VS 2022 creates tens of thousands of htm-files (obviuosly log-files) in c:\Temp\Default and c:\Temp\NativeImage.
After a couple of weeks of work with VS they add upp to several GB. This slows down work as the Virus scanner will take all cpu for several minutes after starting VS.
Deleting those folders and I'm back to normal for a week or so. And is not good for my SSD.
What can be done to prevent this?
I havn't seen this with VS2019 or early versions of VS2022.
From your comment, this sounds like logs from the Fusion Log Viewer. Double-check your settings by running fuslogvw.exe from an elevated command prompt (need to be elevated to change settings).
If you have enabled either of the last 2 options (Log bind failures to disk or Log all binds to disk), it will create a log file for each applicable event. This can end up consuming lots of disk space, as you're observing.
If you set it to the second option (Log in exception text), you'll be able to view these details in the debugger if you're encountering assembly bind failures, but it doesn't write to disk anywhere (just a slight memory increase in the exception objects).
I need help, maybe someone had similar problem with JMeter report generation
I have JMeter script with SOAP API requests, which are placing a purchasing order. There are no issues during order creation time, but when all requests are finished and JMeter is trying to generate report I am getting an error:
java.lang.OutOfMemoryError: Java heap space
Dumping heap to java_pid8676.hprof ...
Heap dump file created [7011161840 bytes in 93.212 secs]
Uncaught Exception java.lang.OutOfMemoryError: Java heap space in thread Thread[StandardJMeterEngine,5,main]. See log file for details.
I used JConsole to monitor JMeter during execution and noticed that heap mostly was at 25% during test run and went up to 100% during report generation.
Thanks in advance
I've hit this issue numerous times when the results file from a test is very large. What you need to do is set the max heap size before generating the Dashboard report. What value you can set the max heap size depends on whether you're running on a 32-bit OS versus a 64-bit and how much RAM is available on the machine/VM. If the machine you're generating the report on doesn't have enough RAM available, then you can copy the results file to another machine which has more. For example, when I hit this issue on a test VM, I normally just copy the results file locally to my laptop which has 16GB and run the following command:
JVM_ARGS="-Xms3072m -Xmx12g" && export JVM_ARGS && jmeter -g resultsFile.jtl -o outputReport
The error clearly states that JMeter lacks Java Heap space in order to complete the report generation operation, it might be the case you executed a long-running test and your .jtl results file is very big so it doesn't fit into 7GB of heap. It normally indicates that a developer is not too familiar with memory management and cannot come up with a better solution than load everything into memory in one shot instead of doing it in batches/buffers so it might be a good idea to raise an issue in JMeter's Bugzilla
So just increase JVM heap size allocated to JMeter by manipulating -Xmx parameter, even if your system will start intensively using the swap file I believe you should be able to live with this.
Alternative option is generating tables/charts using JMeter Plugins Command Line Graph Plotting Tool, however this way you will get individual results rather than the fancy HTML dashboard
I'm performing some queries over a tpch 100gb dataset on presto, I have 4 nodes, 1 master, 3 workers. When I try to run some queries, not all of them, I see on Presto web interface that the nodes die during the execution, resulting in query failure, the error is the following:
.facebook.presto.operator.PageTransportTimeoutException: Encountered too many errors talking to a worker node. The node may have crashed or been under too much load. This is probably a transient issue, so please retry your query in a few minutes.
I rebooted all nodes and presto service but the error remains, this problem doesn't exist if I run the same queries over a smaller dataset.Can someone provide some help on this problem?
Thanks
3 possible causes for this kind of error. You may ssh into one of worker to find out what the problem is when the query is running.
High CPU
Tune down the task.concurrency to, for example, 8
High memory
In the jvm.config, -Xmx should no more than 80% total memory. In the config.properties, query.max-memory-per-node should be no more than the half of Xmx number.
Low open file limit
Set in the /etc/security/limits.conf a larger number for the Presto process. The default is definitely way too low.
