E. Bertino and W. Kim. Indexing techniques for queries on nested objects. IEEE Trans. on Knowledge and Data Engineering, 1(2):196--214, Jun 1989.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....in our language. We can therefore fully describe a join index by a triple consisting of a materialized binary relation view and two indexes. In our example, the join index for joining Dept with Proj is (Dept, I, JI) Access support relations [KM90a, KM90b] generalize path indexes [MS86, Ber94, BK89] and translate the join index idea from the relational to the object model, generalizing it from binary to n ary relations. An access support relation (ASR) for a given path is a separate precomputed relation that explicitly stores the oids of objects related to each other via the attributes of ....

E. Bertino and W. Kim. Indexing techniques for queries on nested objects. IEEE Trans. on Knowledege and Data Engineering, 1(2), 1989.

....surrogates to index into the relations. We can therefore fully describe a join index by a triple consisting of a materialized binary relation view and two indexes. In our example, the join index for joining Dept with Proj is (Dept, I, JI) Access support relations [28, 29] generalize path indexes [34, 10, 11] and translate the join index idea from the relational to the object model, generalizing it from binary to n ary relations. An access support relation (ASR) for a given path is a separate precomputed relation that explicitly stores the oids of objects related to each other via the attributes of ....

E. Bertino and W. Kim. Indexing techniques for queries on nested objects. IEEE Trans. on Knowledege and Data Engineering, 1(2), 1989.

....Moscow, June 27 30, 1995. the presence of set valued attributes makes set comparison operations more frequent. Several data structures were proposed to support the valuebased querying in the object oriented databases, including join indices [20] access support relations [12] nested indices [2], and signature files [10] Many of these structures were introduced for completely different environments and their relevance and efficiency for support of object querying is not obvious. Therefore, it is important to evaluate the behavior of different indexing structures in the object oriented ....

....contained in the objects, accompanied with corresponding OIDs. The performance characteristics for this structure are different from that for text retrieval systems, as shown in [17] 3. 2 Nested Indices The indexing techniques to support search queries on nested complex objects were proposed in [2]. This kind of indices is based on traditional one dimensional access method, such as B tree. An index entry consists of a nested attribute value (obtained via certain path) used as a key, and a set of OIDs of all objects that refer to (or contain) this value through specified path. The ....

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E. Bertino and W. Kim. Indexing techniques for queries on nested objects. IEEE Trans. on Knowledge and Data Eng., 2(1):196--214, 1989.

....as a limited index function in which the only kinds of calls that can be made are get methods that return the objects referenced by the instance variables of the object implementations. Path based indexing appeared first in GemStone[47] with subsequent implementations proposed by Bertino and Kim[11] and Valduriez[60] Note that path based indexing guarantees that every time a path expression is evaluated, it accesses the same objects. There are several disadvantages in using path based indexing. Path based indexing violates abstraction and encapsulation: Users must know an object s ....

....[9] Of these the multi index is the most commonly used scheme; it was originally proposed for GemStone[47] and is also used in the O 2 [24, 23] and ObjectStore[40, 52] databases. We will cover the GemStone scheme in some detail, then briefly cover the nested index and path index of Bertino and Kim[11] and the join index of Valduriez[60] emphasizing their differences from the GemStone scheme and each other. 4.1.1 Multi indexes (GemStone) In the GemStone scheme[47] the notion of a link in a path expression is introduced. A link is conceptually a connection between parts of a path expression ....

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Elisa Bertino and Won Kim. Indexing techniques for queries on nested objects. IEEE Transactions on Knowledge and Data Engineering, 1(2):196--214, June 1989. 167

....they provide techniques for handling object migration, minimizing replication and migration of objects upfront is not emphasized. Moreover, with these approaches, logical design and organization of data is not clearly independent of the physical organization of data. The work of Bertino and Kim [1] on index selection is also complementary to our work, but different in the sense that they aim at efficient design at the physical level (local internal schema) while our design aims at efficient design at the logical level (local conceptual schema) Distributed relational databases [17] benefit ....

Elisa Bertino and Won kim. Indexing techniques for queries on nested objects. IEEE Transactions on Knowledge and Data Engineering, 1(2), 1989.

....degradation. Recent work has addressed the problem of efficiently evaluating path queries in this area [CCM96, FS98, MW97] In order to optimize path query processing, several indexing schemes have been proposed in the past for objectoriented databases. Example of such schemes are Path Indexes [BK89, SB96] and Access Support Relations [KM92] which materialize frequently traversed paths in the database in order to support navigation along reference chains leading from one object to another. However, since these approaches are based on the paths found in the schema, it is not possible to use them ....

