Apache Spark
A Study on New Challenges of Big Data and Apache Spark
... frameworks. Apache Spark runs on Hadoop, Mesos, standalone, or inside the ...run Spark the use of its standalone cluster mode, on EC2, on Hadoop YARN, or on Apache ...
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Apache Spark usage and deployment models for scientific computing
... and Spark service provided by CERN IT is used by the IT Monitoring service which is critical for CC operations and WLCG, IT Security for intrusion detection, LHC experiments (CMS, ATLAS) for the analytics on ...
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Using Apache Spark on genome assembly for scalable overlap-graph reduction
... Apache Spark is a cluster-based engine that processes very large-scale ...computation, Apache Spark provides GraphX library that contributes a set of fundamental operations and graph ...
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Leveraging resource management for efficient performance of Apache Spark
... [4], Apache Spark quickly becomes the most popular com- plement of Apache Hadoop ...and Apache Spark. In their study, they show that Spark is very con- suming memory, and ...
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Analytics For Healthcare Using Hadoop Mapreduce, Apache Spark And In Cloud Services
... use Spark easily. Apache Spark is the fast general purpose big data analytics engine and it is very suitable for any kindof big data ...of Apache spark are Low Tolerance to Latency ...
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Time series analysis with apache spark and its applications to energy informatics
... There is no time series package for Apache Spark and R (R Core Team, 2018) on the market. So, another method to perform forecasts with R on a Spark-Cluster is needed. With the API SparkR the function ...
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Partitional Based Clustering Algorithms on Big Data Using Apache Spark
... Apache Spark, a framework similar to the Von Neumann architecture. It has an efficient implementation of in- memory computations and iterative optimization is processed to analyze large volume of data. Data ...
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StreamAligner: a streaming based sequence aligner on Apache Spark
... on Spark stream- ing ...in Spark memory and can be used for an unlimited times without reload- ...alignment, Apache Spark, Hadoop, Distributed computing ...
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Optimizing machine learning on Apache Spark in HPC environments
... of Apache Spark, a distributed data-flow framework, to support the use of machine learning in HPC environments for the purposes of machine ...using Spark in this context; memory management, ...
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Incremental-Parallel Data Stream Classification in Apache Spark Environment
... on apache spark, to address the problems on the real-time streaming data communication cost and workload imbalance problem of large scale data in a parallel and distributed ...
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GeoMatch:Efficient Large Scale Map Matching on Apache Spark
... Abstract—We contribute by developing GeoMatch as a novel, scalable, and efficient big-data pipeline for large-scale map matching on Apache Spark. GeoMatch improves ex- isting spatial big data solutions by ...
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Efficient iterative virtual screening with Apache Spark and conformal prediction
... Due to the recent availability of large molecule datasets (e.g., ZINC [7]) and their structure being highly paral- lelizable, parallel approaches have been used for virtual screening. In our previous studies [8, 9], we ...
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Study of Machine Learning Techniques using Apache Spark
... as Apache Spark MLlib have been ...of Apache Spark.One of the major libraries of Apache Spark, Spark MLlib is the most prominent platform available for big data analysis to carry ...
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Choice of Cluster Computing System Hadoop and Apache Spark for Network Systems
... internal Spark functions written in Scala running on a JVM, translation between two different environments and the selected languages can be the source of more errors, problems, and reduced ...of Apache ...
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A comparison on scalability for batch big data processing on Apache Spark and Apache Flink
... Data, Apache Spark and Apache ...platforms. Apache Spark have shown to be the frame- work with better scalability and overall faster ...and Spark ML are minimal, MLlib performs ...
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Assessing Apache Spark Streaming with Scientific Data
... using Spark instead. Apache Spark Streaming lets the program store results in an intermediate data-form within the memory, and when new data arrives as another discrete set, it is batched to perform ...
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Evolutionary Optimization Using Big Data from Engineering Simulations and Apache Spark
... within Apache Spark. The reduced order model from Spark is then utilized by anevolutionary algorithm in the optimization of an industrial system ...utilizing Spark as the common ...
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Apache Spark based Big Data Analytics for Social Network Cybercrime Forensics
... The study relied on distributed contributing framework Apache Spark and made use of Spark streaming API to stream Twitter data and Spark ML API for tweet analysis and classification. the study ...
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A Technological Survey On Apache Spark And Hadoop Technologies.
... as Spark which is developed by Matei Zaharia in AMPLab of UC Berkeley in ...2009. Spark was donated to apache software foundation which was open sourced in 2010 with BSD Licensed and this ...
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Liver Disorderprognosis With Apache Spark Random Forest And Gradient Booster Algorithms Thari Krishna, Dr C Rajabhushanam Abstract PDF IJIRMET1604020013
... the spark random forests algorithm with spark gradient booster tree ...data, apache spark concepts in section ...learning, spark machine learning code work flow, random forests ...
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