Architecting, installing and maintaining your SAS environment

Migrate Content from Local To Server

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Contributor
Posts: 35

Migrate Content from Local To Server

Hi masters!

 

We have an old environment that works in a local machine, this machine only have Enterprise Guide.

 

Now we have an SAS Server, and we want migrate the actual content to the Server. What is the best mode to do this task?

 

If i define the same libraries in the server, it's enought? Then, if I import a project in another pc with EG and connected to the SAS server, the project will works?

 

Thx

Super User
Posts: 8,037

Re: Migrate Content from Local To Server

Posted in reply to JuanDaniel

How did you define your libraries in the desktop-only environment? Did you specify them in a global autoexec.sas, or in every EG project?

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Maxims of Maximally Efficient SAS Programmers
Contributor
Posts: 35

Re: Migrate Content from Local To Server

Posted in reply to JuanDaniel
Yes, only in desktop environment and in every EG project.

Thx
Super User
Posts: 8,037

Re: Migrate Content from Local To Server

Posted in reply to JuanDaniel

So you have code within a project that assigns libraries? Probably in the autoexec section of the project?

 

I'd suggest that you pull as many library definitions as you can out of individual projects and make them global, either by writing them into autoexec_usermods.sas files on the server or (preferred nowadays) by defining your libraries in metadata. The obvious advantage of centralized library definitions is the fact that you maintain them in only one place. If you have to shift physical locations, you only have to change one definition. Same if you need to tinker with permissions.

 

Once the logical framework is set up, move your existing data to the new platform. Use either proc cport/cimport, or SAS/CONNECT if you have that licensed. Create cntlout datasets from existing custom formats, and use those as cntlin files on the server. Still better: make sure that all proc format code is migrated to the server.

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Maxims of Maximally Efficient SAS Programmers
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