Options compress=binary reuse=yes


options compress=binary reuse=yes

Data Set Options.". Use SAS/Toolkit software to specify your own compression method. Therefore, if compression was unable for those engines, it is also not available when you access those data sets in Version. Data Set Options: System Option: Copyright 1999 by SAS Institute Inc., Cary, NC, USA. When compressbinary, SAS uses Ross Data Compression, which combines run-length encoding and sliding-window compression to compress the data set. This method is highly effective for compressing medium to large (several hundred bytes or larger) blocks of binary data (that is, numeric variables). Alias: N, binary specifies that observations in a newly created SAS output data set are compressed. The advantages that are gained by using the compress system option include: reduced storage requirements for the data set fewer input and output operations necessary to read from or write to the data set during processing. NO specifies that observations in a newly created SAS output data set are uncompressed (fixed-length records). Category: Files: SAS files, pROC options group, sasfiles.

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When compressyes or compresschar, SAS compresses the size of the data set with run-length encoding. Note: compressbinary is accepted by Version 7 and later versions of SAS software. Tip: SAS uses RDC (Ross Data Compression) for work at home jobs for moms in dubai this setting. Compressyes NO char binary, syntax Description, yES char specifies that observations in a newly created SAS output data set are compressed (variable-length records). Run-length encoding compresses the data set by reducing repeated consecutive characters to two- or three-byte representations. Compress, controls the compression of observations in output SAS data sets. When using compressyes and reuseyes system option settings, observations cannot be addressed by observation number. On the command line or in a configuration file, the syntax is specific to your operating environment. This compression algorithm (RLE) is better for character data.


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