Oracle International Corporation

Linkedin Corporation

Bhaskar Ghosh

Thierry Cruanes

Benoit Dageville

Rushan Chen

Rafi Ahmed

Subramanian Muralidhar

Andrew Witkowski

Mohamed Zait

Ashish Thusoo

Shrikanth Shankar

Hermann Baer

Adiel Yoaz

Ravi Murthy

William H Waddington

Kapil Laxmikant Surlaker

Srikanth Bellamkonda

Dinesh Das

Sankar Subramanian

Harmeek Singh Bedi

Patrick A Amor

Ajay Sethi

Shirshanka Das

Nathan K Folkert

Allison Waingold

Chavdar Botev

Shashaanka Agrawal

Jemiah Westerman

Appla Jagadesh Padala

Lei Gao

Jean-Luc Vaillant

Mitch Stuart

Dane Roberts

Hernan Capdevila

A method of maintaining a data store is disclosed. The data store is distributed across a plurality of storage provider instances, including a master storage provider instance and a plurality of additional storage provider instances. A master data log is updated to reflect a change to the data store. The master data log is synchronized with a plurality of replicas of the master data log. The change is propagated across the plurality of additional storage provider instances based on an analysis of the replicas.

Middleware data log system

A computer-readable medium, computer-implemented method, and apparatus are provided. In one embodiment, financial data is extracted from a financial manager, and the financial data is mapped to compliance data from a compliance manager. One or more controls of one or more accounts from compliance data is selected to be in scope, and an assessment plan is created for the selected one or more controls within scope.

Financial audit scoping workbench

Techniques are described for parallelizing qualifying window functions without reliance on partitioning criteria specified in the command that includes the qualifying window functions. Because the techniques do not rely on partitioning criteria specified in the command, the techniques may be used on commands in which no partitioning criteria is specified. In general, the techniques involve partitioning the work of a qualified window function into ranges, and sharing precomputed aggregate values between computational elements to calculate the value for the window functions.

Parallel execution of window functions

Techniques are provided for executing query statements, or portions thereof, in parallel without using slave SQL to communicate to each slave the operations to be performed by the slave. Instead of generating one cursor for the query coordinator (QC) based on the original statement, and separate cursors for each DFO based on the slave SQL, the techniques involve sharing the cursor that is generated from the original statement among the various participants involved in the parallel execution of the operations specified in the original statement.

Compilation and processing a parallel single cursor model

Techniques are provided for generating execution plans for, and executing, database statements that contain filter subqueries. Upon receiving a database statement that contains a filter subquery, the database server builds an execution plan that includes a filter operation that is fed by a subtree that corresponds to the subquery. The database server performs a cost analysis to determine whether (1) the filter operation should be parallelized, and (2) the subquery tree should be parallelized. Techniques are also described for generating plans and executing queries where (1) both the filter operation and the subquery subtree are parallelized, (2) the filter operation is parallelized but the subquery subtree operation is performed serially, and (3) the filter operation is performed serially but the subquery subtree operation is parallelized.

Executing filter subqueries using a parallel single cursor model

Techniques are provided for delaying evaluation of expensive expressions in a query. Expensive expressions in the query are established by cost information or by looking up a list of known expensive expressions for a match. After an execution plan is determined by using the early evaluation technique, one or more equivalent execution plans is established. The one or more equivalent execution plans may include both a type of execution plans that delay evaluation of expensive expressions and a type of execution plans that do not. In addition, the one or more equivalent execution plans may include both parallelized and non-parallelized alternatives to the execution plan identified by the early evaluation technique. Finally, based on a set of criteria, which may include comparing cost information among all the equivalent execution plans generated thus far, the best execution plan is chosen for the query.

Delaying evaluation of expensive expressions in a query

Various techniques are described for processing database commands that include MINUS and/or INTERSECT operators. The queries containing the MINUS and/or INTERSECT operators are transformed to create a plurality of transformed queries. Each of the transformed queries produces the same result as the original query, but does not include the MINUS and/or INTERSECT operator. To achieve the same result set as the original query, the transformed queries employ equijoins, antijoins, and/or semijoins, and duplicate elimination operations. Costs are estimated for each of the various transformed queries. Based on the cost estimates, one of the transformed queries is selected as the query that is to be executed to perform the operations specified in the original query.

