نتایج جستجو برای: apache spark

تعداد نتایج: 18089  

Journal: :Softw., Pract. Exper. 2018
Daniel Lemire Owen Kaser Nathan Kurz Luca Deri Chris O'Hara François Saint-Jacques Gregory Ssi Yan Kai

Compressed bitmap indexes are used in systems such as Git or Oracle to accelerate queries. They represent sets and often support operations such as unions, intersections, differences, and symmetric differences. Several important systems such as Elasticsearch, Apache Spark, Netflix’s Atlas, LinkedIn’s Pivot, Metamarkets’ Druid, Pilosa, Apache Hive, Apache Tez, Microsoft Visual Studio Team Servic...

Journal: :Indian Journal of Science and Technology 2016

Journal: :Epj Web of Conferences 2021

Apache Spark[1] is one of the predominant frameworks in big data space, providing a fully-functional query processing engine, vendor support for hardware accelerators, and performant integrations with scientific computing libraries. One difficulty adopting conventional to HEP workflows lack ROOT file format these frameworks. Laurelin[6] implements I/O pure Java library, no bindings C++ ROOT[2] ...

2017

The components forming the information society nowadays are seen in all areas of our lives. As computers have a great deal of importance in our lives, the amount of information has begun to gather meaningful and specific qualities. Not only the amount of information is increased, but also the speed of access to information has increased. Large data is the transformed form of all data recovered ...

2014
Jamie O’Brien

New potential risk factors for cardioembolic strokes are being considered in the medical community. The presence of these factors can be determined by reading an electrocradiogram (ECG). Manual ECG analysis can take hours. We propose combining accurate Hidden Markov Model (HMM) techniques with Apache Spark to improve the speed of ECG analysis. The potential exists for developing a fast classife...

Journal: :PVLDB 2016
Matthias Boehm Michael Dusenberry Deron Eriksson Alexandre V. Evfimievski Faraz Makari Manshadi Niketan Pansare Berthold Reinwald Frederick Reiss Prithviraj Sen Arvind Surve Shirish Tatikonda

The rising need for custom machine learning (ML) algorithms and the growing data sizes that require the exploitation of distributed, data-parallel frameworks such as MapReduce or Spark, pose significant productivity challenges to data scientists. Apache SystemML addresses these challenges through declarative ML by (1) increasing the productivity of data scientists as they are able to express cu...

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