# Knn\_vectors field understanding

**URL:** <https://discuss.elastic.co/t/knn-vectors-field-understanding/374923>\
**Category:** Elasticsearch\
**Tags:** vector-search\
**Created:** [February 24, 2025, 7:01am UTC](https://discuss.elastic.co/t/knn-vectors-field-understanding/374923 "2025-02-24T07:01:02Z")\
**Posts on this page:** 1\
**Showing post:** 4

<div class="post-metadata">

**Author:** ![yli](https://avatars.discourse-cdn.com/v4/letter/y/bbe5ce/32.png) [@yli](https://discuss.elastic.co/u/yli)\
**Post date:** [February 25, 2025, 8:53am UTC](https://discuss.elastic.co/t/knn-vectors-field-understanding/374923/4 "2025-02-25T08:53:10Z")

</div>

Based on my understanding of your comments, that the raw value of dense vector field will be stored in Lucene and again in `_source` if not excluded, so there is a duplication, and this resulted additional 40 GB storage on disk, right? How the configuration of 1 replica influences the storage additionally?

What about the quantized vectors, will they be duplicated as well in replica shards?

I attached partially the response from the disk usage api

```json
{
    "_shards": {
        "total": 2,
        "successful": 2,
        "failed": 0
    },
    "file_flat_1024": {
        "store_size": "216.5gb",
        "store_size_in_bytes": 232469055909,
        "all_fields": {
            "total": "216.4gb",
            "total_in_bytes": 232444165546,
            "inverted_index": {
                "total": "2.9gb",
                "total_in_bytes": 3147344422
            },
            "stored_fields": "163.7gb",
            "stored_fields_in_bytes": 175830555711,
            "doc_values": "97.1mb",
            "doc_values_in_bytes": 101829561,
            "points": "92.2mb",
            "points_in_bytes": 96760144,
            "norms": "9.8mb",
            "norms_in_bytes": 10375998,
            "term_vectors": "0b",
            "term_vectors_in_bytes": 0,
            "knn_vectors": "49.5gb",
            "knn_vectors_in_bytes": 53257299710
        },
        "fields": {
            "_source": {
                "total": "163.5gb",
                "total_in_bytes": 175628654805,
                "inverted_index": {
                    "total": "0b",
                    "total_in_bytes": 0
                },
                "stored_fields": "163.5gb",
                "stored_fields_in_bytes": 175628654805,
                "doc_values": "0b",
                "doc_values_in_bytes": 0,
                "points": "0b",
                "points_in_bytes": 0,
                "norms": "0b",
                "norms_in_bytes": 0,
                "term_vectors": "0b",
                "term_vectors_in_bytes": 0,
                "knn_vectors": "0b",
                "knn_vectors_in_bytes": 0
            },
            "file_section_embedding": {
                "total": "49.5gb",
                "total_in_bytes": 53257299710,
                "inverted_index": {
                    "total": "0b",
                    "total_in_bytes": 0
                },
                "stored_fields": "0b",
                "stored_fields_in_bytes": 0,
                "doc_values": "0b",
                "doc_values_in_bytes": 0,
                "points": "0b",
                "points_in_bytes": 0,
                "norms": "0b",
                "norms_in_bytes": 0,
                "term_vectors": "0b",
                "term_vectors_in_bytes": 0,
                "knn_vectors": "49.5gb",
                "knn_vectors_in_bytes": 53257299710
            }
        }
    }
}

```

Btw, from the response of disk usage API, it seems that it returns the disk usage based on the primary shards, right?

---

_[View the full topic](https://discuss.elastic.co/t/knn-vectors-field-understanding/374923)._
