You can access data implicitly
in the context of a job. When code is generated for a job, it is generated
in the current context. The context includes the default SAS Application
Server when the code was generated, the credentials of the person
who generated the code, and other information. The context of a job
affects how data is accessed when the job is executed.
In order to access data
in the context of a job, you need to understand the distinction between
local data and remote data. Local data is addressable by the SAS Application
Server when code is generated for the job. Remote data is not addressable
by the SAS Application Server when code is generated for the job.
For example, the following
data is considered local in the context of a job:
-
data that can be accessed as if
it were on one or more of the same computers as the SAS Workspace
Server components of the default SAS Application Server
-
data that is accessed with a
SAS/ACCESS
engine (used by the default SAS Application Server)
The following data is
considered remote in a SAS Data Integration Studio job:
-
data that cannot be accessed as
if it were on one or more of the same computers as the SAS Workspace
Server components of the default SAS Application Server
-
data that exists in a different
operating environment from the SAS Workspace Server components of
the default SAS Application Server (such as MVS data that is accessed
by servers running under Microsoft Windows)
Note: Avoid or minimize remote
data access in the context of a SAS Data Integration Studio job.
Remote data has to be
moved because it is not addressable by the relevant components in
the default SAS Application Server at the time that the code was generated.
SAS Data Integration Studio uses
SAS/CONNECT and the UPLOAD and DOWNLOAD
procedures to move data. Accordingly, it can take longer to access
remote data than local data, especially for large data sets. It is
especially important to understand where the data is located when
using advanced techniques such as parallel processing because the
UPLOAD and DOWNLOAD procedures run in each iteration of the parallel
process.
For information about
accessing remote data in the context of a job, administrators should
see the section on "Multi-Tier Environments" in the "SAS Data Integration
Studio" chapter of the
SAS Intelligence Platform: Desktop
Application Administration Guide. Administrators should
also see
Using Deploy for Scheduling to Execute Jobs on a Remote Host. For details
about the code that is generated for local and remote jobs, see the
subheadings about LIBNAME statements and remote connection statements
in
Common Code Generated for a Job.