Alan J Halverson

US Patent:

8219539, Jul 10, 2012

Filed:

Apr 7, 2009

Appl. No.:

12/419363

Inventors:

Alan Dale Halverson - Verona WI, US
Krishnaram Kenthapadi - Mountain View CA, US
Nina Mishra - Newark CA, US
Umar Ali Syed - Philadelphia PA, US

Assignee:

Microsoft Corporation - Redmond WA

International Classification:

G06F 7/00
G06F 17/30

US Classification:

707706, 707746, 707765, 707770

Abstract:

Techniques and systems are disclosed for returning temporally-aware results from an Internet-based search query. To determine if a query is temporally-based one or more query features are collected and input into a trained classifier, yielding a temporal classification for the query. Further, if a query is classified as temporal, the query results are shifted by determining an alternate set of results for the query, and returning one or more alternate results to one or more users. Based on user interactions with the one or more alternate results, the classifier can be updated, for example, by changing the query to a non-temporal query if the user interactions identify it as such.

US Patent:

8473483, Jun 25, 2013

Filed:

Jun 7, 2011

Appl. No.:

13/154911

Inventors:

Nikhil Teletia - Madison WI, US
Alan Dale Halverson - Verona WI, US
José A. Blakeley - Redmond WA, US
Milind Madhukar Joshi - Redmond WA, US
Jose Aguilar Saborit - Dana Point CA, US

Assignee:

Microsoft Corporation - Redmond WA

International Classification:

G06F 17/30

US Classification:

707714, 707764

Abstract:

The present invention extends to methods, systems, and computer program products for performing parallel joins on distributed database data. Embodiments of the invention include a phased semi-join reduction strategy using replication and shuffle operations to join a first and a second data source. A filter building phase uses replication and pushes down a “Distinct” (e. g. , SQL) operator to produce a list of join keys for the first data source (one side of the join). A shuffle phase for the second data source is modified to join to the key list produced in the first phase as a row filtering mechanism. A join phase then joins the first and second data sources.

US Patent:

20220318263, Oct 6, 2022

Filed:

Mar 31, 2021

Appl. No.:

17/219007

Inventors:

- Redmond WA, US
Alan Dale HALVERSON - Verona WI, US
Sandeep LINGAM - Redmond WA, US
Srikumar RANGARAJAN - Sammamish WA, US

International Classification:

G06F 16/27
G06F 9/46
G06F 16/901

Abstract:

Methods for data visibility in nested transactions in distributed systems are performed by systems and devices. Distributed executions of queries are performed in processing systems according to isolation level protocols with unique nested transaction identifiers for data management and versioning across one or more data sets, one or more compute pools, etc., within a logical server via a single transaction manager that oversees the isolation semantics and data versioning. A distributed query processor of the systems and devices performs nested transaction versioning for distributed tasks by generating nested transaction identifiers, encoded in data rows, which are used to enforce correct data visibility. Data visibility is restricted to previously committed data from distributed transactions and tasks, and is blocked for distributed transactions and tasks that run concurrently. Local commits for completed transactions and tasks are used to minimize transaction manager interactions, and instant rollbacks are enabled for aborted transactions and tasks.

US Patent:

20200104397, Apr 2, 2020

Filed:

Sep 30, 2018

Appl. No.:

16/147820

Inventors:

- Redmond WA, US
Rathijit Sen - Madison WI, US
Harshada Chavan - Plymouth MN, US
Alan Halverson - Verona WI, US

International Classification:

G06F 17/30
G06F 9/52

Abstract:

Methods for automatic selection of degrees of parallelism for efficient execution of queries in a database system are performed by systems and devices. An incoming query associated with a query system is received and features of the incoming query are determined. A system state of the query system and a set of executing queries are also determined, along with a query state of each executing query in the set. At runtime of the incoming query, allocation of a degree of parallelism for executing the query is determined by calculating different possible execution times for the incoming query at least partially concurrently with the set of executing queries. Execution times are calculated for different parallel thread options and based on query features, system state, or query states of executing queries. The execution of the incoming query is initialized with the parallel thread option corresponding to a specific execution completion time.

