5th Workshop on Big Data Benchmarking (2014) - tele-TASKhttps://www.tele-task.de/series/1019/The objective of the WBDB workshops is to make progress towards development of industry standard application-level benchmarks for evaluating hardware and software systems for big data applications. To make progress towards a big data benchmarking standard, the workshop will explore a range of issues including: Data features: New feature sets of data including, high-dimensional data, sparse data, event-based data, and enormous data sizes. System characteristics: System-level issues including, large-scale and evolving system configurations, shifting loads, and heterogeneous technologies for big data and cloud platforms. Implementation options: Different implementation options such as SQL, NoSQL, Hadoop software ecosystem, and different implementations of HDFS. Workload: Representative big data business problems and corresponding benchmark implementations. Specification of benchmark applications that represent the different modalities of big data, including graphs, streams, scientific data, and document collections. Hardware options: Evaluation of new options in hardware including different types of HDD, SSD, and main memory, and large-memory systems, and new platform options that include dedicated commodity clusters and cloud platforms. Synthetic data generation: Models and procedures for generating large-scale synthetic data with requisite properties. Benchmark execution rules: E.g. data scale factors, benchmark versioning to account for rapidly evolving workloads and system configurations, benchmark metrics. Metrics for efficiency: Measuring the efficiency of the solution, e.g. based on costs of acquisition, ownership, energy and/or other factors, while encouraging innovation and avoiding benchmark escalations that favor large inefficient configuration over small efficient configurations. Evaluation frameworks: Tool chains, suites and frameworks for evaluating big data systems. Early implementations: Of the Deep Analytics Pipeline or BigBench and lessons learned in benchmarking big data applications. Enhancements: Proposals to augment these benchmarks, e.g. by adding more data genres (e.g. graphs), or incorporating a range of machine learning and other algorithms, will be entertained and are encouraged.High quality e-learning content created with tele-TASK - more than video! Powered by Hasso Plattner Institute (HPI)various lecturersThe objective of the WBDB workshops is to make progress towards development of industry standard application-level benchmarks for evaluating hardware and software systems for big data applications. To make progress towards a big data benchmarking standard, the workshop will explore a range of issues including: Data features: New feature sets of data including, high-dimensional data, sparse data, event-based data, and enormous data sizes. System characteristics: System-level issues including, large-scale and evolving system configurations, shifting loads, and heterogeneous technologies for big data and cloud platforms. Implementation options: Different implementation options such as SQL, NoSQL, Hadoop software ecosystem, and different implementations of HDFS. Workload: Representative big data business problems and corresponding benchmark implementations. Specification of benchmark applications that represent the different modalities of big data, including graphs, streams, scientific data, and document collections. Hardware options: Evaluation of new options in hardware including different types of HDD, SSD, and main memory, and large-memory systems, and new platform options that include dedicated commodity clusters and cloud platforms. Synthetic data generation: Models and procedures for generating large-scale synthetic data with requisite properties. Benchmark execution rules: E.g. data scale factors, benchmark versioning to account for rapidly evolving workloads and system configurations, benchmark metrics. Metrics for efficiency: Measuring the efficiency of the solution, e.g. based on costs of acquisition, ownership, energy and/or other factors, while encouraging innovation and avoiding benchmark escalations that favor large inefficient configuration over small efficient configurations. Evaluation frameworks: Tool chains, suites and frameworks for evaluating big data systems. Early implementations: Of the Deep Analytics Pipeline or BigBench and lessons learned in benchmarking big data applications. Enhancements: Proposals to augment these benchmarks, e.g. by adding more data genres (e.g. graphs), or incorporating a range of machine learning and other algorithms, will be entertained and