Скачать или смотреть How to Effectively Query ElasticSearch with Nested Fields and Existence Conditions

Discover how to construct a powerful query in `ElasticSearch` to handle nested fields and filter documents based on their existence. Get solutions to common pitfalls when querying.
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This video is based on the question https://stackoverflow.com/q/63041859/ asked by the user 'Will Jenkins' ( https://stackoverflow.com/u/93812/ ) and on the answer https://stackoverflow.com/a/63042116/ provided by the user 'Kamal Kunjapur' ( https://stackoverflow.com/u/3838328/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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Mastering ElasticSearch: Querying Nested Fields with Must-Not Conditions

ElasticSearch is a powerful search tool that allows for flexible querying of complex data structures. However, users often encounter challenges, especially when working with nested fields and conditions that check for the existence of data. In this post, we will address a common problem: how to construct a query that returns documents with a nested categories field that either have a score above a certain threshold in a specified category or do not include the categories field at all.

Understanding the Problem

You have defined a mapping for a categories field as a nested type, which means that it can contain multiple objects, each having their own properties. Your goal is to query documents based on two criteria:

Documents that have a score higher than a certain threshold (e.g., 0.5) in a specific category.

Documents that do not have the categories field.

However, your initial attempt at querying did not yield the expected results for documents with scores below the threshold. Let's dive into why that happened and how you can adjust your approach.

Why the Initial Query Failed

The confusion arises from how ElasticSearch treats fields within nested objects. In ElasticSearch, while categories is defined as a nested field, only the inner properties—such as categories.category and categories.score—are indexed for querying. If no document exists with the categories field, the query struggles to yield the correct results. Here's what to consider:

Non-existence of Parent Field: When querying, ElasticSearch first checks for the existence of the categories nested field. If it finds no matching documents based on that, it may affect the score evaluations of those documents.

Boolean Logic in Queries: The way Boolean conditions like must and must_not are structured significantly influences query outcomes.

Let’s refine the query to achieve the desired results.

Crafting the Solution: Modified Query

To ensure you can correctly retrieve the desired documents, you can modify your query by specifying that the nested fields be evaluated individually.

Here’s how the modified query should look:

[[See Video to Reveal this Text or Code Snippet]]

Key Changes Explained

Nested Query Structure: Using a nested query specifically checks the path to the categories, ensuring ElasticSearch evaluates scores within those nested documents.

Must Not Clause Modification: The must_not clause now focuses on ensuring that documents without categories.category and categories.score will also be included in your results. This prevents any documents that do have these fields from impacting returned results improperly.

Summary

By restructuring your query and understanding the nuance of nested fields, you can successfully retrieve documents from your ElasticSearch index that meet your specified conditions. This approach not only helps in getting valid results but also enhances the performance of your queries.

Armed with this knowledge, you should be able to handle similar queries in your ElasticSearch environment confidently!