US Patent:

20190362005, Nov 28, 2019

Filed:

May 22, 2018

Appl. No.:

15/986493

Inventors:

- Redmond WA, US
Karthik S. Ramachandra - Madison WI, US
Alan D. Halverson - Verona WI, US

Assignee:

Microsoft Technology Licensing, LLC - Redmond WA

International Classification:

G06F 17/30
G06F 9/50

Abstract:

According to examples, an apparatus may include a machine readable medium on which is stored machine readable instructions that may cause a processor to, for each of a plurality of resource setting levels, determine resource usage characteristics and execution times of executed workloads, assign, based on the resource usage characteristics of the executed workloads, each of the executed workloads into one of a plurality of resource bins, determine, for each of the resource bins, an average execution time of the executed workloads in the resource bin, determine a total average execution time of the executed workloads from the determined average execution times, identify a lowest total average execution time of the determined total average execution times, determine the resource setting level corresponding to the identified lowest total average execution time, and tune a resource setting to the determined resource setting level.

US Patent:

20180329952, Nov 15, 2018

Filed:

May 15, 2017

Appl. No.:

15/595752

Inventors:

- Redmond WA, US
Kwanghyun PARK - Madison WI, US
Alan Dale HALVERSON - Verona WI, US
Conor John CUNNINGHAM - Austin TX, US
Cesar Alejandro GALINDO-LEGARIA - Redmond WA, US
Kameswara Venkatesh EMANI - Mumbai, IN

International Classification:

G06F 17/30

Abstract:

Processing a database query. A method includes receiving a database query from a user. The database query includes one or more imperative functions. The one or more imperative functions are converted to one or more declarative query representations. The one or more declarative query representations include standardized relational operators included in a relational query language. Further, the one or more declarative query representations are optimizable by a query optimizer of the database. The database query is optimized at the query optimizer to create a query plan by evaluating any declarative query representation originally in the database query received from the user and the one or more declarative query representations.

US Patent:

20170316043, Nov 2, 2017

Filed:

Jul 14, 2017

Appl. No.:

15/650827

Inventors:

- Redmond WA, US
Vinitha Reddy Gankidi - Madison WI, US
Alan D. Halverson - Verona WI, US
Jignesh M. Patel - Madison WI, US

International Classification:

G06F 17/30
G06F 17/30
G06F 3/06
G06F 17/30

Abstract:

A split-index can be employed for access to external data. The index can be created on a primary data storage system for data stored externally on a secondary data storage system. After creation, the index can be utilized to expedite at least query execution over the externally stored data. The index can be updated upon detection of changes to data. Further, even when the index is not completely up to date, the index can be exploited for query execution. Furthermore, hybrid execution is enabled with the index and without the index.

US Patent:

20170083588, Mar 23, 2017

Filed:

Dec 7, 2016

Appl. No.:

15/371245

Inventors:

- Redmond WA, US
Nikhil Teletia - Madison WI, US
Hideaki Kimura - Madison WI, US
Alan D. Halverson - Verona WI, US
Srinath Shankar - Madison WI, US
Karthik Ramachandra - Madison WI, US

International Classification:

G06F 17/30

Abstract:

Distributed query processing is often performed by a set of nodes that apply MapReduce to a data set and materialize partial results to storage, which are then aggregated to produce the query result. However, this architecture requires a preconfigured set of database nodes; can only fulfill queries that utilize MapReduce processing; and may be slowed down by materializing partial results to storage. Instead, distributed query processing can be achieved by choosing a node for various portions of the query, and generating customized code for the node that only performs the query portion that is allocated to the node. The node executes the code to perform the query portion, and rather than materializing partial results to storage, streams intermediate query results to a next selected node in the distributed query. Nodes selection may be involve matching the details of the query portion with the characteristics and capabilities of the available nodes.