Abstract: Systems and methods for query generation based on a logical data model are described. For example, methods may include accessing a first join graph representing tables in a database; receiving a first query that references data in two or more of the tables of the database; selecting a connected subgraph of the first join graph that includes the two or more tables referenced in the first query; generating multiple leaf queries that reference respective subject tables that are each a root table of the connected subgraph or a table including a measure referenced in the first query; generating a query graph that specifies joining of results from queries based on the multiple leaf queries to obtain a transformed query result; and invoking a transformed query on the database that is based on the query graph and the queries based on the multiple leaf queries to obtain the transformed query result.

Abstract: Operating a low-latency database analysis system with phrase translation may include obtaining a locale-specific phrase localization rule and a canonical phrase localization rule for a phrase, generating a locale-specific index and a locale-specific finite state machine for the locale using the localization definition data and a canonical finite state machine, generating a resolved-request by obtaining a locale-specific token representing locale-specific input data by traversing the locale-specific index, obtaining a canonical token associated with locale-specific token, obtaining a locale-specific phrase by traversing the locale-specific finite state machine, obtaining a canonical phrase corresponding to the locale-specific phrase, the canonical phrase including the canonical token, generate a data-query based on the canonical phrase, obtaining results data responsive to the data expressing the usage intent by executing a query corresponding to the data-query by an in-memory database of the low-latency datab

Abstract: Operating a low-latency database analysis system using domain-specific chronometry may include obtaining, in the low-latency database analysis system, data expressing a usage intent with respect to the low-latency database analysis system, in response to obtaining the data expressing the usage intent, obtaining ontological data for a chronometric object in the low-latency database analysis system indicated by the data expressing the usage intent, identifying a chronometry dataset from a plurality of chronometry datasets, wherein the plurality of chronometry datasets includes a domain-specific chronometry dataset and a canonical chronometry dataset, obtaining results data in accordance with the chronometry dataset and the chronometric object, generating output data representing the results data in accordance with the chronometry dataset, and outputting the output data for presentation via a user interface.

Abstract: Operating a low-latency database analysis system using domain-specific chronometry may include obtaining chronometry configuration data including chronometric instance data describing an instance of a chronometric unit of a domain-specific chronometry dataset that describes an era, such that the chronometry configuration data includes respective chronometric instance data describing each instance of the first chronometric unit of the domain-specific chronometry dataset for the era of the domain-specific chronometry dataset, generating, in the low-latency database analysis system, a domain-specific chronometry dataset in accordance with the chronometry configuration data, such that the domain-specific chronometry dataset describes a chronometric unit such that a temporal location expressed with reference to the chronometric unit and indicative of an epoch value differs from a temporal location indicative of the epoch value and expressed in accordance with a canonical chronometry, and storing the domain-specifi

Abstract: Intent-resolution using a phrase index may include obtaining data expressing a usage intent, the data expressing the usage intent including an unresolved data portion, identifying a phrase fragment based on the data expressing the usage intent and a defined phrase pattern, the phrase fragment including the unresolved data portion, identifying, by a processor, an indexed phrase as a candidate phrase by searching a phrase index based on the phrase fragment, wherein the candidate phrase at least partially matches the phrase fragment in accordance with the defined phrase pattern, and outputting the candidate phrase for presentation to a user as a candidate for resolving the unresolved portion.

Abstract: Intent-resolution using a phrase index may include obtaining data expressing a usage intent, the data indicating an unresolved data portion, identifying a phrase fragment based on the data expressing the usage intent and a phrase pattern, the phrase fragment including the unresolved data portion, identifying candidate tokens, identifying candidate phrases by traversing a phrase index based on the phrase fragment, wherein identifying the candidate phrases includes, in response to a determination that the phrase index includes an indexed phrase at least partially matching the phrase fragment in accordance with the phrase pattern, the indexed phrase is identified as one of the candidate phrases, identifying candidate resolved-requests, weighting and sorting the candidate tokens, the candidate phrases, and the candidate resolved-request, to obtain sorted candidate resolutions, and outputting one or more of the sorted candidate resolutions for presentation to a user as respective candidates for resolving the unres

Abstract: Systems and methods for query generation based on merger of subqueries are described. For example, methods may include accessing a first join graph representing tables in a database, wherein the first join graph has vertices corresponding to respective tables in the database and directed edges corresponding to join relationships; receiving a first query specification that references data in two or more of the tables of the database to specify multiple subqueries in a set of subqueries; checking that two or more subqueries from the set of subqueries have the same join graph; checking that the two or more subqueries have the same set of grouping columns; responsive, at least in part, to the two or more subqueries having the same join graph and the same set of grouping columns, merging the two or more subqueries to obtain a consolidated query.

Abstract: Object scriptability methods and system are described herein. The method includes generating a graph-based data structure including a plurality of nodes, where each node from the plurality of nodes represents a respective data-analysis object in a data analysis system, where each node from the plurality of nodes is connected to at least one other node from the plurality of nodes by an edge, where the edge represents a relationship between the respective objects in the data analysis system, and where generating the graph-based data structure includes receiving a high-level language script describing at least one data-analysis object, and generating at least one node from the plurality of nodes in accordance with the high-level language script.

Abstract: Intent-resolution using a phrase index may include obtaining data expressing a usage intent, the data indicating an unresolved data portion, identifying a phrase fragment based on the data expressing the usage intent and a phrase pattern, the phrase fragment including the unresolved data portion, identifying candidate tokens, identifying candidate phrases by traversing a phrase index based on the phrase fragment, wherein identifying the candidate phrases includes, in response to a determination that the phrase index includes an indexed phrase at least partially matching the phrase fragment in accordance with the phrase pattern, the indexed phrase is identified as one of the candidate phrases, identifying candidate resolved-requests, weighting and sorting the candidate tokens, the candidate phrases, and the candidate resolved-request, to obtain sorted candidate resolutions, and outputting one or more of the sorted candidate resolutions for presentation to a user as respective candidates for resolving the unres

Abstract: Systems and methods for query generation based on a logical data model are described. For example, methods may include accessing a first join graph representing tables in a database; receiving a first query that references data in two or more of the tables of the database; selecting a connected subgraph of the first join graph that includes the two or more tables referenced in the first query; generating multiple leaf queries that reference respective subject tables that are each a root table of the connected subgraph or a table including a measure referenced in the first query; generating a query graph that specifies joining of results from queries based on the multiple leaf queries to obtain a transformed query result; and invoking a transformed query on the database that is based on the query graph and the queries based on the multiple leaf queries to obtain the transformed query result.