %>% 
  mutate(updated_dt = paste(UPDATE_DATE, UPDATE_TIME, sep= " "),
         shed_dept_hour = hour(SCHED_DEPARTURE_TIME),
         DEADHEAD = if_else(is.na(DEADHEAD), "C", DEADHEAD)) %>%
  relocate(updated_dt, .after=PAIRING_NO) %>%
  group_by(PAIRING_POSITION,
           DEPARTING_CITY,
           ARRIVAL_CITY,
           SCHED_DEPARTURE_DATE,
           shed_dept_hour,
           PAIRING_NO,
           PAIRING_DATE) %>% 
  filter(DEADHEAD == "C",
         updated_dt == max(updated_dt)) %>% 
  mutate(temp_id = cur_group_id(), .after = CREW_INDICATOR) %>%
  filter(!duplicated(temp_id)) %>%
  ungroup() %>% 
  select(PAIRING_NO, PAIRING_DATE, FLIGHT_NO, SCHED_DEPARTURE_DATE, SCHED_ARRIVAL_DATE, DEPARTING_CITY, ARRIVAL_CITY,
        PAIRING_POSITION)

rm(view_flightleg)
gc()

Process 3

# MasterPairing Query
q_masterpairing <- "SELECT *
                    FROM CT_MASTER_PAIRING;" # WHERE PAIRING_DATE BETWEEN '2024-06-28' AND '2024-07-02';"
dbGetQuery(q_masterpairing, "view_masterpairing")


join_masterpairing <- view_masterpairing %>% 
    mutate(updated_dt = paste(UPDATE_DATE, UPDATE_TIME, sep = " ")) %>% 
    relocate(updated_dt, .after=PAIRING_NO) %>%
    group_by(PAIRING_DATE, CREW_ID) %>% 
    filter(updated_dt == max(updated_dt),
           PAIRING_STATUS == "A") %>% 
  select(PAIRING_POSITION, CREW_ID, PAIRING_NO, PAIRING_DATE, CREW_INDICATOR, updated_dt) %>% 
  ungroup()
  
rm(view_masterpairing)
gc()