For more information about server logging and monitoring, see the SAS Intelligence
Platform: System Administration Guide, the SAS Logging: Configuration and
Programming Reference, and the SAS Environment Manager Help.
SAS Grid Computing
You can use SAS grid computing tools to manage a distributed grid environment for
your SAS deployment. SAS Grid Manager, working together with Platform Suite for
SAS, enables you to distribute server workloads across multiple computers on a network
to obtain the following benefits:
• the ability to accelerate SAS analytical results by adding additional computers to the
grid and by dividing jobs into separate processes that run in parallel across multiple
• the flexibility to upgrade and maintain the computing resources on which your SAS
servers are deployed without disrupting operations, and to add computing resources
quickly to handle increased workloads and peak demands
• continuity of service through the high availability of critical components running in
Implementation of a grid environment involves planning and design efforts to determine
the topology and configuration that best meets the needs of your organization. In some
cases, third-party data sharing facilities or hardware load balancers might be required.
For more information, see Grid Computing in SAS and “Introduction to Grid
Computing” at http://support.sas.com/rnd/scalability/grid/index.html.
SAS LASR Analytic Server
The SAS LASR Analytic Server is an analytic platform that is provided with SAS Visual
Analytics, SAS Visual Statistics, and other high-performance products. This secure,
multi-user server provides concurrent access to data that is loaded into memory. The
server can take advantage of a distributed computing environment by distributing data
and the workload among multiple machines and performing massively parallel
processing. The server can also be deployed on a single machine where the workload
and data volumes do not demand a distributed computing environment but can still
benefit from the speed of in-memory processing.
The server handles both big data and smaller sets of data, and it is designed with high-
performance, multi-threaded, analytic code. The server processes client requests at
extraordinarily high speeds due to the combination of hardware and software that is
designed for rapid access to tables in memory. By loading tables into memory for
analytic processing, the server enables business analysts to explore data and discover
relationships in data at the speed of the RAM that is installed on the system.
The server can also perform text analysis on unstructured data. The unstructured data is
loaded to memory in the form of a table, with one document in each row.
Data can be loaded into a distributed server in the following ways:
• You can load tables into the server by using the SAS LASR Analytic Server engine
or the LASR procedure from a SAS session that has a network connection to the
cluster. Any data source that can be accessed with a SAS engine can be loaded into
memory. The data is transferred to the root node of the server, and the root node
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