Ab Initio Technology LLC

A method implemented by a data processing system including: accessing the container image that includes the first application and a second application; determining, by the data processing system, the number of parallel executions of the given module of the first application; for the given module, generating a plurality of instances of the container image in accordance with the number of parallel executions determined, for each instance, configuring that instance to execute the given module of the first application; causing each of the plurality of configured instances to execute on one or more of the host systems; and for at least one of the plurality of configured instances, causing, by the second application of that configured instance, communication between the data processing system and the one or more of the host systems executing that configured instance.

Techniques for determining processing layouts to nodes of a dataflow graph. The techniques include: obtaining information specifying a dataflow graph, the dataflow graph comprising a plurality of nodes and a plurality of edges connecting the plurality nodes, the plurality of edges representing flows of data among nodes in the plurality of nodes, the plurality of nodes comprising: a first set of one or more nodes; and a second set of one or more nodes disjoint from the first set of nodes; obtaining a first set of one or more processing layouts for the first set of nodes; and determining a processing layout for each node in the second set of nodes based on the first set of processing layouts and one or more layout determination rules, the one or more layout determination rules including at least one rule for selecting among processing layouts having different degrees of parallelism, and information indicating that data generated by at least one node in the first and/or third set of nodes is not used by any nodes in the dataflow graph downstream from the at least one node.

A method for performing real-time segmentation by updating a wide record based on receipt of real-time data, wherein an item of real-time data represents a transaction, detecting that the updated wide record satisfies criteria for performing real-time segmentation, and performing real-time segmentation on the updated, wide record, wherein real-time is relative to when a transaction represented in the updated wide record occurs.

A method performed by a data processing system for processing data, the method including: intermittently receiving data from one or more data streams, the received data including data records; detecting two or more particular data records in the received data records, where the detected two or more particular data records each include a particular identifier; for that particular identifier, creating a collection of data records; for at least one particular data record included in the collection of data records, searching data records for a historical aggregation of data; and computing combined data; modifying a data record by inserting the combined data into a field of the data record and by inserting data from at least one of the data records in the collection into another field of the data record; based on applying the rules, writing to memory one or more instructions for initiation of one or more actions.

A computing system includes a distributed computing cluster including a plurality of computing nodes interconnected by an interconnect network over which the computing nodes of the plurality of computing nodes communicate with each other by passing messages. The computing nodes are configured with a first parameter governing transmissions of messages by the computing nodes over the interconnect network. The computing nodes are configured to accumulate messages for transmission as a group of messages according to the first parameter, and the computing system is configured to limit injections of computing requests into the distributed computing cluster according to a second parameter. A controller is configured to receive at least one predetermined service level requirement and to control a value of the second parameter and a value of the first parameter to control a computational throughput of the distributed computing cluster while complying with the at least one service level requirement.

A method implemented by a data processing system including: accessing the container image that includes the first application and a second application; determining, by the data processing system, the number of parallel executions of the given module of the first application; for the given module, generating a plurality of instances of the container image in accordance with the number of parallel executions determined, for each instance, configuring that instance to execute the given module of the first application; causing each of the plurality of configured instances to execute on one or more of the host systems; and for at least one of the plurality of configured instances, causing, by the second application of that configured instance, communication between the data processing system and the one or more of the host systems executing that configured instance.

In a first aspect, a method includes, at a node of a Hadoop cluster, the node storing a first portion of data in HDFS data storage, executing a first instance of a data processing engine capable of receiving data from a data source external to the Hadoop cluster, receiving a computer-executable program by the data processing engine, executing at least part of the program by the first instance of the data processing engine, receiving, by the data processing engine, a second portion of data from the external data source, storing the second portion of data other than in HDFS storage, and performing, by the data processing engine, a data processing operation identified by the program using at least the first portion of data and the second portion of data.

Techniques for determining processing layouts to nodes of a dataflow graph. The techniques include: obtaining information specifying a dataflow graph, the dataflow graph comprising a plurality of nodes and a plurality of edges connecting the plurality nodes, the plurality of edges representing flows of data among nodes in the plurality of nodes, the plurality of nodes comprising: a first set of one or more nodes; and a second set of one or more nodes disjoint from the first set of nodes; obtaining a first set of one or more processing layouts for the first set of nodes; and determining a processing layout for each node in the second set of nodes based on the first set of processing layouts and one or more layout determination rules, the one or more layout determination rules including at least one rule for selecting among processing layouts having different degrees of parallelism, and information indicating that data generated by at least one node in the first and/or third set of nodes is not used by any nodes in the dataflow graph downstream from the at least one node.

An approach to parallel access of data from a distributed filesystem provides parallel access to one or more named units (e.g., files) in the filesystem by creating multiple parallel data streams such that all the data of the desired units is partitioned over the multiple streams. In some examples, the multiple streams form multiple inputs to a parallel implementation of a computation system, such as a graph-based computation system, dataflow-based system, and/or a (e.g., relational) database system.

A method for performing a distributed computation on a computing system using computational resources dynamically allocated using a computational resource manager includes storing information specifying quantities of computational resources associated with respective ones of a number of program portions of the program, where the program portions perform successive transformations of data and each program portion uses computational resources granted by the computational resource manager enabling computation associated with that program portion to be performed in the computing system, requesting a first quantity of computational resources associated with a first program portion of the number of program portions from the computational resource manager, receiving a second quantity of computational resources from the computational resource manager, less than the requested first quantity of computational resources, performing computation associated with the first portion of the program using the second quantity of computational resources, while performing the computation associated with the first portion of the program using the second quantity of computational resources, receiving an additional quantity of computational resources from the computational resource manager, and performing an additional computation associated with the first portion of the program using the additional quantity of computational resources while performing the computation associated with the first portion using the second quantity of computational resources.