Microsoft Technology Licensing, LLC

Linkedin Corporation

Sanjay Sureshchandra Dubey

Praveen Neppalli Naga

Volodymyr Zhabiuk

Liang Zhang

Yang Yang

Dhaval Chandrakant Patel

Ritesh Maheshwari

Deepak Agarwal

David Q He

Ashvin Kannan

Nihar Niranjan Mehta

Ruixuan Hou

Sanjay Kshetramade

Carleton Miyamoto

Steven Scott Noble

Jieying Chen

Toon Sripatanaskul

Anmol Bhasin

Xiang Yu

Hardik Bati

Lihong Pei

Edward Wu

Yawen Wei

Zaid A Kahn

Qi Liu

Jiansheng Huang

James C Shieh

Jintae Jung

Dhaval H Patel

Waitat Peter Poon

David Hahn

Ganesh Shekharipuram Hariharan

Jack Weichieh Chou

Generally discussed herein are methods, systems, and apparatuses for tracking user interaction with sponsored and/or unsponsored content. A method can include receiving a tracking event packet including data fields comprising a packet identification, a tracking event identifier, a content identifier, a cost, a campaign identifier, and/or an advertiser identifier, determining whether the tracking event packet is a duplicate based on the packet identification, aggregating non-duplicate tracking event packets by advertiser identification such that packets with advertiser identifications that hash to a same value are aggregated together, and transferring aggregated tracking event packets to a first database and a second database, the first database includes data stored for analytics and the second database includes data stored for billing and campaign performance monitoring.

Tracking interaction with sponsored and unsponsored content

A system for processing data is provided. During operation, the system obtains a current window of one or more intervals of timeseries data collected from a monitored system. Next, the system continuously performs a statistical hypothesis test that compares the one or more intervals of the time-series data with baseline values from historic time-series data associated with the monitored system. When the statistical hypothesis test indicates a deviation of the time-series data from the baseline values, the system outputs an alert of an anomaly represented by the deviation.

Statistical detection of site speed performance anomalies

A system may include a database configured with individual partitions, one of the partitions corresponding to a sponsored content campaign of a social network. The system may further include multiple servers each communicatively coupled to the database, and each configured to implement a campaign having a campaign termination criterion. Each of the servers may include a processor configured to track sponsored content event data received from a user device based on the campaign and transmit the event data to the database and terminate the campaign based on a comparison of the event data as received from a partition of the database corresponding to the campaign and an estimation of event data not received from the database. The database may be configured to store the event data as received from the servers in the partition corresponding to the campaign upon receipt of the event data.

Independent targeted sponsored content management system and method

The disclosed embodiments provide a system for processing data. During operation, the system obtains a set of components of a time-series performance metric associated with an anomaly in a performance of one or more monitored systems. For each component in the set of components, the system performs a statistical hypothesis test on the component to assess a deviation of the component from a baseline value of the component. When the statistical hypothesis test identifies a statistically significant deviation of the component from the baseline value, the system outputs an alert comprising a root cause of the anomaly that is represented by the statistically significant deviation of the component from the baseline value.

Root cause investigation of site speed performance anomalies

The disclosed embodiments provide a system for processing data. During operation, the system obtains a component of a time-series performance metric associated with a server-side root cause of an anomaly in the time-series performance metric. Next, the system obtains a call graph representation of the component, wherein the call graph representation includes a parent node having a parent value of the component and a set of child nodes of the parent node, each child node having a corresponding child value of the component. The system then analyzes the call graph representation to identify one or more of the child nodes as sources of the anomaly. Finally, the system outputs an alert that identifies the sources of the anomaly.

Analysis of site speed performance anomalies caused by server-side issues

A system may include a network interface and a batch processor coupled to the network interface. The batch processor may be configured to obtain social network profiles corresponding to entities and to obtain a target criterion. The batch processor may be configured to identify at least some of the entities based on a relationship between the social network profiles and the target criterion and to transmit, via the network interface, a data file to a computing device of the at least some of the entities, wherein the data file contains information related, at least in part, to the target criterion.

Target criterion-based data file distribution

Techniques for automatically recommending a new data center, such as a point-of-presence (POP) center are provided. In one technique, multiple candidate locations for a new POP center are considered. An impact of adding a new POP to each candidate location is estimated and a score is generated. Each candidate location is ranked based on the score. In a related technique, an impact score for a candidate location is based on a prediction of whether and how much a new POP center at the candidate location would reduce response times of clients that would connect to the new POP center. The prediction may be based on a model that is generated based on response data generated by clients that are connecting to existing POP centers. The model may take into account multiple factors, such as geographic distance, network distance, type of browser executing on the clients, type of operating system, etc.

Automatically recommending point of presence centers

The disclosed embodiments provide a method and system for processing data. During operation, the system obtains a set of records, wherein each of the records comprises one or more metrics and at least one dimension associated with the one or more metrics. Next, the system creates a data segment comprising at least one of a forward index and an inverted index for a column in the records. The system then stores the data segment in network-accessible storage and assigns the data segment to a partition. Finally, the system enables querying of the data segment through a query node associated with the partition.

Management of data segments for analytics queries

The disclosed embodiments provide a system that processes data. During operation, the system obtains a set of records, wherein each of the records comprises one or more metrics and at least one dimension associated with the one or more metrics. Next, the system creates a data segment from the records by sorting the records by a primary sort column having a first set of possible values, creating a set of dictionaries for a set of columns in the records, and building a set of forward indexes for the columns using the set of dictionaries.

Indexing of data segments to facilitate analytics

The disclosed embodiments provide a system that processes data. During operation, the system obtains a set of records, wherein each of the records comprises one or more metrics and at least one dimension associated with the one or more metrics. Next, the system creates, in a data segment comprising the records, an inverted index for a column in the records based on a cardinality of the column. Finally, the system compresses the inverted index based on a jump value associated with record identifiers in the column.

Inverted indexes for accelerating analytics queries

The disclosed embodiments provide a system that processes data. During operation, the system obtains, in a buffer, records to be included in a data segment as the records are generated, wherein each of the records comprises one or more metrics and at least one dimension associated with the one or more metrics. After the buffer reaches a threshold size, the system creates a data segment comprising at least one of a forward index and an inverted index for a column in the records. The system then enables querying of the data segment and a set of offline data segments comprising older records of the one or more metrics and the at least one dimension.

Real-time indexing of data for analytics

Growing community of inventors

Fremont, CA, United States of America

Sanjay Sureshchandra Dubey