Abstract: Techniques are disclosed relating to executing a bifurcated computer system for different types of data processing. The system receives a plurality of requests to execute queries and executes a first service of the system for a first query specified by the requests based on the first query specifying a first type of data. The system accesses, via the first service for the first query, a first database storing the first type of data. The system executes a second service for a second query specified by the requests based on the second query specifying a second type of data. The system accesses, via the second service for the second query, a second database storing the second type of data. The system transmits results of the first database to a user device of the first query and results of the second database to a user device of the second query.

Abstract: Techniques are disclosed for implementing cross-zone communication for computing zones executing different coding protocols. A server computer system may receive, via a proxy layer of a first instance of an application executing within a first computing zone according to a first set of coding protocols, a request for a service executed via a second instance of the application in a second computing zone according to a second, different set of coding protocols. The system may alter, via a remote layer of the first instance, a set of data specified in the request to comply with the second, set of protocols. The system may transmit, via the remote layer of the first instance to a remote layer of the second instance, the altered set of data. The system may advantageously provide a simplified development interface allowing for both development and testing within a local environment without deployment of multiple different services.

Abstract: Techniques are disclosed relating to determining a minimum search region with a threshold number of entities within the minimum search region. In some embodiments, a system selects, based on a location of a user device, a first region, where the location of the device is at a center of the first region. The system executes, based on the first region, a query on a database storing entity locations. The system increases the first region by a specified amount to generate a second search region, where the increasing is based on determining that entities returned by the first query does not satisfy an entity threshold requirement. The system executes, based on the second region, a second query on the database. In response to the second query returning a number of entities that satisfy the threshold requirement, the system causes display, at the device, of the entities returned by the second query.

Abstract: Techniques are disclosed relating to partitioning batch queries for multi-engine execution. A system receives a batch query specifying query data and including a request for geospatial data for regions corresponding to the query data. Based on locations corresponding to the query data, the system partitions the query data into subsets. The system may assign the subsets of query data to query engines corresponding to the locations of the subsets. The system may cause the engines to retrieve geographic region data corresponding to the locations included in the subsets, where the retrieving is performed by a given query engine for a corresponding subset by accessing an in-memory index of the given engine that stores geographic region data for a geographic partition within which the corresponding subset of query data is located. The system may store region data retrieved by the engines for the subsets in an aggregated data store.

Abstract: A method for operating a graph database, including receiving, by a computer system, a query to a particular graph database, the query identifying a plurality of vertices of the particular graph database. The method further includes performing, by the computer system, hash operations on two or more of the plurality of vertices to generate respective hash values and dividing, using the respective hash values, the query into a plurality of sub-queries, each corresponding to a subset of the plurality of vertices. The method also includes sending, by the computer system, ones of the plurality of sub-queries to a plurality of database repositories for the particular graph database.

Abstract: Techniques are disclosed relating to executing a bifurcated computer system for different types of data processing. The system receives a plurality of requests to execute queries and executes a first service of the system for a first query specified by the requests based on the first query specifying a first type of data. The system accesses, via the first service for the first query, a first database storing the first type of data. The system executes a second service for a second query specified by the requests based on the second query specifying a second type of data. The system accesses, via the second service for the second query, a second database storing the second type of data. The system transmits results of the first database to a user device of the first query and results of the second database to a user device of the second query.

Abstract: Techniques are disclosed relating to determining a minimum search region with a threshold number of entities within the minimum search region. In some embodiments, a system selects, based on a location of a user device, a first region, where the location of the device is at a center of the first region. The system executes, based on the first region, a query on a database storing entity locations. The system increases the first region by a specified amount to generate a second search region, where the increasing is based on determining that entities returned by the first query does not satisfy an entity threshold requirement. The system executes, based on the second region, a second query on the database. In response to the second query returning a number of entities that satisfy the threshold requirement, the system causes display, at the device, of the entities returned by the second query.

Abstract: A method for operating a graph database, including receiving, by a computer system, a query to a particular graph database, the query identifying a plurality of vertices of the particular graph database. The method further includes performing, by the computer system, hash operations on two or more of the plurality of vertices to generate respective hash values and dividing, using the respective hash values, the query into a plurality of sub-queries, each corresponding to a subset of the plurality of vertices. The method also includes sending, by the computer system, ones of the plurality of sub-queries to a plurality of database repositories for the particular graph database.

Abstract: Methods and systems are presented for assisting a user to identify and evaluate features for use in a machine learning model configured to perform a task. Based on graph data associated with a graph data structure, a user interface is provided on a device. Based on user inputs received via the user interface, a feature candidate for the machine learning model is determined. The feature candidate is associated with a particular way of traversing the graph data structure to obtain attribute values associated with one or more vertices and/or one or more edges in the graph data structure. Based on the attribute values, a value corresponding to the feature candidate can be calculated. The value can be used to evaluate the effectiveness of the feature candidate in performing the task. The feature candidate can then be incorporated into the machine learning model as one of the input features.

Abstract: Techniques are disclosed for implementing cross-zone communication for computing zones executing different coding protocols. A server computer system may receive, via a proxy layer of a first instance of an application executing within a first computing zone according to a first set of coding protocols, a request for a service executed via a second instance of the application in a second computing zone according to a second, different set of coding protocols. The system may alter, via a remote layer of the first instance, a set of data specified in the request to comply with the second, set of protocols. The system may transmit, via the remote layer of the first instance to a remote layer of the second instance, the altered set of data. The system may advantageously provide a simplified development interface allowing for both development and testing within a local environment without deployment of multiple different services.

Abstract: A method for operating a graph database, including receiving, by a computer system, a query to a particular graph database, the query identifying a plurality of vertices of the particular graph database. The method further includes performing, by the computer system, hash operations on two or more of the plurality of vertices to generate respective hash values and dividing, using the respective hash values, the query into a plurality of sub-queries, each corresponding to a subset of the plurality of vertices. The method also includes sending, by the computer system, ones of the plurality of sub-queries to a plurality of database repositories for the particular graph database.

Abstract: Methods and systems are presented for assisting a user to identify and evaluate features for use in a machine learning model configured to perform a task. Based on graph data associated with a graph data structure, a user interface is provided on a device. Based on user inputs received via the user interface, a feature candidate for the machine learning model is determined. The feature candidate is associated with a particular way of traversing the graph data structure to obtain attribute values associated with one or more vertices and/or one or more edges in the graph data structure. Based on the attribute values, a value corresponding to the feature candidate can be calculated. The value can be used to evaluate the effectiveness of the feature candidate in performing the task. The feature candidate can then be incorporated into the machine learning model as one of the input features.