Oracle International Corporation

Weiwei Gong

Shasank Kisan Chavan

James Kearney

Dieter Gawlick

William Martinez Cortes

Garret Frederick Swart

Christoph Bussler

Tirthankar Lahiri

Vasudha Krishnaswamy

Chinmayi Krishnappa

Kangnyeon Kim

Jim Kearney

Harshada Chavan

A Lock-Free Reservation mechanism is provided. When a transaction issues an update that affects a value in a 'reservable column' of a row, the database server does not immediately obtain a lock that covers the row. Instead, the database server adds a reservation to a reservation journal. At the time the transaction commits, a lock is obtained and the requested update is made. In one implementation, before adding the reservation to the reservation journal, the database server determines whether making the update would violate any constraints involving the reservable column. In one implementation, the constraint check not only takes into account the current value of the data item that is being updated and the amount of the update, but also pre-existing reservations in the reservation journal that affect the same data item.

System and method for increased transaction throughput and improved response time under high contention

Data structures and methods are described to enable a hardware optimized dynamic string table for accelerating relational database queries. A method comprises retrieving a lookup key for a query against a dynamic string table, the lookup key associated with a key length and a key hash. The method further comprises configuring a formatted lookup key as in-line or out-of-line based on whether the key length exceeds a maximum inline key size. The method further comprises replicating, into a first plurality of single instruction, multiple data (SIMD) lanes, the formatted lookup key. The method further comprises writing a candidate bucket, selected from the dynamic string table based on the key hash, into a second plurality of SIMD lanes. The method further comprises performing a SIMD compare of the first plurality of SIMD lanes and the second plurality of SIMD lanes, and returning an associated code when the lookup key is matched.

Hardware optimized string table for accelerated relational database queries

An append operation is provided for using a plurality of threads on a plurality of streaming multiprocessors of a graphical processing unit. The append operation writes results into a result buffer. Executing the append operation comprises claiming, by each given thread within the plurality of threads having a result to write, a portion of a selected WCB, writing, by the given thread, the result to the portion of the selected WCB, and in response to a flush condition being met for the selected WCB, copying contents of the selected WCB to a result buffer.

GPU-optimized append operation with latch-free write combining on shared memory

The present invention relates to optimized access of a database. Herein are techniques to accelerate execution of any combination of ad hoc query, heterogenous hardware, and fluctuating workload. In an embodiment, a computer receives a data access request for data tuples and compiles the data access request into relational operators. A particular implementation of a particular relational operator is dynamically selected from multiple interchangeable implementations. Each interchangeable implementation contains respective physical operators. A particular hardware operator for a particular physical operator is selected from multiple interchangeable hardware operators that include: a first hardware operator that executes on first processing hardware, and a second hardware operator that executes on second processing hardware that is functionally different from the first processing hardware. A response to the data access request is generated based on: the data tuples, the particular implementation of the particular relational operator, and the particular hardware operator.

Techniques of heterogeneous hardware execution for SQL analytic queries for high volume data processing

Herein are techniques for dynamic aggregation of results of a database request, including concurrent grouping of result items in memory based on quasi-dense keys. Each of many computational threads concurrently performs as follows. A hash code is calculated that represents a particular natural grouping key (NGK) for an aggregate result of a database request. Based on the hash code, the thread detects that a set of distinct NGKs that are already stored in the aggregate result does not contain the particular NGK. A distinct dense grouping key for the particular NGK is statefully generated. The dense grouping key is bound to the particular NGK. Based on said binding, the particular NGK is added to the set of distinct NGKs in the aggregate result.

Cache conscious techniques for generation of quasi-dense grouping codes of compressed columnar data in relational database systems

The present invention relates to join acceleration. In an embodiment, a computer receives a request for a relational join of build data rows with probe data rows. Based on the request for the relational join, a particular kind of data map from many kinds of data map that can implement the relational join is dynamically selected. Based on the build data rows, an instance of the particular kind of data map is populated. A response is sent for the request for the relational join that is based on the probe data rows and the instance of the particular kind of data map.

Hardware friendly key value table design to support relational hash join

The present invention relates to hash join acceleration. In an embodiment, a computer receives a request to join build data rows with probe data rows. Each data row is associated with a respective join key value. From multiple buckets of a hash table, a bucket is selected that contains entries of multiple respective join key values in respective locations within the bucket. Whether or not the bucket contains an entry of the join key value of a build data row is detected. While building, multiple locations within the bucket are concurrently inspected to find an empty location in which to store the entry of the join key value of the build data row. The bucket is concurrently probed to detect whether or not the entries in the bucket include an entry of a join key value of a probe data row. For the join request, a response is sent that is based on the concurrent probing of the bucket.

Accelerated building and probing of hash tables using symmetric vector processing

For join acceleration, a computer stores local encoding dictionaries (ED), including a build ED that contains a plurality of distinct build dictionary codes (DC) and a probe ED that contains a plurality of distinct probe DCs that is not identical to the plurality of distinct build DCs (BDC). Build data rows (DR) that contain a build key that contains BDCs from the plurality of distinct BDCs is stored. Probe DRs that contain a probe key that contains probe DCs from the plurality of distinct probe DCs is stored. A request for a relational join of the build DRs with the probe DRs is received. The BDCs from the build key and the probe DCs from the probe key are transcoded to global DCs (GDC) of a global ED. Based on GDCs for the build key, a build array whose offsets are respective GDCs of the global ED is populated. Based on GDCs for the probe key, offsets of the build array are accessed. A response to the request for the relational join that is based on accessing offsets of the build array is sent.

Technique for fast join processing of dictionary encoded key columns in relational database systems

Techniques related to an in-memory key-value store for a multi-model database are disclosed. In an embodiment, a relational database may be maintained on persistent storage. The relational database may be managed by a database server and may include a database table. The database table may be stored in a persistent format. Key-value records may be generated within volatile memory accessible to the database server by converting data in the database table to a key-value format. The key-value format may be different from and independent of the persistent format. A database statement referencing the database table may be executed based on determining whether to access one or more key-value records in the volatile memory or to access the data in the database table. In response to determining to access the one or more key-value records, the database server may access the one or more key-value records in the volatile memory.

Growing community of inventors

Belmont, CA, United States of America

Weiwei Gong