README.md

doric

Type-safe columns for spark DataFrames!

Spark	Maven Central	Codecov
2.4.x
3.0.x
3.1.x
3.2.x
3.3.x

---

Doric offers type-safety in DataFrame column expressions at a minimum cost, without compromising performance. In particular, doric allows you to:

• Get rid of malformed column expressions at compile time
• Avoid implicit type castings
• Run DataFrames only when it is safe to do so
• Get all errors at once
• Modularize your business logic

You'll get all these goodies:

• Without resorting to Datasets and sacrificing performance, i.e. sticking to DataFrames
• With minimal learning curve: almost no change in your code with respect to conventional column expressions
• Without fully committing to a strong static typing discipline throughout all your code

User guide

Please, check out this notebook for examples of use and rationale (also available through the binder link).

You can also check our documentation page

Installation

Fetch the JAR from Maven:

Sbt

libraryDependencies += "org.hablapps" %% "doric_3-2" % "0.0.5"

Maven

<dependency>
    <groupId>org.hablapps</groupId>
    <artifactId>doric_3-2_2.12</artifactId>
    <version>0.0.5</version>
</dependency>

Doric depends on Spark internals, and it's been tested against the following spark versions.

Spark	Scala	Tested	doric
2.4.1	2.11	✅	-
2.4.2	2.11	✅	-
2.4.3	2.11	✅	-
2.4.4	2.11	✅	-
2.4.5	2.11	✅	-
2.4.6	2.11	✅	-
2.4.7	2.11	✅	-
2.4.8	2.11	✅
3.0.0	2.12	✅	-
3.0.1	2.12	✅	-
3.0.2	2.12	✅
3.1.0	2.12	✅	-
3.1.1	2.12	✅	-
3.1.2	2.12	✅	-
3.1.3	2.12	✅
3.2.0	2.12	✅	-
3.2.1	2.12	✅	-
3.2.2	2.12	✅
3.3.0	2.12	✅

Contributing

Doric is intended to offer a type-safe version of the whole Spark Column API. Please, check the list of open issues and help us to achieve that goal!

Please read the contribution guide 📋