Yahoo! Inc.

Revenue Science, Inc.

Google Inc.

Audiencescience Inc.

Radha Krishna Uppala

Roman Basko

Krishnamohan Nareddy

Jay Sauls

Usama M Fayyad

Stella Yick Chan

Neal Rothleder

Jason Carlisle

Umachandar Jayachandaran

Paul Bradley

Sri Krishna Nakka

Prasana Kumar

An improved system and method for query processing in a distributed column chunk data store is provided. A distributed column chunk data store may be provided by multiple storage servers operably coupled to a network. A storage server provided may include a database engine for partitioning a data table into the column chunks for distributing across multiple storage servers, a storage shared memory for storing the column chunks during processing of semantic operations performed on the column chunks, and a storage services manager for striping column chunks of a partitioned data table across multiple storage servers. Query processing may be performed by storage servers or query processing servers operably coupled by a network to storage servers in the column chunk data store. To do so, a hierarchy of servers may be dynamically determined to process execution steps of a query transformed for distributed processing.

Hierarchy of servers for query processing of column chunks in a distributed column chunk data store

An improved system and method for adding a storage server in a distributed column chunk data store is provided. A distributed column chunk data store may be provided by multiple storage servers operably coupled to a network. A storage server provided may include a database engine for partitioning a data table into the column chunks for distributing across multiple storage servers, a storage shared memory for storing the column chunks during processing of semantic operations performed on the column chunks, and a storage services manager for striping column chunks of a partitioned data table across multiple storage servers. Any data table may be flexibly partitioned into column chunks using one or more columns with various partitioning methods. Additional storage servers may then be added and column chunks may be redistributed among the storage servers in the column chunk data store.

System and method for adding a storage server in a distributed column chunk data store

Assuring recovery from failure of a storage server in a distributed column chunk data store of operably coupled storage servers, includes: partitioning a data table into chunks; implementing a distribution scheme with a specified level of redundancy for recovery of one or more failed servers among multiple storage servers; distributing the column chunks according to the distribution scheme; calculating column chunk parity; storing the calculated column chunk parity; managing metadata for the column chunk data store; and updating the metadata for distributing the column chunks among remaining storage servers upon receiving an indication to remove a storage serve.

System and method for removing a storage server in a distributed column chunk data store

A facility for defining a distinguished segment of individuals within a population of individuals is described. The facility displays a prompt for user input specifying a natural-language characterization of a segment membership criterion for identifying individuals who are members of the distinguished segment. The facility then receives, in response to the displayed prompt, user input specifying a natural-language characterization of a segment membership criterion for identifying individuals who are members of the distinguished segment.

User segmentation user interface

An improved system and method for removing a storage server in a distributed column chunk data store is provided. A distributed column chunk data store may be provided by multiple storage servers operably coupled to a network. A storage server provided may include a database engine for partitioning a data table into the column chunks for distributing across multiple storage servers, a storage shared memory for storing the column chunks during processing of semantic operations performed on the column chunks, and a storage services manager for striping column chunks of a partitioned data table across multiple storage servers. Any data table may be flexibly partitioned into column chunks using one or more columns with various partitioning methods. Storage servers may then be removed and column chunks may be redistributed among the remaining storage servers in the column chunk data store.

Method for query processing of column chunks in a distributed column chunk data store

Method using a hierarchy of servers for query processing of column chunks in a distributed column chunk data store

System for query processing of column chunks in a distributed column chunk data store

System of a hierarchy of servers for query processing of column chunks in a distributed column chunk data store

An improved system and method for recovery from failure of a storage server in a distributed column chunk data store is provided. A distributed column chunk data store may be provided by multiple storage servers operably coupled to a network. A storage server provided may include a database engine for partitioning a data table into the column chunks for distributing across multiple storage servers, a storage shared memory for storing the column chunks during processing of semantic operations performed on the column chunks, and a storage services manager for striping column chunks of a partitioned data table across multiple storage servers. Any data table may be flexibly partitioned into column chunks using one or more columns with various partitioning methods. Storage servers may then fail and column chunks may be recreated from parity column chunks and redistributed among the remaining storage servers in the column chunk data store.

System and method for recovery from failure of a storage server in a distributed column chunk data store

A method, system and computer-readable medium for analyzing interaction or usage data, such as for customers, is described. The interaction or usage data may be stored in log files and supplemented with data from other sources. Various data parsing information may be defined and used as part of the analysis, such as by using customer-specific information to identify various occurrences of interest. For example, when analyzing a customer's web site interaction data, the parser component can use data defining customer-specific types of web site events of interest. Such high-level types of occurrences can be specified in a variety of ways, such as by using a combination of a logical web site, one or more URIs corresponding to web pages, and/or one or more query strings. The data parsing information may also specify a mapping of actual web sites to one or more logical sites.

Parsing navigation information to identify occurrences of events of interest

An improved system and method for importing update data in a distributed column chunk data store is provided. A distributed column chunk data store may be provided by multiple storage servers operably coupled to a network. A storage server provided may include a database engine for partitioning a data table into the column chunks for distributing across multiple storage servers, a storage shared memory for storing the column chunks during processing of semantic operations performed on the column chunks, and a storage services manager for striping column chunks of a partitioned data table across multiple storage servers. Any data table may be flexibly partitioned into column chunks using one or more columns with various partitioning methods. Update data may then be incrementally imported as separate column chunks that may later be merged with the column chunks of the partitioned data table.

Growing community of inventors

Bellevue, WA, United States of America

Radha Krishna Uppala