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Accelerating Apache Spark with FPGAs
Concurrency and Computation: Practice and Experience, 2017SummaryApache Spark has become one of the most popular engines forbig dataprocessing. Spark provides a platform‐independent, high‐abstraction programming paradigm for large‐scale data processing by leveraging the Java framework. Though it provides software portability across various machines, Java also limits the performance of distributed environments,
Ehsan Ghasemi, Paul Chow
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2019
Doesn't it feel good when you are in the vicinity of your envisioned and cherished destination? When you see in retrospect that you've been through a long journey and the milestone that you once dreamed of is in your reach? You must have the same feeling as you start this chapter, because this last chapter of the book is all about how you can put the ...
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Doesn't it feel good when you are in the vicinity of your envisioned and cherished destination? When you see in retrospect that you've been through a long journey and the milestone that you once dreamed of is in your reach? You must have the same feeling as you start this chapter, because this last chapter of the book is all about how you can put the ...
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2016
Apache Spark is a data processing engine for large data sets. Apache Spark is much faster (up to 100 times faster in memory) than Apache Hadoop MapReduce. In cluster mode, Spark applications run as independent processes coordinated by the SparkContext object in the driver program, which is the main program. The SparkContext may connect to several types
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Apache Spark is a data processing engine for large data sets. Apache Spark is much faster (up to 100 times faster in memory) than Apache Hadoop MapReduce. In cluster mode, Spark applications run as independent processes coordinated by the SparkContext object in the driver program, which is the main program. The SparkContext may connect to several types
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Fraud Detection Using Apache Spark
2019 5th International Conference on Optimization and Applications (ICOA), 2019Fraud detection methods are continuously developed to defend criminals. They allow us to identify quickly and easily the frauds. In this work, we will focus on the problem of fraud detection in banking transactions. A single algorithm may not be suitable for every problem.
Abdelkbir ARMEL, Dounia ZAIDOUNI
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Introduction to Apache Spark and Spark Core
2018In the previous chapters, the fundamental concepts of Scala programming, pure function, pattern matching, singleton objects, Scala collections, and functional programming features of Scala have been covered.
Subhashini Chellappan +1 more
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2018
There is no better time to learn Spark than now. Spark has become one of the critical components in the big data stack because of its ease of use, speed, and flexibility. This scalable data processing system is being widely adopted across many industries by many small and big companies, including Facebook, Microsoft, Netflix, and LinkedIn. This chapter
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There is no better time to learn Spark than now. Spark has become one of the critical components in the big data stack because of its ease of use, speed, and flexibility. This scalable data processing system is being widely adopted across many industries by many small and big companies, including Facebook, Microsoft, Netflix, and LinkedIn. This chapter
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2018
This chapter provides details about the different ways of working with Spark, including using the Spark shell, submitting a Spark application from the command line, and using a hosted cloud platform called Databricks. The last part of this chapter is geared toward software engineers who want to set up the Apache Spark source code on a local machine to ...
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This chapter provides details about the different ways of working with Spark, including using the Spark shell, submitting a Spark application from the command line, and using a hosted cloud platform called Databricks. The last part of this chapter is geared toward software engineers who want to set up the Apache Spark source code on a local machine to ...
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Join Algorithms under Apache Spark
Proceedings of the 2019 5th International Conference on Computer and Technology Applications, 2019Currently, we are dealing with large scale applications, which in turn generate massive amount of data and information. Large amount of data often requires processing algorithms using massive parallelism, where the main performance metrics is the communication cost. Apache Spark is highly scalable, fault-tolerance, and can be used across many computers.
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