есть способы оптимизировать следующее, но она не может быть необходимо в вашем случае:
library(jsonlite)
library(dplyr)
df <- data_frame()
jsonlite::stream_in(file("/tmp/apps.json"), function(x) { df <<- bind_rows(df, filter(x, app=="15b")) })
Я сделал файл, который выглядит следующим образом:
{"app":"15c","device_carrier":"Verizon Wireless"}
{"app":"15b","device_carrier":"Verizon Wireless"}
{"app":"15a","device_carrier":"Verizon Wireless"}
{"app":"15c","device_carrier":"Verizon Wireless"}
{"app":"15b","device_carrier":"Verizon Wireless"}
{"app":"15a","device_carrier":"Verizon Wireless"}
{"app":"15c","device_carrier":"Verizon Wireless"}
{"app":"15b","device_carrier":"Verizon Wireless"}
{"app":"15a","device_carrier":"Verizon Wireless"}
{"app":"15c","device_carrier":"Verizon Wireless"}
{"app":"15b","device_carrier":"Verizon Wireless"}
{"app":"15a","device_carrier":"Verizon Wireless"}
{"app":"15c","device_carrier":"Verizon Wireless"}
{"app":"15b","device_carrier":"Verizon Wireless"}
{"app":"15a","device_carrier":"Verizon Wireless"}
{"app":"15c","device_carrier":"Verizon Wireless"}
{"app":"15b","device_carrier":"Verizon Wireless"}
{"app":"15a","device_carrier":"Verizon Wireless"}
{"app":"15c","device_carrier":"Verizon Wireless"}
{"app":"15b","device_carrier":"Verizon Wireless"}
{"app":"15a","device_carrier":"Verizon Wireless"}
{"app":"15c","device_carrier":"Verizon Wireless"}
{"app":"15b","device_carrier":"Verizon Wireless"}
{"app":"15a","device_carrier":"Verizon Wireless"}
{"app":"15c","device_carrier":"Verizon Wireless"}
{"app":"15b","device_carrier":"Verizon Wireless"}
{"app":"15a","device_carrier":"Verizon Wireless"}
{"app":"15c","device_carrier":"Verizon Wireless"}
{"app":"15b","device_carrier":"Verizon Wireless"}
{"app":"15a","device_carrier":"Verizon Wireless"}
{"app":"15c","device_carrier":"Verizon Wireless"}
{"app":"15b","device_carrier":"Verizon Wireless"}
{"app":"15a","device_carrier":"Verizon Wireless"}
{"app":"15c","device_carrier":"Verizon Wireless"}
{"app":"15b","device_carrier":"Verizon Wireless"}
{"app":"15a","device_carrier":"Verizon Wireless"}
{"app":"15c","device_carrier":"Verizon Wireless"}
{"app":"15b","device_carrier":"Verizon Wireless"}
{"app":"15a","device_carrier":"Verizon Wireless"}
Выполнить этот код, и вы получите:
df
## # A tibble: 13 × 2
## app device_carrier
## <chr> <chr>
## 1 15b Verizon Wireless
## 2 15b Verizon Wireless
## 3 15b Verizon Wireless
## 4 15b Verizon Wireless
## 5 15b Verizon Wireless
## 6 15b Verizon Wireless
## 7 15b Verizon Wireless
## 8 15b Verizon Wireless
## 9 15b Verizon Wireless
## 10 15b Verizon Wireless
## 11 15b Verizon Wireless
## 12 15b Verizon Wireless
## 13 15b Verizon Wireless
Hi Smasell, вы можете предоставить пример JSON вы хотите, чтобы разобрать, желаемых результатов, и что вы пробовали до сих пор? –
Самый надежный способ - разобрать все, а затем отфильтровать список. Фильтрация перед синтаксическим анализом гораздо более утомительна, так как форматирование JSON может потенциально различаться. – MrMobster
@MrMobster Да, теперь я это! Я отредактировал вопрос! Возможно ли без разбора всего файла? – Smasell