Abstract: Techniques described herein perform implement a query using a synthetic time series (STS), for example applying an STS on time series data to obtain an answer to the query. In an embodiment, a method receives a times series and query relating to the time series. The method translates the query into a synthetic time series. The method executes a reduce operation on the STS and the time series. The method then returns the result of the operation as an answer to the query. A result of the reduce operation is returned as an answer to the query.

Abstract: Techniques described herein perform implement a query using a synthetic time series (STS), for example applying an STS on time series data to obtain an answer to the query. In an embodiment, a method receives a times series and query relating to the time series. The method translates the query into a synthetic time series. The method executes a reduce operation on the STS and the time series. The method then returns the result of the operation as an answer to the query. A result of the reduce operation is returned as an answer to the query.

Abstract: Techniques described herein perform implement a query using a synthetic time series (STS), for example applying an STS on time series data to obtain an answer to the query. In an embodiment, a method receives a times series and query relating to the time series, where the query specifies a condition. The method translates the condition into a synthetic time series and an operation on: the STS and the time series. The method executes the operation on the STS and the time series. The method then returns the result of the operation as an answer to the query. In some embodiments, the execution of the operation on the STS and the time series includes reducing the STS and time series without needing to grid.

Abstract: Techniques and structures relating to processing of data in an information sharing service are disclosed. Implementation of a data structure including entries identifying data that may be shared amongst users in the information service facilitates efficient processing. The data structure entries may include pointers usable to access corresponding details of the sharable data. The entries may also include information useful for filtering the entities, such as an indication of a user account that originates an account update, and a time associated with an update. The data structure may be used to generate data feeds that allow users to access the identified data.

Abstract: Techniques described herein perform implement a query using a synthetic time series (STS), for example applying an STS on time series data to obtain an answer to the query. In an embodiment, a method receives a times series and query relating to the time series, where the query specifies a condition. The method translates the condition into a synthetic time series and an operation on: the STS and the time series. The method executes the operation on the STS and the time series. The method then returns the result of the operation as an answer to the query. In some embodiments, the execution of the operation on the STS and the time series includes reducing the STS and time series without needing to grid.

Abstract: Techniques and structures relating to processing of data in an information sharing service are disclosed. Implementation of a data structure including entries identifying data that may be shared amongst users in the information service facilitates efficient processing. The data structure entries may include pointers usable to access corresponding details of the sharable data. The entries may also include information useful for filtering the entities, such as an indication of a user account that originates an account update, and a time associated with an update. The data structure may be used to generate data feeds that allow users to access the identified data.