I have a sales app develpmented in Flex Builder. For use photos by off-line way, i upload a compressed file with all photos to the site and when need i sincronize with my smartphone. In that process is made a download to the dispositive and exist a responsable plugin to descompress the archive and disponibilize it in apropriate folder to later use.
That compressed file has 500MB size - 6700 photos approximately - and in Flex i have no type of problem to do that.
I'm rewriting the app in Flutter, using a archive package, dont getting the same results. In the descompress process i have problem with Out of memory.
Somebody already faced for something like that ?
Is there an best way to do this ?
I already tried other two alternatives:
- To use the Image.network, but, one of requires is work off-line.
- To save all the photos in assets folder, but i think that is not the best alternative, because the app will get bigger
Thank you in advance for.
Follow the error message and the code
code:
unarchiveAndSave()async{
var zippedFile = await initDir();
var bytes = zippedFile.readAsBytesSync();
var archive = ZipDecoder().decodeBytes(bytes);
for (var file in archive) {
var fileName = '$_dir/${file.name}';
if (file.isFile) {
var outFile = File(fileName);
print('File:: ${outFile.path}');
outFile = await outFile.create();
await outFile.writeAsBytes(file.content);
}
}
print('terminei de descompactar os arquivos');
}
Does anyone know what is maximum size to upload file via Azure HDFS Rest API? (https://learn.microsoft.com/en-us/azure/data-lake-store/data-lake-store-data-operations-rest-api).
I found someplace 256MB, some place 32MB, so wondering.
Or similar limits for other SDKs?
I was wrestling with the same problem some months ago and it turned out that the IIS which is in front of ADLS is setting the maxAllowedContentLength with default value of 30000000 bytes (or 28.6Mb). This essentially means that whenever we want to push anything bigger that 30Mb, that request never reaches ADL as IIS throws 404.13 before that. Reference.
As already suggested in the links, ADLS has a driver with a 4-MB buffer, I'm using the .NET SDK myself and following code has served me well
public async Task AddFile(byte[] content, string path)
{
const int fourMb = 4 * 1024 * 1024;
var buffer = new byte[fourMb];
using (var stream = new MemoryStream(content))
{
if (!_adlsFileSystemClient.FileSystem.PathExists(_account, path))
{
_adlsFileSystemClient.FileSystem.Create(_account, path);
}
int bytesToRead;
while ((bytesToRead = stream.Read(buffer, 0, buffer.Length)) > 0)
{
if (bytesToRead < fourMb)
{
Array.Resize(ref buffer, bytesToRead);
}
using (var s = new MemoryStream(buffer))
{
await _adlsFileSystemClient.FileSystem.AppendAsync(_account, path, s);
}
//skipped for brevity
In my tests, I am finding a maximum file size limit somewhere between 28MB and 30MB.
Using the Azure Data Lake Storage REST API, I have had no issues creating files as large as 28MB. However, when I try to create a file that is 30MB, I receive a 404 Not Found error.
The following references align with the file size limit and 404 error I am observing. The references are about the SDK, but it could be that the SDK is also calling the REST API under the covers. My tests are calling the REST API directly.
NotFound error on call to Data Lake Store Create
https://stackoverflow.com/a/41469724/10363
I am kinda confused about:
After downloading an assetbundle at the first time, how Unity knows I have already downloaded it and directly load from cache(disk) at the second time?
Does it use url to mapping to local storage? If in that case, if I update my assetbundle on the server using the same name, at the second time, it will still be loading from cache since the url doesn't change?
Sample code:
UnityEngine.Networking.UnityWebRequest request = UnityEngine.Networking.UnityWebRequest.GetAssetBundle(uri, 0);
yield return request.Send();
//only download at the first time, at the second time, it can be loaded from cache
AssetBundle bundle = DownloadHandlerAssetBundle.GetContent(request);
GameObject cube = bundle.LoadAsset<GameObject>("Cube");
To have caching;
Instead of calling:
UnityEngine.Networking.UnityWebRequest request = UnityEngine.Networking.UnityWebRequest.GetAssetBundle(uri, 0);
You must call GetAssetBundle with a version number:
UnityEngine.Networking.UnityWebRequest request = UnityEngine.Networking.UnityWebRequest.GetAssetBundle(uri, 1, 0);
See documentation here:
https://docs.unity3d.com/ScriptReference/Networking.UnityWebRequest.GetAssetBundle.html
You can also implement this with a call to new DownloadHandlerAssetBundle(string url, uint version, uint crc);. See sample code here:
https://docs.unity3d.com/ScriptReference/Networking.DownloadHandlerAssetBundle-ctor.html
And documentation here:
https://docs.unity3d.com/ScriptReference/Networking.DownloadHandlerAssetBundle-ctor.html
Note that when you use caching, the request.responseCode will no longer be value 200 (success), but will be 0, when the data is retrieved from cache!
