Enhance Milvus Queries Converting Multiple Not Equal (!=) To NOT IN Expressions

Introduction

In the realm of vector databases, efficient query construction is paramount for optimal performance. Milvus, as a leading vector database, provides a rich set of query expressions to facilitate data retrieval. This article delves into a specific enhancement proposal aimed at streamlining query construction within Milvus, focusing on converting multiple "not equal" (!=) conditions into a single "not in" expression. This optimization not only simplifies the query syntax but also holds the potential to improve query execution efficiency. Guys, let's dive into this topic and see how this enhancement can make our lives easier when working with Milvus!

The current approach of using multiple "not equal" conditions, especially when dealing with a large set of values, can lead to verbose and potentially less efficient queries. Imagine you need to filter data where a certain field is not equal to a list of values. The naive approach would involve chaining multiple a != value1 && a != value2 && ... conditions. This not only makes the query harder to read and maintain but also might impact the query execution performance. The proposed solution suggests a more elegant and efficient way to express such conditions using the NOT IN operator. By converting multiple != conditions into a single NOT IN expression, we can significantly simplify the query and potentially improve its performance. This enhancement aligns with the broader goal of making Milvus more user-friendly and performant, allowing users to focus on their data analysis tasks rather than wrestling with complex query syntax. So, stay tuned as we explore the benefits, implementation details, and potential impact of this exciting enhancement to Milvus.

The Problem: Verbose and Potentially Inefficient Queries

Currently, Milvus users who need to filter data based on multiple "not equal" conditions often resort to chaining these conditions together using the && (AND) operator. This approach, while functional, suffers from several drawbacks. First and foremost, it leads to verbose queries that are difficult to read and understand. Imagine a scenario where you need to exclude a field from, say, ten different values. The resulting query would be a long chain of a != value1 && a != value2 && ... a != value10, making it a nightmare to debug and maintain. Secondly, this approach can be less efficient than using a single NOT IN expression. The database engine might need to evaluate each != condition separately, potentially leading to increased processing time and resource consumption. Thirdly, this syntax is simply not as intuitive or expressive as the NOT IN operator. The NOT IN operator clearly conveys the intent of excluding a set of values, whereas the chained != conditions require a bit more mental parsing to understand.

To illustrate the problem, consider a real-world example where you are filtering customer data based on their location. Suppose you want to exclude customers from three specific cities: New York, Los Angeles, and Chicago. Using the current approach, you would write a query like `city !=