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how to optimize the cpu/memory usage in jmp on Windows

robust1972

Community Trekker

Joined:

Jan 15, 2014

hi, I often have to handle data tables with few million rows and 20s to 30s columns. The frustration is whenever I need to edit a plot basing on this big table, the system start the waiting sign(turning ring) which take 1 to few minutes. It normally consume ~60% CPU and few GB memory if I look at the "task manager". Luckily I am using 64bit jmp on 64 bit Win7 workstation which has enough resources but I still have to wait and waste time on waiting.

I hope there is an option/method to optimize the cpu/memory usage or just hold the refreshing till user let it to do so.

Thanks!

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1 ACCEPTED SOLUTION

Accepted Solutions
Solution

Compress Selected Columns

JMP lets you compress columns in a data table to minimize the size of the file and reduce the

amount of memory required to analyze data. This feature is helpful when numeric columns

contain many small integers or when any column contains fewer than 255 unique values. For

example, compressing columns in a data table with 389 columns and 85,000 rows might

decrease the file size from 250MB to 33MB, depending on the type of data.

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );

dt << Compress Selected Columns(

{:age, :sex, :height, :weight}

);

3 REPLIES
XanGregg

Staff

Joined:

Jun 23, 2011

The simplest thing is to work with a random subset of your data while you're tuning a plot appearance, then save the script and reapply it to your full data table. Otherwise, strategies probably depend on the specific platform and task you're doing.

robust1972

Community Trekker

Joined:

Jan 15, 2014

thanks, I will try to use small subset of my data to work out the script then.

Solution

Compress Selected Columns

JMP lets you compress columns in a data table to minimize the size of the file and reduce the

amount of memory required to analyze data. This feature is helpful when numeric columns

contain many small integers or when any column contains fewer than 255 unique values. For

example, compressing columns in a data table with 389 columns and 85,000 rows might

decrease the file size from 250MB to 33MB, depending on the type of data.

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );

dt << Compress Selected Columns(

{:age, :sex, :height, :weight}

);