Fetching large json data results in OutOfMemoryError
Nadie ha tomado este issue todavía.
- Lenguaje dominante
- C++
- Estrellas
- 127k
- Forks
- 25.3k
- Merge medio
- 1 d 23 h
- PR fusionados (30 d)
- 4
Descripción
Description
Using fetch to get several Megabytes (currently happens for me at around 80Mb) of JSON data causes Android to panic and throw an OutOfMemoryError. This is due to the fact that the whole response is being read as bytes, quickly filling up the heap.
Stacktrace:
09-01 21:32:21.035 5480 5555 E AndroidRuntime: java.lang.OutOfMemoryError: Failed to allocate a 98836368 byte allocation with 25165824 free bytes and 88MB until OOM, target footprint 133385952, growth limit 201326592
09-01 21:32:21.035 5480 5555 E AndroidRuntime: at okio.Buffer.readByteArray(Buffer.kt:1429)
09-01 21:32:21.035 5480 5555 E AndroidRuntime: at okio.Buffer.readByteArray(Buffer.kt:1424)
09-01 21:32:21.035 5480 5555 E AndroidRuntime: at okio.RealBufferedSource.readByteArray(RealBufferedSource.kt:238)
09-01 21:32:21.035 5480 5555 E AndroidRuntime: at okhttp3.ResponseBody.bytes(ResponseBody.kt:124)
09-01 21:32:21.035 5480 5555 E AndroidRuntime: at com.facebook.react.modules.blob.BlobModule$4.toResponseData(BlobModule.java:134)
09-01 21:32:21.035 5480 5555 E AndroidRuntime: at com.facebook.react.modules.network.NetworkingModule$2.onResponse(NetworkingModule.java:512)
09-01 21:32:21.035 5480 5555 E AndroidRuntime: at okhttp3.internal.connection.RealCall$AsyncCall.run(RealCall.kt:519)
09-01 21:32:21.035 5480 5555 E AndroidRuntime: at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1167)
09-01 21:32:21.035 5480 5555 E AndroidRuntime: at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:641)
09-01 21:32:21.035 5480 5555 E AndroidRuntime: at java.lang.Thread.run(Thread.java:923)
React Native version:
System:
OS: Linux 5.13 Solus 4.3
CPU: (8) x64 Intel(R) Core(TM) i7-7700HQ CPU @ 2.80GHz
Memory: 1.39 GB / 15.52 GB
Shell: 5.1.8 - /bin/bash
Binaries:
Node: 14.17.5 - /usr/bin/node
Yarn: 1.22.10 - /usr/bin/yarn
npm: 6.14.14 - /usr/bin/npm
Watchman: Not Found
SDKs:
Android SDK: Not Found
IDEs:
Android Studio: Not Found
Languages:
Java: 1.8.0_302-solus - /usr/lib64/openjdk-8/bin/javac
npmPackages:
@react-native-community/cli: Not Found
react: 17.0.2 => 17.0.2
react-native: 0.65.1 => 0.65.1
npmGlobalPackages:
*react-native*: Not Found
Steps To Reproduce
I created a test repository that shows the aforementioned behaviour. It also includes a 100Mb JSON file for testing, that you can serve locally or access via GitHub directly.
Steps are as follows
- Tap on the load data button
- Wait for the app to crash
Expected Results
Getting an out of memory error shouldn't really happen with this size of data in my opinion. Sure 100Mb sounds a lot at first, but in enterprise-grade apps this is probably a common scenario. In any case I think there should be a possibility to dynamically switch to streaming the response since okhttp offers bytestream and charstream as well. I'm not that well versed in Java but it would probably help reduce all of the 150Mb landing on the heap at once?
Snack, code example, screenshot, or link to a repository:
Guía de contribución
Primeros pasos
- Lee el issue completo y luego la guía de contribución del proyecto.
- Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
- Haz un fork del repositorio y trabaja en una rama.
- Abre un pull request que haga referencia al número del issue.
Línea de trabajo
Comienza con el manejo de respuestas de Android mostrado en BlobModule.java y NetworkingModule.java; después, ejecuta el repositorio ReactNativeFetchRepro enlazado con su archivo data.json de 100MB. Compara la ruta actual de fetch con las referencias a OkHttp ResponseBody byteStream y charStream en el issue; se considera terminado cuando las respuestas JSON grandes ya no provocan el OutOfMemoryError reportado.
Escrito por el modelo de indexación a partir del texto del issue.
Evaluación
- Stack tecnológico
- android, java, react-native
- Área
- mobile, networking
- Tipo de issue
- Error
- Dificultad
- 4/5
- Tiempo estimado
- 3-5 días
- Estado de actividad
- Estancado
- Claridad
- Bastante claro
- Aptitud para principiantes
- 42/100