Daniel (dB.) DoubrovkineandGitHub
bcfef113c4
* Added samples for nox format. Signed-off-by: dblock <[email protected]> * Added space after #!/usr/bin/env python. Signed-off-by: dblock <[email protected]> * Added benchmarks and docs. Signed-off-by: dblock <[email protected]> --------- Signed-off-by: dblock <[email protected]>
181 lines
4.1 KiB
Python
Executable File
181 lines
4.1 KiB
Python
Executable File
#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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# SPDX-License-Identifier: Apache-2.0
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#
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# The OpenSearch Contributors require contributions made to
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# this file be licensed under the Apache-2.0 license or a
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# compatible open source license.
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#
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# Modifications Copyright OpenSearch Contributors. See
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# GitHub history for details.
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import os
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from opensearchpy import OpenSearch, helpers
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# connect to an instance of OpenSearch
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host = os.getenv("HOST", default="localhost")
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port = int(os.getenv("PORT", 9200))
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auth = (os.getenv("USERNAME", "admin"), os.getenv("PASSWORD", "admin"))
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client = OpenSearch(
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hosts=[{"host": host, "port": port}],
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http_auth=auth,
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use_ssl=True,
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verify_certs=False,
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ssl_show_warn=False,
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)
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# check whether an index exists
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index_name = "hotels-index"
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if not client.indices.exists(index_name):
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client.indices.create(
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index_name,
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body={
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"settings": {
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"index.knn": True,
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"knn.algo_param.ef_search": 100,
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"number_of_shards": 1,
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"number_of_replicas": 0,
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},
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"mappings": {
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"properties": {
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"location": {
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"type": "knn_vector",
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"dimension": 2,
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"method": {
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"name": "hnsw",
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"space_type": "l2",
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"engine": "lucene",
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"parameters": {"ef_construction": 100, "m": 16},
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},
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},
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}
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},
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},
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)
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# index data
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vectors = [
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{
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"_index": "hotels-index",
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"_id": "1",
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"location": [5.2, 4.4],
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"parking": "true",
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"rating": 5,
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},
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{
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"_index": "hotels-index",
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"_id": "2",
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"location": [5.2, 3.9],
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"parking": "false",
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"rating": 4,
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},
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{
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"_index": "hotels-index",
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"_id": "3",
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"location": [4.9, 3.4],
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"parking": "true",
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"rating": 9,
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},
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{
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"_index": "hotels-index",
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"_id": "4",
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"location": [4.2, 4.6],
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"parking": "false",
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"rating": 6,
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},
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{
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"_index": "hotels-index",
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"_id": "5",
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"location": [3.3, 4.5],
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"parking": "true",
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"rating": 8,
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},
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{
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"_index": "hotels-index",
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"_id": "6",
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"location": [6.4, 3.4],
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"parking": "true",
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"rating": 9,
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},
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{
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"_index": "hotels-index",
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"_id": "7",
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"location": [4.2, 6.2],
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"parking": "true",
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"rating": 5,
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},
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{
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"_index": "hotels-index",
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"_id": "8",
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"location": [2.4, 4.0],
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"parking": "true",
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"rating": 8,
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},
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{
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"_index": "hotels-index",
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"_id": "9",
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"location": [1.4, 3.2],
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"parking": "false",
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"rating": 5,
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},
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{
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"_index": "hotels-index",
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"_id": "10",
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"location": [7.0, 9.9],
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"parking": "true",
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"rating": 9,
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},
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{
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"_index": "hotels-index",
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"_id": "11",
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"location": [3.0, 2.3],
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"parking": "false",
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"rating": 6,
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},
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{
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"_index": "hotels-index",
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"_id": "12",
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"location": [5.0, 1.0],
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"parking": "true",
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"rating": 3,
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},
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]
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helpers.bulk(client, vectors)
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client.indices.refresh(index=index_name)
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# search
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search_query = {
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"size": 3,
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"query": {
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"knn": {
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"location": {
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"vector": [5, 4],
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"k": 3,
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"filter": {
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"bool": {
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"must": [
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{"range": {"rating": {"gte": 8, "lte": 10}}},
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{"term": {"parking": "true"}},
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]
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}
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},
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}
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}
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},
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}
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results = client.search(index=index_name, body=search_query)
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for hit in results["hits"]["hits"]:
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print(hit)
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# delete index
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client.indices.delete(index=index_name)
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