Abstract: Systems and methods are described for merging customer profiles, such as may be implemented by a computer-implemented contact center service. In some aspects, a subset of profiles may be determined that satisfy merging criteria, where individual profiles include a plurality of data fields. At least one value in a first data field that conflicts between at least two profiles may be identified. Next a merged value may be selected for the first data field based on data deduplication criteria, where the data deduplication criteria includes at least one indicator of accuracy of values of the plurality of data fields. As a result of a determination that at least the subset of profiles of the group of profiles meet the merging criteria, at least the subset of profiles may be combined into a combined profile using the merged value.

Abstract: Systems and methods for the execution and operation of compute instances and tasks to perform batch jobs on behalf of customers of a computing resource service provider. Batch jobs can be subdivided into job fragments that can be concurrently executed by compute resources instantiated by the computing resource service provider. The computing resource service provider utilizes control mechanisms in the form of a maximum concurrent job fragment thresholds to mitigate the potential impact of resource constraints associated with larger batch jobs.

Abstract: Embodiments of the present invention provide improved techniques for securely delivering content and messages to endpoints. Based on a strategic program for delivering the content, the messages may be delivered according to a schedule and to particular endpoints. Embodiments of the present invention provide the ability to apply filters in order to determine a set of endpoints according to the delivery schedule. The messages may be further modified to improve security by adding authentication mechanisms and other attributes that enhance the content delivered to the endpoints.

Abstract: Approaches are described for managing workload, or other tasks in a data center, shared resource environment or other such electronic environment. In particular, a customer (or other end user, etc.) is able to use a computing device to submit a request to process information across at least one appropriate network to be received by a provider environment. The provider environment includes a set of resources (e.g., computing devices) operable to process the information for any of a variety of different purposes. Code can be deployed and executed at one or more of the host machines, wherein when executed, can enable the host machines to perform operations to process a workload in a distributed self-organizing manner, without a master server or other management device, to distribute work, handle situations where host machines go offline, etc.

Abstract: A system, method, and computer-readable medium for performing a predictive caching operation in which a hit rate is improved by pre executing statements that are predicted based upon previous use patterns. More specifically, by analyzing a stream of statements provided to a server, such as a database server, patterns of usage are detected and based upon these patterns, statements provided to the server are executed before the actual application executes the predicted statements. Thus the application executes faster because the data requested is already cached based upon the predictive execution.

Abstract: Devices and processes perform a metrics aggregation process within the context of a serverless compute environment that includes a fleet of execution environment containers for executing ephemeral functions. In response to receipt of triggering events, functions, registered to handle the events, are launched in separate execution environments of an event-driven compute service. The functions generate metrics that are sent to the execution environment via a call (e.g., via asynchronous call) to the execution environment, and the functions may retire, without saving execution state for the function, and before the execution environment passes the metrics to an intermediate metrics aggregation service. The metric aggregation system receives the metrics generated by the fleet of instances of the function from the plurality of execution environments of the event-driven compute service, batch processes the metrics into an aggregated record, and transmits the aggregate record to a metrics reporting service.

Abstract: A computing resource service receives a request to execute a batch job. The computing resource service invokes a first compute instance to divide the batch job into a plurality of job fragments, where each job fragment comprises a respective subset of operations for the batch job that can be processed within a limited lifespan of a compute instance. The job fragments are distributed among a plurality of second compute instances to enable collective processing of the job fragments. The status of the batch job is determined based at least in part on individual statuses of the job fragments.

Abstract: In one embodiment, a method includes receiving a data-transformation request in relation to a visualization of a first dataset, wherein the data-transformation request expresses at least one transformation of the first dataset without using Structured Query Language (SQL) syntax, wherein the visualization is characterized by a first SQL statement. In addition, the method includes automatically determining based, at least in part, on a mapping of the visualization to the first SQL statement, a second SQL statement operable to return a second dataset. Further, the method includes causing the second SQL statement to be executed on one or more databases. Moreover, the method includes receiving, in response to the causing, the second dataset. The method also includes updating the visualization to reflect the second dataset.

Abstract: Disclosed are systems and methods that allow a database engine to access a non-relational document database and dynamically apply a schema that maps documents comprising semi-structured data into a relational data structure. In embodiments, mapping may be accomplished by parsing and analyzing a set of sample documents to empirically generate a normalized tabular schema. In embodiments, the schema accommodates format evolution and variability of documents having different structures and different sets of attributes is automatically executed in a background process without requiring user involvement. This normalization process eliminates the need to create unique modeling languages for semi-structured data. In embodiments, an SQL dialect may be used to join query results and combine the resulting document data with tables from different dimensional or relational databases to generate a combined result without the need to create additional temporary tables for non-conforming documents.

Abstract: In one embodiment, a method includes defining a slice of a dimensional database. The slice includes at least one dimension and at least one measurement and is expressable as a table. The method further includes building, in a structured query language (SQL) dialect, a single query that queries the slice and one or more non-dimensional databases. The SQL dialect represents the at least one dimension, the at least one measurement, and data attributes of the one or more non-dimensional databases. In addition, the method includes parsing the single query. The parsing includes generating a dimensional query for the dimensional database and a non-dimensional query for each of the one or more non-dimensional databases. Furthermore, the method includes executing the dimensional query on the dimensional database. Moreover, the method includes, for each non-dimensional database of the one or more non-dimensional databases, executing the non-dimensional query on the non-dimensional database.

Abstract: A system, method, and computer-readable medium for performing a predictive caching operation in which a hit rate is improved by pre executing statements that are predicted based upon previous use patterns. More specifically, by analyzing a stream of statements provided to a server, such as a database server, patterns of usage are detected and based upon these patterns, statements provided to the server are executed before the actual application executes the predicted statements. Thus the application executes faster because the data requested is already cached based upon the predictive execution.

Abstract: In one embodiment, a method includes enrolling a supplicant device as an authentication factor for a user. The enrolling includes storing a public key of an asymmetric key pair generated by an authentication application on the supplicant device. The method also includes receiving, from an access device, a request to access a service using an identity of the user. In addition, the method includes, responsive to the receiving, publishing an authentication code to the access device. The method further includes receiving an authentication package from the authentication application without contacting the authentication application. The authentication package includes a digital signature of the authentication code. The method additionally includes validating the digital signature using the public key. Moreover, the method includes, responsive to a determination that the validating is successful, allowing the access device to access the service.

Abstract: In one embodiment, a method includes defining a slice of a dimensional database. The slice includes at least one dimension and at least one measurement and is expressable as a table. The method further includes building, in a structured query language (SQL) dialect, a single query that queries the slice and one or more non-dimensional databases. The SQL dialect represents the at least one dimension, the at least one measurement, and data attributes of the one or more non-dimensional databases. In addition, the method includes parsing the single query. The parsing includes generating a dimensional query for the dimensional database and a non-dimensional query for each of the one or more non-dimensional databases. Furthermore, the method includes executing the dimensional query on the dimensional database. Moreover, the method includes, for each non-dimensional database of the one or more non-dimensional databases, executing the non-dimensional query on the non-dimensional database.