I'm trying to fetch 50 mails or so and then call GetMessage() in a foreach loop, but it took a long time! Is there any way to speed up getting message in mailkit?
here is my code:
var mailItems = folder.Fetch(startRange, endRange,MessageSummaryItems.UniqueId);
foreach (var item in mailItems)
{
var message = folder.GetMessage(item.UniqueId);
}
after using dotTrace profiling tools for Yahoo Mails the results are as follows:
dotTrace profiling result
You could try using a profiling tool such as dotTrace to try and find performance bottlenecks that you could fix to make it faster.
That's what performance profilers are for.
Related
I'm trying to print a series of objects in a List using the C# version of AWS Lambda. Its linked to my AWS RDS and my Lex bot. Currently, when I test the bot using the LEX test console, the output that is printed isn't formatted with line breaks even though I'm using the \n line break for C#.
Example Code:
var result = string.Empty;
result = $"Events for {User}:";
foreach (var evt in events)
{
result += $"\n\n{evt.ID} - {evt.FeedbackType} - {evt.Status} - {evt.OpenedDate.ToString()}";
}
return result;
Below is the output I am getting on Lex:
Can anyone please explain how to fix this or if its an issue with the LEX Console?
Thanks!
I believe it is simply a limitation of the lex console. You are at the mercy of the program rendering the chat to handle formatting. Try integrating to Slack - you'll see it work there. The lex console is pretty basic.
BTW if it is of any use, I've got a little app to let you chat with your bot in the commandline. As long as you are logging into the AWS CLI: https://github.com/dwmkerr/lex-chat.
Can we use graph database neo4j with react js? If not so is there any alternate option for including graph database in react JS?
Easily, all you need is neo4j-driver: https://www.npmjs.com/package/neo4j-driver
Here is the most simplistic usage:
neo4j.js
//import { v1 as neo4j } from 'neo4j-driver'
const neo4j = require('neo4j-driver').v1
const driver = neo4j.driver('bolt://localhost', neo4j.auth.basic('username', 'password'))
const session = driver.session()
session
.run(`
MATCH (n:Node)
RETURN n AS someName
`)
.then((results) => {
results.records.forEach((record) => console.log(record.get('someName')))
session.close()
driver.close()
})
It is best practice to close the session always after you get the data. It is inexpensive and lightweight.
It is best practice to only close the driver session once your program is done (like Mongo DB). You will see extreme errors if you close the driver at a bad time, which is incredibly important to note if you are beginner. You will see errors like 'connection to server closed', etc. In async code, for example, if you run a query and close the driver before the results are parsed, you will have a bad time.
You can see in my example that I close the driver after, but only to illustrate proper cleanup. If you run this code in a standalone JS file to test, you will see node.js hangs after the query and you need to press CTRL + C to exit. Adding driver.close() fixes that. Normally, the driver is not closed until the program exits/crashes, which is never in a Backend API, and not until the user logs out in the Frontend.
Knowing this now, you are off to a great start.
Remember, session.close() immediately every time, and be careful with the driver.close().
You could put this code in a React component or action creator easily and render the data.
You will find it no different than hooking up and working with Axios.
You can run statements in a transaction also, which is beneficial for writelocking affected nodes. You should research that thoroughly first, but transaction flow is like this:
const session = driver.session()
const tx = session.beginTransaction()
tx
.run(query)
.then(// same as normal)
.catch(// errors)
// the difference is you can chain multiple transactions:
const tx1 = await tx.run().then()
// use results
const tx2 = await tx.run().then()
// then, once you are ready to commit the changes:
if (results.good !== true) {
tx.rollback()
session.close()
throw error
}
await tx.commit()
session.close()
const finalResults = { tx1, tx2 }
return finalResults
// in my experience, you have to await tx.commit
// in async/await syntax conditions, otherwise it may not commit properly
// that operation is not instant
tl;dr;
Yes, you can!
You are mixing two different technologies together. Neo4j is graph database and React.js is framework for front-end.
You can connect to Neo4j from JavaScript - http://neo4j.com/developer/javascript/
Interesting topic. I am using the driver in a React App and recently experienced some issues. I am closing the session every time a lifecycle hook completes like in your example. When there where more intensive queries I would see a timeout error. Going back to my setup decided to experiment by closing the driver in some more expensive queries and it looks like (still need more testing) the crashes are gone.
If you are deploying a real-world application I would urge you to think about Authentication and Authorization when using a DB-React setup only as you would have to store username/password of the neo4j server in the client. I am looking into options of having the Neo4J server issuing a token and receiving it for Authorization but the best practice is for sure to have a Node.js server in the middle with something like Passport to handle Authentication.
So, all in all, maybe the best scenario is to only use the driver in Node and have the browser always communicating with the Node server using axios...
I generate a very large .csv file from a database using the method outlined in
https://stackoverflow.com/a/13456219/141172
It works fine, up to a point. When the exported file is too large, I get an OutOfMemoryException.
If I turn off output buffering by modifying that code like this:
protected override void WriteFile(System.Web.HttpResponseBase response)
{
response.BufferOutput = false; // <--- Added this
this.Content(response.OutputStream);
}
the file download completes. However, it is several orders of magnitude slower than when output buffering was enabled (measured for the same file with buffering true/false, on localhost).
