Facebook, Inc.

Timothy Williamson

Samuel Rash

Martin Traverso

Disclosed here are methods, systems, paradigms and structures for predicting queries, creating tables to store data for the predicted queries, and selecting a particular table to obtain the data from in response to a query. The methods include determining various combinations of a finite set of columns users may query on, based on (i) a list of columns users are interested in obtaining data for, and (ii) cardinality information of a column or combinations of columns in the list of columns. The methods further includes creating various tables based on the determined combinations of the columns using a meta query language. A query is responded to by selecting a table that has least number of rows, among the tables that satisfy query parameters. The methods include selecting a table that has a longest sequence of columns matching with a portion of the query parameters.

Query prediction

Disclosed are methods, systems, paradigms and structures for managing cache memory in computer systems. Certain caching techniques anticipate queries and caches the data that may be required by the anticipated queries. The queries are predicted based on previously executed queries. The features of the previously executed queries are extracted and correlated to identify a usage pattern of the features. The prediction model predicts queries based on the identified usage pattern of the features. The disclosed method includes purging data from the cache based on predefined eviction policies that are influenced by the predicted queries. The disclosed method supports caching time series data. The disclosed system includes a storage unit that stores previously executed queries and features of the queries.

Intelligent caching

Disclosed are methods, systems, paradigms and structures for caching data associated with a sliding window in computer systems. A sliding window can include a time window that progresses with time, and the data can include time series data. As time progresses, the sliding window changes bringing in new data. The cache is updated with new data as and when the sliding window moves. The sliding window data is cached at various granularity levels. The method includes storing a first portion of the data at a first granularity level and a second portion at a second granularity level. The data is cached at various granularity levels in order to effectively use the cache considering at least cache updating criteria such as (i) number of times a storage unit is queried to retrieve the data for updating the cache, (ii) the day/date/time at which the storage unit is queried.

Growing community of inventors

Palo Alto, CA, United States of America

Timothy Williamson