I have been trying to save game data using a binary formatter and Application.persistentDataPath on my Tango device. After saving however, the file is nowhere to be found.
Right now the path is reading out as "Storage/emulated/0/Android/data/com.mine.project/files/filename.bin", but as stated above, the path doesn't actually exist anywhere.
Is there another way to save all of this data on the Tango that I have yet to find? If not, is there a way to get these files to show up?
This is the code that I am currently using, minus some debugging functions I use.
string path = Application.persistentDataPath + Path.DirectorySeparatorChar + "file.bin";
BinaryFormatter bf = new BinaryFormatter ();
FileStream file = File.Open (path, FileMode.OpenOrCreate);
bf.Serialize(file, data);
file.Close ();
From what I can tell this isn't throwing any errors, I can even find the file again via the File.Exists() function, but I need to find the file again for access through other programs, and so far it has proven impossible.
Meteor is great but it lacks native supports for traditional file uploading. There are several options to handle file uploading:
From the client, data can be sent using:
Meteor.call('saveFile',data) or collection.insert({file:data})
'POST' form or HTTP.call('POST')
In the server, the file can be saved to:
a mongodb file collection by collection.insert({file:data})
file system in /path/to/dir
mongodb GridFS
What are the pros and cons for these methods and how best to implement them? I am aware that there are also other options such as saving to a third party site and obtain an url.
You can achieve file uploading with Meteor without using any more packages or a third party
Option 1: DDP, saving file to a mongo collection
/*** client.js ***/
// asign a change event into input tag
'change input' : function(event,template){
var file = event.target.files[0]; //assuming 1 file only
if (!file) return;
var reader = new FileReader(); //create a reader according to HTML5 File API
reader.onload = function(event){
var buffer = new Uint8Array(reader.result) // convert to binary
Meteor.call('saveFile', buffer);
}
reader.readAsArrayBuffer(file); //read the file as arraybuffer
}
/*** server.js ***/
Files = new Mongo.Collection('files');
Meteor.methods({
'saveFile': function(buffer){
Files.insert({data:buffer})
}
});
Explanation
First, the file is grabbed from the input using HTML5 File API. A reader is created using new FileReader. The file is read as readAsArrayBuffer. This arraybuffer, if you console.log, returns {} and DDP can't send this over the wire, so it has to be converted to Uint8Array.
When you put this in Meteor.call, Meteor automatically runs EJSON.stringify(Uint8Array) and sends it with DDP. You can check the data in chrome console websocket traffic, you will see a string resembling base64
On the server side, Meteor call EJSON.parse() and converts it back to buffer
Pros
Simple, no hacky way, no extra packages
Stick to the Data on the Wire principle
Cons
More bandwidth: the resulting base64 string is ~ 33% larger than the original file
File size limit: can't send big files (limit ~ 16 MB?)
No caching
No gzip or compression yet
Take up lots of memory if you publish files
Option 2: XHR, post from client to file system
/*** client.js ***/
// asign a change event into input tag
'change input' : function(event,template){
var file = event.target.files[0];
if (!file) return;
var xhr = new XMLHttpRequest();
xhr.open('POST', '/uploadSomeWhere', true);
xhr.onload = function(event){...}
xhr.send(file);
}
/*** server.js ***/
var fs = Npm.require('fs');
//using interal webapp or iron:router
WebApp.connectHandlers.use('/uploadSomeWhere',function(req,res){
//var start = Date.now()
var file = fs.createWriteStream('/path/to/dir/filename');
file.on('error',function(error){...});
file.on('finish',function(){
res.writeHead(...)
res.end(); //end the respone
//console.log('Finish uploading, time taken: ' + Date.now() - start);
});
req.pipe(file); //pipe the request to the file
});
Explanation
The file in the client is grabbed, an XHR object is created and the file is sent via 'POST' to the server.
On the server, the data is piped into an underlying file system. You can additionally determine the filename, perform sanitisation or check if it exists already etc before saving.
Pros
Taking advantage of XHR 2 so you can send arraybuffer, no new FileReader() is needed as compared to option 1
Arraybuffer is less bulky compared to base64 string
No size limit, I sent a file ~ 200 MB in localhost with no problem
File system is faster than mongodb (more of this later in benchmarking below)
Cachable and gzip
Cons
XHR 2 is not available in older browsers, e.g. below IE10, but of course you can implement a traditional post <form> I only used xhr = new XMLHttpRequest(), rather than HTTP.call('POST') because the current HTTP.call in Meteor is not yet able to send arraybuffer (point me if I am wrong).
