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Compression Types Exist in SAP HANA

Updated Dec 18, 2019

Which compression types exist?

The following compression types exist:

Compression type M_CS_COLUMNS -> COMPRESSION_TYPE Valid for Details Typical Scenario
Dictionary DEFAULT main delta The standard column store dictionary approach already provides a significant space reduction, because the distinct column values are mapped to value ID numbers which typically require much less space in memory.Dictionary compression is always used. Additionally any one of the other compression techniques mentioned below can be in place. generally
Prefix encoding PREFIXED main Identical values at the beginning of the value ID array are stored only once, together with the number of occurrences. single predominant column value
Run-length encoding RLE main Consecutive identical value IDs are replaced with a single instance of this value ID and its start position. several frequent column values
Cluster encoding CLUSTERED main The value ID array is cut into clusters of 1024 elements. If a cluster contains only occurrences of a single value, the cluster is replaced by a single occurrence of that value. several frequent column values
Indirect encoding INDIRECT main The value ID array is cut into clusters of 1024 elements. If a cluster contains only a few distinct value IDs, a cluster specific dictionary is created, so that each value ID is represented with even fewer bits. several frequent column values
Sparse encoding SPARSE main The most popular value is removed from the value ID array. A bit vector indicates at which positions the value was removed. single predominant column value, value ID array not well clustered

Additionally there is a compression of consecutive string values in the dictionary done ("delta compression"). It can't be influenced and so it is not discussed in detail at this point.

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The following pictures illustrate the different types of compression.

Dictionary compression:

Other compression types:


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