Aggregate

An aggregate is a collection of items that are gathered together to form a total quantity.

Canonical hours

In the practice of Christianity, canonical hours mark the divisions of the day in terms of periods of fixed prayer at regular intervals. A Book of Hours normally contains a version of, or selection from, such prayers.

The practice of daily prayers grew from the Jewish practice of reciting prayers at set times of the day: for example, in the Book of Acts, Peter and John visit the temple for the afternoon prayers (Acts 3:1). Psalm 119:164 states: "Seven times a day I praise you for your righteous laws" which is among the scriptural quotes in the attestation of Saint Symeon of Thessaloniki that commences "The times of prayer and the services are seven in number, like the number of gifts of the Spirit, since the holy prayers are from the Spirit."

This practice is believed to have been passed down through the centuries from the Apostles, with different practices developing in different places. As monasticism spread, the practice of specified hours and liturgical formats began to develop and become standardized. Around the year 484, Sabbas began the process of recording the liturgical practices around Jerusalem while the cathedral and parish rites in the Patriarchate of Constantinople evolved in an entirely different manner; the two were synthesized commencing in the eighth century to yield an office of great complexity. In 525, Benedict of Nursia set out one of the earliest schemes for the recitation of the Psalter at the Office. With the Cluniac reforms of the 11th century there was a new emphasis on liturgy and the canonical hours in the reformed Benedictine priories with the Abbey of Cluny at their head.

Aggregate (data warehouse)

Aggregates are used in dimensional models of the data warehouse to produce dramatic positive effects on the time it takes to query large sets of data. At the simplest form an aggregate is a simple summary table that can be derived by performing a Group by SQL query. A more common use of aggregates is to take a dimension and change the granularity of this dimension. When changing the granularity of the dimension the fact table has to be partially summarized to fit the new grain of the new dimension, thus creating new dimensional and fact tables, fitting this new level of grain. Aggregates are sometimes referred to as pre-calculated summary data, since aggregations are usually precomputed, partially summarized data, that are stored in new aggregated tables. When facts are aggregated, it is either done by eliminating dimensionality or by associating the facts with a rolled up dimension. Rolled up dimensions should be shrunken versions of the dimensions associated with the granular base facts. This way, the aggregated dimension tables should conform to the base dimension tables. So the reason why aggregates can make such a dramatic increase in the performance of the data warehouse is the reduction of the number of rows to be accessed when responding to a query.