Im looking for a quick and dirty way to get a graph to show a rate of lines added to a log file, such as php.log, or any text file for that matter.
Know of any open source projects out there?
I know there are a lot of charting tools out there and am familiar with rrd and such, but the answer I'm interested in is the actual nuts and bolts of implementing the solution for any of those charting systems.
If you are familiar with rrd, then you can make a simple database which stores the actual line count of the log file, then visualize with the standard rrd tools.
You can update your database with the following snippet:
rrdtool update test.rrd `date +%s`:`wc -l logfile.txt`
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I'm writing a program which needs to look at a very large number of files, some of which are very large in size. I'd like to visit a file only once, unless it changes. If it changes I need to revisit it again.
The way I know of to do this is with datestamps. One can look at the modified date to see if it is newer than the last time you looked at the file. Obviously those can be changed programmatically, so I'm wondering if there is a way to determine if a file has changed other than that. (I'm thinking along the lines of a UUID for the file which is changed every time it is modified or an epoch counter, but I'm open to more exotic solutions)
You can monitor changes for these files, assuming you continue to run the whole time. Check the FindFirstChangeNotification API. You can take a look at this project as an example. Sysinternals also has a similar tool, I believe it's implemented in a similar way.
I've never seen this line ending before and I am trying to load the file into a database.
The lines all have a fixed width. After the CSV text which contains the data (the length varies line-by-line), there is a CR followed by multiple spaces and ending with LF. The spaces provide the padding to equalize the line width.
Line1,Data 1,Data 2,Data 3,4,50D20202020200A
Line2,Data 11,Data 21,Data 31,41,510D2020200A
Line3,Data12,Data22,Data 32,42,520D202020200A
I am about to handle this with a stream reader / writer in C#, but there are 40 files that come in each month and if there is a way to convert them all at once instead of one line at a time, I would rather do that.
Any thoughts?
Line-by-line processing of a stream doesn't have to be a bottleneck if you implement it at the right point in your overall process.
When I've had to do this kind of preprocessing I put a folder watch on the inbound folder, then automatically pick up each file and process it upon arrival, putting the original into an archive folder and writing the processed file into another location from which data will be parsed or loaded into the database. Unless you have unusual real-time requirements, you'll never notice this kind of overhead. If you do have real-time requirements, this issue will pale in comparison to all the other issues you'll face with batched data files :)
But you may not even have to go through a preprocessing step at all. You didn't indicate what database you will be using or how you plan to load the data, but many databases do include utilities to process fixed-length records. In the past, fixed-format files came with every imaginable kind of bizarre format (and contained all kinds of stuff that had to be stripped out or converted). As a result those utilities tend to be very efficient at this kind of task. In my experience they can easily be at least an order of magnitude faster than line-by-line processing, which can make a real difference on larger bulk loads.
If your database doesn't have good bulk import processing tools, there are a number of many open-source or freeware utilities already written that do pretty much exactly what you need. You can find them on GitHub and other places. For example, NPM replace is here and zzzprojects findandreplace is here.
For a quick and dirty approach that allows you to preview all the changes as you develop a more robust solution, many text editors have the ability to find and replace in multiple files. I've used that approach successfully in the past. For example, here's the window from NotePad++ that lets you use RegEx to remove or change whatever you like in all files matching defined criteria.
I have been asked to create a system for allowing third party companies to dump data into several of our tables. These third parties provide csv files on a periodic basis, and after doing some research it seemed like Oracle themselves had a standard tool for doing so, "sqlldr". I've since gotten it working to an acceptable degree, and we have a job scheduled to run that script once a day.
But one of the third parties supplies really dirty data, of the sort where I can't expect it to always load every row/record (looking like up to about 8% will fail). My boss asked me to forward "all output" from the first few tests to him, and like a moron I also sent the log file.
He has asked that this "report" be modified to include those exceptions that aren't unique constraints along with the line in the input file that caused the exception.
This means that I need data from the log file, but also from the (I believe) reject file in a single document. Rather than write a convoluted shell script to combine those two, does SQL*Loader itself allow any customization that might achieve the same thing? I've read through the Oracle documentation and haven't found anything that suggests this, but I've also learned not to trust it entirely either.
Is this possible? Ideally, the solution would allow me to add values to the reject file that don't exist in the original input file, but I'm also interested in any customization of the log file or reject file.
No.
I was going to stop there, but you can define the name of the log file, which might help with issue. Most automation with SQL*Loader involves wrapping it within shell scripts; aka "roll your own."
I'm trying to look at the Freebase data dump which is stored on a server that I access through ssh. The trouble is I don't know how I can view it in a way that doesn't take forever, make things freeze or crash, I had been trying to view it with nano and it evokes the precisely the behaviour just described.
The operating system is Darwin.
How can I examine this data?
Basically you could use command more or less to scroll over the file. If you know which lines in the file you are interested in, like from line 3000 to 3999, you could show them with sed -n '3000,3999p' your_file_name.
I am using JMeter and have 2 questions (I have read the FAQ + Wiki etc):
I use the Graph Results listener. It seems to have a fixed span, e.g. 2 hours (just guessing - this is not indicated anywhere AFAIK), after which it wraps around and starts drawing on same canvas from the left again. Hence after a long weekend run it only shows the results of last 2 hours. Can I configure that span or other properties (beyond the check boxes I see on the Graph Results listener itself)?
Can I save the results of a run and later open them? I know I can save the test plan or parts of it. I am unclear if I can save separately just the test results data, and later open them and perform comparisons etc. And furthermore can I open them with different listeners even if they weren't part of original test (i.e. I think of the test as accumulating data, and later on I want to view and interpret the data using different "viewers").
Thanks,
-- Shaul
Don't know about 1. Regarding 2: listeners typically have a configuration field for "Write All Data to a File", which lets you specify the file name. You can use the Simple Data Writer to store results efficiently for later analysis.
You can load results from a previous test into a visualizer by choosing "Write All Data to a File" and browsing for the file you wish to load. Somewhat counterintuitively, selecting a file for writing also loads that file into the visualizer and displays the results. Just make sure you don't run the test again while that file is selected, otherwise you will lose your saved test data. :-)
Well, I later found a JMeter group that was discussing the issue raised in my first question, and B.Ramann gave me an excellent suggestion to use instead a better graph found here.
-- Shaul