/path/to/dir/ has to be outside meteor, otherwise writing a file in /public triggers a reload
Option 3: XHR, save to GridFS
/*** client.js ***/
//same as option 2
/*** version A: server.js ***/
var db = MongoInternals.defaultRemoteCollectionDriver().mongo.db;
var GridStore = MongoInternals.NpmModule.GridStore;
WebApp.connectHandlers.use('/uploadSomeWhere',function(req,res){
//var start = Date.now()
var file = new GridStore(db,'filename','w');
file.open(function(error,gs){
file.stream(true); //true will close the file automatically once piping finishes
file.on('error',function(e){...});
file.on('end',function(){
res.end(); //send end respone
//console.log('Finish uploading, time taken: ' + Date.now() - start);
});
req.pipe(file);
});
});
/*** version B: server.js ***/
var db = MongoInternals.defaultRemoteCollectionDriver().mongo.db;
var GridStore = Npm.require('mongodb').GridStore; //also need to add Npm.depends({mongodb:'2.0.13'}) in package.js
WebApp.connectHandlers.use('/uploadSomeWhere',function(req,res){
//var start = Date.now()
var file = new GridStore(db,'filename','w').stream(true); //start the stream
file.on('error',function(e){...});
file.on('end',function(){
res.end(); //send end respone
//console.log('Finish uploading, time taken: ' + Date.now() - start);
});
req.pipe(file);
});
Explanation
The client script is the same as in option 2.
According to Meteor 1.0.x mongo_driver.js last line, a global object called MongoInternals is exposed, you can call defaultRemoteCollectionDriver() to return the current database db object which is required for the GridStore. In version A, the GridStore is also exposed by the MongoInternals. The mongo used by current meteor is v1.4.x
Then inside a route, you can create a new write object by calling var file = new GridStore(...) (API). You then open the file and create a stream.
I also included a version B. In this version, the GridStore is called using a new mongodb drive via Npm.require('mongodb'), this mongo is the latest v2.0.13 as of this writing. The new API doesn't require you to open the file, you can call stream(true) directly and start piping
Pros
Same as in option 2, sent using arraybuffer, less overhead compared to base64 string in option 1
No need to worry about file name sanitisation
Separation from file system, no need to write to temp dir, the db can be backed up, rep, shard etc
No need to implement any other package
Cachable and can be gzipped
Store much larger sizes compared to normal mongo collection
Using pipe to reduce memory overload
Cons
Unstable Mongo GridFS. I included version A (mongo 1.x) and B (mongo 2.x). In version A, when piping large files > 10 MB, I got lots of error, including corrupted file, unfinished pipe. This problem is solved in version B using mongo 2.x, hopefully meteor will upgrade to mongodb 2.x soon
API confusion. In version A, you need to open the file before you can stream, but in version B, you can stream without calling open. The API doc is also not very clear and the stream is not 100% syntax exchangeable with Npm.require('fs'). In fs, you call file.on('finish') but in GridFS you call file.on('end') when writing finishes/ends.
GridFS doesn't provide write atomicity, so if there are multiple concurrent writes to the same file, the final result may be very different
Speed. Mongo GridFS is much slower than file system.
Benchmark
You can see in option 2 and option 3, I included var start = Date.now() and when writing end, I console.log out the time in ms, below is the result. Dual Core, 4 GB ram, HDD, ubuntu 14.04 based.
file size GridFS FS
100 KB 50 2
1 MB 400 30
10 MB 3500 100
200 MB 80000 1240
You can see that FS is much faster than GridFS. For a file of 200 MB, it takes ~80 sec using GridFS but only ~ 1 sec in FS. I haven't tried SSD, the result may be different. However, in real life, the bandwidth may dictate how fast the file is streamed from client to server, achieving 200 MB/sec transfer speed is not typical. On the other hand, a transfer speed ~2 MB/sec (GridFS) is more the norm.
Conclusion
By no mean this is comprehensive, but you can decide which option is best for your need.
DDP is the simplest and sticks to the core Meteor principle but the data are more bulky, not compressible during transfer, not cachable. But this option may be good if you only need small files.
XHR coupled with file system is the 'traditional' way. Stable API, fast, 'streamable', compressible, cachable (ETag etc), but needs to be in a separate folder
XHR coupled with GridFS, you get the benefit of rep set, scalable, no touching file system dir, large files and many files if file system restricts the numbers, also cachable compressible. However, the API is unstable, you get errors in multiple writes, it's s..l..o..w..
Hopefully soon, meteor DDP can support gzip, caching etc and GridFS can be faster...
Hi just to add on to Option1 regarding viewing of the file. I did it without ejson.
<template name='tryUpload'>
<p>Choose file to upload</p>
<input name="upload" class='fileupload' type='file'>
</template>
Template.tryUpload.events({
'change .fileupload':function(event,template){
console.log('change & view');
var f = event.target.files[0];//assuming upload 1 file only
if(!f) return;
var r = new FileReader();
r.onload=function(event){
var buffer = new Uint8Array(r.result);//convert to binary
for (var i = 0, strLen = r.length; i < strLen; i++){
buffer[i] = r.charCodeAt(i);
}
var toString = String.fromCharCode.apply(null, buffer );
console.log(toString);
//Meteor.call('saveFiles',buffer);
}
r.readAsArrayBuffer(f);};