Abstract: An example method of using ad-hoc stored procedures for OLTP operations includes: identifying, by a processing device, one or more values for updating a dataset stored in a database; creating an ad-hoc stored procedure comprising a sequence of commands specifying atomically-executable database update operations with respect to the dataset, wherein the atomically-executable database update operations utilize the one or more values that are encoded into the sequence of commands by respective inline constant values; executing the ad-hoc stored procedure, wherein the executing comprises acquiring a temporary lock of at least part of the dataset; and dropping the ad-hoc stored procedure.

Abstract: In one embodiment, a method includes accessing a log associated with a user. The log includes a number of entries that each indicate a geo-location of the user at a particular time of day of a particular day of a week. The entries are based on a geo-location determined and reported by a mobile computing device of the user without manual user input. The method also includes determining one or more geo-location centroids based on a distance between the respective geo-location centroid and each geo-location data point. Each geo-location centroid is representative of one or more of the geo-location data points obtained during the particular time of day of the particular day of a week. The method also includes determining a routine center of one or more of the number of geo-location centroids based on a distance between its respective routine center and each geo-location centroid.

Abstract: In one embodiment, a method includes accessing a log associated with a user. The log includes a number of entries that each indicate a geo-location of the user at a particular time of day of a particular day of a week. At least some of the data points being based on a geo-location determined and reported by a mobile computing device of the user without manual user input. The method also includes determining one or more geo-location centroids based on a distance between the respective geo-location centroid and each geo-location data point. Each geo-location centroid is representative of one or more of the geo-location data points obtained during the particular time of day of the particular day of a week.

Abstract: In one embodiment, a method includes transmitting at a pre-determined polling frequency an activation signal waking from a sleep mode an application on a mobile computing device and causing the application to activate a location service of the mobile computing device for a pre-determined sampling duration. The pre-determined polling frequency and the pre-determined sampling duration are determined at least in part by detecting a movement of the mobile computing device. The method also includes receiving location data from the mobile computing device after the pre-determined sampling duration. The location data is responsive to a transmission signal.

Abstract: In one embodiment, a method includes transmitting at a pre-determined polling frequency an activation signal waking from a sleep mode an application on a mobile computing device and causing the application to activate a location service of the mobile computing device for a pre-determined sampling duration. The pre-determined polling frequency and the pre-determined sampling duration are determined at least in part by detecting a movement of the mobile computing device. The method also includes receiving location data from the mobile computing device after the pre-determined sampling duration. The location data is responsive to a transmission signal.

Abstract: In one embodiment, a method includes accessing a log associated with a user. The log includes a number of entries that each indicate a geo-location of the user at a particular time of day of a particular day of a week. The entries are based on a geo-location determined and reported by a mobile computing device of the user without manual user input. The method also includes determining one or more geo-location centroids based on a distance between the respective geo-location centroid and each geo-location data point. Each geo-location centroid is representative of one or more of the geo-location data points obtained during the particular time of day of the particular day of a week. The method also includes determining a routine center of one or more of the number of geo-location centroids based on a distance between its respective routine center and each geo-location centroid.

Abstract: In one embodiment, a method includes accessing a log associated with a user. The log includes a number of entries that each indicate a geo-location of the user at a particular time of day of a particular day of a week. At least some of the data points being based on a geo-location determined and reported by a mobile computing device of the user without manual user input. The method also includes determining one or more geo-location centroids based on a distance between the respective geo-location centroid and each geo-location data point. Each geo-location centroid is representative of one or more of the geo-location data points obtained during the particular time of day of the particular day of a week.

Abstract: In one embodiment, a method includes accessing a log associated with a user. The log includes a number of entries that each indicate a geo-location of the user at a point in time. The log spans a period of time and some of the entries are based on a geo-location determined and reported by a mobile computing device of the user without manual user input. The method also includes determining a pattern among the geo-locations of the user at the points in time; and determining for some of the geo-locations of the user at the points in time, a place corresponding to the geo-location; and inferring by the computing device a routine of the user based at least in part the pattern and the places.

Abstract: In one embodiment, a method includes determining a pattern among a number of geo-locations of a user over a period of time. Each geo-location is determined and reported by a mobile computing device of the user without manual user input. The method also includes determining a particular geo-location among the geo-locations in the pattern with a minimum distance to a current geo-location of the mobile computing device; determining a distance between the particular geo-location and the current geo-location; and sending a notification of the current geo-location to one or more other users in response to the distance being longer than a pre-determined deviation threshold value. One or more of the other users have a relationship to the user based at least in part on social-graph information associated with the user.

