Replace memmap_threshold with indexing_threshold (#2041)

* Replace memmap_threshold with indexing_threshold

* Update GitHub Stars

* Update GitHub Stars

* Update GitHub Stars

---------

Co-authored-by: myyrakle <16988115+myyrakle@users.noreply.github.com>
This commit is contained in:
myyrakle
2025-12-28 22:38:46 +01:00
committed by GitHub
co-authored by myyrakle
parent 95daf35026
commit 0316544a1a
14 changed files with 17 additions and 15 deletions
@@ -26,7 +26,7 @@ public class Snippet {
.build())
.build())
.setOptimizersConfig(
OptimizersConfigDiff.newBuilder().setMemmapThreshold(20000).build())
OptimizersConfigDiff.newBuilder().setIndexingThreshold(20000).build())
.build())
.get();
}
@@ -1 +1 @@
Creates a collection with vectors stored in memmap storage and specifies an optimizer configuration with a `memmap_threshold` set to 20000. This configuration is particularly useful for Qdrant instances with fast disks and large collections. The `memmap_threshold` option determines the threshold after which a segment will be converted to memmap storage. It can be set globally in the configuration file or for each collection individually during creation or update.
Creates a collection with vectors stored in memmap storage and specifies an optimizer configuration with a `indexing_threshold` set to 20000. This configuration is particularly useful for Qdrant instances with fast disks and large collections. The `indexing_threshold` option determines the threshold after which a segment will be converted to memmap storage. It can be set globally in the configuration file or for each collection individually during creation or update.
@@ -10,7 +10,7 @@ public class Snippet
await client.CreateCollectionAsync(
collectionName: "{collection_name}",
vectorsConfig: new VectorParams { Size = 768, Distance = Distance.Cosine },
optimizersConfig: new OptimizersConfigDiff { MemmapThreshold = 20000 }
optimizersConfig: new OptimizersConfigDiff { IndexingThreshold = 20000 }
);
}
}
@@ -7,6 +7,6 @@ var client = new QdrantClient("localhost", 6334);
await client.CreateCollectionAsync(
collectionName: "{collection_name}",
vectorsConfig: new VectorParams { Size = 768, Distance = Distance.Cosine },
optimizersConfig: new OptimizersConfigDiff { MemmapThreshold = 20000 }
optimizersConfig: new OptimizersConfigDiff { IndexingThreshold = 20000 }
);
```
@@ -17,7 +17,7 @@ client.CreateCollection(context.Background(), &qdrant.CreateCollection{
Distance: qdrant.Distance_Cosine,
}),
OptimizersConfig: &qdrant.OptimizersConfigDiff{
MaxSegmentSize: qdrant.PtrOf(uint64(20000)),
IndexingThreshold: qdrant.PtrOf(uint64(20000)),
},
})
```
@@ -23,7 +23,7 @@ client
.build())
.build())
.setOptimizersConfig(
OptimizersConfigDiff.newBuilder().setMemmapThreshold(20000).build())
OptimizersConfigDiff.newBuilder().setIndexingThreshold(20000).build())
.build())
.get();
```
@@ -6,6 +6,6 @@ client = QdrantClient(url="http://localhost:6333")
client.create_collection(
collection_name="{collection_name}",
vectors_config=models.VectorParams(size=768, distance=models.Distance.COSINE),
optimizers_config=models.OptimizersConfigDiff(memmap_threshold=20000),
optimizers_config=models.OptimizersConfigDiff(indexing_threshold=20000),
)
```
@@ -10,7 +10,7 @@ client
.create_collection(
CreateCollectionBuilder::new("{collection_name}")
.vectors_config(VectorParamsBuilder::new(768, Distance::Cosine))
.optimizers_config(OptimizersConfigDiffBuilder::default().memmap_threshold(20000)),
.optimizers_config(OptimizersConfigDiffBuilder::default().indexing_threshold(20000)),
)
.await?;
```
@@ -9,7 +9,7 @@ client.createCollection("{collection_name}", {
distance: "Cosine",
},
optimizers_config: {
memmap_threshold: 20000,
indexing_threshold: 20000,
},
});
```
@@ -12,7 +12,9 @@ func Main() {
Port: 6334,
})
if err != nil { panic(err) } // @hide
if err != nil {
panic(err)
} // @hide
client.CreateCollection(context.Background(), &qdrant.CreateCollection{
CollectionName: "{collection_name}",
@@ -21,7 +23,7 @@ func Main() {
Distance: qdrant.Distance_Cosine,
}),
OptimizersConfig: &qdrant.OptimizersConfigDiff{
MaxSegmentSize: qdrant.PtrOf(uint64(20000)),
IndexingThreshold: qdrant.PtrOf(uint64(20000)),
},
})
}
@@ -6,7 +6,7 @@ PUT /collections/{collection_name}
"distance": "Cosine"
},
"optimizers_config": {
"memmap_threshold": 20000
"indexing_threshold": 20000
}
}
```
@@ -5,5 +5,5 @@ client = QdrantClient(url="http://localhost:6333")
client.create_collection(
collection_name="{collection_name}",
vectors_config=models.VectorParams(size=768, distance=models.Distance.COSINE),
optimizers_config=models.OptimizersConfigDiff(memmap_threshold=20000),
optimizers_config=models.OptimizersConfigDiff(indexing_threshold=20000),
)
@@ -10,7 +10,7 @@ pub async fn main() -> anyhow::Result<()> {
.create_collection(
CreateCollectionBuilder::new("{collection_name}")
.vectors_config(VectorParamsBuilder::new(768, Distance::Cosine))
.optimizers_config(OptimizersConfigDiffBuilder::default().memmap_threshold(20000)),
.optimizers_config(OptimizersConfigDiffBuilder::default().indexing_threshold(20000)),
)
.await?;
@@ -8,6 +8,6 @@ client.createCollection("{collection_name}", {
distance: "Cosine",
},
optimizers_config: {
memmap_threshold: 20000,
indexing_threshold: 20000,
},
});