Abstract: Upon receiving a query at a local database server from a client directed to a LOB stored at a remote database server, a remote LOB locator is created comprising a local LOB locator indicating the LOB's location and a database link associated with the remote database server. The remote LOB locator is communicated to the client, which submits a request to the local database server to perform an operation directed to the LOB. The request is forwarded to the remote database server using the remote LOB locator, where the operation is performed. This mechanism is extended to work with sharded databases. Character set conversions are minimized when returning data to the client from the remote database server. Remote LOB locators may serve as bind variables for DML statements directed to local or remote tables. Local LOB locators may serve as bind variables for DML statements directed to remote tables.

Abstract: Herein is a self-tuning database management system (DBMS) storing JavaScript object notation (JSON) documents and operating a JSON datatype as native to the DBMS. In an embodiment, a computer hosts a DBMS that executes a data definition language (DDL) statement that defines, in a database dictionary of the DBMS, a JSON document column of a database table that stores JSON documents as instances of the JSON datatype that is native in the DBMS. The DBMS may autonomously set or adjust configuration settings that control behaviors such as a default width of a JSON document column, in lining or not of the JSON document column, kind and scope and duration of indexing of the JSON document column, and/or caching of the JSON document column such as in an in memory columnar unit (IMCU). The DBMS may use the various configuration settings to control how JSON documents and the native JSON datatype are stored and/or processed.

Abstract: Herein is a self-tuning database management system (DBMS) storing JavaScript object notation (JSON) documents and operating a JSON datatype as native to the DBMS. In an embodiment, a computer hosts a DBMS that executes a data definition language (DDL) statement that defines, in a database dictionary of the DBMS, a JSON document column of a database table that stores JSON documents as instances of the JSON datatype that is native in the DBMS. The DBMS may autonomously set or adjust configuration settings that control behaviors such as a default width of a JSON document column, in lining or not of the JSON document column, kind and scope and duration of indexing of the JSON document column, and/or caching of the JSON document column such as in an in memory columnar unit (IMCU). The DBMS may use the various configuration settings to control how JSON documents and the native JSON datatype are stored and/or processed.

Abstract: Herein is a self-tuning database management system (DBMS) storing JavaScript object notation (JSON) documents and operating a JSON datatype as native to the DBMS. In an embodiment, a computer hosts a DBMS that executes a data definition language (DDL) statement that defines, in a database dictionary of the DBMS, a JSON document column of a database table that stores JSON documents as instances of the JSON datatype that is native in the DBMS. The DBMS may autonomously set or adjust configuration settings that control behaviors such as a default width of a JSON document column, in lining or not of the JSON document column, kind and scope and duration of indexing of the JSON document column, and/or caching of the JSON document column such as in an in memory columnar unit (IMCU). The DBMS may use the various configuration settings to control how JSON documents and the native JSON datatype are stored and/or processed.

Abstract: Herein is a self-tuning database management system (DBMS) storing JavaScript object notation (JSON) documents and operating a JSON datatype as native to the DBMS. In an embodiment, a computer hosts a DBMS that executes a data definition language (DDL) statement that defines, in a database dictionary of the DBMS, a JSON document column of a database table that stores JSON documents as instances of the JSON datatype that is native in the DBMS. The DBMS may autonomously set or adjust configuration settings that control behaviors such as a default width of a JSON document column, in lining or not of the JSON document column, kind and scope and duration of indexing of the JSON document column, and/or caching of the JSON document column such as in an in memory columnar unit (IMCU). The DBMS may use the various configuration settings to control how JSON documents and the native JSON datatype are stored and/or processed.

