Columnar database compression

A computer program product comprising:

• a computer readable storage medium having computer readable program instructions embodied therewith to:
• provide a columnar database comprising at least one column partitioned into a plurality of partitions including at least one empty partition and a plurality of filled partitions each comprising data entries associated with a set of parameters, the data entries compressed in accordance with a compression dictionary based on respective recurrence frequencies of the data entries in the filled partition;
• receive forecasted parameter values for a set of parameters, having parameter values relevant to a recurrence frequency of a data entry in a partition, for an expected set of data entries to be stored in an empty partition of the column;
• predict a recurrence frequency of the data entries in the expected set using the forecasted parameter values by evaluating data entry ranking histories associated with the respective compression dictionaries of the filled partitions with a machine learning algorithm;
• generate a predictive compression dictionary for the expected set of data entries based on the predicted recurrence frequency of the data entries in the expected set;
• receive the expected set of data entries;
• and
• compress at least part of the received expected set of data entries using the predictive compression dictionary.

A computer system comprising:

• a processor arrangement, the processor arrangement being adapted to:
• provide a columnar database comprising at least one column partitioned into a plurality of partitions including at least one empty partition and a plurality of filled partitions each comprising data entries associated with a set of parameters, the data entries compressed in accordance with a compression dictionary based on respective recurrence frequencies of the data entries in the filled partition;
• receive forecasted parameter values for a set of parameters, having parameter values relevant to a recurrence frequency of a data entry in a partition, for an expected set of data entries to be stored in an empty partition of the column;
• predict a recurrence frequency of the data entries in the expected set using the forecasted parameter values by evaluating data entry ranking histories associated with the respective compression dictionaries of the filled partitions with a machine learning algorithm;
• generate a predictive compression dictionary for the expected set of data entries based on the predicted recurrence frequency of the data entries in the expected set;
• receive the expected set of data entries;
• and
• compress at least part of the received expected set of data entries using the predictive compression dictionary.