It might be an issue for configuration. For example, if the local maximum memory is not set appropriately and the query use too much heap memory, full GC might happen to cause such errors. I would suggest to ask in the Presto Google Group and describe someway to reproduce the issue :)
I was running presto on Mac with 16GB of ram below is the configuration of java.config file.
-server
-Xmx16G
-XX:+UseG1GC
-XX:G1HeapRegionSize=32M
-XX:+UseGCOverheadLimit
-XX:+ExplicitGCInvokesConcurrent
-XX:+HeapDumpOnOutOfMemoryError
-XX:OnOutOfMemoryError=kill -9 %p
I was getting following error even for running the Query
Select now();
Query 20200817_134204_00005_ud7tk failed: Encountered too many errors talking to a worker node. The node may have crashed or be under too much load. This is probably a transient issue, so please retry your query in a few minutes.
I changed my -Xmx16G value to -Xmx10G and it works fine.
I used following link to install presto on my system.
Link for Presto Installation
I have a multi-user application that keeps a centralized logfile for activity. Right now, that logging is going into text files to the tune of about 10MB-50MB / day. The text files are rotated daily by the logger, and we keep the past 4 or 5 days worth. Older than that is of no interest to us.
They're read rarely: either when developing the application for error messages, diagnostic messages, or when the application is in production to do triage on a user-reported problem or a bug.
(This is strictly an application log. Security logging is kept elsewhere.)
But when they are read, they're a pain in the ass. Grepping 10MB text files is no fun even with Perl: the fields (transaction ID, user ID, etc..) in the file are useful, but just text. Messages are written sequentially, one like at a time, so interleaved activity is all mixed up when trying to follow a particular transaction or user.
I'm looking for thoughts on the topic. Anyone done application-level logging with an SQL database and liked it? Hated it?
I think that logging directly to a database is usually a bad idea, and I would avoid it.
The main reason is this: a good log will be most useful when you can use it to debug your application post-mortem, once the error has already occurred and you can't reproduce it. To be able to do that, you need to make sure that the logging itself is reliable. And to make any system reliable, a good start is to keep it simple.
So having a simple file-based log with just a few lines of code (open file, append line, close file or keep it opened, repeat...) will usually be more reliable and useful in the future, when you really need it to work.
On the other hand, logging successfully to an SQL server will require that a lot more components work correctly, and there will be a lot more possible error situations where you won't be able to log the information you need, simply because the log infrastructure itself won't be working. And something worst: a failure in the log procedure (like a database corruption or a deadlock) will probably affect the performance of the application, and then you'll have a situation where a secondary component prevents the application of performing it's primary function.
If you need to do a lot of analysis of the logs and you are not comfortable using text-based tools like grep, then keep the logs in text files, and periodically import them to an SQL database. If the SQL fails you won't loose any log information, and it won't even affect the application's ability to function. Then you can do all the data analysis in the DB.
I think those are the main reasons why I don't do logging to a database, although I have done it in the past. Hope it helps.
We used a Log Database at my last job, and it was great.
We had stored procedures that would spit out overviews of general system health for different metrics that I could load from a web page. We could also quickly spit out a trace for a given app over a given period, and if I wanted it was easy to get that as a text file, if you really just like grep-ing files.
To ensure the logging system does not itself become a problem, there is of course a common code framework we used among different apps that handled writing to the log table. Part of that framework included also logging to a file, in case the problem is with the database itself, and part of it involves cycling the logs. As for the space issues, the log database is on a different backup schedule, and it's really not an issue. Space (not-backed-up) is cheap.
I think that addresses most of the concerns expressed elsewhere. It's all a matter of implementation. But if I stopped here it would still be a case of "not much worse", and that's a bad reason to go the trouble of setting up DB logging. What I liked about this is that it allowed us to do some new things that would be much harder to do with flat files.
