Abstract: A low-latency database analysis system using an object index may include obtaining data expressing a usage intent, and, in response to a determination that the data expressing the usage intent includes object search request data including a user identifier and zero or more object search terms, obtaining, from an object-index responsive to the object search request data, object indexing data for an object, obtaining object detail data for the object, obtaining an object visualization capture for the object, and outputting object search response data including the object visualization capture and at least a portion of the object detail data for presentation to a user.

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: Identifying table joins includes obtaining respective casting similarities between pairs of columns of a first table and a second table. Each pair of columns includes a first column of the first table and a second column of the second table. Ones of the pairs of columns not satisfying a casting similarity condition are discarded to obtain first join candidates. Respective string similarities for the first join candidates are obtained. Ones of the first join candidates not satisfying a string similarity condition are discarded to obtain second join candidates. Final join candidates are obtained using the respective casting similarities and the respective string similarities of the second join candidates. A selected join candidate of the final join candidates is received from a user.

Abstract: Systems and methods for conversational user experiences and conversational database analysis disclosed herein improve the efficiency and accessibility of low-latency database analytics.

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: Automatic data modeling in a low-latency data access and analysis system 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

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: 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: 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: Distributed pseudo-random subset generation includes obtaining a data-query indicating a first table having a first column including unique values, a second table having a second column including unique values, a join clause joining the first table and the second table on the first column and the second column, and a limit value, pseudo-random filtering the first table to obtain left intermediate data and left filtering criteria, pseudo-random filtering the second table to obtain right intermediate data and right filtering criteria, obtaining intermediate results data by full outer joining the left intermediate data and the right intermediate data, obtaining results data by filtering the intermediate results data using most-restrictive filtering criteria among the left filtering criteria and the right filtering criteria, and outputting the results data, wherein outputting the results data includes limiting the cardinality of rows of the results data to be at most the limit value.

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 by searching a phrase index based on the phrase fragment, wherein the indexed phrase at least partially matches the phrase fragment in accordance with the defined phrase pattern, in response to identifying the indexed phrase, obtaining a resolved request representing the data expressing the usage intent in accordance with the indexed phrase, generating a data query in accordance with the resolved request and a defined structured query language, obtaining results data responsive to execution of the data query by a database that implements the defined structured query language, and outputting the results data.

Abstract: Performing, by a low-latency data access and analysis system, automatic grammar switching includes, in response to obtaining data indicating a request to switch from using a first defined grammar to using a second defined grammar, wherein the request includes data representing a first resolved-request generated for a first input string using the first defined grammar, generating, using the second defined grammar, a second resolved-request for the first input string, automatically generating a data-query in accordance with the second resolved-request, and outputting output data including results data obtained by executing the data-query.

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: Injecting override instructions associated with query executions instructions performed on a distributed database includes receiving a data-query; generating, by a first database instance, a query plan that includes a first query execution instruction for transmission to a second database instance; transmitting, by the first database instance, a request for partial results to the second database instance, where the request includes the first query execution instruction and an indication of override instructions corresponding to the first query execution instruction; responsive to a determination that the request includes the indication, including, by the second database instance, the override instructions in a set of high-level language query instructions; obtaining, by the second database instance, a machine language query based on the set; executing, at the second database instance, the machine language query to obtain the partial results; and transmitting, by the second database instance, the partial resul

Abstract: Providing a search interface for a database includes receiving string data entered via a user interface. A sequence of tokens representative of the string data is determined. Determining the sequence of tokens includes applying natural language processing to the string data. A first database query is generated in accordance with the sequence of tokens. Respective text representations for tokens in the sequence of tokens are presented via the user interface. Feedback data related to the sequence of tokens is received via the user interface. A token of the sequence of tokens is modified based on the feedback data to obtain a modified sequence of tokens. A second database query is generated based on the modified sequence of tokens. Results data are obtained from the database responsive to execution of the second database query by the database. Data based on the results data are output for presentation in the user interface.

Abstract: Search guidance includes generating user interface data for at least a portion of a user interface including a user input element, a data-analytics request construct card, and a data-analytics guidance portion. The data-analytics request construct card includes text describing usage of a data-analytics request construct card grammatical function. The user interface data is output for presentation to a user. Data-analytic request construct card data expressing usage intent is received and updated user interface data is generated. The updated user interface data corresponds to an updated user input element in accordance with the data-analytic request construct card data and an updated data-analytics guidance portion in accordance with the data-analytic request construct card data. The updated user interface data is output. Resolved-request data is generated in accordance with the data-analytic request construct card data.

Abstract: Obtaining an approximate unique count for a column from a table from a database includes, generating, for a value from an unevaluated row, a hash value in a defined range of hash values, determining a cardinality of leading zeros in the hash value, identifying a bucket with respect to the hash value from a plurality of buckets corresponding to the defined range of hash values, wherein the buckets from the plurality of buckets correspond with respective non-overlapping portions of the defined range of hash values, such that the hash value is in the portion of the defined range of hash values corresponding to the bucket, and appending to an unsorted sparse representation a bucket identifier for the bucket and the cardinality of the leading zeros, and, in response to a determination that unevaluated rows are unavailable in the table, determining the approximate unique count using the unsorted sparse representation.

Abstract: Automatic database analysis includes identifying a current context for accessing data from a low-latency database and generating an exploration query based on the current context, which includes identifying a column from the low-latency database as a column of utility in response to determining that a probabilistic utility for the column satisfies a defined utility criterion. The current context includes a requested result set satisfying a requested search criterion, and the probabilistic utility is based on the current context. The analysis includes generating an exploration result set based on the exploration query, generating insights based on the exploration result set, ranking the insights, and outputting at least one insight based on the ranking.

Abstract: Querying a distributed database including a table sharded into shards distributed to database instances includes receiving a data-query that includes an aggregation clause on a first column and a grouping clause on a second column; obtaining and outputting results data. Obtaining the results data includes receiving, by a query coordinator, intermediate results data; and combining, by the query coordinator, the intermediate results to obtain the results data.

Abstract: Enabling auto-completion of database commands includes receiving, at a database command execution device from a client device, a request to execute a database command where the request includes a first indicator of a first set of tokens of the database that is available at the client device; executing the database command; transmitting, from the database command execution device to the client device, a response to the request that includes a status of the execution of the database command and a second indicator of a second set of tokens of the database that is different from the first set of tokens; receiving, at the database command execution device and from the client device, an update-tokens request that includes the first indicator; and transmitting, from the database command execution device and to the client device, data indicative of differences between the second set of tokens and the first set of tokens.