Nec Laboratories America, Inc.

International Business Machines Corporation

Nec Corporation

Vahit Hakan Hacigumus

Yun Chi

Balakrishna Raghavendra Iyer

Junichi Tatemura

Jagan Sankaranarayanan

Hyun Jin Moon

Sharad Mehrotra

Ziyang Liu

Jeffrey LeFevre

Dante Aligheri Aubert

Shenghuo Zhu

Lu Nguyen

Wang-Pin Hsiung

Neoklis Polyzotis

Sanjoy Das

John T Flynn

Wentao Wu

Jeffrey Thomas Kreulen

James J Rhodes

Jeffrey F Naughton

Tobin Jon Lehman

Charles William Lickel

H Raymond Strong, Jr

Hatem Abdelghani Mahmoud

Greg Eyres

Jenny Duggan

Sean Barker

Mohamed Sarwat

Haopeng Zhang

Shenoda Guirguis

Pengchong Xiong

Xin He

A method and system for forming service compositions to provide service components to business processes. Service components independently needed by each business process are identified. At least one of the service components is needed by at least two business processes. At least two different service components are needed by at least one business process. At least two service compositions are specified. Each service composition includes at least one service component. At least one service composition comprises at least two service components. An optimal subset of the service compositions is ascertained, such that the total cost of deploying the service compositions in the optimal subset to provide the service components independently needed by each business process does not exceed the total cost of deploying the service compositions in any other subset of the service compositions to provide the service components independently needed by each business process.

Optimal group of service compositions

A computer-implemented method for pairing a new document to a document from a plurality of documents. Embodiments include, for each of the new document and the plurality of documents, generating a vector of terms of interest uniquely associated with a document of the new document and the plurality of documents. For each term of interest, an associated element value of the vector is assigned as zero if the term of interest does not occur in the document and one otherwise. The method also includes, for each document from the plurality of documents, determining a similarity between the vectors. The method also includes selecting a document from the plurality of documents as related to the new document if the similarity between the vector for the new document and the vector for the document from the plurality of documents is greater than or equal to a threshold value.

System, method, and apparatus for pairing a short document to another short document from a plurality of short documents

Systems and methods are disclosed for query processing in a big data analytics platform by enumerating plans for a current query using a processor; building a dominance graph for the current query; for each plan, determining a regret value and a score for the plan based on the regret value and cost; and selecting query plans in an online fashion for query processing in big data analytics platforms where intermediate results are materialized and can be reused later.

Visionary query processing in Hadoop utilizing opportunistic views

A system includes first and second data stores, each store having a set of materialized views of the base data and the views comprise a multistore physical design; an execution layer coupled to the data stores; a query optimizer coupled to the execution layer; and a tuner coupled to the query optimizer and the execution layer, wherein the tuner determines a placement of the materialized views across the stores to improve workload performance upon considering each store's view storage budget and a transfer budget when moving views across the stores.

MISO (multistore-online-tuning) system

Systems and methods for predicting query execution time for concurrent and dynamic database workloads include decomposing each query into a sequence of query pipelines based on the query plan from a query optimizer, and predicting an execution time of each pipeline with a progress predictor for a progress chart of query pipelines.

System and methods for predicting query execution time for concurrent and dynamic database workloads

Systems and methods are disclosed for managing a multi-store execution environment by applying opportunistic materialized views to improve workload performance and executing a plan on multiple database engines to increase query processing speed by leveraging unique capabilities of each engine by enabling stages of a query to execute on multiple engines, and by moving materialized views across engines.

System for multi-store analytics execution environments with storage constraints

A system includes a task scheduler that works collaboratively with a flow scheduler; a network-aware task scheduler based on software-defined network, the task scheduler scheduling tasks according to available network bandwidth.

System and methods for collaborative query processing for large scale data processing with software defined networking

Systems and methods for consolidating workload on one or more computing devices, comprising: generating tenant performance profiles for at least one of a buffer memory size and a buffer warmness; assigning one or more tenants to a database management system (DBMS) instance; configuring the one or more tenants to minimize a total server count needed to host the one or more tenants; and reducing the total server count by adjusting of buffer sizes while satisfying Service Level Agreement (SLA) requirements.

System and method for SLA-aware database consolidation using per-tenant memory size configuration

Systems and methods for prioritizing queries in a cloud based database by determining a priority score in real time under an imprecise query execution time; and incrementally maintaining query priority scores.

System and methods for prioritizing queries under imprecise query execution time

A system for evolutionary analytics supports three dimensions (analytical workflows, the users, and the data) by rewriting workflows to be more efficient by using answers materialized as part of previous workflow execution runs in the system.

System for evolutionary analytics

Systems and methods are disclosed to perform performance prediction for cloud-based databases by building on a computer a cloud database performance model using a set of training workloads; and using a learned model on the computer to predict database performance in the cloud for a new workload, wherein for each reference workload r and hardware configuration h, system throughput t, average throughput of &#x3b1;and standard deviation &#x3c3;, comprising normalizing each throughput as: 

Portable workload performance prediction for the cloud

A method for database consolidation includes generating a model for expected penalty estimation; determining a tenant's value as a function of query arrival rate and SLA penalty; placing a tenant to minimize a total expected cost in the order of the tenant value; and progressively using additional servers to prevent any server from being saturated to guarantee a tenant placement that costs no more than four times the cost of any other placement.

Tenant placement in multitenant databases for profit maximization

A method for balancing database workloads among a plurality of database servers includes when a new server is available, selecting a set of master and slave databases to be migrated to the new server; and migrating the selected databases to result in a balanced new workload among all servers while minimizing migration cost; and during operation, if workload unbalance is detected in real time from a workload change in a certain database, iteratively selecting one database at a time to migrate to a different server to balance the workload.

Balancing database workloads through migration

A method for tenant placement in a multi-tenant system is shown that includes creating a weighted graph of tenants and sharing relationships between tenants, where a weight for each tenant and each sharing relationship represents an associated degree of resource consumption; and adding one or more tenants to a database using a processor based on said weighted graph and a database capacity, such that the combined weight of the added tenants and the sharing relationships belonging to the added tenants are within the database capacity. If a tenant cannot be added to the database without exceeding the database capacity, a new database is created and the one or more tenants are added to the new database, subject to a new database capacity. The adding and creating steps are repeated until all tenants have been added to a database.

Tenant placement in multitenant cloud databases with data sharing

A computer implemented method of workload scheduling under two different types of Service Level Agreements (SLAs), namely soft and hard SLA which employ both a deadline- and cost-aware scheduler called iCBS-DH. The scheduler is evaluated against deadline and cost performance of various scheduling policies under a large range of SLA cost function and deadline types.

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San Jose, CA, United States of America

Vahit Hakan Hacigumus