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1. 发明申请

US20180081939A1 TECHNIQUES FOR DICTIONARY BASED JOIN AND AGGREGATION 审中-公开
公开(公告)号：US20180081939A1
公开(公告)日：2018-03-22
申请号：US15268521
申请日：2016-09-16
申请人： Oracle International Corporation
发明人： Albert Hopeman , Martin Roth , Ekrem Soylemez , Adam Kociubes
IPC分类号： G06F17/30
摘要： Techniques are described herein for performing join and aggregation operations for a received query using column dictionaries. In an embodiment, a query is received that requests to aggregate a measure column of a fact table based on an aggregate function and join the fact table with a dimension table on a join key column. Data of the fact table may be stored in one or more storage data units, for example a particular data portion of the fact table may be stored on a particular data storage unit. The respective data portion may include one or more column vectors corresponding to one or more columns of the fact table in which a cell element corresponds to a value at a particular row and a particular column of the one or more columns of the fact table. The cell element of the one or more column vectors includes a dictionary encoded value of the value at the particular column and row. This dictionary encoded value is mapped to the value of by a dictionary data structure of the particular column. In an embodiment, in response to receiving the query, using the query, for a particular storage unit, the DBMS identifies a fact join key vector of the one or more column vectors of the particular data storage unit and a fact join key dictionary data structure corresponding to the fact join key vector. The DBMS generates a dictionary-grouping key mapping based on the fact join key dictionary data structure and a dense grouping key data structure. Such a dense grouping key data structure represents a mapping of unique dimension join key values of the join key column of the dimension table to grouping key values of a grouping key of the dimension table. Based on the generated dictionary-grouping key mapping and the fact join key vector, the DBMS may generate a transformed vector, which represents the grouping key values of the dictionary-grouping key mapping arranged according to the fact join key vector. Alternatively, the dictionary-grouping key mapping may be directly accessed during the aggregation. Based on the generated transformed vector and/or by directly accessing the dictionary-grouping key mapping, the DBMS aggregates a column vector in that particular data storage unit that corresponds to the measure column in the received query.

2. 发明授权

US10067954B2 Use of dynamic dictionary encoding with an associated hash table to support many-to-many joins and aggregations 有权
公开(公告)号：US10067954B2
公开(公告)日：2018-09-04
申请号：US14806576
申请日：2015-07-22
申请人： Oracle International Corporation
发明人： Adam Kociubes , Ekrem Soylemez , Hyemin Chung
IPC分类号： G06F17/30
摘要： Techniques are described herein for using a dynamic dictionary encoding with an associated hash table to support many-to-many join and aggregation operations. In an embodiment, within a first storage of a computing device, a first data structure that comprises a first dense grouping key column is created. The dense grouping key column includes a first plurality of dense grouping key values and one or more instances of a flag value. Within the first storage of the computing device, a second data structure is created that comprises a group-by column and a second dense grouping key column. The group-by column includes a plurality of group-by key values and the second dense grouping key column includes a second plurality of dense grouping key values. Within the first storage of the computing device, a third data structure, a hash table, is created that includes a hash bucket for each join key value that corresponds to an instance of the flag value. A result set for a query is determined using a combination of the first data structure, second data structure and/or the third data structure.

3. 发明授权

US10558659B2 Techniques for dictionary based join and aggregation 有权
公开(公告)号：US10558659B2
公开(公告)日：2020-02-11
申请号：US15268521
申请日：2016-09-16
申请人： Oracle International Corporation
发明人： Albert Hopeman , Martin Roth , Ekrem Soylemez , Adam Kociubes
IPC分类号： G06F16/00 , G06F16/2453 , G06F16/28 , G06F16/22
摘要： Techniques are described herein for performing join and aggregation operations for a received query using column dictionaries. In an embodiment, a query is received that requests to aggregate a measure column of a fact table based on an aggregate function and join the fact table with a dimension table on a join key column. Data of the fact table may be stored in one or more storage data units, for example a particular data portion of the fact table may be stored on a particular data storage unit. The respective data portion may include one or more column vectors corresponding to one or more columns of the fact table in which a cell element corresponds to a value at a particular row and a particular column of the one or more columns of the fact table. The cell element of the one or more column vectors includes a dictionary encoded value of the value at the particular column and row. This dictionary encoded value is mapped to the value of by a dictionary data structure of the particular column. In an embodiment, in response to receiving the query, using the query, for a particular storage unit, the DBMS identifies a fact join key vector of the one or more column vectors of the particular data storage unit and a fact join key dictionary data structure corresponding to the fact join key vector. The DBMS generates a dictionary-grouping key mapping based on the fact join key dictionary data structure and a dense grouping key data structure. Such a dense grouping key data structure represents a mapping of unique dimension join key values of the join key column of the dimension table to grouping key values of a grouping key of the dimension table. Based on the generated dictionary-grouping key mapping and the fact join key vector, the DBMS may generate a transformed vector, which represents the grouping key values of the dictionary-grouping key mapping arranged according to the fact join key vector. Alternatively, the dictionary-grouping key mapping may be directly accessed during the aggregation. Based on the generated transformed vector and/or by directly accessing the dictionary-grouping key mapping, the DBMS aggregates a column vector in that particular data storage unit that corresponds to the measure column in the received query.

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