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What is the advantage of using Apache Spark over Elasticsearch for analysing data?

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Apache Spark and Elasticsearch are two different technologies to solve different set of problem. Classical example would be you can not multiply 100 * 100 matrix in Elasticsearch but you can do in Spark. Spark allows to run the desired machine learning algorithms and perform analysis on it. Elasticsearch...
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Apache Spark and Elasticsearch are two different technologies to solve different set of problem. Classical example would be you can not multiply 100 * 100 matrix in Elasticsearch but you can do in Spark. Spark allows to run the desired machine learning algorithms and perform analysis on it. Elasticsearch offer wide range of search capabilities based on ranking with relevancy. There are connectivity between Spark and Elastisearch which helps to combine both the technology and utilise maximum out of both. read less
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Those are two entirely different technologies and serve different purposes and used for different use-cases. While Elasticsearch is a full-text search engine, Spark is a distributed in-memory computing framework for doing advanced analytics workloads such as interactive or ad-hoc queries, batch and streaming...
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Those are two entirely different technologies and serve different purposes and used for different use-cases. While Elasticsearch is a full-text search engine, Spark is a distributed in-memory computing framework for doing advanced analytics workloads such as interactive or ad-hoc queries, batch and streaming ETL, and machine and deep learning applications. To put it simply one is to distribute your compute operations to all the workers or nodes in the Spark clusters, the other is to do your text search on a large corpus of text stored as books or indexed as text files. This not to say that they cannot be used together for certain use-cases. For instance, you may be doing some semantic analysis using Spark’s MLlib library, and consult Elasticsearch for some ranking or relevancy or search frequency of certain words in the text. Both serve different purposes, yet can work together. Cheers Jules read less
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