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updating recommendations to defer indexing
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@@ -114,7 +114,9 @@ if not client.collection_exists(collection_name):
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),
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optimizers_config=models.OptimizersConfigDiff(
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default_segment_number=5,
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indexing_threshold=0,
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),
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hnsw_config=models.HnswConfigDiff(
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m=0,
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),
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quantization_config=models.BinaryQuantization(
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binary=models.BinaryQuantizationConfig(always_ram=True),
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@@ -122,11 +124,11 @@ if not client.collection_exists(collection_name):
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)
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```
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#### What is happening in the OptimizerConfig?
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#### What is happening in the HnswConfig?
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We're setting `indexing_threshold` to 0 i.e. disabling the indexing to zero. This allows faster uploads of vectors and payloads. We will turn it back on down below, once all the data is loaded
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We're setting `m` to 0 i.e. disabling the HNSW graph construction. This allows faster uploads of vectors and payloads. We will turn it back on down below, once all the data is loaded.
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#### Next, we upload our vectors to this and then enable indexing:
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#### Next, we upload our vectors to this and then enable the graph construction:
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```python
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batch_size = 10000
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@@ -141,14 +143,14 @@ client.upload_collection(
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)
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```
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Enable indexing again:
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Enable HNSW graph construction again:
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```python
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client.update_collection(
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collection_name=f"{collection_name}",
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optimizer_config=models.OptimizersConfigDiff(
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indexing_threshold=20000
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)
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hnsw_config=models.HnswConfigDiff(
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m=16,
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,
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)
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```
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#### Configure the search parameters:
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