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Overview - Spark 4. 0. 0 Documentation - Apache Spark Apache Spark is a unified analytics engine for large-scale data processing It provides high-level APIs in Java, Scala, Python and R, and an optimized engine that supports general execution graphs
Examples - Apache Spark Apache Spark ™ examples This page shows you how to use different Apache Spark APIs with simple examples Spark is a great engine for small and large datasets It can be used with single-node localhost environments, or distributed clusters Spark’s expansive API, excellent performance, and flexibility make it a good option for many analyses
Documentation - Apache Spark These let you install Spark on your laptop and learn basic concepts, Spark SQL, Spark Streaming, GraphX and MLlib Hands-on exercises from Spark Summit 2013 These exercises let you launch a small EC2 cluster, load a dataset, and query it with Spark, Shark, Spark Streaming, and MLlib
Quick Start - Spark 4. 0. 0 Documentation - Apache Spark Spark’s shell provides a simple way to learn the API, as well as a powerful tool to analyze data interactively It is available in either Scala (which runs on the Java VM and is thus a good way to use existing Java libraries) or Python Start it by running the following in the Spark directory:
Spark SQL and DataFrames - Spark 4. 0. 0 Documentation - Apache Spark Spark SQL, DataFrames and Datasets Guide Spark SQL is a Spark module for structured data processing Unlike the basic Spark RDD API, the interfaces provided by Spark SQL provide Spark with more information about the structure of both the data and the computation being performed
Chapter 1: DataFrames - A view into your structured data Apache Spark DataFrames support a rich set of APIs (select columns, filter, join, aggregate, etc ) that allow you to solve common data analysis problems efficiently Compared to traditional relational databases, Spark DataFrames offer several key advantages for big data processing and analytics:
Spark SQL DataFrames - Apache Spark Seamlessly mix SQL queries with Spark programs Spark SQL lets you query structured data inside Spark programs, using either SQL or a familiar DataFrame API Usable in Java, Scala, Python and R
Data Sources - Spark 4. 0. 0 Documentation - Apache Spark Registering a DataFrame as a temporary view allows you to run SQL queries over its data This section describes the general methods for loading and saving data using the Spark Data Sources and then goes into specific options that are available for the built-in data sources
Overview - Spark 3. 5. 5 Documentation - Apache Spark Apache Spark is a unified analytics engine for large-scale data processing It provides high-level APIs in Java, Scala, Python and R, and an optimized engine that supports general execution graphs