Articles

Llamaverse

Loading the llamaverse

The Llamaverse is a comprehensive sample dataset featuring a collection of documents about llamas with human characteristics, designed to demonstrate MarkLogic capabilities through practical examples. This article explains how to access, deploy, and work with the Llamaverse, including its security model with roles and privileges, TDE templates, and content structure. The dataset is version-controlled and freely available on GitHub, making it an ideal resource for learning and testing MarkLogic features.

1 Day Challenge - Kendo UI and MarkLogic

This article documents a one-day challenge to integrate Kendo UI with MarkLogic following Progress Software's acquisition of MarkLogic. The experiment explores the potential of combining MarkLogic's backend capabilities with Progress's Kendo UI frontend framework. Through a video demonstration, it showcases what can be achieved in a single day of focused development using these complementary technologies.

MarkLogic 11Kendo UI

Marklogic 11

This comprehensive review of MarkLogic 11 is based on over 120 hours of detailed testing and analysis, covering new features, improvements, and bug fixes. The article provides insights into major updates including the new UI, GraphQL implementation, enhanced CTS and XDMP functions, Optic Update preview, and Geospatial capabilities. Through extensive testing and code review, it offers a balanced assessment of this significant release's practical implications for developers and organizations.

Data Pipelines with n8n and MarkLogic

Part 1 - Data Ingestion

This comprehensive guide demonstrates how to build automated data pipelines using n8n and MarkLogic for efficient data ingestion and management. The article walks through setting up n8n workflows to watch folders and automatically ingest JSON documents into MarkLogic, laying the groundwork for advanced AI applications. It serves as the first part in a series exploring how to leverage AI technologies including LLMs, vector search, and RAG for secure analysis of corporate data.

n8nMarkLogicingestion

Element Level Security

Working with TDE's

This article explores the complex interaction between Template Driven Extraction (TDE) and Element Level Security (ELS) in MarkLogic, highlighting important security considerations and potential pitfalls. Through practical examples, it demonstrates how different security levels affect data visibility in TDE views and document-level access. The article concludes with crucial insights about the unexpected behavior of TDE with ELS, essential knowledge for designing robust security models in MarkLogic applications.

TDE Document Fragment

Using the document fragment in your views

This article explores the use of document fragments in Template Driven Extraction (TDE) views within MarkLogic, focusing on optimizing view performance and runtime data access. It demonstrates how to use fragment IDs for document joins and XPath expressions to retrieve additional information not included in the view. The article concludes with best practices for using document fragments efficiently, particularly in scenarios involving large datasets.

TDEToolboxOptic API

Prototype TDE templates

Test SQL and Optic Against TDE Template Without Installing

This technical guide presents an innovative approach to prototyping Template Driven Extraction (TDE) templates in MarkLogic without requiring database installation and reindexing. The article demonstrates how to use tde:node-data-extract() with op:from-literals() and op:from-sparql(), explaining the importance of proper datatype handling and providing portable examples for testing against live data. This method significantly streamlines the TDE development process by enabling rapid prototyping and testing.

TDEToolboxOptic API

cts:document-permission-query()

Released in MarkLogic 11

This article examines the powerful new cts:document-permission-query() function introduced in MarkLogic 11, which revolutionizes how developers can query documents based on their permissions. Through practical examples comparing MarkLogic 10 and 11 approaches, it demonstrates significant improvements in code complexity, resource utilization, and performance when handling permission-based queries. The article includes comprehensive test scenarios with 360,000 documents to illustrate the feature's capabilities and benefits.

MarkLogic 11CTS Query

cts:document-root-query()

Released in MarkLogic 11

This technical analysis explores the new cts:document-root-query() feature in MarkLogic 11, comparing it with previous methods of querying root elements. Through detailed examples and test cases, it demonstrates how the feature works differently with XML and JSON documents, particularly highlighting its behavior with JSON's top-level properties. The article provides important insights for developers implementing root-level queries across different document types.

MarkLogic 11CTS Query

MarkLogic Community Event

This article recaps Clever Llamas' presentation at the July 2023 MarkLogic Community Event, highlighting their comprehensive service offerings and specialized training programs. The presentation focuses on their innovative approach to MarkLogic training, featuring focused modules designed for rapid skill development. Through a recorded session, it demonstrates how their training solutions address the challenges of building and maintaining MarkLogic expertise within organizations.

Word Searches and the Optic API

Exploring how they can be used together

This guide demonstrates how to incorporate word search relevance scoring into Optic API queries using op.fromSearch() with cts.wordQuery. Through examples with the Llamaverse dataset, it shows the difference between using word queries in where clauses (which don't provide scoring) versus using op.fromSearch() to get relevance-ranked results. The article explores how to combine structured data access via TDE views with full-text search capabilities, enabling powerful hybrid queries that can both filter data and rank results by relevance.

ToolboxOptic APICTS Query

Exploring op.fromView()

Accessing TDE and Relational Views in MarkLogic Optic API

This comprehensive guide explores op.fromView(), a fundamental function in MarkLogic's Optic API for accessing structured data through TDE and relational views. The article demonstrates various usage patterns including basic queries, explicit column references, and runtime view name modifications using qualifiers. Through practical examples using the Llamaverse dataset, it illustrates how to effectively query and manipulate document data in a relational manner.

ToolboxOptic API

Exploring op.select()

Selecting specific content from an Optic plan or set of plans

This article provides a detailed guide to using op.select() in MarkLogic's Optic API, demonstrating how to efficiently extract and manipulate specific columns from data plans. Through practical examples with the Llamaverse dataset, it shows how to handle multiple views, resolve naming conflicts, and normalize column names. The guide includes advanced techniques for managing column qualifiers and working with complex joins, making it essential for developers working with MarkLogic's Optic API.

ToolboxOptic API

GraphQL

Explicit schemas

This article explores the creation and implementation of explicit GraphQL schemas in MarkLogic 11, focusing on defining complex relationships between data entities. Through the Llamaverse example, it demonstrates how to use custom directives like @View and @Join to create sophisticated data relationships and enhance query capabilities. The article provides practical examples of configuring and querying explicit schemas, while highlighting both the current limitations and potential of GraphQL in MarkLogic.

MarkLogic 11GraphQL

GraphQL

Getting started

This introductory guide demonstrates how to use GraphQL with MarkLogic 11, explaining how the built-in implementation works with existing schemas and views. The article walks through setting up TDE templates, exploring implicit schemas, and using custom MarkLogic-specific directives for advanced querying capabilities. Through practical examples using the Llamaverse dataset, it showcases how to perform range queries, sorting, and pagination in GraphQL.

MarkLogic 11GraphQL

Optic Geospatial

Released in MarkLogic 11

This article explores the new geospatial capabilities in MarkLogic 11's Optic API, demonstrating how to effectively work with spatial data using TDE templates and the Llamaverse dataset. Through practical examples using both SQL and Optic API approaches, it shows how to query and analyze location-based data, track movement patterns, and perform spatial relationship analysis. The article concludes with important insights about implementation considerations, including TDE template limitations, performance optimization, and query design strategies.

MarkLogic 11Optic APIGeospatial

Optic Update

Released in MarkLogic 11

This article examines the preview release of Optic Update in MarkLogic 11, a JavaScript-only feature that extends the Optic API with document modification capabilities. Through detailed code analysis and practical examples, it explores key components including document descriptors, URI handling, locking mechanisms, and temporal support. The article demonstrates both simple and complex update scenarios, highlighting the feature's potential while noting current limitations and implementation considerations.

MarkLogic 11Optic API