Apache Spark Cheat Sheet

  



Apache Spark is an open source cluster computing framework that is frequently used in big data processing. How to process real-time data with Apache tools Open source is leading the way with a rich canvas of projects for processing real-time events. Data Science in Spark with Sparklyr:: CHEAT SHEET Intro Using sparklyr. 2016-12 sparklyr is an R interface for Apache Spark™, it provides a complete dplyr backend and the option to query directly using Spark SQL statement. With sparklyr, you can orchestrate.

Open source is leading the way with a rich canvas of projects for processing real-time events.
Case study with NASA logs to show how Spark can be leveraged for analyzing data at scale.

Apache Spark Config Cheat Sheet

Case study with NASA logs to show how Spark can be leveraged for analyzing data at scale.
As the Apache Software Foundation turns 20, let's celebrate by recognizing 20 influential and up-and-coming Apache projects.
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Apache Spark Cheat Sheet
Apache Spark is an open source cluster computing framework. In contrast to Hadoop’s two-stage disk-...
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Spark's new DataFrame API is inspired by data frames in R and Python (Pandas), but designed from...

Having a good cheatsheet at hand can significantly speed up the development process.One of the best cheatsheet I have came across is sparklyr’s cheatsheet.

SparkApache

For my work, I’m using Spark’s DataFrame API in Scala to create data transformation pipelines. These are some functions and design patterns that I’ve found to be extremely useful.

Load data

Apache Spark Cheat Sheet Printable

Get SparkContext information

Get Spark version

Get number of partitions

Microsoft

Count number of rows

Print schema

Preview top 20 rows

Design pattern for constructing as data transformation pipeline

Drop duplicate rows

Apache Spark Cheat Sheet Download

For an exhaustive list of the functions, you can check out the Spark’s Dataset class documentation.

Apache Spark Cheat Sheet Free

Hope you’ve found this cheatsheet useful. Thank you!