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| // _ _ | |
| // __ _____ __ ___ ___ __ _| |_ ___ | |
| // \ \ /\ / / _ \/ _` \ \ / / |/ _` | __/ _ \ | |
| // \ V V / __/ (_| |\ V /| | (_| | || __/ | |
| // \_/\_/ \___|\__,_| \_/ |_|\__,_|\__\___| | |
| // | |
| // Copyright © 2016 - 2024 Weaviate B.V. All rights reserved. | |
| // | |
| // CONTACT: [email protected] | |
| // | |
| //go:build integrationTest | |
| // +build integrationTest | |
| package db | |
| import ( | |
| "fmt" | |
| "github.com/go-openapi/strfmt" | |
| "github.com/weaviate/weaviate/entities/models" | |
| "github.com/weaviate/weaviate/entities/schema" | |
| enthnsw "github.com/weaviate/weaviate/entities/vectorindex/hnsw" | |
| ) | |
| var productClass = &models.Class{ | |
| Class: "AggregationsTestProduct", | |
| VectorIndexConfig: enthnsw.NewDefaultUserConfig(), | |
| InvertedIndexConfig: invertedConfig(), | |
| Properties: []*models.Property{ | |
| { | |
| Name: "name", | |
| DataType: schema.DataTypeText.PropString(), | |
| Tokenization: models.PropertyTokenizationWhitespace, | |
| }, | |
| }, | |
| } | |
| var companyClass = &models.Class{ | |
| Class: "AggregationsTestCompany", | |
| VectorIndexConfig: enthnsw.NewDefaultUserConfig(), | |
| InvertedIndexConfig: invertedConfig(), | |
| Properties: []*models.Property{ | |
| { | |
| Name: "sector", | |
| DataType: schema.DataTypeText.PropString(), | |
| Tokenization: models.PropertyTokenizationWhitespace, | |
| }, | |
| { | |
| Name: "location", | |
| DataType: []string{"text"}, | |
| Tokenization: "word", | |
| }, | |
| { | |
| Name: "dividendYield", | |
| DataType: []string{"number"}, | |
| }, | |
| { | |
| Name: "price", | |
| DataType: []string{"int"}, // unrealistic for this to be an int, but | |
| // we've already tested another number prop ;-) | |
| }, | |
| { | |
| Name: "listedInIndex", | |
| DataType: []string{"boolean"}, | |
| }, | |
| { | |
| Name: "makesProduct", | |
| DataType: []string{"AggregationsTestProduct"}, | |
| }, | |
| }, | |
| } | |
| var arrayTypesClass = &models.Class{ | |
| Class: "AggregationsTestArrayTypes", | |
| VectorIndexConfig: enthnsw.NewDefaultUserConfig(), | |
| InvertedIndexConfig: invertedConfig(), | |
| Properties: []*models.Property{ | |
| { | |
| Name: "strings", | |
| DataType: schema.DataTypeTextArray.PropString(), | |
| Tokenization: models.PropertyTokenizationWhitespace, | |
| }, | |
| { | |
| Name: "numbers", | |
| DataType: []string{"number[]"}, | |
| }, | |
| }, | |
| } | |
| var customerClass = &models.Class{ | |
| Class: "AggregationsTestCustomer", | |
| VectorIndexConfig: enthnsw.NewDefaultUserConfig(), | |
| InvertedIndexConfig: invertedConfig(), | |
| Properties: []*models.Property{ | |
| { | |
| Name: "internalId", | |
| DataType: schema.DataTypeText.PropString(), | |
| Tokenization: models.PropertyTokenizationWhitespace, | |
| }, | |
| { | |
| Name: "timeArrived", | |
| DataType: []string{"date"}, | |
| }, | |
| { | |
| Name: "countryOfOrigin", | |
| DataType: schema.DataTypeText.PropString(), | |
| Tokenization: models.PropertyTokenizationWhitespace, | |
| }, | |
| }, | |
| } | |
| var products = []map[string]interface{}{ | |
| { | |
| "name": "Superbread", | |
| }, | |
| } | |
| var productsIds = []strfmt.UUID{ | |
| "1295c052-263d-4aae-99dd-920c5a370d06", | |
| } | |
| // company objects are imported not just once each, but each is imported | |
| // importFactor times. This should even out shard imbalances a bit better. | |
| var importFactor = 10 | |
| var companies = []map[string]interface{}{ | |
| { | |
| "sector": "Financials", | |