Abstract: In one embodiment, a method includes transmitting at a pre-determined polling frequency an activation signal waking from a sleep mode an application on a mobile computing device and causing the application to activate a location service of the mobile computing device for a pre-determined sampling duration. The pre-determined polling frequency and the pre-determined sampling duration are determined at least in part by detecting a movement of the mobile computing device. The method also includes receiving location data from the mobile computing device after the pre-determined sampling duration. The location data is responsive to a transmission signal.

Abstract: In one embodiment, a method includes receiving location data from a mobile device associated with a user. The location data includes one or more location readings sent automatically and without manual input from the user. The method also includes representing the location data as one or more geo-location data points based at least in part on a distance between the location readings and the geo-location data points; and grouping one or more of the geo-location data points into one or more geo-location clusters based at least in part on a distance between each geo-location data point and a geo-location centroid of each geo-location cluster.

Abstract: In one embodiment, a method includes determining a geo-location centroid of each of one or more geo-location clusters. The geo-location centroid corresponds to one or more geo-location data points within its geo-location cluster. The geo-location data points represent one or more location readings from a mobile computing device associated with a user. The geo-location centroids are based at least in part on location readings obtained during a particular time of day of a particular day of a week. The method also includes grouping one or more geo-location centroids into one or more groups; and determining a time-based routine based at least in part on a number of geo-location centroids within each group.

Abstract: In one embodiment, a method includes transmitting at a pre-determined polling frequency an activation signal waking from a sleep mode an application on a mobile computing device and causing the application to activate a location service of the mobile computing device for a pre-determined sampling duration. The pre-determined polling frequency and the pre-determined sampling duration are determined at least in part by detecting a movement of the mobile computing device. The method also includes receiving location data from the mobile computing device after the pre-determined sampling duration. The location data is responsive to a transmission signal.

Abstract: In one embodiment, a method includes receiving location data from a mobile device associated with a user. The location data includes one or more location readings sent automatically and without manual input from the user. The method also includes representing the location data as one or more geo-location data points based at least in part on a distance between the location readings and the geo-location data points; and grouping one or more of the geo-location data points into one or more geo-location clusters based at least in part on a distance between each geo-location data point and a geo-location centroid of each geo-location cluster.

Abstract: In one embodiment, a method includes determining a pattern among a number of geo-locations of a user over a period of time. Each geo-location is determined and reported by a mobile computing device of the user without manual user input. The method also includes determining a particular geo-location among the geo-locations in the pattern with a minimum distance to a current geo-location of the mobile computing device; determining a distance between the particular geo-location and the current geo-location; and sending a notification of the current geo-location to one or more other users in response to the distance being longer than a pre-determined deviation threshold value. One or more of the other users have a relationship to the user based at least in part on social-graph information associated with the user.

Abstract: In one embodiment, a method includes accessing a log associated with a user. The log includes a number of entries that each indicate a geo-location of the user at a point in time. The log spans a period of time and some of the entries are based on a geo-location determined and reported by a mobile computing device of the user without manual user input. The method also includes determining a pattern among the geo-locations of the user at the points in time; and determining for some of the geo-locations of the user at the points in time, a place corresponding to the geo-location; and inferring by the computing device a routine of the user based at least in part the pattern and the places.

Abstract: In one embodiment, a method includes determining a geo-location centroid of each of one or more geo-location clusters. The geo-location centroid corresponds to one or more geo-location data points within its geo-location cluster. The geo-location data points represent one or more location readings from a mobile computing device associated with a user. The geo-location centroids are based at least in part on location readings obtained during a particular time of day of a particular day of a week. The method also includes grouping one or more geo-location centroids into one or more groups; and determining a time-based routine based at least in part on a number of geo-location centroids within each group.

Abstract: In one embodiment, a method includes transmitting at a pre-determined polling frequency an activation signal waking from a sleep mode an application on a mobile computing device and causing the application to activate a location service of the mobile computing device for a pre-determined sampling duration. The pre-determined polling frequency and the pre-determined sampling duration are determined at least in part by detecting a movement of the mobile computing device. The method also includes receiving location data from the mobile computing device after the pre-determined sampling duration. The location data is responsive to a transmission signal.