| Patent application number | Description | Published |
|---|
| 20080270346 | Estimating the static execution time of a database query - In a method for estimating a static execution time of a database query, a prediction of query runtime tree is built from historical query information. A database query is received. The prediction of query runtime tree is used to estimate the static execution time of the database query. | 10-30-2008 |
| 20090178042 | Managing A Workload In A Database - Described herein is a workload manager for managing a workload in a database that includes: an admission controller operating to divide the workload into a plurality of batches, with each batch having at least one workload process to be performed in the database, and each batch having a memory requirement based on the available memory for processing workloads in the database; a scheduler operating to assign a unique priority to each of the at least one workload process in each of the plurality of batches, the unique priority provides an order in which each workload process is executed in the database; and an execution manager operating to execute the at least one workload process in each of the plurality of batches in accordance with the unique priority assigned to each workload process. | 07-09-2009 |
| 20090178045 | Scheduling Memory Usage Of A Workload - Described herein is a method for scheduling memory usage of a workload, the method comprising: receiving the workload, wherein the workload includes a plurality of jobs; determining a memory requirement to execute each of the plurality of jobs; arranging the plurality of jobs in an order of the memory requirements of the plurality of jobs such that the job with the largest memory requirement is at one end of the order and the job with the smallest memory requirement is at the other end of the order; assigning in order a unique priority to each of the plurality of jobs in accordance with the arranged order such that the job with the largest memory requirement is assigned the highest priority for execution and the job with the smallest memory requirement is assigned the lowest priority for execution; and executing the workload by concurrently executing the jobs in the workload in accordance with the arranged order of the plurality of jobs and the unique priority assigned to each of the plurality of jobs. | 07-09-2009 |
| 20100094827 | Query Stream Execution Using Priority Gradient Multiprogramming - A workload management system and operating method are configured for query stream execution using priority gradient programming. The workload management system comprises a database system that executes queries at a priority gradient wherein no more than a predetermined number of queries execute at a particular priority, and a scheduler that schedules queries for execution on the database system and restricts the queries to a number that consumes less than total system memory. | 04-15-2010 |
| 20100094828 | QUERY SCHEDULER - A mixed workload management system and associated operating method modify a shortest job first (SJF) by service levels. The workload management system comprises a scheduler configured for scheduling mixed workloads. The scheduler comprises an analyzer that determines query execution time, assigns scheduling priority to a query in order inverse to the query execution time, weights the assigned scheduling priority by service level of the query, and sorts a list of queries in order of weighted scheduling priority. A schedule controller selects a query for execution from head of the sorted list of queries. | 04-15-2010 |
| 20100094852 | SCHEDULING QUERIES USING A STRETCH METRIC - A query scheduler orders queries in a queue. Each query is executed based on its position in the queue. When a new query is received, the new query is inserted in the queue. A position in the queue for inserting the new query is determined based on a stretch metric for each query in the queue. | 04-15-2010 |
| 20100095299 | MIXED WORKLOAD SCHEDULER - A mixed workload scheduler and operating method efficiently handle diverse queries ranging from short less-intensive queries to long resource-intensive queries. A scheduler is configured for scheduling mixed workloads and comprises an analyzer and a schedule controller. The analyzer detects execution time and wait time of a plurality of queries and balances average stretch and maximum stretch of scheduled queries wherein query stretch is defined as a ratio of a sum of wait time and execution time to execution time of a query. The schedule controller modifies scheduling of queries according to service level differentiation. | 04-15-2010 |
| 20100114865 | Reverse Mapping Of Feature Space To Predict Execution In A Database - One embodiment is a method that generates points from an input space obtained from a query for a database. A kernel function maps the points from the input space to a feature space. Given a point in the feature space, a reverse mapping identifies coordinates in the input space for the point to predict performance of the query before the query executes in the database. | 05-06-2010 |
| 20100198758 | DATA CLASSIFICATION METHOD FOR UNKNOWN CLASSES - A system and method for creating a CD Tree for data having unknown classes are provided. Such a method can include dividing training data into a plurality of subsets of node training data at a plurality of nodes arranged in a hierarchical arrangement, wherein the node training data has a range. Furthermore, dividing node training data at each node can include, ordering the node training data, generating a plurality of separation points and a plurality of pairs of bins from the node training data, wherein each pair of bins includes a first bin and a second bin with a separation point being located between the first bin and the second bin, and classifying the node training data into either the first bin or the second bin for each of the separation points, wherein the classifying is based on a data classifier. Validation data can be utilized to calculate the bin accuracy between the node training data bin pairs and the validation data bin pairs for each separation point, and the separation point having a high bin accuracy can be selected as the node separation point. | 08-05-2010 |
| 20100262613 | Data Stream Processing - A method of processing a stream of raw data from a plurality of distributed data producing devices includes reducing the raw data to a plurality of representative synopsis coefficients, organizing the synopsis coefficients into a data structure with at least three dimensions, including a time window dimension and an accuracy dimension. Responsive to a detected anomaly in the data structure, at least one of a predetermined autonomous action and an action directed by a user is performed. | 10-14-2010 |
| 20100280857 | MODELING MULTI-DIMENSIONAL SEQUENCE DATA OVER STREAMS - One embodiment is a method that builds a model of multi-dimensional sequence data in real-time with cuboids that aggregate the multi-dimensional sequence data over both patterns and dimensions. The model provides search results for a query. | 11-04-2010 |
| 20110010405 | Compression of non-dyadic sensor data organized within a non-dyadic hierarchy - Sensor data is received from one or more sensors. The sensor data is organized within a hierarchy. The sensor data is organized within a hierarchy that is non-dyadic. A processor of a computing device generates a discrete wavelet transform, based on the sensor data and based on the hierarchy of the sensor data, to compress the sensor data. The sensor data, as has been compressed via generation of the discrete wavelet transform, is processed. | 01-13-2011 |
| 20110055222 | Energy-based wavelet thresholding - A data processing system, implemented as programming on a suitably-programmed device includes a data input module that supplies a data input; and a wavelet transformation and compression module coupled to the data input module. The wavelet transformation and compression module receives a representation of the input data. The wavelet transformation and compression module includes an input module having a wavelet basis function, a wavelet coefficient generator that computes wavelet coefficients based on the wavelet basis function and the representation of the input data, a ranking module that orders the n wavelet coefficients, a coefficient multiplier that computes an energy value for each wavelet coefficient, an adder that iteratively computes cumulative energy as a function of the number of coefficients, and a comparator that computes total energy of the data input to the iterative, cumulative energy and selects a number of coefficients whose cumulative energy is substantially invariant with additional coefficients, wherein the selected number of coefficients results in compression of the data input. | 03-03-2011 |
| 20110113009 | Outlier data point detection - New data points are added to a streaming window of data points and existing data points are removed from the window over time. Each data point has a value for each of one or more dimensions. Each time a given new data point is added to the window or a given existing data point is removed from the window, one or more outlier detection data structures are updated. Each outlier detection data structure encompasses the data points within the streaming window for a corresponding dimension. The outlier detection data structures are used to detect outlier data points within the window over selected one or more dimensions. | 05-12-2011 |