There were four main improvements over files. The first is the system overviews I've already mentioned. The second, and imo most important, was a check to see if any app was missing messages where we would normally expect to find them. That kind of thing is near-impossible to spot in traditional file logging unless you spend a lot of time each day reviewing mind-numbing logs for apps that just tell you everything's okay 99% of the time. It's amazing how freeing the view to show missing log entries is. Most days we didn't need to look at most of the log files at all... something that would be dangerous and irresponsible without the database.
That brings up the third improvement. We generated a single daily status e-mail, and it was the only thing we needed to review on days that everything ran normally. The e-mail included showed errors and warnings. Missing logs were re-logged as warning by the same db job that sends the e-mail, and missing the e-mail was a big deal. We could send forward a particular log message to our bug tracker with one click, right from within the daily e-mail (it was html-formatted, pulled data from a web app).
The final improvement was that if we did want to follow a specific app more closely, say after making a change, we could subscribe to an RSS feed for that specific application until we were satisfied. It's harder to do that from a text file.
Where I'm at now, we rely a lot more on third party tools and their logging abilities, and that means going back to a lot more manual review. I really miss the DB, and I'm contemplated writing a tool to read those logs and re-log them into a DB to get these abilities back.
Again, we did this with text files as a fallback, and it's the new abilities that really make the database worthwhile. If all you're gonna do is write to a DB and try to use it the same way you did the old text files, it adds unnecessary complexity and you may as well just use the old text files. It's the ability to build out the system for new features that makes it worthwhile.
yeah, we do it here, and I can't stand it. One problem we have here is if there is a problem with the db (connection, corrupted etc), all logging stops. My other big problem with it is that it's difficult to look through to trace problems. We also have problems here with the table logs taking up too much space, and having to worry about truncating them when we move databases because our logs are so large.
I think its clunky compared to log files. I find it difficult to see the "big picture" with it being stored in the database. I'll admit I'm a log file person, I like being able to open a text file and look through (regex) it instead of using sql to try and search for something.
The last place I worked we had log files of 100 meg plus. They're a little difficult to open, but if you have the right tool it's not that bad. We had a system to log messages too. You could quickly look at the file and determine which set of log entries belonged which process.
We've used SQL Server centralized logging before, and as the previous posted mentioned, the biggest problem was that interrupted connectivity to the database would mean interrupted logging. I actually ended up adding a queuing routine to the logging that would try the DB first, and write to a physical file if it failed. You'd just have to add code to that routine that, on a successful log to the db, would check to see if any other entries are queued locally, and write those too.
I like having everything in a DB, as opposed to physical log files, but just because I like parsing it with reports I've written.
I think the problem you have with logging could be solved with logging to SQL, provided that you are able to split out the fields you are interested in, into different columns. You can't treat the SQL database like a text field and expect it to be better, it won't.
Once you get everything you're interested in logging to the columns you want it in, it's much easier to track the sequential actions of something by being able to isolate it by column. Like if you had an "entry" process, you log everything normally with the text "entry process" being put into the "logtype" column or "process" column. Then when you have problems with the "entry process", a WHERE statement on that column isolates all entry processes.
we do it in our organization in large volumes with SQL Server. In my openion writing to database is better because of the search and filter capability. Performance wise 10 to 50 MB worth of data and keeping it only for 5 days, does not affect your application. Tracking transaction and users will be very easy compare to tracking it from text file since you can filter by transaction or user.
You are mentioning that the files read rarely. So, decide if is it worth putting time in development effort to develop the logging framework? Calculate your time spent on searching the logs from log files in a year vs the time it will take to code and test. If the time spending is 1 hour or more a day to search logs it is better to dump logs in to database. Which can drastically reduce time spend on solving issues.
If you spend less than an hour then you can use some text search tools like "SRSearch", which is a great tool that I used, searches from multiple files in a folder and gives you the results in small snippts ("like google search result"), where you click to open the file with the result interested. There are other Text search tools available too. If the environment is windows, then you have Microsoft LogParser also a good tool available for free where you can query your file like a database if the file is written in a specific format.