Abstract: Herein is a self-tuning database management system (DBMS) storing JavaScript object notation (JSON) documents and operating a JSON datatype as native to the DBMS. In an embodiment, a computer hosts a DBMS that executes a data definition language (DDL) statement that defines, in a database dictionary of the DBMS, a JSON document column of a database table that stores JSON documents as instances of the JSON datatype that is native in the DBMS. The DBMS may autonomously set or adjust configuration settings that control behaviors such as a default width of a JSON document column, in lining or not of the JSON document column, kind and scope and duration of indexing of the JSON document column, and/or caching of the JSON document column such as in an in memory columnar unit (IMCU). The DBMS may use the various configuration settings to control how JSON documents and the native JSON datatype are stored and/or processed.

Abstract: Described are improved systems, computer program products, and methods for an improved approach to access small to medium size objects (MOBs) stored in LOB data type columns of a RDBMS. The approach includes receiving a SQL statement comprising a retrieval of a large object (LOB). The approach also includes determining whether to return a value of the LOB or a reference to a storage location storing the value of the LOB based on: a data dictionary property of the LOB to return the value of the LOB, a function included in the SQL statement to return the value of the LOB, or a flag derived from a SQL operator tree propagation to return the value of the LOB.

Abstract: Herein is a self-tuning database management system (DBMS) storing JavaScript object notation (JSON) documents and operating a JSON datatype as native to the DBMS. In an embodiment, a computer hosts a DBMS that executes a data definition language (DDL) statement that defines, in a database dictionary of the DBMS, a JSON document column of a database table that stores JSON documents as instances of the JSON datatype that is native in the DBMS. The DBMS may autonomously set or adjust configuration settings that control behaviors such as a default width of a JSON document column, in lining or not of the JSON document column, kind and scope and duration of indexing of the JSON document column, and/or caching of the JSON document column such as in an in memory columnar unit (IMCU). The DBMS may use the various configuration settings to control how JSON documents and the native JSON datatype are stored and/or processed.

Abstract: Described are improved systems, computer program products, and methods for an improved approach to access small to medium size objects (MOBs) stored in LOB data type columns of a RDBMS. The approach includes receiving a SQL statement comprising a retrieval of a large object (LOB). The approach also includes determining whether to return a value of the LOB or a reference to a storage location storing the value of the LOB based on: a data dictionary property of the LOB to return the value of the LOB, a function included in the SQL statement to return the value of the LOB, or a flag derived from a SQL operator tree propagation to return the value of the LOB.

Abstract: An approach for improving LOB query performance via automatic inference of locator-less LOB by value semantics in a relational database system is provided. A relational database management system (RDBMS) is implemented to perform operations on LOBs based on the semantics of a statement. During statement compilation, the RDBMS identifies inline LOB column(s) that are not required to be returned to a client. During execution, the identified column(s) are accessed via a shared buffer cache and fed to an operator for evaluation. For inline LOB column(s) that must be returned to the client, during execution, the inline LOB data is copied from the shared buffer cache to a temporary buffer area. Data in the temporary buffer area is fed to an operator for evaluation and is used to create a LOB locator for the inline LOB column(s) that must be returned to the client.

Abstract: An approach for improving LOB query performance via automatic inference of locator-less LOB by value semantics in a relational database system is provided. A relational database management system (RDBMS) is implemented to perform operations on LOBs based on the semantics of a statement. During statement compilation, the RDBMS identifies inline LOB column(s) that are not required to be returned to a client. During execution, the identified column(s) are accessed via a shared buffer cache and fed to an operator for evaluation. For inline LOB column(s) that must be returned to the client, during execution, the inline LOB data is copied from the shared buffer cache to a temporary buffer area. Data in the temporary buffer area is fed to an operator for evaluation and is used to create a LOB locator for the inline LOB column(s) that must be returned to the client.

Abstract: Upon receiving a query at a local database server from a client directed to a LOB stored at a remote database server, a remote LOB locator is created comprising a local LOB locator indicating the LOB's location and a database link associated with the remote database server. The remote LOB locator is communicated to the client, which submits a request to the local database server to perform an operation directed to the LOB. The request is forwarded to the remote database server using the remote LOB locator, where the operation is performed. This mechanism is extended to work with sharded databases. Character set conversions are minimized when returning data to the client from the remote database server. Remote LOB locators may serve as bind variables for DML statements directed to local or remote tables. Local LOB locators may serve as bind variables for DML statements directed to remote tables.