E. Bertino and W. Kim. Indexing techniques for queries on nested objects. IEEE Transactions on Knowledge and Data Engineering, 1(2): 196-214, 1989.

....complicates the definition and representation of vertical partitioning of the classes, and makes the problem of vertical partitioning in OODBs very challenging. In contrast to vertical partitioning, indexing in OODBs is a facility to reduce the number of disk IOs in query processing (e.g. see [2, 10]) by reducing the accesses to irrelevant object instances. Note that indexing reduces disk IOs at the object instance level, and it may still access some irrelevant instance variables (i.e. not all the instance variables accessed will always be relevant to the query) While vertical partitioning ....

....19. Class Emp DeptInfo Dept; EmpId char[8] EName char[50] Skill char[200] EAddress char[100] Class Dept ProjInfo setof Proj; DeptId char[8] DName char[50] DeptType char[10] DAddress char[100] Class Proj ProjType char[8] PId char[8] PName char[50] Priority char[2]; Location char[100] Similar to experiment one, we also have a P factor. For example, a P factor of 10 means that all the sizes of value based instance variables are scaled up by 10, but the sizes of object based instance variables are not scaled up (since object based instance variables are ....

E. Bertino and W. Kim, "Indexing Technique for Queries on Nested Objects", in IEEE Trans. Knowledge and Data Engineering, Vol. 1, No. 2, pages 196--214, 1989.

....Index, Partitioning, Hyper Graph, Query Processing, Spatial Join. 1 Introduction The join operation is a fundamental operation in databases, and it has been a subject of intense scrutiny by leading database researchers. Much work has been done in optimizing join operation [13, 26] A join index [2, 8, 20, 24, 30, 33] is a data structure that facilitates rapid join query processing. For data sets which are updated infrequently and use pre computation and materialization techniques to speed up online query processing, the join index can be particularly useful. A fully materialized relationship keeps the ....

E. Bertino and W. Kim. Indexing Techniques for Queries on Nested Objects. IEEE Trans. Knowledge and Data Eng., 1(2):196--214, June 1989.

....techniques are combined, the number of possible expressions of a simple query is so large that it is fundamental to investigate heuristics to limit the search space for an equivalent expression, thereby reducing the rewriting phase. The heuristics we advocate rely on the knowledge of indexes [8] and objects placement policies [7] Indexes and object placement policies can respectively be represented in our model by paths of length equal or greater than one and by trees. We have chosen for algebraic expressions a DAG representation on which they are easily mapped. Evaluation algorithms ....

....As such, extents are useful elements for an optimizer. Indexes in relational systems involve only one relation. In object oriented systems, structures are more complex and, as a consequence, one has to consider having indexes on path of length greater than one going through several classes. In [8], different kinds of index are proposed. In this paper, we will only consider path indexes but the way we are using them can easily be extended to others. A path index is a data structure which provides a direct backward link. The last information that we consider concerns knowledge about the ....

E. Bertino and W. Kim. Indexing Techniques for Queries on Nested Objects. IEEE Transaction Knowledge and Date Engineering, January 1989.

....form of a library of routines that can be used to directly manipulate the database. These routines can be used for developing new design tools that directly use the database interface. For efficient processing and fast access of data, access methods such as B tree indexing [6] and Path Index [4] have been incorporated. Issues related to object management and transaction processing are handled by the Shore server. In summary, DIAS forms part of an information framework that extends chip design database systems to include support for analysis of interconnect parasitics. Our initial study ....

....is to have a reference to an object at the leaf of the hierarchy and then try to find the root object of the hierarchy which requires a reverse (bottom up) traversal of the aggregation hierarchy. Access methods suggested for aggregation hierarchies include nested index and path index mechanisms [4]. The nested index uses a modified B tree organization. The nested index maintains references to the root and the leaf of the aggregation hierarchy in question. This association between the root and the leaf of the aggregation hierarchy facilitates retrieval of the reference to one end of the ....

E. Bertino and W. Kim, "Indexing Techniques for queries on nested objects", IEEE Trans. on Knowledge and Data Engineering, 1989.

....Object oriented databases (OODB) have received considerable attention in recent years. One problem cited by practitioners in using OODBs in industry, is their performance. Indexing is a common technique to enhance performance. Two types of indexes special to OODB were described by Bertino and Kim [1, 7, 9]: the Class Hierarchy index and the Nested or Path index. The classhierarchy index provides indexing on some attribute value to a class and its sub classes along the is a (sub super type, generalization) hierarchy. The original class hierarchy indexing scheme does not support well multi class ....

