Category: ES|QL

Articles tagged ES|QL

Filters

One query, three data sources: ES|QL subqueries get FROM, TS and ROW

Filter application logs by live metric behavior and combine indexed data with inline test values. Your filter lists pull from time-series data on the fly, so nothing is hard-coded.

Fang Xing

One ES|QL query instead of two: WHERE IN subquery replaces the copy-paste loop in Elasticsearch

ES|QL's WHERE clause can filter by another Elasticsearch subquery's results instead of a static ID list you copied by hand, with nested subqueries, NOT IN and compound conditions built in.

Fang Xing

From search to checkout in 20 lines of code: building a 4-stage conversion funnel with OpenTelemetry

Add cart and purchase tracking to your search analytics pipeline and use ES|QL to answer the question every product manager asks: which search queries drive the most revenue?

Matthew Adams

Elasticsearch ES|QL brings full-text search to data you never indexed

MATCH and TO_TEXT bring full-text search to data you never indexed. Search computed columns, unmapped fields and federated sources in ES|QL.

Kevin Corcoran

Prompt to dashboard in under a minute, 5x cheaper: AI dashboards and custom Vega-Lite charts in Kibana

Describe your metrics in natural language and Kibana's AI chat generates ES|QL-backed dashboards and Vega-Lite charts, from scatter plots to conditional formatting and custom tooltips.

Marta Bondyra

Close enough is fast enough: How ES|QL Fast mode makes Kibana dashboards up to 100x faster

Fast mode samples a fraction of the data instead of scanning all of it. This release also brings click-to-filter for ES|QL charts, query-powered controls, and cleaner metric and bar chart layouts.

Teresa Alvarez Soler

15 lines of click tracking code that tell you what search logs can't

Three ES|QL queries calculate click-through rate, mean reciprocal rank and click position distribution from your search click data, so you can pinpoint which queries need relevance tuning and where ranking improvements will have the most impact.

Matthew Adams

How Elasticsearch detects multiple change points in time series with 0.99 recall

ES|QL's CHANGE_POINT command finds structural shifts, variance changes and spikes in any metric in ~1ms, without tuning anything per series.

Thomas Veasey

How to instrument your search API with OpenTelemetry and query it with ES|QL

Add custom attributes to OpenTelemetry spans and run six ES|QL queries that reveal your top searches, zero-result rate and slowest queries.

Matthew Adams

How to build search analytics on Elastic using OpenTelemetry, no extra pipeline required

How to instrument your search application to use modern Open Telemetry standard to drive insights in to your search and users.

Matthew Adams

Follow the money: tracing laundering networks with ES|QL and cross-cluster search

The data model, cross-cluster architecture and five ES|QL queries that power mule detection and laundering network tracing, built from infrastructure most financial institutions already run.

Jon Williams

One command. Natural language. Your Elasticsearch data, straight to the terminal.

Query your Elasticsearch data from the terminal in plain English. The official Elastic GitHub Copilot CLI plugin generates and runs ES|QL queries against your cluster. No Kibana, no manual syntax.

Greg Crist

Ready to build state of the art search experiences?

Sufficiently advanced search isn’t achieved with the efforts of one. Elasticsearch is powered by data scientists, ML ops, engineers, and many more who are just as passionate about search as you are. Let’s connect and work together to build the magical search experience that will get you the results you want.

Try it yourself