Oracle International Corporation

Nutanix, Inc.

Sigma Computing, Inc.

Dmitri Bronnikov

Binny Sher Gill

Jason D Frantz

Dmitry Mikhailovich Potapov

Ajaykrishna Raghavan

Varun Kumar Arora

Minghui Yang

Jaya Singhvi

Charles Wetherell

Timothy Sujay Isaacs

Peihong Huang

Prefetching query results using expanded queries including generating a database query using a state specification of a graphical user interface, wherein the database query is composed to retrieve initial results from a cloud-based data warehouse; determining that the database query is expandable; modifying the database query to retrieve expanded results from the cloud-based data warehouse, wherein the expanded results include the initial results; and fetching, from the cloud-based data warehouse, the expanded results using the modified database query.

Prefetching query results using expanded queries

Dynamic erasure coding for computing and data storage systems. A method embodiment commences upon accessing a set of fault tolerance policy attributes associated with the computing and data storage system. The topology of the system is analyzed to form mappings between the computing nodes of the system and the availability domains of the system. Based on the fault tolerance policy attributes, the topology, and the generated mapping, a plurality of feasible erasure coding configurations are generated. The feasible erasure coding configurations are scored. One or more high-scoring feasible erasure coding configurations are selected and deployed to the computing and data storage system. The method is repeated when there is a change in the fault tolerance policy attributes or in the topology. Depending on the topology and/or the nature of a change in the topology, more than one erasure coding configurations can be deployed onto the computing and data storage system.

Dynamic erasure coding

Systems and methods for key-value pair management. A method embodiment commences upon receiving data records comprising key-value pairs. The key-value pairs are stored in two locations, (1) in an in-memory data structure in a first storage tier, and (2) in a log file in a second storage tier. At some moment in time, an event causes a flush of the in-memory data structure. The flush operations comprise renaming the log file to refer to it as a uniquely identifiable data file in the second storage tier, and populating an index file in the second storage tier. Requests for a value corresponding to a key is satisfied by using the index file to access the uniquely identifiable data file by byte or word offset to a location in the data file so as to retrieve the value of the corresponding key.

Repurposing log files

A method for implementing erasure coding, including identifying a plurality of storage units, determining a number of storage unit failures to be tolerated, organizing data within the plurality of storage units as a matrix of rows and columns for computing one or more parity data, configuring the matrix to include one or more additional rows having preset values, computing the one or more parity data from the matrix that corresponds to the number of storage unit failures to be tolerated, wherein the one or more parity data comprises a row parity, a first diagonal parity, and a second diagonal parity, wherein the one or more additional rows having the preset values are used to compute the first diagonal parity and the second diagonal parity; and wherein the first diagonal parity comprises a different slope from the second diagonal parity.

Architecture for implementing erasure coding

After receipt of an instruction (e.g. a database statement), one or more computers specialize an interpreter with the received instruction as constant, to obtain a specialized interpreter that is stored in memory and/or disk. The specialized interpreter is then invoked to execute the received instruction. Depending on the embodiment, the interpreter being specialized may additionally be received and used in binary form without specialization. Specifically, in some embodiments, an identical interpreter is received in two forms: in a binary language specific to the one or more computers and also in a language that is acceptable to a specializer, such as a source language or an intermediate language. The interpreter in the binary language is invoked by default unless a predetermined condition for specialization is met. When the predetermined condition is met, the interpreter in the specializer-acceptable language is specialized by the specializer, and then the specialized interpreter is invoked.

Generation of machine code for a database statement by specialization of interpreter code

Systems, methods, media, and other embodiments associated with optimizing code motion with delayed exception handling are described. One exemplary system embodiment includes a data store to store information about a relocated instruction, a relocation logic to relocate instructions, and a run-time logic to detect exceptions raised by executed instructions. The run-time logic may selectively delay handling exceptions based on whether an executed instruction is a relocated instruction.

Optimizing code motion with delayed exception handling

A vulnerability analysis tool is provided for identifying SQL injection threats. The tool is able to take advantage of the fact that the code for many database applications is located in modules stored within a database. The tool constructs a data flow graph based on all, or a specified subset, of the application code within the database. The tool identifies, within the data flow graph, the nodes that represent values used to construct SQL commands. Paths to those nodes are analyzed to determine whether any SQL injection threats exist.

Growing community of inventors

Foster City, CA, United States of America

Dmitri Bronnikov