PARTSIZE= Data Set Option

Specifies the maximum size (in megabytes, gigabytes, or terabytes) that the data component partitions can be. The value is specified when an SPD Engine data set is created. This size is a fixed size. This specification applies only to the data component files.
Valid in: DATA step and PROC step
Used by: MINPARTSIZE= system option
Default: 128M
Interaction: DATAPATH=
Engine: SPD Engine only

Syntax

PARTSIZE=n | nM | nG | nT

Required Argument

n | nM | nG | nT
is the size of the partition in megabytes, gigabytes, or terabytes. If n is specified without M, G, or T, the default is megabytes. For example, PARTSIZE=128 is the same as PARTSIZE=128M. The maximum value is 8,796,093,022,207 megabytes.
Restriction:This restriction applies only to 32–bit hosts with the following operating systems: z/OS, Linux SLES 9 x86, and the Windows family. In SAS 9.3, if you create a data set with a partition size greater than or equal to 2 gigabytes, you cannot open the data set with any version of SPD Engine before SAS 9.2. The following error message is written to the SAS log: ERROR: Unable to open data file because its data representation differs from the SAS session data representation.

Details

Multiple partitions are necessary to read the data in parallel. The option PARTSIZE= forces the software to partition SPD Engine data files at the specified size. The actual size of the partition is computed to accommodate the maximum number of observations that fit in the specified size of n megabytes, gigabytes, or terabytes. If you have a table with an observation length greater than 65K, you might find that the PARTSIZE= that you specify and the actual partition size do not match. To get these numbers to match, specify a PARTSIZE= that is a multiple of 32 and the observation length.
By splitting (partitioning) the data portion of an SPD Engine data set into fixed-sized files, the software can introduce a high degree of scalability for some operations. The SPD Engine can spawn threads in parallel (for example, up to one thread per partition for WHERE evaluations). Separate data partitions also enable the SPD Engine to process the data without the overhead of file access contention between the threads. Because each partition is one file, the trade-off for a small partition size is that an increased number of files (for example, UNIX i-nodes) are required to store the observations.
Scalability limitations using PARTSIZE= depend on how you configure and spread the file systems specified in the DATAPATH= option across striped volumes. (You should spread each individual volume's striping configuration across multiple disk controllers or SCSI channels in the disk storage array.) The goal for the configuration, at the hardware level, is to maximize parallelism during data retrieval. For information about disk striping, see “I/O Setup and Validation” under “SPD Engine” in Scalability and Performance at http://support.sas.com/rnd/scalability.
The PARTSIZE= specification is limited by the SPD Engine system option MINPARTSIZE=, which is usually maintained by the system administrator. MINPARTSIZE= ensures that an inexperienced user does not arbitrarily create small partitions, thereby generating a large number of data files.
The partition size determines a unit of work for many of the parallel operations that require full data set scans. But, more partitions does not always mean faster processing. The trade-offs involve balancing the increased number of physical files (partitions) required to store the data set against the amount of work that can be done in parallel by having more partitions. More partitions means more open files to process the data set, but a smaller number of observations in each partition. A general rule is to have 10 or fewer partitions per data path, and 3 to 4 partitions per CPU. (Some operating systems have a limit on the number of open files that you can use.)
To determine an adequate partition size for a new SPD Engine data set, you should be aware of the following:
  • the types of applications that run against the data
  • how much data you have
  • how many CPUs are available to the applications
  • which disks are available for storing the partitions
  • the relationships of these disks to the CPUs
For example, if each CPU controls only one disk, then an appropriate partition size would be one in which each disk contains approximately the same amount of data. If each CPU controls two disks, then an appropriate partition size would be one in which the load is balanced. Each CPU does approximately the same amount of work.
Note: The PARTSIZE= value for a data set cannot be changed after a data set is created. To change PARTSIZE=, you must re-create the data set and specify a different PARTSIZE= value in the LIBNAME statement or on the new (output) data set.

Example: Using PROC SQL

You have 100 gigabytes of data and 8 disks, so you can store 12.5 gigabytes per disk. Optimally, you want 3 to 4 partitions per disk. A partition size of 3.125 gigabytes is appropriate. So, you can specify PARTSIZE=3200M.
data salecent.sw (partsize=3200m);
Using the same amount of data, you anticipate the amount of data doubles within a year. You can either specify the same PARTSIZE= and have about 7 partitions per disk, or you can increase PARTSIZE= to 5000M and have 5 partitions per disk.