Add more dense_vector details for cluster stats field stats #113607
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,5 @@ | ||
| pr: 113607 | ||
| summary: Add more `dense_vector` details for cluster stats field stats | ||
| area: Search | ||
| type: enhancement | ||
| issues: [] |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
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@@ -86,9 +86,30 @@ public static MappingStats of(Metadata metadata, Runnable ensureNotCancelled) { | |
| FieldStats stats; | ||
| if (type.equals("dense_vector")) { | ||
| stats = fieldTypes.computeIfAbsent(type, DenseVectorFieldStats::new); | ||
| DenseVectorFieldStats vStats = (DenseVectorFieldStats) stats; | ||
| if (fieldMapping.containsKey("similarity")) { | ||
|
There was a problem hiding this comment. I thought |
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| Object similarity = fieldMapping.get("similarity"); | ||
| vStats.vectorSimilarityTypeCount.compute(similarity.toString(), (t, c) -> c == null ? count : c + count); | ||
| } | ||
| String elementTypeStr = "float"; | ||
| if (fieldMapping.containsKey("element_type")) { | ||
| Object elementType = fieldMapping.get("element_type"); | ||
| elementTypeStr = elementType.toString(); | ||
| } | ||
| vStats.vectorElementTypeCount.compute(elementTypeStr, (t, c) -> c == null ? count : c + count); | ||
| boolean indexed = fieldMapping.containsKey("index") && (boolean) fieldMapping.get("index"); | ||
| if (indexed) { | ||
| Object indexOptions = fieldMapping.get("index_options"); | ||
| // NOTE, while the default for `float` is now `int8_hnsw`, that is actually added to the mapping | ||
| // if the value is truly missing & we are indexed, we default to hnsw. | ||
|
There was a problem hiding this comment. Under what condition this could happen that the value for There was a problem hiding this comment. @mayya-sharipova when we default to |
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| String indexTypeStr = "hnsw"; | ||
| if (indexOptions instanceof Map<?, ?> indexOptionsMap) { | ||
| Object indexType = indexOptionsMap.get("type"); | ||
| if (indexType != null) { | ||
| indexTypeStr = indexType.toString(); | ||
| } | ||
| } | ||
| vStats.vectorIndexTypeCount.compute(indexTypeStr, (t, c) -> c == null ? count : c + count); | ||
| vStats.indexedVectorCount += count; | ||
| Object obj = fieldMapping.get("dims"); | ||
| if (obj != null) { | ||
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@@ -100,6 +121,8 @@ public static MappingStats of(Metadata metadata, Runnable ensureNotCancelled) { | |
| vStats.indexedVectorDimMax = dims; | ||
| } | ||
| } | ||
| } else { | ||
| vStats.vectorIndexTypeCount.compute(DenseVectorFieldStats.NOT_INDEXED, (t, c) -> c == null ? 1 : c + 1); | ||
| } | ||
| } else { | ||
| stats = fieldTypes.computeIfAbsent(type, FieldStats::new); | ||
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should we be concerned about these becoming huge (and hence OOMs & co)?
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@tteofili I wouldn't think so. We have a static number of element types, index types, and similarity types. Since we are counting each separately, we won't have combinatoric explosion. These each will be hashmaps of < 10 elements each or so.