D. Chatziantoniou and K. A. Ross. Groupwise processing of relational queries. In VLDB, 1997.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....that handles relation valued variables. To the best of our knowledge, the first reference to this operator and its implementation in Microsoft SQL Server 2000 appeared in [12] The notion of binding variables to sets of It is called SegmentApply in [12] tuples has also been proposed in [5, 6]. Interestingly, the motivation in this previous work was to support data warehousing applications. In this respect our work adds weight to the claim that such an operator is an important addition to relational query evaluation engines. 2. Even with the GApply operator added to the query ....

....as shown to the left in Figure 2. As opposed to [5] we allow only traditional relational operations in the per group query. Adding new operators that perform multiple aggregations more e#ciently is an orthogonal extension but is not the focus of this paper. Finally, pursuing the terminology of [6], we refer to the operation of GApply as groupwise processing. Formally, the expression RE1 GAC RE2 denotes the application of GApply(denoted as GA) on the result of relational algebra expression RE1 where C is the list of grouping columns and RE2 is a parameterized relational algebra expression ....

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D. Chatziantoniou and K. A. Ross. Groupwise processing of relational queries. In VLDB, 1997.

....or SORT BY Example 12. The SPRINT Algorithm in AXL [ 1] AGGREGATE sprint(iNode INT, RecId INT, iCol INT, iValue REAL, iYorN INT) 2] f [ 3] TABLE treenodes(RecId INT, Col INT, Value REAL, YorN INT, KEY(Col, Value) 4] TABLE summary(Col INT, SplitGini REAL, SplitVal REAL, Yc INT, Nc INT) [ 5] TABLE split(RecId INT, LeftOrRight INT, KEY (RecId) 6] TABLE mincol(Col INT, Value REAL, Gini REAL) 7] TABLE node(Node INT) AS VALUES(iNode) 8] 9] INITIALIZE : ITERATE : f [10] INSERT INTO treenodes VALUES (RecId, iCol, iValue, iYorN) 11] UPDATE summary [12] SET Yc=Yc iYorN, ....

....distributed and parallel data mining. Example 13. Categorical Classifier Expressed in AXL [ 1] AGGREGATE classify(RecId INT, iNode INT, iCol INT, iValue INT, iYorN INT) 2] f [ 3] TABLE treenodes(RecId INT, Node INT, Col INT, Value INT, YorN INT) 4] TABLE mincol(Col INT, MinGini REAL) [ 5] TABLE summary(Col INT, Value INT, Yc INT, Nc INT, KEY fCol,Valueg) 6] TABLE ginitable(Col INT, Gini REAL) 7] 8] INITIALIZE : ITERATE : f [ 9] INSERT INTO treenodes [10] VALUES(RecId, iNode, iCol, iValue, iYorN) 11] UPDATE summary [12] SET Yc=Yc iYorN, Nc=Nc 1 iYorN [13] WHERE ....

D. Chatziantoniou and K. A. Ross, "Groupwise Processing of Relational Queries." Proceedings of the 1997 VLDB Conference, pages 476-485, August 1997.

.... AS (Col, Val, YorN) FROM PlayTennis) AS t; Example 8 Using Recursive Aggregates to Implement a Classifier in AXL [ 1]AGGREGATE classify(RecId INT, iNode INT, iCol INT, 2] iValue INT, iYorN INT) 3] 4] TABLE treenodes(RecId INT, Node INT, 5] Col INT, Value INT, YorN INT) [ 6] TABLE mincol(Col INT) 7] TABLE summary(Col INT, Value INT, Yc INT, Nc INT, 8] KEY fCol,Valueg) 9] TABLE ginitable(Col INT, Gini INT) 10] 11] INITIALIZE : ITERATE : f [12] INSERT INTO treenodes [13] VALUES(RecId, iNode, iCol, iValue, iYorN) 14] UPDATE summary [15] SET ....

D. Chatziantoniou and K. A. Ross, "Groupwise Processing of Relational Queries." Proceedings of the 1997 VLDB Conference, pages 476-485, August 1997.

....or SORT BY Example 12. The SPRINT Algorithm in AXL [ 1] AGGREGATE sprint(iNode INT, RecId INT, iCol INT, iValue REAL, iYorN INT) 2] f [ 3] TABLE treenodes(RecId INT, Col INT, Value REAL, YorN INT, KEY(Col, Value) 4] TABLE summary(Col INT, SplitGini REAL, SplitVal REAL, Yc INT, Nc INT) [ 5] TABLE split(RecId INT, LeftOrRight INT, KEY (RecId) 6] TABLE mincol(Col INT, Value REAL, Gini REAL) 7] TABLE node(Node INT) AS VALUES(iNode) 8] 9] INITIALIZE : ITERATE : f [10] INSERT INTO treenodes VALUES (RecId, iCol, iValue, iYorN) 11] UPDATE summary [12] SET Yc=Yc iYorN, ....

....distributed and parallel data mining. Example 13. Categorical Classi er Expressed in AXL [ 1] AGGREGATE classify(RecId INT, iNode INT, iCol INT, iValue INT, iYorN INT) 2] f [ 3] TABLE treenodes(RecId INT, Node INT, Col INT, Value INT, YorN INT) 4] TABLE mincol(Col INT, MinGini REAL) [ 5] TABLE summary(Col INT, Value INT, Yc INT, Nc INT, KEY fCol,Valueg) 6] TABLE ginitable(Col INT, Gini REAL) 7] 8] INITIALIZE : ITERATE : f [ 9] INSERT INTO treenodes [10] VALUES(RecId, iNode, iCol, iValue, iYorN) 11] UPDATE summary [12] SET Yc=Yc iYorN, Nc=Nc 1 iYorN [13] WHERE ....

D. Chatziantoniou and K. A. Ross, \Groupwise Processing of Relational Queries." Proceedings of the 1997 VLDB Conference, pages 476-485, August 1997.

....queries such as Find the total sales among minimum price suppliers of each item. Such queries need multiple views and or subqueries in standard SQL. We demonstrate significant performance improvements over a commercial system of a specialized evaluation algorithm for multi feature queries. In [2] we have developed techniques for recognizing when an arbitrary relational query is amenable to the following kind of evaluation strategy: a) Partition the data according to some attributes, b) apply a (simpler) query to each partition, and (c) union the results. Such evaluation strategies are ....

D. Chatziantoniou and K. A. Ross. Groupwise processing of relational queries. In VLDB Conference, pages 476--485, 1997.

....queries, difficult to understand and optimize. Standard query processing techniques [8, 22] help somehow. The problem is that a traditional SQL optimizer will not consider the big picture , but will try to optimize a series of joins and aggregations, which is not always the best approach. In [7] we have addressed this issue and provided techniques to combine joins and aggregations into a more general operation. Similar concerns are discussed in [23] However, there are many important queries that do not fall in this framework. Consider some typical OLAP queries over the following ....

D. Chatziantoniou and K. Ross. Groupwise Processing of Relational Queries. In 23rd VLDB Conference, 1997.

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