Oracle International Corporation

Hui Joe Chang

Zhen Hua Liu

Vikas Arora

Ying Lu

Douglas James McMahon

Beda Christoph Hammerschmidt

Muralidhar Krishnaprasad

Sundeep Abraham

Sriram Krishnamurthy

Geeta Arora

Joshua Jeffrey Spiegel

James W Warner

Susan M Kotsovolos

Aurosish Mishra

Hui Zhang

Srikrishnan Suresh

Alfonso Colunga Sosa

Juan R Loaiza

Tirthankar Lahiri

Thomas Baby

Ananth Raghavan

Ajit Mylavarapu

Anand Manikutty

Sukhada Pendse

Shubha Bose

Amit Ganesh

Vineet Marwah

Shasank Kisan Chavan

Teck Hua Lee

Balasubramanyam Sthanikam

Ying Li

Shubhro Jyoti Roy

Shashank Gugnani

Douglas J Mcmahon

JSON Duality Views are object views that return JDV objects. JDV objects are virtual because they are not stored in a database as JSON objects. Rather, JDV objects are stored in shredded form across tables and table attributes (e.g. columns) and returned by a DBMS in response to database commands that request a JDV object from a JSON Duality View. Through JSON Duality Views, changes to the state of a JDV object may be specified at the level of a JDV object. JDV objects are updated in a database using optimistic lock.

Natively supporting JSON duality view in a database management system

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.

Technique of efficiently, comprehensively and autonomously support native JSON datatype in RDBMS for both OLTP and OLAP

Techniques are described to improve query evaluation in computer systems. In an embodiment, a system receives a full text query for evaluation against a collection of hierarchically marked data object sets. The query specifies token(s) and context(s) which indicate hierarchical location(s) to match within a queried hierarchical data structure. To evaluate the query, the system determines a) data object set(s) that contain the query specified token(s) using token list(s), and/or b) data object set(s) that contain the query specified context(s) using label list(s).

Evaluating XML full text search

A 'hybrid derived cache' stores semi-structured data or unstructured text data in an in-memory mirrored form and columns in another form, such as column-major format. The hybrid derived cache may cache scalar type columns in column-major format. The structure of the in-memory mirrored form of semi-structured data or unstructured text data enables and/or enhances access to perform path-based and/or text based query operations. A hybrid derived cache improves cache containment for executing query operations. The in-memory mirrored form is used to compute queries in a transactionally consistent manner through the use of an invalid vector that used to determine when to retrieve the transactionally consistent persistent form of semi-structured data or unstructured text data in lieu of the in-memory form.

Techniques for enabling and integrating in-memory semi-structured data and text document searches with in-memory columnar query processing

The present invention relates to autonomous tuning of a data grid of documents in a database. Herein are techniques for storage cells to autonomously maintain local indices and other optimization metadata and algorithms to accelerate selective access into a distributed collection of documents. In an embodiment, each storage cell persists a respective subset of documents. Each storage cell stores, in memory, respective index(s) that map each item to location(s), in one or more documents of the respective subset of documents, where the item occurs. One or more computers execute, based on at least a subset of the indices of the storage cells, a data access request from a database management system. In an embodiment, a cloud of JSON document services provides an easy-to-use, fully autonomous JSON document database that horizontally and elastically scales to deliver fast execution of document transactions and queries without needing tuning by a database administrator.

Technique of comprehensively support autonomous JSON document object (AJD) cloud service

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.

LOB query performance via automatic inference of locator-less LOB by value semantics

Methods and systems for improved query evaluation in computer systems are provided. A system receives a full text query for evaluation against a collection of XML documents. The query comprises specifies one or more tokens and one or more contexts. The contexts each represent a path within an XML expression. The query is used to make multiple determinations. First, determining, using token lists, first documents that contain the tokens included in the query. Second, determining, using tag lists, second documents that contain the contexts included in the query. Third, determining third documents by comparing the first documents and the second documents to determine which documents contain both the tokens and the contexts. The query is then evaluated in view of the third documents.

In an approach, the database server generates a request for data representing rows of a table, the request identifying one or more data blocks stored on a storage system. The database server then generates metadata describing one or more filtering conditions to be applied to the rows and sends the metadata along with the request to the storage system. The storage system, when applying filtering conditions to a column containing a LOB, determines whether the LOB is stored in-line or out-of-line. If the column contains an out-of-line LOB, the storage system skips the filtering conditions on the column. If the column contains an in-line LOB, the storage system applies the filtering conditions to the column. Upon obtaining the filtered data from the storage system, the database server retrieves the data blocks for out-of-line LOBs and applies the skipped filtering conditions to create a final result set.

Predicate offload of large objects

A query may be rewritten to leverage information stored in a structured XML index. An operator in the query may be analyzed to determine an input source database object for the operator by traversing an operator tree rooted at the operator. The path expressions associated with the operator tree may be fused together to form an effective path expression for the operator. If the effective path expression directly matches a path expression derived from the index, the query may be rewritten using references to the index. Operators in a query that have effective paths that refer to data in the same index table may be grouped together. A single subquery may be written for a group of operators. Also, a structured XML index may be used as an implied schema for indexed XML data. This implied schema may be used to optimize queries that refer to the indexed XML data.

Leveraging structured XML index data for evaluating database queries

A mechanism is provided for accessing XML data in a database system using a combination of a XML Table Index table and a XML Path Index table. By using a combination of a XML Table Index and a XML Path Index, both selection access and navigational access involved in a query can be optimized. For example, the XML Table Index gives the database system an ability to readily evaluate the predicate expression, thereby improving the selection access. Moreover, in some embodiments, the selection access can be further improved by using secondary indexes on columns contained in the XML Table Index table. In a complementary manner, the XML Path Index table gives the database system an ability to navigate to a specific location given a path expression, thereby improving the navigational access. Thus, by combining both tables, both selection and navigational accesses are improved.

Techniques of efficient XML query using combination of XML table index and path/value index

The approaches described herein provide an efficient way to process certain kinds of queries that update XML data stored in an object-relational database. A query may include an XML query expression that conforms to a language for querying XML documents. A technique first determines whether the query contains an XML updating expression, and in response rewrites the query to comprise one or more path-based query operators that specify operations for updating XML data. The query may then be further rewritten to comprise one or more storage format specific query operators based on the particular database storage format associated with the XML data specified in the query. The rewritten query operators are used to generate a query execution plan that provides for several query execution optimizations.

Techniques for efficiently supporting XQuery update facility in SQL/XML

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San Jose, CA, United States of America

Hui Joe Chang