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Part 2 - Spark over MapReduce #spark #databricks #programming #learning #python #jeenu

Mukesh Singh
and datasetsdataframesdiscuss the significance of partitioning in sparkexplain the difference between rddshow does spark handle fault tolerancehow does spark handle memory managementwhat is the role of spark sql in data processingwhat is the significance of caching in spark

Why Spark is often preferred over MapReduce?

Apache Spark is an open-source distributed computing system meant for large data processing and analytics.

1.Performance Spark's in-memory compute paradigm and efficient DAG (Directed Acyclic Graph) execution engine enable much faster processing rates than MapReduce, particularly for iterative algorithms and interactive analytics.

  1. Ease of Use Spark offers higher-level APIs and libraries (including DataFrame API, Spark SQL, MLlib, and GraphX) that abstract away most of the complexities of distributed data processing. This makes it easy for developers to create and manage big data apps.

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2024-03-20
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