are encouraged.notele-TASKtele-task@hpi.deen℗; ©; tele-TASKSun, 07 Jun 2020 06:47:28 GMTPyRSS2Gen-1.1.0http://blogs.law.harvard.edu/tech/rssBenchmarking Elastic Query Processing on Big Datahttps://www.tele-task.de/lecture/video/4712/Dimitri Vorona00:27:09tele-TASK, HPI, computer science, technology, Germany, PotsdamDimitri VoronaDimitri Voronahttps://www.tele-task.de/lecture/video/4712/Wed, 06 Aug 2014 00:00:00 GMTPopulAid: In-Memory Data Generation for Customized Benchmarkshttps://www.tele-task.de/lecture/video/4711/Ralf Teusner00:18:06tele-TASK, HPI, computer science, technology, Germany, PotsdamRalf TeusnerRalf Teusnerhttps://www.tele-task.de/lecture/video/4711/Wed, 06 Aug 2014 00:00:00 GMTBuilding Efficient Data Intensive Environmentshttps://www.tele-task.de/lecture/video/4710/Eyal Gutkind00:08:48tele-TASK, HPI, computer science, technology, Germany, PotsdamEyal GutkindEyal Gutkindhttps://www.tele-task.de/lecture/video/4710/Wed, 06 Aug 2014 00:00:00 GMTMain Memory Is Less Expensive Than Diskhttps://www.tele-task.de/lecture/video/4709/Martin Boissier00:15:39tele-TASK, HPI, computer science, technology, Germany, PotsdamMartin BoissierMartin Boissierhttps://www.tele-task.de/lecture/video/4709/Wed, 06 Aug 2014 00:00:00 GMTFoodBroker - Generating Synthetic Datasets for Graph-Based Business Analyticshttps://www.tele-task.de/lecture/video/4708/André Petermann00:19:03tele-TASK, HPI, computer science, technology, Germany, PotsdamAndré PetermannAndré Petermannhttps://www.tele-task.de/lecture/video/4708/Wed, 06 Aug 2014 00:00:00 GMTBW-EML SAP Standard Application Benchmarkhttps://www.tele-task.de/lecture/video/4707/Heiko Gerwens00:22:36tele-TASK, HPI, computer science, technology, Germany, PotsdamHeiko GerwensHeiko Gerwenshttps://www.tele-task.de/lecture/video/4707/Wed, 06 Aug 2014 00:00:00 GMTA TU Delft Perspective on Benchmarking Big Data in the Data Centerhttps://www.tele-task.de/lecture/video/4706/Alexander Iosup00:39:57tele-TASK, HPI, computer science, technology, Germany, PotsdamAlexander IosupAlexander Iosuphttps://www.tele-task.de/lecture/video/4706/Wed, 06 Aug 2014 00:00:00 GMTWelcome & Introduction to WBDBhttps://www.tele-task.de/lecture/video/4696/Chaitan Baru, Dr. Matthias Uflacker00:13:02tele-TASK, HPI, computer science, technology, Germany, PotsdamChaitan Baru, Dr. Matthias UflackerChaitan Baru, Dr. Matthias Uflackerhttps://www.tele-task.de/lecture/video/4696/Tue, 05 Aug 2014 09:00:00 GMTBenchmarking Virtualized Hadoop Clustershttps://www.tele-task.de/lecture/video/4704/Todor Ivanov00:18:59tele-TASK, HPI, computer science, technology, Germany, PotsdamTodor IvanovTodor Ivanovhttps://www.tele-task.de/lecture/video/4704/Tue, 05 Aug 2014 00:00:00 GMTSQL on Hadoop Benchmarkhttps://www.tele-task.de/lecture/video/4703/Prof. Dr. Tilmann Rabl00:07:01tele-TASK, HPI, computer science, technology, Germany, PotsdamProf. Dr. Tilmann RablProf. Dr. Tilmann Rablhttps://www.tele-task.de/lecture/video/4703/Tue, 05 Aug 2014 00:00:00 GMTLDBC: Linked Data Benchmark Councilhttps://www.tele-task.de/lecture/video/4702/Andrey Gubichev00:28:07tele-TASK, HPI, computer science, technology, Germany, PotsdamAndrey GubichevAndrey Gubichevhttps://www.tele-task.de/lecture/video/4702/Tue, 05 Aug 2014 00:00:00 GMTExtending The OLTP-Bench Framework for Big Data Systemshttps://www.tele-task.de/lecture/video/4701/Djelell Eddine Difallah00:21:08tele-TASK, HPI, computer science, technology, Germany, PotsdamDjelell Eddine DifallahDjelell Eddine Difallahhttps://www.tele-task.de/lecture/video/4701/Tue, 05 Aug 2014 00:00:00 GMTBenchmarking SQL-on-Hadoop Systems: TPC or not TPC?https://www.tele-task.de/lecture/video/4700/Berni Schiefer00:22:04tele-TASK, HPI, computer science, technology, Germany, PotsdamBerni SchieferBerni Schieferhttps://www.tele-task.de/lecture/video/4700/Tue, 05 Aug 2014 00:00:00 GMTIn-Memory Processing in Healthcare and Life Scienceshttps://www.tele-task.de/lecture/video/4697/Dominik Bertram00:29:08tele-TASK, HPI, computer science, technology, Germany, PotsdamDominik BertramDominik Bertramhttps://www.tele-task.de/lecture/video/4697/Tue, 05 Aug 2014 00:00:00 GMTAn Approach to Benchmarking Industrial Big Data Applicationshttps://www.tele-task.de/lecture/video/4698/Umesh Dayal00:42:07tele-TASK, HPI, computer science, technology, Germany, PotsdamUmesh DayalUmesh Dayalhttps://www.tele-task.de/lecture/video/4698/Tue, 05 Aug 2014 00:00:00 GMTTowards A Complete BigBench Implementationhttps://www.tele-task.de/lecture/video/4705/Prof. Dr. Tilmann Rabl00:15:41tele-TASK, HPI, computer science, technology, Germany, PotsdamProf. Dr. Tilmann RablProf. Dr. Tilmann Rablhttps://www.tele-task.de/lecture/video/4705/Tue, 05 Aug 2014 00:00:00 GMT