Abstract: The example embodiments are directed to a system and method for detecting phantom data items in a blockchain transaction. In an example, the method includes one or more of generating a transaction data set during a read phase of a blockchain transaction, the transaction data set including an identification of each query of the transaction executed during the read phase and results of each query, generating a validation data set by re-executing each query during a validation phase of the blockchain transaction, the validation data set including query results of each respective re-executed query, determining whether the blockchain transaction observes one or more phantom data items based on the query results of the transaction data set and the validation data set, and, in response to determining the transaction observes the one or more phantom data items, preventing the transaction data set from being written to the blockchain.

Abstract: The example embodiments are directed to a system and method for detecting phantom data items in a blockchain transaction. In an example, the method includes one or more of generating a transaction data set during a read phase of a blockchain transaction, the transaction data set including an identification of each query of the transaction executed during the read phase and results of each query, generating a validation data set by re-executing each query during a validation phase of the blockchain transaction, the validation data set including query results of each respective re-executed query, determining whether the blockchain transaction observes one or more phantom data items based on the query results of the transaction data set and the validation data set, and, in response to determining the transaction observes the one or more phantom data items, preventing the transaction data set from being written to the blockchain.

Abstract: An improved method and system for preserving data constraints during parallel apply in asynchronous transaction replication in a database system have been disclosed. The method and system preserves secondary unique constraints and referential integrity constraints, while also allowing a high degree of parallelism in the application of asynchronous replication transactions. The method and system also detects and resolves ordering problems introduced by referential integrity cascade deletes, and allows the parallel initial loading of parent and child tables of a referential integrity constraint.

Abstract: An XML query compilation processor (20) includes an execution compiler (42) that transforms an XML query into an executable XML query plan (22). A query rewrite processor (34) performs query transformations on the XML query. Said query transformations include transforming an expression input (60) received by an expression (62) conditional upon a set of items defined by an output (64) of the expression (62) being independent of grouping of items in the expression input (60).

Abstract: A method for using pre-computed information stored in auxiliary structures to speed up processing of expensive queries on hierarchical documents such as XML documents being queried using XPath. The invention defines a taxonomy of such structures such as indexes and materialized views for storing pre-computed XPath results (PXRs), determines what portion of the query can be evaluated by the structures, and computes the compensation for the results generated by the structures. The invention detects all structures applicable to the query and rewrites the query to use such structures, speeding up the performance of the queries. The invention identifies the matching structures by detecting containment mappings between XPath expressions in the query and the structure. The invention also includes a new representation for XPath expressions that is rich enough to express all features of XPath.

Abstract: Disclosed is a method and system for incrementally maintaining algebraic functions in automatic summary tables (ASTs) of at least one relational database. The method associates a work area with each algebraic function in each AST. Each work area is comprised of one or more variables. The method populates the variables within each work area for each algebraic function when each AST is created and when each AST is updated. The method maintains each work area by adding and subtracting to and from its associated variables when the associated data changes in the relational database. The functions that compute the variables of the work areas are distributive and thus incrementally maintainable. The method computes and recomputes the algebraic function within an AST after the updates have changed one or more of the variables of its workarea.