Scalding

What it is

Scalding is a Scala library that simplifies the process of writing and running Hadoop MapReduce jobs. It provides a high-level, functional programming interface for data processing tasks.

Scalding stands out by offering a high-level Scala API for Hadoop MapReduce, making it easier to write complex data pipelines compared to using Java or other lower-level languages directly.

When it fits — and when it doesn’t

Known weaknesses

Each one links to the public issue, changelog or docs page it came from, where we have one.

1. 01

   Steep learning curve for developers unfamiliar with Scala and functional programming

   Scalding leverages advanced Scala features which can be challenging to master, especially for those coming from imperative programming backgrounds.

2. 02

   Limited language support restricts usage to Scala environments

   As Scalding is built on top of Scala and Cascading, it does not natively support other languages like Java or Python, limiting its accessibility and integration with polyglot teams.

3. 03

   Performance overhead due to the abstraction layer over Hadoop MapReduce

   While Scalding simplifies development, the additional layers of abstraction can introduce performance penalties compared to directly writing MapReduce jobs in Java or other lower-level languages.

4. 04

   Community and ecosystem are smaller compared to more mainstream data processing frameworks like Apache Spark

   The community around Scalding is not as large, which can result in fewer resources for troubleshooting, less third-party tool integration, and slower response times for bug fixes.

What it does well

• High-level, functional programming interface for Hadoop MapReduce jobs.

• Simplified data processing tasks with Scala's expressive syntax.

• Integration with Cascading for advanced data flow operations.

Pricing

Free tier

YesOpen source — free to use

Paid from

$0

Model

Flat rate

Enterprise plan

No

Pricing not independently confirmed — check the vendor’s page.