ThoughtSpot, Inc.

A low-latency database analysis system outputs visualization data for presenting a visualization representing results data responsive to the request for data, and, in response to outputting the visualization data, generates a diverse plurality of candidate modifications for the request for data, outputs candidate modification data for presenting the diverse plurality of candidate modifications in association with the presentation of the visualization representing the results data, in response to outputting the candidate modification data, obtains user input data identifying a candidate modification from the diverse plurality of candidate modifications as a selected modification, in response to the user input data, executes a data-query expressing the request for data modified by the selected modification to obtain second results data responsive to the request for data modified by the selected modification, and in response to the second results data, outputs visualization data for presenting a visualization representing the second results data.

Natural language to query language transformation using prompting templates includes obtaining natural language input data, first embeddings data for the natural language input data, prompting template data, ranked list data, candidate prompting data, second embeddings data for the candidate prompting data, score data indicating similarity between the first embeddings data and the second embeddings data, language model input data including the natural language input data and a defined cardinality of demonstrations from the candidate prompting data, and language model generated data from a language model responsive to the language model input data, transforming the language model generated data to obtain a data query expressing the natural language input data in accordance with a defined structured query language implemented by the database, and obtaining results data generated by execution of the data query by the database.

Generating a first database query in accordance with a first structured query language includes obtaining first results data responsive to execution of the first database query by a database system, determining that the first results data indicates that the database system is incompatible with the first database query, generating first database operation mapping configuration data, wherein the first database operation mapping configuration data includes first database operation definition data describing the database operation, obtaining second database operation mapping configuration data, wherein the second database operation mapping configuration data includes the first database operation mapping configuration data mapped to second database operation definition data describing the database operation in accordance with the second structured query language, generating a second database query, obtaining second results data responsive to execution of the second database query by the database system, outputting data representing the second results data.

Obtaining results data using agentic analysis includes obtaining, by a data access and analysis system, natural language input data expressing an input analytical request related to data stored in a database accessible by the data access and analysis system, performing iterations of agentic analysis, wherein agentic analysis includes obtaining, from a language model, responsive to first language model input data generated in accordance with the natural language input data, first language model generated output, wherein, at least one iteration includes obtaining, by the data access and analysis system, in accordance with the first language model generated output, structured data generated by the database executing a data query automatically generated by the data access and analysis system in response to the first language model generated output, and outputting data for presenting at least a portion of the first language model generated output corresponding to a sequentially last iteration.

A distributed database that includes multiple database instances receives a data-query that includes an aggregation clause on a first column of a table. The table is partitioned into shards according to a sharding criterion based on the first column such that all rows having the same value for the first column are included in the same shard. The shards are distributed to the multiple database instances. Respective intermediate results are received from at least some of the database instances. Each intermediate result received from a respective database instance that includes a respective shard aggregates values of the first column in the respective shard. The respective intermediate results are combined to obtain a final result of the data-query. The final result is then output.

Low-latency autonomous-analysis includes obtaining data expressing a usage intent with respect to a low-latency database analysis system that intent omits data corresponding to user input expressly requesting low-latency autonomous-analysis, obtaining requested results data based on the data expressing the usage intent, outputting requested visualization data representing at least a portion of the requested results data for presentation to a user, and, in response to outputting the requested visualization data, obtaining low-latency autonomous-analysis data by performing low-latency autonomous-analysis based on the data expressing the usage intent by identifying an autonomous-analysis predicate based on the requested visualization data, obtaining a defined autonomous-analysis latency constraint, obtaining the low-latency autonomous-analysis data based on the autonomous-analysis predicate in accordance with the defined autonomous-analysis latency constraint, such that the low-latency autonomous-analysis data differs from the requested results data, and outputting at least a portion of the low-latency autonomous-analysis data for presentation to a user.

Generating a first data query in accordance with a first structured query language includes obtaining first results data responsive to execution of the first data query by a database system, determining that the first result data indicates that the database system is incompatible with the first data query, generating first database operation mapping configuration data, wherein the first database operation mapping configuration data includes first database operation definition data describing the database operation, obtaining second database operation mapping configuration data, wherein the second database operation mapping configuration data includes the first database operation mapping configuration data mapped to second database operation definition data describing the database operation in accordance with the second structured query language, generating a second data query, obtaining second results data responsive to execution of the second data query by the database system, outputting data representing the second results data.

Indexing in a low-latency data access and analysis system includes accessing, by an indexing unit of a low-latency data access and analysis system, constituent data from a data source of the low-latency data access and analysis system and indexing the constituent data in an index of the low-latency data access and analysis system by an indexing unit of the low-latency data access and analysis system. Indexing includes partitioning the constituent data based on a characteristic of the constituent data into at least a first partition and a second partition, segmenting the first partition into a first segment of the first partition, sharding the first segment into a first shard of the first segment of the first partition, segmenting, using hash-partitioning, the second partition into one or more segments of the second partition, and for respective segments of the second partition, sharding the respective segment into one or more respective shards.

A visualization data is obtained for an answer object. A generation-identifier is associated with the visualization data. The generation-identifier corresponds to access control data associated with a first user. A snapshot of the first visualization data is received from a user device of the first user. The first snapshot is obtained using instructions that, when executed at the user device, obtain the first snapshot as the first visualization data is displayed at the user device of the first user. An association is stored between the generation-identifier and the snapshot. The answer object is then identified responsive to data expressing a usage intent received from a device of a second user. Responsive to access control data associated with the second user matching the generation-identifier, instructions for rendering the first snapshot at the device of the second user are output.

Updating a constituent-data index includes determining whether sampling is currently contraindicated for the column, in response to determining that sampling is currently contraindicated for the column, omitting sampling the column, in response to determining that sampling is currently other than contraindicated for the column, sampling the column, determining whether updating the constituent-data index is currently contraindicated for the column, in response to determining that updating the constituent-data index is currently contraindicated for the column, omitting updating the constituent-data index with respect to the column, and in response to determining that updating is currently other than contraindicated for the column, updating the constituent-data index with respect to the column.