A database system receives a query and determines that the query includes an inner join between a parent table and a child table. The database system determines that the following relationships exists between the parent table and the child table: referential integrity (“RI”) between a primary key attribute (pk) in the parent table and a foreign key attribute (fk) in the child table and a temporal relationship constraint (“TRC”) between a period attribute in the parent table and a TRC-attribute in the child table. The database system determines that the query satisfies non-temporal join elimination conditions and temporal join elimination conditions and that the query contains no other qualification conditions on the parent table's period attribute and eliminates the inner join when planning execution of the query.

Systems and methods are disclosed for processing and executing queries in a data intake and query system. The data intake and query system receives a query identifying a set of data to be processed and a manner of processing the set of data. The data intake and query system identifies buckets that are to be searched and stores a copy of buckets in memory associated with one or more search nodes. A search node performs a search on buckets residing in its memory.

Methods and systems for determining at least one candidate user for a license plate number (LPN) are described herein. A set of license plate recognition (LPR) events that correspond to the LPN and a set of access events of a plurality of users may be obtained. One or more associated events for each respective user of the plurality of users may be determined. A confidence score for each respective user may be determined based on the one or more associated events for the respective user. At least one candidate user for the LPN may be identified based on the confidence score. An indication that the at least one candidate user is a candidate for the LPN is output. Methods and systems for determining at least one candidate license plate number for a user are also described herein. Additional related methods and systems are described herein.

Systems, methods, and devices are provided for dynamically generating a histogram for viewing via a user interface. Embodiments presented herein provide apparatus and techniques for generating a histogram and adjusting a view of the histogram without the computations being perceived by a user. To do so, histogram indices may be computed for various time intervals (e.g., minutes, hours, days, etc.) of input data. The indices may be used to generate a histogram for a time interval that may be larger than the interval used to compute the histogram indices. At the time period for the histogram displayed via the user interface is changed by the user, a dynamic histogram builder computes an adjusted histogram using histogram indices for the updated and/or changed time period. Embodiments herein provide techniques which reduce the time to compute the histogram and consume less computing resources to do so.

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.

Presently disclosed are systems and methods for generating customized filtered-and-partitioned market-data feeds. In an embodiment, an output-feed profile is maintained in data storage at a market-data-processing device (MDPD). The output-feed profile specifies a subset of ticker symbols and a ticker-symbol-based feed-partitioning scheme. An input feed of order-book updates to ticker symbols is received at the MDPD from an upstream device. At the MDPD, a customized market-data output feed is generated according to the maintained output-feed profile at least in part by filtering the input feed down to the order-book updates to ticker symbols in the specified subset and partitioning the filtered feed according to the specified ticker-symbol-based feed-partitioning scheme. The customized market-data output feed is transmitted from the MDPD to a downstream device.

A search request for content can be initiated by a user, and the content that is relevant to the search request can be identified and presented in a manner that indicates the content's trustworthiness or relevancy. The identified content can be ranked based on the number of times the content has been referenced as well as by source that referenced the content. The relevant identified content can then be displayed in an ordered list that is ordered based on the number of times the content has been referenced. In some cases, the order may be modified by the authority of the source.

A columnar storage method and a query method and system for time series data. The storage method includes: dividing a column of time series data into a plurality of pages, wherein each page stores a part of data points of the column of time series data and the sum of the data points stored in all the pages is all the data points in the column of time series data (S1); and setting two parts, i.e., a page header and a page body, for each page, storing summary index information of all the data points in the page in the page header of the page and storing data value information of all the data points in the page in the page body of the page (S2).

A method and system identify characteristics of transaction description strings. The method and system extracts time data and location data from transaction description strings. The method and system generate estimated time data and location data for transaction strings that lack time data and location data by analyzing the time data and location data extracted from other transaction description strings. The method and system generate a user profile based on the estimated time data and estimated location data.

A system for extracting latent information from data includes obtaining or generating components of the data, where the data components include scores indicating how the component relates to the data. Memory is allocated for the components and the components are stored in the allocated memory. The components are then transformed into documents using a suitable transformation function, and the documents are analyzed using natural language processing, to extract latent information contained in the data.