Abstract: A communication method implemented by a first network device, the method includes receiving, by the first network device, a first packet. The first packet may include a first segment identifier (SID) and a second SID. Determining, by the first network device whether the first SID is unavailable. If the first SID is unavailable, the first network device obtains the second SID based on the first SID, and updates a destination address in the first packet with the second SID, to generate a second packet.

Abstract: System, method, and computer program product to modify a received query, the received query including a first predicate specifying a comparison operator and a second predicate specifying an IS NULL operator, by replacing the comparison operator of the first predicate with an extended comparison operator, and removing the IS NULL operator from the received query, the extended comparison operator configured to support searching of NULL values in a database management system (DBMS), wherein the extended comparison operator is configured to return rows having column data matching a value predefined to represent NULL values.

Abstract: System, method, and computer program product to modify a received query, the received query including a first predicate specifying a comparison operator and a second predicate specifying an IS NULL operator, by replacing the comparison operator of the first predicate with an extended comparison operator, and removing the IS NULL operator from the received query, the extended comparison operator configured to support searching of NULL values in a database management system (DBMS), wherein the extended comparison operator is configured to return rows having column data matching a value predefined to represent NULL values.

Abstract: System, method, and computer program product to modify a received query, the received query including a first predicate specifying a comparison operator and a second predicate specifying an IS NULL operator, by replacing the comparison operator of the first predicate with an extended comparison operator, and removing the IS NULL operator from the received query, the extended comparison operator configured to support searching of NULL values in a database management system (DBMS), wherein the extended comparison operator is configured to return rows having column data matching a value predefined to represent NULL values.

Abstract: System, method, and computer program product to modify a received query, the received query including a first predicate specifying a comparison operator and a second predicate specifying an IS NULL operator, by replacing the comparison operator of the first predicate with an extended comparison operator, and removing the IS NULL operator from the received query, the extended comparison operator configured to support searching of NULL values in a database management system (DBMS), wherein the extended comparison operator is configured to return rows having column data matching a value predefined to represent NULL values.

Abstract: According to one embodiment of the present invention, a system processes a database query, and comprises a computer system including at least one processor. The system identifies one or more expressions within the database query utilizing a database object with value masking. Masking requirements are determined for each identified expression and the database object utilized by that identified expression is replicated to provide masked and actual versions of that database object in response to the masking requirements for that expression including masked values and actual values of that database object. The value masking of the database object is applied to the identified expressions within the database query based on the determined masking requirements to produce search results with masked values for the database query. Embodiments of the present invention further include a method and computer program product for processing a database query in substantially the same manner described above.

Abstract: According to one embodiment of the present invention, a system processes a database query, and comprises a computer system including at least one processor. The system identifies one or more expressions within the database query utilizing a database object with value masking. Masking requirements are determined for each identified expression and the database object utilized by that identified expression is replicated to provide masked and actual versions of that database object in response to the masking requirements for that expression including masked values and actual values of that database object. The value masking of the database object is applied to the identified expressions within the database query based on the determined masking requirements to produce search results with masked values for the database query. Embodiments of the present invention further include a method and computer program product for processing a database query in substantially the same manner described above.

Abstract: A compilation time estimator provides a quantified estimate of the optimizer compilation time for a given query optimizer. The estimator automates the optimizer to choose the right level of optimization in commercial database systems. The estimator reuses an optimizer's join enumerator to obtain actual number of joins, but bypasses plan generation to save estimation overhead, and maintains a small number of interesting physical properties to estimate the number of plans by using a linear regression model. The estimator uses the number of generated plans to estimate query compilation time.

Abstract: A method is provided for generating a materialized view recommendation for at least one back-end server that is connected to a front-end server in a heterogeneous, distributed database system that comprises parsing a workload of federated queries to generate a plurality of query fragments; invoking a materialized view advisor on each back-end server with the plurality of query fragments to generate a set of candidate materialized views for each of the plurality of query fragments; identifying a first set of subsets corresponding to all nonempty subsets of the set of candidate materialized views for each of the plurality of query fragments; identifying a second set of subsets corresponding to all subsets of the first set of subsets that are sorted according to a dominance relationship based upon a resource time for the at least one back-end server to provide results to the front-end server for each of the first set of subsets; and performing a cost-benefit analysis of each of the second set of subsets to deter

Abstract: A compilation time estimator provides a quantified estimate of the optimizer compilation time for a given query optimizer. The estimator automates the optimizer to choose the right level of optimization in commercial database systems. The estimator reuses an optimizer's join enumerator to obtain actual number of joins, but bypasses plan generation to save estimation overhead, and maintains a small number of interesting physical properties to estimate the number of plans by using a linear regression model. The estimator uses the number of generated plans to estimate query compilation time.

Abstract: A compilation time estimator provides a quantified estimate of the optimizer compilation time for a given query optimizer. The estimator automates the optimizer to choose the right level of optimization in commercial database systems. The estimator reuses an optimizer's join enumerator to obtain actual number of joins, but bypasses plan generation to save estimation overhead, and maintains a small number of interesting physical properties to estimate the number of plans by using a linear regression model. The estimator uses the number of generated plans to estimate query compilation time.

Abstract: A compilation time estimator provides a quantified estimate of the optimizer compilation time for a given query optimizer. The estimator automates the optimizer to choose the right level of optimization in commercial database systems. The estimator reuses an optimizer's join enumerator to obtain actual number of joins, but bypasses plan generation to save estimation overhead, and maintains a small number of interesting physical properties to estimate the number of plans by using a linear regression model. The estimator uses the number of generated plans to estimate query compilation time.