Abstract: Provided are techniques for automatically enhancing content items through identifying relationships. One or more content items and an associated transcript for each of the one or more content items are received. One or more terms are identified in the one or more content items. A content tree is built for each of the one or more content items using the one or more terms and corresponding contexts. A content graph is built using each content tree. One or more subgraphs of the content graph are identified. One or more paths through each of the one or more subgraphs are identified and one or more content expansion recommendations are provided. In response to selection of a content item, the one or more paths are used to provide an enhanced content item with one or more prerequisite content items and one or more subsequent content items.

Abstract: A computer-implemented method, according to one embodiment, includes: receiving multiple data blocks from a central data storage location, and modifying data in one or more of the received data blocks. Modifying data in one or more of the data blocks further includes creating copies of the one or more data blocks and the data included therein, and modifying the data in the copies of the one or more data blocks. A copy of the modified data blocks are sent to the central data storage location. Moreover, the modified data blocks are used to replace corresponding ones of the data blocks received from the central data storage location in response to receiving an indication that the modified data blocks have been implemented at the central data storage location.

Abstract: In an approach to improve the extraction of test datasets for testing and resource optimization, embodiments execute a test run on a full dataset of a job, and identify existing bottlenecks in the job through a run-time monitoring interface. Additionally, embodiments execute a run-time metrics analysis, a source code analysis, and a source data impact analysis of a distributed data processing engine executing a distributed data processing job, and generate, by an analysis and impact scoring engine, an impact scoring table of job transformations based on the source code analysis. Furthermore, embodiments generate data extraction rules based on the impact scoring table, and extract a test dataset based on the data extraction rules. Moreover, embodiments evaluate the data extraction rules against user defined thresholds, and prepare a representative test dataset, and output, through a user interface on a computing device, the representative test dataset to a user.

Abstract: In an approach to improve the extracting test datasets for testing and resource optimization, embodiments execute a test run on a full dataset of a job, and identify existing bottlenecks in the job through a run-time monitoring interface. Additionally, embodiments execute a run-time metrics analysis, a source code analysis, and a source data impact analysis of a distributed data processing engine executing a distributed data processing job, and generate, by an analysis and impact scoring engine, an impact scoring table of job transformations based on the source code analysis. Furthermore, embodiments generate data extraction rules based on the impact scoring table, and extract a test dataset based on the data extraction rules. Moreover, embodiments evaluate the data extraction rules against user defined thresholds, and prepare a representative test dataset, and output, through a user interface on a computing device, the representative test dataset to a user.

Abstract: In an approach to improve the extracting test datasets for testing and resource optimization, embodiments execute a test run on a full dataset of a job, and identify existing bottlenecks in the job through a run-time monitoring interface. Additionally, embodiments execute a run-time metrics analysis, a source code analysis, and a source data impact analysis of a distributed data processing engine executing a distributed data processing job, and generate, by an analysis and impact scoring engine, an impact scoring table of job transformations based on the source code analysis. Furthermore, embodiments generate data extraction rules based on the impact scoring table, and extract a test dataset based on the data extraction rules. Moreover, embodiments evaluate the data extraction rules against user defined thresholds, and prepare a representative test dataset, and output, through a user interface on a computing device, the representative test dataset to a user.

Abstract: Provided are techniques for automatically enhancing content items through identifying relationships. One or more content items and an associated transcript for each of the one or more content items are received. One or more terms are identified in the one or more content items. A content tree is built for each of the one or more content items using the one or more terms and corresponding contexts. A content graph is built using each content tree. One or more subgraphs of the content graph are identified. One or more paths through each of the one or more subgraphs are identified and one or more content expansion recommendations are provided. In response to selection of a content item, the one or more paths are used to provide an enhanced content item with one or more prerequisite content items and one or more subsequent content items.

Abstract: In an approach to improve the extracting test datasets for testing and resource optimization, embodiments execute a test run on a full dataset of a job, and identify existing bottlenecks in the job through a run-time monitoring interface. Additionally, embodiments execute a run-time metrics analysis, a source code analysis, and a source data impact analysis of a distributed data processing engine executing a distributed data processing job, and generate, by an analysis and impact scoring engine, an impact scoring table of job transformations based on the source code analysis. Furthermore, embodiments generate data extraction rules based on the impact scoring table, and extract a test dataset based on the data extraction rules. Moreover, embodiments evaluate the data extraction rules against user defined thresholds, and prepare a representative test dataset, and output, through a user interface on a computing device, the representative test dataset to a user.