Adventures & experiences in contemporary technology
To generate the package list on the GNOME version of Linux Mint, I used the Backup Tool. It simply was a matter of using the Backup Software Selection button and telling it where to put the file that it generates. Alternatively, dpkg can be used from the command line like this:
sudo dpkg --get-selections > /backup/installed-software.txt
After transferring the file to the machine with Linux Mint Debian Edition, I tried using the Backup Tool on there too. However, using the Restore Software Selection button and loading the required only produced an irrecoverable error. Therefore, I set to looking around the web and found a command line approach that did the job for me.
The first step is to load the software selection using dpkg by issuing this command (it didn’t matter that the file wasn’t made using the dpkg command though I suspect that’s what the Linux Mint Backup Tool was doing that behind the scenes):
sudo dpkg --set-selections < /backup/installed-software.txt
Then, I started dselect and chose the installation option from the menu that appeared. First time around, it fell over but trying again was enough to complete the job. Packages available to the vanilla variant of Linux Mint but not found in the LMDE repositories were overlooked as I had hoped and installation of the extra packages had no impact on system stability either.
sudo dselect
Apparently, there is an alternative to using dselect that is based on the much used apt-get command but I didn’t make use of it so cannot say more:
sudo apt-get dselect-upgrade
All that I can say is that the dpkg/dselect combination did what I wanted so I’ll keep them in mind if ever need to synchronise software selections between two Debian-based distributions in the future again. The standard edition of Linux Mint may be based on Ubuntu rather than Debian but Ubuntu is itself based on Debian so the description holds here.
A habit of mine is to put a LENGTH or ATTRIB statement between DATA and SET statements in a SAS data step to reset variable lengths. By default, it seems that this triggers truncation warnings in SAS 9.2 or SAS 9.3 when it didn’t in previous versions. SAS 9.1.3, for instance, allowed you have something like the following for shortening a variable length without issuing any messages at all:
data b;
length x $100;
set a;
run;
In this case, x could have a length of 200 previously and SAS 9.1.3 wouldn’t have complained. Now, SAS 9.2 and 9.3 will issue a warning if the new length is less than the old length. This can be useful to know but it can be changed using the VARLENCHK system option. The default value is WARN but it can be set to ERROR if you really want to ensure that there is no chance of truncation. Then, you get error messages and the program fails where it normally would run with warnings. Setting the value of the option to NOWARN restores the type of behaviour seen in SAS 9.1.3 and versions prior to that.
The SAS documentation says that the ability to change VARLENCHK can be restricted by an administrator so you might need to deal with this situation in a more locked down environment. Then, one option would be to do something like the following:
data b;
drop x;
rename _x=x;
set a;
length _x $100;
_x=strip(x);
run;
It’s a bit more laborious than setting to the VARLENCHK option to NOWARN but the idea is that you create a new variable of the right length and replace the old one with it. That gets rid of warnings or errors in the log and resets the variable length as needed. Of course, you have to ensure that there is no value truncation with either remedy. If any is found, then the dataset specification probably needs updating to accommodate the length of the values in the data. After all, there is no substitute for getting to know your data and doing your own checking should you decide to take matters into your hands.
There is a use for the default behaviour though. If you use a specification to specify a shell for a dataset, then you will be warned when the shell shortens variable lengths. That allows you to either adjust the dataset or your program. Also, it gives more information when you get variable length mismatch warnings when concatenating or merging datasets. There was a time when SAS wasn’t so communicative in these situations and some investigation was needed to establish which variable was affected. Now, that has changed without leaving the option to work differently if you so do desire. Sometimes, what can seem like an added restriction can have its uses.
This is one of the classic SAS errors that you can get from PROC SQL and it can be thrown by a number of things. Missing out a comma in a list of variables on a SELECT statement is one situation that will do it, as will having an extraneous one. As I discovered recently, an ill-defined SAS function nesting like LEFT(TRIM(PERIOD,BEST.)) will have the same effect; notice the missing PUT function in the example. The latter surprised me because I might have expected something more descriptive for this as would be the case in data step code. In the event, it took some looking before the problem hit me because it’s amazing how blind you can become to things that are staring you in the face. Familiarity really can make you pay less attention.