Abstract: A method and apparatus for automatically analyzing and providing feedback regarding the optimizability of a relational database query. A query developer's primary goal is to ensure that queries and DML operations are rewritten for the most efficient execution. Rewrite diagnosability captures metadata for each attempted query optimization including success or failure and the reasons for failure. The metadata is stored in association with the operators that were not removed through rewriting. Once all optimizations have been attempted and rewriting is complete, the metadata is selectively displayed based on the cost to perform the associated operation. The context of performing the operation may affect the cost. The cost may be based at least on the type of operation and where within the query tree the operation is located. A query developer may configure the database system not to execute the resulting query plan based on one or more criteria.

Abstract: A method and apparatus for receiving objects is provided. Embodiments provide for receiving, from a source database server, at a target database server, an object. If the object type of the object is involved in an inheritance hierarchy, then the target database server inspects the object to determine a source identifier that identifies to a source database server the object type associated with the object. The target database determines a target identifier that identifies to the target database server the object type associated with the object based on a mapping that associates source identifiers to target identifiers. Alternately, if the object type of the object is not involved in an inheritance hierarchy, then the target database server inspects the object to determine a set of characteristics of the object. The target database server determines the target identifier for the object based on the characteristics of the object.

Abstract: A method and apparatus for automatically analyzing and providing feedback regarding the optimizability of a relational database query. A query developer's primary goal is to ensure that queries and DML operations are rewritten for the most efficient execution. Rewrite diagnosability captures metadata for each attempted query optimization including success or failure and the reasons for failure. The metadata is stored in association with the operators that were not removed through rewriting. Once all optimizations have been attempted and rewriting is complete, the metadata is selectively displayed based on the cost to perform the associated operation. The context of performing the operation may affect the cost. The cost may be based at least on the type of operation and where within the query tree the operation is located. A query developer may configure the database system not to execute the resulting query plan based on one or more criteria.

Abstract: Techniques are described herein for altering the datatype of a column without having to immediately migrate the data items that currently reside in the column. In one embodiment, the alteration is performed without migration by creating a new column having the desired datatype while retaining the old column. Instead of migrating the data items from to the new column at the time the column is altered, the items remain in the original column until the items are updated.

Abstract: Efficiently replicating XML data among databases includes techniques for (a) replicating XML data involved with an insert operation; (b) replicating XML data involved with an update operation; (c) leveraging existing relational replication techniques for XML data stored in shredded form using object-relational constructs; and (d) replicating XQuery Data Model sequences. Each technique reduces the amount of information that would otherwise need to be transmitted over a network for XML data replication purposes.

Abstract: Systems, methods, and other embodiments associated with selectively acquiring and utilizing query statistics are described. One example method includes selectively acquiring statistics associated with search queries submitted to a search process during a sample period. The statistics may be associated with an index and tokens associated with the index and search queries. The method may also include selecting tokens and/or queries to optimize based, at least in part, on the statistics. In one example, whether and/or how the tokens and/or queries are optimized may depend on estimating index fragmentation based, at least in part, on the statistics.

Abstract: Instances of complex types are logically replicated. In general, the logical replication of complex types involves converting a complex type instance from its storage format into a logical representation written in a markup language, like XML. The logical representation is then propagated to a destination (or destinations), which converts the logical representation to a storage format used at the destination for that complex type.

Abstract: Techniques for partitioning nested tables are provided. A parent table includes a column for collection items. A nested table is created for storing items that belong to the collection items. The nested table is partitioned to create a plurality of nested table partitions. Each nested table partition is a distinct, separately stored structure within a database. How the nested table is partitioned may, or may not, be based on how the parent table is partitioned. For example, a nested table may be partitioned based on the same criteria in which the parent table is partitioned. As another example, a nested table may be partitioned, whereas the parent table is not partitioned.