Multi-tiered query processing techniques for minus and intersect operators

Techniques are provided for performing a parallel aggregation operation on data that resides in a container, such as a relational table. During generation of the execution plan for the operation, it is determined whether partition-wise aggregation should be performed, based on the grouping keys involved in the aggregation and the partition keys used to partition the container. If partition-wise aggregation is to be performed, then the assignments given to the slave processes that are assigned to scan a container are made on a partition-wise basis. The scan slaves themselves may perform full or partial aggregation (depending on whether they are the only scan slaves assigned to the partition). If the scan slaves perform no aggregation, or only partial aggregation, then the scan slaves redistribute the data items to aggregation slaves that are local to the scan slaves.

Parallel partition-wise aggregation

Techniques are provided for executing database statements, or portions thereof, in parallel without using slave SQL to communicate to each slave the operations to be performed by the slave. Techniques are provided for incorporating within a shared cursor the code fragments that govern both sides of the interaction between a query coordinator (QC) and remotely-located slaves. Further, techniques are provided for the QC to communicate with each slave on how and which portions of the execution plan to execute and when. A state-transition engine for slave execution under the control of the query-coordinator is also provided.

Executing a parallel single cursor model

Various techniques are described for processing database commands that include MINUS and/or INTERSECT operators. According to one technique, the database server executes the MINUS/INTERSECT in a specialized rowsource in parallel. In one approach, the specialized rowsource implements a sort merge-join like solution, where: a DISTINCT SORT is performed on each input, a left and right pointer is maintained on the respective input streams of tuples, the left or right pointer is incremented based on whether there is a match between the tuples pointed-to by the pointers, and the tuple of the left side is returned (or not returned) based on whether there is a match. Techniques are described for generating multiple query plans for executing a query, where each of the query plans includes a plan portion for executing, in parallel, the operation associated with a MINUS/INTERSECT operator. Cost estimates are generated for the query plans. The database server selects from the query plans a particular query plan to execute based, at least in part, on the cost estimates.

Parallel query processing techniques for minus and intersect operators

While generating an execution plan for a database statement that includes a user-defined table function that requires partitioning of input data to the function, it is determined whether the partitioning of output data from an operation that feeds the function is compatible with the partitioning required by the function. If the partitioning of output data from the operation that feeds the function is compatible with the partitioning required by the function, then the execution plan is constructed to specify execution of both (1) the function and (2) the operation that feeds the function, by a same set of processes. For example, the operation that feeds the function and the function itself are clumped into the same sub-plan or sub-tree, which is scheduled and run in parallel on a set of parallel execution slaves.

Communication optimization for parallel execution of user-defined table functions

A database statement is processed in a multi-server system, in a manner to increase the possibility that slave server processes on remote nodes will generate execution plans that are equivalent to the corresponding execution plan generated by the query coordinator process. A set of hints is generated based on the same information on which the master plan is based. The set of hints is sent to remote nodes, where respective remote plans are generated based in part on the set of hints. Use of the hints in generation of the remote plan increases the possibility that the remote plan will be equivalent to the master plan and that the slaves on the other database server will be able to join in parallel processing of the database statement.

Query processing in a parallel single cursor model on multi-instance configurations, using hints

Techniques are provided for processing a database statement that includes a table function capable of parallel execution, where the input of the table function is specified in a subquery. During compilation of the database statement, a global cursor is generated for the database statement. The global cursor includes a first plan component for executing the table function and a second plan component for generating input for the table function. A 'dummy' cursor is then generated. When slaves execute the table function, they call the dummy cursor for input. When a slave calls the dummy cursor for input, the dummy cursor causes a context switch back to the global cursor, so that the second plan component within the first cursor generates the input for the slave.

Executing nested subqueries of parallel table functions in the parallel single cursor model

A cursor that is generated from an original database statement includes a master plan that is shared among the various participants involved in the parallel execution of the operations specified in the original statement. For participants that cannot share the same cursor, such as slave processes on remote servers, a remote cursor is generated. Signatures are generated for both the master plan and the remote plans, and compared to ensure that the remote plans are equivalent to the master plans. Various parameters and statistics are provided to remote servers to increase the likelihood that the remote plans will be equivalent to the master plan.

Parallel single cursor model on multiple-server configurations

Techniques are provided for processing, within a database server, a database statement, where at least one subtask required by the database statement is to be executed in parallel by a slave set. The database server determines whether the database statement includes an external expression, relative to the subtask, that (a) produces information that is required by slave processes in the slave set in order to perform the subtask, and (b) is not to be evaluated by each slave process in the slave set. During execution of the statement, if the database statement includes an external expression, then one or more external values are generated by causing the external expression to be evaluated, and the one or more external values are communicated to slaves of the slave set to allow the slave processes to perform respective portions of the subtask in parallel, without requiring each slave of the slave set to evaluate the external expression.

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Burlingame, CA, United States of America

Bhaskar Ghosh