Scalding is a Scala library that makes it easy to specify Hadoop MapReduce jobs. Scalding is built on top of Cascading, a Java library that abstracts away low-level Hadoop details. Scalding is comparable to Pig, but offers tight integration with Scala, bringing advantages of Scala to your MapReduce jobs.

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Word Count

Hadoop is a distributed system for counting words. Here is how it’s done in Scalding.

package com.twitter.scalding.examples

import com.twitter.scalding._
import com.twitter.scalding.source.TypedText

class WordCountJob(args: Args) extends Job(args) {
  TypedPipe.from(TextLine(args("input")))
    .flatMap { line => tokenize(line) }
    .groupBy { word => word } // use each word for a key
    .size // in each group, get the size
    .write(TypedText.tsv[(String, Long)](args("output")))

  // Split a piece of text into individual words.
  def tokenize(text: String): Array[String] = {
    // Lowercase each word and remove punctuation.
    text.toLowerCase.replaceAll("[^a-zA-Z0-9\\s]", "").split("\\s+")
  }
}

Notice that the tokenize function, which is standard Scala, integrates naturally with the rest of the MapReduce job. This is a very powerful feature of Scalding. (Compare it to the use of UDFs in Pig.)

You can find more example code under examples/. If you’re interested in comparing Scalding to other languages, see our Rosetta Code page, which has several MapReduce tasks in Scalding and other frameworks (e.g., Pig and Hadoop Streaming).

Documentation and Getting Started

The latest API docs are hosted at Scalding’s ScalaDoc index.

Please feel free to use the beautiful Scalding logo artwork anywhere.

Get Involved + Code of Conduct

Pull requests and bug reports are always welcome!

Discussion occurs primarily on the Gitter channel: Chat Issues should be reported on the GitHub issue tracker. Follow @Scalding on Twitter for updates.

We use a lightweight form of project governance inspired by the one used by Apache projects.

Please see Contributing and Committership for our code of conduct and our pull request review process.

The TL;DR is send us a pull request, iterate on the feedback + discussion, and get a +1 from a Committer in order to get your PR accepted.

The current list of active committers (who can +1 a pull request) can be found here: Committers

A list of contributors to the project can be found here: Contributors

License

Copyright 2016 Twitter, Inc.

Licensed under the Apache License, Version 2.0.