Does anyone have any experience with JMP Table and/or Column compression?
Any concerns/watchouts to using either? I have some JMP tables that are >1GB so would be nice to compress them...
As far as I can tell, there are 2 types of compression built into JMP:
You've outlined the two options very well.
The main difference is that Compress Tables affects only how big the file is on disk. JMP will use the un-compressed version in memory. So, this option is useful to keep your drive from filling up with JMP data tables.
Compress Selected Columns results in smaller files on disk as well as using less memory. Unfortunately, not every column can benefit here.
Here's what Compress Selected Columns does:
HTH,
-Jeff
You've outlined the two options very well.
The main difference is that Compress Tables affects only how big the file is on disk. JMP will use the un-compressed version in memory. So, this option is useful to keep your drive from filling up with JMP data tables.
Compress Selected Columns results in smaller files on disk as well as using less memory. Unfortunately, not every column can benefit here.
Here's what Compress Selected Columns does:
HTH,
-Jeff
I run "dt<<compress selected columns();" on tables with hundreds of columns and the command fills up my log with all the changes. Can I run the command but stop it from writing in the log?
Unfortunately I don't see any way to keep it from writing to the log. I'll enter an enhancement request to see if we can add this in a future release.
In the meantime I can only come up with some unsatisfying hacks involving saving the log before and clearing it after the call to compress the columns.
I've been working with files that are larger than I typically deal with and started using the 'Compress File When Saved' option. It really cuts down on the size, but I am always suspicious of free-lunch solutions. Is there really no downside? Why wouldn't this be the default for all tables?
If the only downside is a 500 ms lag when opening a table or something, then I'll want to do it all the time.
Thanks!