....access to the top class only, while path index provides access to classes along the path hierarchy. Path indexes can also be used to answer queries with predicates on in path nodes. Such queries, however, may require the search of many index pages. Path indexes were described and analyzed in [1]. A variation of the pathindexing method which can be used to support Joins in relational databases is called Access support relations and is discussed in [5] In this paper a uniform scheme combining both forms of indexing is suggested. This scheme, called the U index, provides support for ....

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W. Kim and E. Bertino. Indexing techniques for queries on nested objects. IEEE Trans. on Knowledge and Data Engineering, 1(2):196--204 (1989).

....own. We then propose new techniques for estimating the cardinalities of unconditional joins and selectivity factors of a query involving partial participation classes. Partial participation has not been considered seriously in the literature [15] Most of existing query optimization techniques [2, 8, 11, 16, 19] except for Whang et al. 24, 21, 22] have not considered partial participation. We discuss in Section 4.1 that these conventional techniques often incur large estimation errors for the queries involving partial participation classes. We also consider the effect of multi valued attributes on the ....

....in Section 4.1 that these conventional techniques often incur large estimation errors for the queries involving partial participation classes. We also consider the effect of multi valued attributes on the estimation of intermediate results cardinalities. Most of existing estimation techniques [2, 16, 19, 24, 21] have not considered multi valued attributes seriously. The proposed technique for estimating the cardinalities of unconditional joins extends Whang s technique [24, 21, 22] so as to consider the characteristics of object oriented databases. The proposed techniques require new types of statistics ....

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E. Bertino and W. Kim. Indexing techniques for queries on nested objects. IEEE Trans. on Knowledge and Data Engineering, 1(2):196--214 (1989).

....to a C pointer based traversal, our nested path traversal operators give the OODB the whole view, such that it can work set at a time and can optimize and parallelize traversal execution. The relation attributes that connect the classes are essentially join indices [16] or OODB nested indices [2]. The closure operator first transforms a complex path to a singular one. In fact, it constructs a join index between the starting class and the ending class (which for closure( are one and the same) Although the construction cost for a join index maybe high, this investment can be turned into ....

E. Bertino and W. Kim. Indexing techniques for queries on nested objects. IEEE Transactions on Knowledge and Data Engineering, 1(2), June 1989. Also published in/as: Mathematisch Centrum (Amsterdam), now CMCSC, TR-ACTOODS, 132-89, Mar.1989.

.... step indexes. They are called Maier Stein indexes in this chapter after the paper [25] Since this seems to be the indexing of choice in most commercial object oriented systems, it is used in the experiments rather than some of the proposed indexes in the academic literature such as path indexes [5] or access support relations [19] In addition, in many of the experiments, only one level of backwards traversal is necessary. Path indexes could be more useful if more than one level of backwards traversals are needed. Path indexes are Maier Stein indexes when only one level backwards traversal ....

Elisa Bertino and Won Kim. Indexing Technique for Queries on Nested Objects. IEEE Transactions on Knowledge and Data Engineering, pages 196--214, 1989.

....into single mixed approach. We show that the mixed approach is not only efficient but can also provide an optimal (otherwise, a near optimal) vertical partitioning scheme. In contrast to partitioning, indexing is a facility in OODBs to reduce the number of disk IOs in query execution (e.g. see [BK89,KM90,KM92]) by reducing the accesses to irrelevant object instances (as compared with sequential scanning) Indexing reduces disk IOs at the object instance level; it still accesses irrelevant instance variables, as not all the instance variables accessed are relevant to the query. Partitioning is also a ....

E. Bertino and W. Kim, "Indexing Technique for Queries on Nested Objects", in IEEE Trans. Knowledge and Data Engineering, Vol. 1, No. 2, pages 196--214, 1989.

....through a structure. Support for complex structures also results in languages that regularly use nested query expressions, where variables from outer expressions are referenced in nested expressions. One difficulty with path expressions is the definition of indices for such expressions [MS86, BK89] The presence of arbitrary methods in the path further complicates this problem. The maintenance of an index can require the application of methods and those methods could manipulate arbitrarily many objects. Another problem with path expressions is that they imply an execution order for ....

Elisa Bertino and Won Kim. Indexing Techniques for Queries on Nested Objects. Technical Report ACT-OODS-132-89, MCC, 1989.

....to a C pointer based traversal, our nested path traversal operators give the OODB the whole view, such that it can work set at a time and can optimize and parallelize traversal execution. The relation attributes that connect the classes are essentially join indices [16] or OODB nested indices [2]. The closure operator first transforms a complex path to a singular one. In fact, it constructs a join index between the starting class and the ending class (which for closure( are one and the same) Although the construction cost for a join index maybe high, this investment can be turned into ....

