How to Rewrite SQL Like Query into Elasticsearch?

Discover how to convert SQL LIKE queries into Elasticsearch queries efficiently with our detailed guide.
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How to Rewrite SQL Like Query into Elasticsearch?

When transitioning from a traditional SQL database to a powerful search engine like Elasticsearch, one common challenge developers face is rewriting queries. One particular case of interest is the SQL 'LIKE' query, which can be relatively straightforward but might leave many puzzled when trying to replicate the same functionality in Elasticsearch's syntax. In this guide, we'll walk through the steps involved in converting a SQL 'LIKE' query to an Elasticsearch query.

Understanding the SQL Query

Let's start with the original SQL query that we want to convert:

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

Breakdown of the Query

SELECT * FROM products: This part specifies that we want to retrieve all columns from the products table.

WHERE (name LIKE 'captain%' OR name LIKE '%captain%' OR manufacturer LIKE '%captain%'): This clause applies filters based on the name and manufacturer columns. It fetches records where:

The name starts with 'captain' ('captain%').

The name includes 'captain' anywhere in the string ('%captain%').

The manufacturer also includes 'captain'.

Converting to Elasticsearch Query

Basics of Elasticsearch Query Structure

In Elasticsearch:

The OR condition in SQL translates to should in Elasticsearch’s query DSL.

Similarly, AND translates to must, but it is not relevant in this case since we are focusing on OR conditions.

The Equivalent Elasticsearch Query

Using the information from the SQL example, the Elasticsearch query can be constructed as follows:

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

Explanation of the Elasticsearch Query

Structure Breakdown

"query": This is the key starting point for any Elasticsearch search.

"bool": This acts as a container for combining multiple conditions together.

"should": Specifies that at least one of the conditions inside the array needs to match.

"wildcard": This indicates that we are doing a wildcard search, similar to the LIKE in SQL.

The value *captain* allows for matches that contain 'captain' anywhere in the name or manufacturer fields.

Conclusion

Converting SQL queries to Elasticsearch queries might seem daunting at first, but by understanding the fundamental differences in syntax and structure, it becomes manageable. Remember that Elasticsearch uses a different approach to filtering data and allows for advanced querying capabilities with flexible structures.

By employing wildcard and bool queries, we can effectively replicate the LIKE functionality of SQL, unlocking the full potential of your Elasticsearch implementation. Embrace these changes, and you’ll be better equipped to integrate your data into a powerful search-driven ecosystem!