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Topics

Spark Installation

In order to run the Apache Spark examples mentioned in this tutorial, you need to have Spark and its needed tools to be installed on your computer. Since most developers use Windows…
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Spark GraphX and GraphFrames

Spark GraphFrames are introduced in Spark 3.0 version to support Graphs on DataFrames. Prior to 3.0, Spark had GraphX library which ideally runs on RDD, and lost all Data Frame capabilities. GraphFrames…
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Spark Streaming

Spark Streaming is a scalable, high-throughput, fault-tolerant streaming processing system that supports both batch and streaming workloads. It is used to process real-time data from sources like file system folders, TCP sockets, S3, Kafka, Flume, Twitter…
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Spark Data Source

Spark SQL supports operating on a variety of data sources through the DataFrame interface. This section of the tutorial describes reading and writing data using the Spark Data Sources with Scala examples…
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SQL Spark

Spark SQL is one of the most used Spark modules which is used for processing structured columnar data format. Once you have a DataFrame created, you can interact with the data by using…
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DataFrame Spark

DataFrame is a distributed collection of data organized into named columns. It is conceptually equivalent to a table in a relational database or a data frame in R/Python, but with richer optimizations…
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RDD Spark

RDD (Resilient Distributed Dataset) is a fundamental data structure of Spark and it is the primary data abstraction in Apache Spark and the Spark Core. RDDs are fault-tolerant, immutable distributed collections of…
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Apache Spark Architecture

Spark works in a master-slave architecture where the master is called the “Driver” and slaves are called “Workers”. When you run a Spark application, Spark Driver creates a context that is an…
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Features & Advantages of Apache Spark

In-memory computation Distributed processing using parallelize Can be used with many cluster managers (Spark, Yarn, Mesos e.t.c) Fault-tolerant Immutable Lazy evaluation Cache & persistence Inbuild-optimization when using DataFrames Supports ANSI SQL Spark…
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