Here are some additional pros and cons and the reason why I prefer log files instead of databases:
Space is not that cheap when using VPS's. Recovering space on live database systems is often a huge hassle and you might have to shut down services while recovering space. If your logs is so important that you have to keep them for years (like we do) then this is a real problem. Remember that most databases does not recover space when you delete data as it simply re-uses the space - not much help if you are actually running out of space.
If you access the logs fequently and you have to pull daily reports from a database with one huge log table and millions and millions of records then you will impact the performance of your database services while querying the data from the database.
Log files can be created and older logs archived daily. Depending on the type of logs massive amounts of space can be recovered by archiving logs. We save around 6x the space when we compress our logs and in most cases you'll probably save much more.
Individual smaller log files can be compressed and transferred easily without impacting the server. Previously we had logs ranging in the 100's of GB's worth of data in a database. Moving such large databases between servers becomes a major hassle, especially due to the fact that you have to shut down the database server while doing so. What I'm saying is that maintenance becomes a real pain the day you have to start moving large databases around.
Writing to log files in general are a lot faster than writing to DB. Don't underestimate the speed of your operating system file IO.
Log files only suck if you don't structure your logs properly. You may have to use additional tools and you may even have to develop your own to help process them, but in the end it will be worth it.
You could log to a comma or tab delimited text format, or enable your logs to be exported to a CSV format. When you need to read from a log export your CSV file to a table on your SQL server then you can query with standard SQL statements. To automate the process you could use SQL Integration Services.
I've been reading all the answers and they're great. But in a company I worked due to several restrictions and audit it was mandatory to log into a database. Anyway, we had several ways to log and the solution was to install a pipeline where our programmers could connect to the pipeline and log into database, file, console, or even forwarding log to a port to be consumed by another applications.
This pipeline doesn't interrupt the normal process and keeping a log file at the same time you log into the database ensures you rarely lose a line.
I suggest you investigate further log4net that it's great for this.
http://logging.apache.org/log4net/
I could see it working well, provided you had the capability to filter what needs to be logged and when it needs to be logged. A log file (or table, such as it is) is useless if you can't find what you're looking for or contains unnecessary information.
Since your logs are read rarely, I would write them on file (better performance and reliability).
Then, if and only if you need to read them, I would import the log file in a data base (better analysis).
Doing so, you get the advantages of both methods.
I often use the "top" command to see what is taking up resources. Mostly it comes up with a long list of Apache httpd processes, which is not very useful. Is there any way to see a similar list, but such that I could see which PHP scripts etc. those httpd processes are actually running?
If you're concerned about long running processes (i.e. requests that take more than a second or two to execute), you'll be able to get an idea of them using Apache's mod_status. See the documentation, and an example of the output (from www.apache.org). This isn't unique to PHP, but applies to anything running inside an apache process.
Note that the www.apache.org status output is publicly available presumably for demonstration purposes -- you'd want to restrict access to yours so that not everyone can see it.
There's a top-like ncurses-based utility called apachetop which provides realtime log analysis for Apache. Unfortunately, the project has been abandoned and the code suffers from some bugs, however it's actually very much usable. Just don't run it as root, run it as any user with access to the web server log files and you should be fine.
The php scripts happen so fast, top wouldn't show you very much. Or it would zip by quite quickly. Most webrequests are quite quick.
I think your best bet would be to have some type of real time log processor, that kept an eye on your access logs and updates stats for you of average run time, memory usage and stuff like that.
You could make your PHP pages time themselves and write their path and execution time to file or database. Note that would slow everything down while you were monitoring, but it would serve as a good measuring method.
It wouldn't be that interactive though. You'd be able to get daily or weekly results from it, but it'd be hard to see something meaningful within minutes or hours.