According to one embodiment, a method that supports queries deploying operators based on multiple programming languages is described. A sequence of operators associated with a query is identified, where the sequence of operators includes at least two neighboring operators including a first operator based on a first programming language and a second operator based on a second programming language that is different from the first programming language. Thereafter, a schema associated with the first operator and a schema associated with the second operator is determined along with the compatibility between the schema of the first operator and the schema of the second operator. A query error message is generated in response to incompatibility between the first operator schema and the second operator schema. Compatibility is determined when an output generated by execution of the first operator provides machine data needed as input for execution of the second operator.

In one embodiment, a method includes receiving a user request to create a reminder from a client system associated with a user, wherein the user request does not specify an activation-condition for the reminder, determining one or more proactive activation-conditions for the reminder, storing the reminder in a reminder store, receiving one or more inputs associated with the user, determining a user context associated with the user based on the one or more inputs, determining the one or more proactive activation-conditions for the reminder are satisfied based on the user context, and sending instructions for presenting the reminder to the user to the client system responsive to determining the one or more proactive activation-conditions are satisfied.

Systems, computer-implemented methods, applications, user interfaces, and tangible non-transitory computer readable media for providing triggers in a system of record are disclosed. For example, a computer-implemented method may include maintaining a trigger associated with an application where the trigger comprises a set of conditions and a set of operations associated with a custom computer language that is supported by the application, evaluating the conditions associated with the trigger based on an occurrence of an event associated with the application, determining that the conditions associated with the trigger are satisfied based on the evaluating of the conditions, and executing the operations associated with the custom computer language based on determining that the conditions of the trigger are satisfied. For example, execution of such operations may include performing one or more actions in association with the application and/or one or more third-party applications that are integrated with the application.

A system for processing database entries includes a memory configured to store a database including multiple line item database entries and multiple receipt entries, a display including a user interface and a processor configured to execute instructions. The instructions include receiving a member identifier, obtaining at least a portion of the multiple line item database entries corresponding to the received member identifier, displaying the obtained multiple line item database entries, receiving a selection of one of the multiple receipt entries, and displaying an image of the selected receipt entry. The instructions further include receiving a selection of a location on the displayed image of the selected receipt entry, receiving a selection of one of the displayed multiple line item database entries, and storing, in the database, a relational link between the selected location on the displayed image of the selected receipt entry and the selected line item database entry.

A client device for storing a data set in a database is provided. The data set includes a plurality of initial data elements. The client device is configured to determine a storage location of the database for each initial data element and to obtain storage location configuration information based on the storage location. The client device is further configured to process, based on the storage location configuration information, each initial data element of a first subset of the plurality of initial data elements into a processed data element using one or more data processing operations and to transmit a modified data set to a data storage server for storing the modified data set in the database, wherein the modified data set comprises the processed data elements in the first subset and unprocessed initial data elements in a second subset which is complementary to the first subset.

Presently disclosed are systems and methods for generating customized filtered-and-partitioned market-data feeds. In an embodiment, an output-feed profile is maintained in data storage at a market-data-processing device (MDPD). The output-feed profile specifies a subset of ticker symbols and a ticker-symbol-based feed-partitioning scheme. An input feed of order-book updates to ticker symbols is received at the MDPD from an upstream device. At the MDPD, a customized market-data output feed is generated according to the maintained output-feed profile at least in part by filtering the input feed down to the order-book updates to ticker symbols in the specified subset and partitioning the filtered feed according to the specified ticker-symbol-based feed-partitioning scheme. The customized market-data output feed is transmitted from the MDPD to a downstream device.

In one aspect, the present disclosure relates to a method comprising: receiving, at a client device, information from a node manager about a plurality of nodes in a computer cluster, the information comprising a network address associated each of the plurality of nodes and sending, by the client device, a request to a load balancer to access a first node from the plurality of nodes, the request comprising a first URL including an encoded representation of the network address associated with the first node. The load balancer is configured to determine the request should be routed to a first network address based on decoding the URL, the first network address associated with a first node from the plurality of nodes and forward the request to the first node in response to the determining.

A data processing system for producing a subset of data from a plurality of data sources, including: memory storing a plurality of data sources to be represented in an editor interface; a data structure modification module that selects a plurality of data sources to be represented in an editor interface and generates a subset of data included in the plurality of data sources; memory that stores the selected data structures included in the subset, with at least one of the stored data structures including the one or more modified attributes of the one or more respective fields; rendering module that displays, in the editor interface, representations of the stored data structures; and a segmentation modules that segments a plurality of received data records.

The present disclosure relates to systems and methods for an intelligent assistant (e.g., a chatbot) that can be used to enable a user to generate a machine learning system. Techniques can be used to automatically generate a machine learning system to assist a user. In some cases, the user may not be a software developer and may have little or no experience in either machine learning techniques or software programming. In some embodiments, a user can interact with an intelligent assistant. The interaction can be aural, textual, or through a graphical user interface. The chatbot can translate natural language inputs into a structural representation of a machine learning solution using an ontology. In this way, a user can work with artificial intelligence without being a data scientist to develop, train, refine, and compile machine learning models as stand-alone executable code.

Methods, systems, and devices supporting managing a data processing flow are described. A device (e.g., an application server) may host a cloud-based collaboration application, such as an interactive document application. The device may receive an instance of a data processing flow for a flow application based on a first user input to the cloud-based collaboration application. The device may receive the instance of the data processing flow from a source device hosting the flow application. The device may embed the flow application in the cloud-based collaboration application. The device may then receive user inputs to the data processing flow from multiple users collaborating on the same flow in the cloud-based collaboration application. Based on the user inputs, the device may modify the instance of the data processing flow and transmit the modified instance back to the source device to synchronize the data processing flow in the flow application.