E. Bertino and W. Kim. Indexing techniques for queries on nested objects. IEEE Transactions on Knowledge and Data Engineering, 1(2), June 1989. Also published in/as: Mathematisch Centrum (Amsterdam), now CMCSC, TR-ACT-OODS,132-89, Mar.1989. References 20

.... are used to combine information from more than one relation (as a result of normalization) In object oriented database systems, besides supporting the conventional value based joins, identity based joins are also needed to 1 optimize the evaluation of path expressions [6] or nested predicates [1]) to retrieve objects related by their class composition hierarchy. Much work has been done in optimizing join operation [8, 4] and many join processing techniques are common to both relational and object oriented database systems. One strategy to compute the join R 1 . R 2 is the following ....

....of tuple identifiers or object identifiers) organized as index structures to expedite join computation in relational and or object oriented database systems. Many such indexes have been proposed: the identity index [6] the join index [12] the composite B tree [2] the nested join index [1], and the access support relation [5] All these indexes materialized the join results to expedite join processing. The performance of the scan join algorithm depends on two factors: the efficiency of the join index(es) step 1) and the efficiency of the page access sequence schedule (step 2) ....

E. Bertino and W. Kim. Indexing techniques for queries on nested objects. IEEE Transactions on Knowledge and Data Engineering, 1(2):196--214, June 1989.

....their path expressions[1,2] For example, #SELECT x.company. addressjtelephone) FROM person. parent x# is a query which retrieves person s parents addresses or telephone numbers. If we can shrink the search space of the tree when we evaluate RPEs, we can improve the performance. The path index[3] is proposed for path expressions in object oriented databases. However, all possible paths cannot be covered by this index due to the high storage requirements. The T index[7] is proposed for RPEs by reducing the 2 index[7] which supports any RPEs because of storage cost. In the worst case, the ....

Elisa Bertino and Won Kim. Indexing Techniques for Queries on Nested Objects. IEEE Transactions on Knowledge and Data Engineering, 1(2), 1989.

....general XML queries such as XML QL[10] and XQL. Some syntaxes, such as the star( in XML queries, enlarge the search space. In this example, almost all nodes under person must be visited because of person. Therefore, regular path indexes have been studied to solve this problem. The path index[4] is proposed for evaluating path expressions in object oriented databases. However, all possible paths cannot be covered by this index due to the high storage requirements. New indexing methods for semi structured data are proposed in [16, 22] to evaluate the regular path expressions more rapidly. ....

E. Bertino and W. Kim. Indexing Techniques for Queries on Nested Objects. IEEE Transactions on Knowledge and Data Engineering, 1(2), 1989.

....to the problem has been proposed by Kanellakis, Ramaswamy at al. KaRa94] They reduced the indexing a simple class attribute to external dynamic 2dimensional range searching and exploited data structures studied in computational geometry. Most techniques for indexing an aggregation hierarchy [BeKi89, BG93, Ber94, BeFo95] originate from the join index structure [Val87] Typically, an indexing structure for an aggregation hierarchy associates the values of nested attributes with the objects in the leading classes of the hierarchy [BeKi89] For fast evaluation of nested predicate, path index and nested index [BG93, ....

.... Most techniques for indexing an aggregation hierarchy [BeKi89, BG93, Ber94, BeFo95] originate from the join index structure [Val87] Typically, an indexing structure for an aggregation hierarchy associates the values of nested attributes with the objects in the leading classes of the hierarchy [BeKi89]. For fast evaluation of nested predicate, path index and nested index [BG93, BeFo95] support object instantiations along an entire hierarchy. Such solution has a rather poor performance for update operations, and it has thus been proposed to split the aggregation hierarchy into several fragments ....

Bertino, E., Kim, W., 1991,Indexing Techniques for Queries on Nested Objects. IEEE Trans. on Knowl. Data Eng.,v.1, No.2, pp.196-214.

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E. Bertino and W. Kim. Indexing techniques for queries on nested objects. IEEE Trans. on Knowledge and Data Engineering, 1(2):196--214, Jun 1989.

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E. Bertino, W. Kim. Indexing techniques for queries on nested objects. In IEEE TKDE, 1(2), 1989.

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E. Bertino and W. Kim. Indexing techniques for queries on nested objects. IEEE Trans. Knowledge and Data Engineering, 1(2):196--214, Jun 1989.

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E. Bertino and W. Kim. Indexing techniques for queries on nested objects. IEEE Trans. on Knowledge and Data Engineering, 1(2):196--214, 1989.

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