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Everything From Data Tips and NoSQL Best Practices to Industry Specific Insights

In this post, we dive into building a full five-card draw poker game with a configurable number of players. Written in XQuery 1.0, along with MarkLogic extensions to the language, this game provides examples of some great programming capabilities, including usage of maps, recursions, random numbers, and side effects. Hopefully, we will show those new to XQuery a look at the language that they may not get to see in other tutorials or examples.
Learn about lazy evaluation -- what it is and when it is appropriate to use. Study it in action with XQuery code that processes and groups search results in a fast and efficient way.
MarkLogic's triple store allows us to use custom inferencing rules, consumer profiles and dynamic behavior to build a simple, foundational, semantic recommendation engine.
Paxton Hare presents a simple checklist to follow for optimizing XQuery performance
How to use triples to store metadata about differences between documents.
How to walk a JSON tree from XQuery, in other words, how to recursively transform JSON.
When documents have a range of values, facets need a different type of bucket. Here we discuss an approach using custom constraints.
This article contains a comprehensive discussion on maps and operators, provides an in-depth discussion on how exactly maps work, as well as delves deeper into the powerful features they provide.
Generally, optimizations in the evaluator try to be lazy whenever they can when evaluating functions. This allows the application to process data only when needed and limits memory use to only what is needed. But sometimes, you need to evaluate eagerly to improve performance. Here we discuss one use case when it is best to specify eager evaluation.
This post covers a technique that’s an oldie but a goodie, with some thoughts on how it applies with MarkLogic features. We will cover some available implementations and the raw technique itself, and when to use each of them.
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