Scalable Performance Data Server and Scalable Performance Data Engine

Overview of Scalable Performance Data Server and Scalable Performance Data Engine

Both the SAS Scalable Performance Data Engine (SPD Engine) and the SAS Scalable Performance Data Server (SPD Server) are designed for high-performance data delivery. They enable rapid access to SAS data for intensive processing by the application. The SAS SPD Engine and SAS SPD Server deliver data to applications rapidly by organizing the data into a streamlined file format that takes advantage of multiple CPUs and I/O channels to perform parallel input and output functions.
The SAS SPD Engine is included with Base SAS software. It is a single-user data storage solution that shares the high-performance parallel processing and parallel I/O capabilities of SAS SPD Server, but it lacks the additional complexity of a full-blown server. It is a multi-user parallel-processing data server with a comprehensive security infrastructure, backup and restore utilities, and sophisticated administrative and tuning options. SAS SPD Server libraries can be defined using SAS Management Console.
SAS SPD Engine and SAS SPD Server use multiple threads to read blocks of data very rapidly and in parallel. The software tasks are performed in conjunction with an operating system that enables threads to execute on any of the machine's available CPUs.
Although threaded I/O is an important part of both product offerings' functionality, their real power comes from how the software structures SAS data. They can read and write partitioned files and, in addition, use a specialized file format. This data structure permits threads, running in parallel, to perform I/O tasks efficiently.
Although not intended to replace the default Base SAS engine for most tables that do not span volumes, SAS SPD Engine and SAS SPD Server are high-speed alternatives for processing very large tables. They read and write tables that contain billions of observations.
The SAS SPD Engine and SAS SPD Server performance are boosted in these ways:
  • support for terabytes of data
  • scalability on symmetric multiprocessing (SMP) machines
  • parallel WHERE selections
  • parallel loads
  • parallel index creation
  • partitioned tables
  • parallel I/O data delivery to applications
  • implicit sorting on BY statements

Symmetric Multiprocessing

The SAS SPD Server exploits a hardware and software architecture known as symmetric multiprocessing (SMP). An SMP machine has multiple CPUs and an operating system that supports threads. An SMP machine is usually configured with multiple disk I/O controllers and multiple disk drives per controller. When the SAS SPD Server reads a data file, it launches one or more threads for each CPU; these threads then read data in parallel. By using these threads, a SAS SPD Server that is running on an SMP machine provides the quick data access capability that is used by SAS in an application.
For more information about using the SAS SPD Server, see SAS Scalable Performance Data Server: Administrator's Guide and
The following figure shows how connectivity to SPD Servers is established:
Establishing Connectivity to a SAS SPD Server
Establishing Connectivity to a SAS SPD Server
For a detailed example of a SAS SPD Server connection, see Establishing Connectivity to a Scalable Performance Data Server.

Dynamic Clustering

The SAS SPD Server provides a virtual table structure called a clustered data table. A cluster contains a number of slots, each of which contains a SAS SPD Server table. The clustered data table uses a layer of metadata to manage the slots.
This virtual table structure provides the SAS SPD Server with the architecture to offer flexible storage to allow a user to organize tables based on values contained in numeric columns, including SAS date, time, or datetime values. This new type of organization is called a dynamic cluster table. Dynamic cluster tables enable parallel loading and selective removal of data from very large tables, making management of large warehouses easier. These unique capabilities provide organizational features and performance benefits that traditional SAS SPD Server tables cannot provide.
Dynamic cluster tables can load and process data in parallel. Dynamic cluster tables provide the flexibility to add new data or to remove historical data from the table by accessing only the slots affected by the change, without having to access the other slots, thus reducing the time needed for the job to complete. In addition, a complete refresh of a dynamic cluster table requires a fraction of the disk space that would otherwise be needed, and can be divided into parallel jobs to complete more quickly. All of these benefits can be realized using simple SPDO procedure commands to create and alter a cluster.
The two most basic commands are CLUSTER CREATE and CLUSTER UNDO. Two additional commands are ADD and LIST. You execute each of these commands within PROC SPDO.
The CLUSTER CREATE command requires three options:
  • the name of the cluster table to create (cluster-table-name)
  • a list of SAS Scalable Performance Data Server tables to include in the cluster (using the MEM= option)
  • the maximum number of slots (member tables) that can be used in the cluster table (using the MAXSLOT= option)
The following example shows the syntax for PROC SPDO with a CLUSTER CREATE command:
PROC SPDO LIBRARY=domain-name;
SET ACLUSER user-name;
CLUSTER CREATE cluster-table-name
MEM = SPD-Server-table1
MEM = SPD-Server-table2
MEM = SPD-Server-table3
MEM = SPD-Server-table4
MEM = SPD-Server-table5
MEM = SPD-Server-table6
MEM = SPD-Server-table7
MEM = SPD-Server-table8
MEM = SPD-Server-table9
MEM = SPD-Server-table10
MEM = SPD-Server-table11
MEM = SPD-Server-table12
Here is the syntax for the UNDO command:
SET ACLUSER user-name;
CLUSTER UNDO sales_hist;
This example shows the syntax for the ADD command:
SET ACLUSER user-name;
CLUSTER ADD sales_hist
MEM = 2005sales_table1
MEM = 2005sales_table2
MEM = 2005sales_table3
MEM = 2005sales_table4
MEM = 2005sales_table5
MEM = 2005sales_table6;
Finally, here is the syntax for the LIST command:
SET ACLUSER user-name;
CLUSTER LIST sales_hist;
These operations run quickly. These features reduce the downtime of the table for maintenance and improve the availability of the warehouse.