Abstract: 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.

Abstract: 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 d

Abstract: 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 th

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: Automatic data modeling in includes identifying an analytical object in response to first data expressing usage intent, generating an analytical model generation data query for the analytical object, obtaining a trained analytical model generated in accordance with the analytical model generation query and trained using results data obtained in accordance with the analytical object, generating a resolved request representing second data expressing usage intent and indicating a request for results data obtained using the trained analytical model, generating an analytical model results data query for obtaining the results data in accordance with the trained analytical model and the analytical object, and outputting data for presenting a visualization of the results data obtained by executing the analytical model results data query, wherein a first portion of the results data corresponds with the analytical object and a second portion of the results data corresponds with the trained analytical model.

Abstract: Automatic data-analysis formula phrase generation includes obtaining a natural language string expressing a request for an automatically generated data-analysis formula phrase, obtaining first prompt data including a first proper subset of defined data-analysis formula phrases previously defined in a data access and analysis system in accordance with a defined data-analysis-formula grammar and associated with defined data-analysis formula phrase categories, obtaining first large language model generate data responsive to the first prompt data, obtaining a proper subset of the defined data-analysis formula phrase categories, obtaining second prompt data including a second proper subset of the defined data-analysis formula phrases identified in accordance with the proper subset of the defined data-analysis formula phrase categories, and obtaining second large language model generated data responsive to the second large language model input data that includes the automatically generated data-analysis formula phr

Abstract: Generating object morphisms during object search includes obtaining object-search request data, wherein the object-search request data includes object-search terms, obtaining resolved-request data representing the object-search terms, determining that a first analytical object partially consistent with the resolved-request data is available, wherein the first analytical object is consistent with a first portion of the resolved-request data, generating candidate object-morphism data with respect to the first analytical object in accordance with a second portion of the resolved-request data, outputting object-search response data including the candidate object-morphism data for presentation to a user, obtaining data indicating a selected object morphism from the candidate object-morphism data, generating a second analytical object in accordance with the first analytical object and the selected object morphism, wherein the second analytical object differs from the first analytical object, and outputting response

Abstract: Systems and methods for mapping natural language to queries using a query grammar are described. For example, methods may include generating, based on a string, a set of tokens of a database syntax; generating a query graph for the set of tokens from a finite state machine representing a query grammar, wherein nodes of the finite state machine represent token types, directed edges of the finite state machine represent valid transitions between token types in the query grammar, vertices of the query graph correspond to respective tokens of the set of tokens, and directed edges of the query graph represent a transition between two tokens in a sequencing of the tokens; determining, based on a tour of the query graph, a sequence of the tokens in the set of tokens, forming a database query; and invoking a search of a database using a query based on the database query to obtain search results.

Abstract: Systems and methods for query generation based on a logical data model with one-to-one joins are described. For example, methods may include accessing a join graph representing tables in a database; receiving a first query; selecting a connected subgraph of the join graph that includes the two or more tables referenced in the first query; accessing an indication that a directed edge of the connected subgraph corresponds to a one-to-one join; modifying the connected subgraph based on the indication to obtain a modified subgraph; generating one or more leaf queries based on the modified subgraph; generating a query graph that specifies joining of results from queries based on the one or more leaf queries; invoking a transformed query on the database that is based on the query graph and the queries based on the one or more leaf queries.

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 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: Semantic analysis to resolve ambiguous user input data with respect to a request for data includes identifying tokens based on the text string, identifying a tables in a database, wherein a token indicates a column from a table and a token indicates a column from another table, identifying candidate join paths for joining tables, obtaining respective candidate results using the candidate join paths, outputting combined candidate results including values from the respective candidate results, obtaining second user input data indicating a selected value, identifying the request for data as unambiguous and identifying a selected join path based on the selected value, and, in response to identifying the request for data as unambiguous, outputting data responsive to the request for data using the selected join path.

Abstract: A request for database results is received from a query coordinator at a database instance of a distributed database. The request includes a query execution instruction of a query plan and an indication of override instructions corresponding to the query execution instruction. The override instructions are such that they do not modify the query plan. The database instance includes the override instructions in a set of high-level language query instructions. The database instance performs just-in-time compiling of the set of high-level language query instructions to obtain a machine language query for performing the query execution instruction of the query plan. The database instance executes the machine language query to obtain the database results. The database instance then transmits the database results to the query coordinator.

Abstract: A current set of context features for a database query that is associated with a string is identified. The database query includes a sequence of tokens of a database syntax, and the current set of context features includes words from the string and tokens from the database query. An inference record is selected from an inference store based on a comparison of the current set of context features to context features of inference records in the inference store. The database query is modified using a resolution of the inference record to obtain an inferred database query. The resolution includes one or more tokens of the database syntax. A search of a database is invoked using a query based on the inferred database query to obtain search results.

Abstract: A first replay log is replayed to generate a first replay result. Replaying the first replay log includes replacing, in the first replay result, a first value of a first field included in a first command in the first replay log with a first hash value responsive to a determination that the first field is not utilized as a condition in at least one command included in the first replay log. A second replay log is replayed to generate a second replay result. The first replay result and the second replay result are compared to verify that the first replay log and the second replay log are equivalent.

Abstract: A request to execute a database command is transmitted from a device to a database command execution device. The request includes a first indicator of a first set of tokens available at the device at a time that the request is transmitted. A response to the request is received. The response includes a second indicator of a second set of tokens available at the database command execution device at a time that the request is received at the database command execution device. Responsive to a determination that the second indicator is different from the first indicator, a request for updated tokens is transmitted to the database command execution device. The first set of tokens is updated based on a received response to the request for the updated tokens. A list of tokens the updated first set of tokens that match a partial token received as an input is output.

Abstract: 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.

Abstract: Query execution on compressed in-memory data includes receiving, at a processor of an instance of a distributed in-memory database, a query for data from a table stored in the distributed in-memory database as compressed table data, obtaining results data responsive to the query from the table, and outputting the results data for presentation to a user. Obtaining results data includes allocating memory to identify allocated memory for decompressing the compressed table data, obtaining uncompressed table data by decompressing the compressed table data into the allocated memory, and obtaining the results data from the uncompressed table data. The allocated memory is deallocated in response to obtaining the results data. Compressing a table to form compressed table data is also described.