474 Implementing the IBM Storwize V5000 Gen2 with IBM Spectrum Virtualize V8.1
Those technologies do not provide immediate capacity savings. Therefore, they are not a
good fit for primary storage workloads, such as databases and active data set applications.
RACE is based on the Lempel-Ziv lossless data compression algorithm and operates using a
real-time method. When a host sends a write request, it is acknowledged by the write cache
of the system and then staged to the storage pool. As part of its staging, it passes through the
compression engine and is then stored in compressed format into the storage pool.
Therefore, writes are acknowledged immediately after they are received by the write cache,
with compression occurring as part of the staging to internal or external physical storage.
Capacity is saved when the data is written by the host because the host writes are smaller
when they are written to the storage pool. IBM Real-time Compression is a self-tuning
solution. It is adapting to the workload that runs on the system at any particular moment.
9.4.3 Random Access Compression Engine
To understand why RACE is unique, you need to review the traditional compression
techniques. This description is not about the compression algorithm itself, that is, how the
data structure is reduced in size mathematically. Rather, the description is about how the data
is laid out within the resulting compressed output.
Compression utilities
Compression is probably most known to users because of the widespread use of
compression utilities. At a high level, these utilities take a file as their input and parse the data
by using a sliding window technique. Repetitions of data are detected within the sliding
window history, most often 32 KiB. Repetitions outside of the window cannot be referenced.
Therefore, the file cannot be reduced in size unless data is repeated when the window
“slides” to the next 32 KiB slot.
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