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Chapter 3: Document Ingestion and Indexing Pipelines

Learn how data flows into a search engine and is prepared for efficient retrieval.

Chapter Overview​

Before documents can be searched, they must be processed, transformed, and stored in structures optimized for retrieval. This chapter covers the complete ingestion pipeline, from raw data extraction through tokenization, normalization, and final indexing.

Understanding this pipeline is crucial for diagnosing indexing issues, optimizing throughput, and ensuring data quality in your search system.

3.1 Data Extraction and ETL​

3.1.1 Parsing

3.1.2 Tokenization

3.1.3 Normalization

3.2 Data Types and Mapping​

3.2.1 Field types

3.2.2 Analyzers

3.2.3 Schemaless vs. schema-first design

3.3 Indexing Models​

3.3.1 Synchronization

3.3.2 Parallelization

3.3.3 Async pipelines

Examples​

Examples coming soon.

Code examples for this chapter will demonstrate building ingestion pipelines, configuring analyzers, and implementing both synchronous and asynchronous indexing patterns with Lucenia.