I understand that is slower, but why would it slow to a relative crawl? Is there anything I can do to improve processing speed?
UPDATE
It would also be an option to use File(Stream stream, String contentType) as suggested in the comments. However, I'm not sure how to create stream. The data is dynamically assembled based on a DB query, and a MemoryStream would run out of contiguous physical memory. Suggestions are welcome.
UPDATE 2
It was suggested in the comments that alternately reading from the database and writing to the stream is causing a degradation. I modified the code to perform the stream writing in a separate thread (using the producer/consumer pattern). There is no appreciable difference in performance.
I don't know what ASP.NET and IIS are doing exactly with output streaming but maybe too small chunks are being uses. Hook in a BufferedStream with a very big buffer, like 4MB.
According to your comments it worked. Now, tune down the buffer size to save memory and have a smaller working set. Good for cache.
As a subjective comment I'm disappointed that this is even necessary. IIS should use the right buffers automatically which is extremely easy with TCP connections.
EDIT FROM OP
Here is the code derived from this answer
public ActionResult Export()
{
// Domain specific stuff here
return new FileGeneratingResult("MyFile.txt", "text/text",
stream => this.StreamExport(stream), false);
}
private void StreamExport(Stream stream)
{
using (BufferedStream bs = new BufferedStream(stream, 256*1024))
using (StreamWriter sw = new StreamWriter(bs))
foreach (var stuff in MyData())
{
sw.Write(stuff);
}
}
In Eric's latest update, he mentioned using another thread. I too had this problem for implementing database exports. Here is some example code for the solution I used:
Handling with temporary file stream
This is probably not of major importance, however I have noticed during testing that the performance of the print statement and also stdout is much faster in the Dart-Editor than from the command-line. From the command-line the performance of print takes around 36% longer than using stdout from the command-line. However, running the program from within the editor, using stdout takes around 900% longer than using the print statement in the editor, but both are considerably faster than from the command-line. ie. Print from a program running in the editor takes around 2.65% of the time it takes from the command-line.
Some relative timings based on average performance from my test :
Running program from command line (5000 iterations) :
print 1700 milliseconds.
stdout 1245 milliseconds.
Running program within Dart-Editor (5000 iterations) :
print 45 milliseconds
stdout 447 milliseconds.
Can someone explain to me the reason for these differences – in particular why performance in the Dart-Editor is so much faster? Also, is it acceptable practice to use stdout and what are the pros and cons versus using print?
Why is the Dart Editor faster?
Because the output handling by the command line is just really slow, and this blocks the output stream, and subsequently the call to print/stdout.
You can test this for yourself - test the following java program (with your own paths, of course):
public static void main(String[] args) {
try {
// the dart file does print and stdout in a loop
Process p = Runtime.getRuntime().exec("C:\\eclipse\\dart-sdk\\bin\\dart.exe D:\\DEVELOP\\Dart\\Console_Playground\\bin\\console_playground.dart");
BufferedReader in = new BufferedReader(new InputStreamReader(p.getInputStream()));
StringBuffer buf = new StringBuffer();
String line;
while((line = in.readLine()) != null) {
buf.append(line + "\r\n");
}
System.out.print(buf.toString());
} catch (IOException e) {
e.printStackTrace();
}
}
On my machine, this is even slightly faster than the Dart Editor (which probably does something like buffering the input and rendering it periodically, but I don't really know).
You will also see that adding a Thread.sleep(1); into the loop will severely impact the performance of the dart program, because the stream is blocked.
Should stdout be used?
I think that's highly subjective. I, for one, do whatever lets me write code more quickly. When i just want to dump a variable, i use print(myvar);. But with stdout, you can do neat stuff like this: stdout.addStream(new File(r"D:\test.csv").openRead());. Of course, if performance is an issue, it depends on how your application will be used - for example, called by another program (where print is faster) vs. command line (where stdout is faster, for some reason).
Why is stdout faster in command line?
I have no idea, sorry. It's the only environment I tested where print() is slower, so I'd guess it has something to do with how the console handles incoming data.
I run the same code from two different locations in my application. I know it is the same code, because it is in a class and that class only has one publicly facing function. Both places call the function with the same arguments and both are running in the UI thread.
The function does a search for a particular printer by name using an asynchronous WMI query-->
var searcher =
new ManagementObjectSearcher(
"SELECT * from Win32_Printer WHERE Name LIKE '%ZDesigner GX430t'");
// Create an observer to trigger a callback when the search is completed.
var watcher = new ManagementOperationObserver();
watcher.Completed += PrinterSearchCompleted;
watcher.ObjectReady += PrinterSearchReady;
// Look for the printer
_printerFound = false;
_searchCompleted = false;
searcher.Get(watcher);
The problem I am having is that the ObjectReady event is not triggered when I run it from one location and when I run it from another, it get's triggered all the time.
Also, another problem is that this seems to be computer specific; some of the computers I run this on work just fine, others exhibit the problem I described above.
Any ideas what I should be looking for?
Couple of things to try:
Check if WMI service is running on all the computers.
Restart WMI service on the computers where it is not working.
You may find this article useful.
If its a Windows 7 or Windows Server 2008 R2 server, WMI has a memory leak problem. Check this.