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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
openaire +1 more source
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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MapReduce accelerated attribute reduction based on neighborhood entropy with Apache Spark
Expert Systems With Applications, 2023Chuan Luo, Trli30, Sizhao Wang
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A fast parallel attribute reduction algorithm using Apache Spark
Knowledge-Based Systems, 2021linzi yin
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