This could be the beginning of a series on error messages from PROC SQL that may appear unclear to a programmer more familiar with Data Step. The cause of my getting the message that heads this posting is that there was a numeric variable with a length less that the default of 8, not the best of situations. Sadly, the message doesn’t pin point the affected variable so it took some commenting out of pieces of code before I found the cause of the problem. That’s never to say that PROC SQL does not have debugging functionality in the form of FEEDBACK, NOEXEC, _METHOD and _TREE options on the PROC SQL line itself or the validation statement but neither of these seemed to help in this instance. Still, they’re worth keeping in mind for the future as is SAS Institute’s own page on SQL query debugging. Of course, now that I know what might be the cause, a simple PROC SQL report using the dictionary tables should help. The following code should do the needful:
proc sql;
select memname, name, type, length
from dictionary.columns
where libname="DATA" and type="num" and length ne 8;
quit;
I have grown to notice that certain bloggers are not removing old content from a blog but merely striking it through using something like CSS. There is a place for this but it does strike me as overkill sometimes and can look untidy. Sometimes, that lack of neatness is a trade-off since the highlighting of a correction itself conveys a message. I have been know to tweak posts immediately after publishing without leaving the previous content on view but my changes generally are readability improvements more than anything else. Typos and spelling mistakes also get corrected like this; nobody needs them highlighted for all to see. I am not trying to fool anyone and, if I want to update the content, I either add another post or use another tactic that I have seen others use: updates at the bottom of the post that are denoted as such. It’s another transparent approach that preserves the authenticity of the piece.
I was trying to upgrade one of my test blogs to WordPress 2.3 RC1 when I got error messages like the above littering the screen during the installation. The PHP functions mysql_noerr (or mysqli_noerr) and mysql_error (or mysqli_error) seem to have been busily at work. These messages told me that the upgrade hadn’t worked so I went off googling as usual and perusing the MySQL tomes in my possession. Not for the first time, the web yielded nothing but dross and, in the end, I tried deleting the relevant database and starting from scratch again. That resolved the problem.
The reason for database deletion sorting things out is that MySQL got confused when there was a mismatch between what was in the file system and what its InnoDB table was saying. I think that the cause of this was that I naively copied in tables using Windows Explorer. Deleting the database cleared the air and all was well once I allowed WordPress to do the needful in its time honoured way. Another lesson learned for the future and I wish that frustration wasn’t part of the learning experience too…
This is a SAS error that can be seen from time to time:
WARNING: The quoted string currently being processed has become more than 262 characters long. You may have unbalanced quotation marks.
In the days prior to SAS version 8, this was something that needed to be immediately corrected. In these days of SAS character variables extending beyond 200 characters in length, it becomes a potential millstone around a SAS programmer’s neck. If you run a piece of code like this:
data _null_;
x="[string with more than 262 characters (putting in an actual string wrecks the appearance of the website)]";
run;
What you get back is the warning message at the heart of the matter. The code is legitimate and works fine but the spurious error is returned because SAS hasn’t found a closing quote by the required position and the 262 character limit is a hard constraint that cannot be extended. There is another way though: the new QUOTELENMAX option in SAS9. Setting it as follows removes the messages in most situations (yes, I did find one where it didn’t play ball):
options noquotelenmax;
This does however beg the question as to how you check for unbalanced quotes in SAS logs these days; clearly, looking for a closing quote is an outmoded approach. Thanks to code highlighting, it is far easier to pick them out before the code gets submitted. The other question that arises is why you would cause this to happen anyway but there are occasions where you assign the value of a macro variable to a data set one and the string is longer than the limit set by SAS. Here’s some example code:
data _null_;
length y $400;
y=repeat("f",400);
call symput("y",y)
run;
data _null_;
x="&y";
run;
My own weakness is where I use PROC SQL to combine strings into a macro variable, a lazy man’s method of combining all distinct values for a variable into a delimited list like this:
proc sql noprint;
select distinct compress(string_var) into :vals separated by " " from dataset;
quit;
Of course, creating a long delimited string using the CATX (new to SAS9) function avoids the whole situation and there are other means but there may be occasions, like the use of system macro variables, where it is unavoidable and NOQUOTELENMAX makes a much better impression when these arise.