Recipes to Help You Model Your Data in MarkLogic
The third installment of a three-part series from O’Reilly Media, this cookbook gives you recipes for Transforming Data in MarkLogic.
Recipes are a useful way to distill simple solutions to common problems — copy and paste these recipes into MarkLogic’s Query Console or your source code, and you’ve solved the problem!
In this Cookbook, you’ll explore the multiple ways MarkLogic represents data. Everything is presented as a document, but MarkLogic also supports SPARQL queries and updates on RDF triples, and SQL queries on rows extracted from document data. With this arrangement, data modeling in MarkLogic is not an up-front activity, but rather an iterative one. Download this cookbook now and learn more about:
- Input Transformations: modify the structure of your data as it’s loaded into the database so that it focuses on a particular field
- Tokenization: understand MarkLogic’s default set of rules for tokenizing content, such as breaking a text stream into words, punctuation, and symbols
- Template-Driven Extraction: put values directly into the row or triple index, without having to modify the actual document structure
- Redaction: transform data as it’s pulled out of MarkLogic to help QA and development teams work with data divested of private information