---
title: "Query Profiling: See Where a Slow Query Spends Its Time"
url: https://daily.dev/posts/query-profiling-see-where-a-slow-query-spends-its-time-eosyw6lmm
source_url: https://weaviate.io/blog/query-profiling
type: article
source: "Weaviate"
published: 2026-07-21T10:10:16.117Z
updated: 2026-07-21T10:10:41.758Z
tags: ["vector-search", "weaviate"]
reading_time: 9
upvotes: 0
comments: 0
language: en
---

> ## Documentation Index
> Fetch the complete documentation index at: https://daily.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# Query Profiling: See Where a Slow Query Spends Its Time

**[Weaviate](https://daily.dev/sources/weaviate)** · 9 min read · 0 upvotes · 0 comments

## Summary

Weaviate's query profiling feature provides per-stage, per-shard timing breakdowns for slow queries without requiring environment variable changes or node restarts. Unlike the existing slow query log, profiling is an opt-in per-query flag that returns timing data inline on the response, aggregated across all shards in the cluster. The post explains how to enable it in Python, JS/TS, Java, and C# clients, and walks through reading key metrics: objects_took (disk-bound hydration), filters_build_allow_list_took (filter cardinality cost), vector_search_took with per-HNSW-layer breakdowns, knn_search_rescore_took (compression rescore disk latency), and BM25-specific kwd_* timers. Three worked examples illustrate diagnosing hydration-dominated queries, overly broad filters, and compressed index rescore bottlenecks. Available since v1.36.9, GA in v1.38.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://weaviate.io/blog/query-profiling>

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---

Tags: [#vector-search](https://daily.dev/tags/vector-search), [#weaviate](https://daily.dev/tags/weaviate)

[View this post on daily.dev](https://daily.dev/posts/query-profiling-see-where-a-slow-query-spends-its-time-eosyw6lmm)