| "location": "New York", | |
| "dividendYield": 1.3, | |
| "price": int64(150), | |
| "listedInIndex": true, | |
| }, | |
| { | |
| "sector": "Financials", | |
| "location": "New York", | |
| "dividendYield": 4.0, | |
| "price": int64(600), | |
| "listedInIndex": true, | |
| }, | |
| { | |
| "sector": "Financials", | |
| "location": "San Francisco", | |
| "dividendYield": 1.3, | |
| "price": int64(47), | |
| "listedInIndex": true, | |
| }, | |
| { | |
| "sector": "Food", | |
| "location": "Atlanta", | |
| "dividendYield": 1.3, | |
| "price": int64(160), | |
| "listedInIndex": true, | |
| }, | |
| { | |
| "sector": "Food", | |
| "location": "Atlanta", | |
| "dividendYield": 2.0, | |
| "price": int64(70), | |
| "listedInIndex": true, | |
| }, | |
| { | |
| "sector": "Food", | |
| "location": "Los Angeles", | |
| "dividendYield": 0.0, | |
| "price": int64(800), | |
| "listedInIndex": false, | |
| }, | |
| { | |
| "sector": "Food", | |
| "location": "Detroit", | |
| "dividendYield": 8.0, | |
| "price": int64(10), | |
| "listedInIndex": true, | |
| "makesProduct": models.MultipleRef{ | |
| &models.SingleRef{ | |
| Beacon: strfmt.URI(fmt.Sprintf("weaviate://localhost/%s", productsIds[0])), | |
| }, | |
| }, | |
| }, | |
| { | |
| "sector": "Food", | |
| "location": "San Francisco", | |
| "dividendYield": 0.0, | |
| "price": int64(200), | |
| "listedInIndex": true, | |
| }, | |
| { | |
| "sector": "Food", | |
| "location": "New York", | |
| "dividendYield": 1.1, | |
| "price": int64(70), | |
| "listedInIndex": true, | |
| }, | |
| } | |
| // Use fixed ids to make the test deterministic. The length of this must match | |
| // the len(companies)*importFactor These are somewhat carefully arranged to | |
| // make sure that we prevent the flakiness that was described in | |
| // https://github.com/weaviate/weaviate/issues/1884 | |
| var companyIDs = []strfmt.UUID{ | |
| "9ee7640f-b4fc-45f1-b502-580e79062c99", | |
| "f745485b-f6ef-4785-bd54-574cc4923899", | |
| "0109289b-88d5-48d5-9f3e-1e5edb7e56c1", | |
| "ce7c2930-2af8-44ec-8789-eceee930c37d", | |
| "3f7b1ea2-e6e8-49d4-b44c-30916dbab43a", | |
| "ed3b417f-2b7e-456e-9599-744541728950", | |
| "175c22ea-190a-4b8c-9fd0-fbffa5b1b8be", | |
| "e0165a52-f504-47d3-b947-b3829eca3563", | |
| "19ede86d-86d6-4ea8-9ae3-a10a1607b433", | |
| "034c8d0b-50d7-4753-811c-abbfad44c653", | |
| "99564c6b-8529-4f56-9c3f-f808385f034a", | |
| "adc362ea-105d-4544-b981-dedc100d25b9", | |
| "21e1dc5b-49e1-4d35-acb4-be969e4e3a30", | |
| "cb278f74-c632-4460-ae78-2c2c140c0e12", | |
| "4d552f33-552a-41aa-b732-da3d0f708b79", | |
| "faf509ad-bdb6-4aa1-ae9f-e9f410210419", | |
| "59992957-65cf-44bd-8894-d8b2364f080f", | |
| "529217e6-9ec3-41c6-bb6d-13e8f380960a", | |
| "058ec709-782d-4b58-a38f-01593d97f181", | |
| "d027204b-805c-46ae-8a61-7d35f9c6eaba", | |
| "0fce8fea-6ca7-4c80-bc81-55d26e1fd0bd", | |
| "1f4832c7-d164-441e-b197-aa193b4d128f", | |
| "15ad080d-49fc-4b8b-b621-d47f98aa5fdb", | |
| "cb40966d-963d-4283-94be-7da5de70992e", | |
| "6516f7d9-c505-40b3-94de-a42498eea22d", | |
| "9dbcbd08-1067-4bec-84a4-4f3ad19286d3", | |
| "dabd68eb-27b9-462b-a271-300058c5798b", | |
| "9a33f431-cb28-49ae-b9c9-94e97f752a2a", | |
| "4aa27f5c-f475-444b-9279-94b8a5da14c9", | |
| "e71cf490-9a59-4475-80c1-b6c872f3b33c", | |
| "a8e7e8bf-237b-4d95-99be-6af332bdf942", | |
| "08c239c3-e19e-4d88-b0fd-861853dd5e36", | |
| "0209ab7c-2573-4d66-9917-942450e02750", | |
| "0a71a4da-d9c9-423e-8dd8-ebd5c2a86a2d", | |
| "f312aa16-992e-4505-82aa-04da30ea5fe3", | |
| "5b9f9449-1336-44e3-88f9-979f3c752bd7", | |
| "dcec96ab-9377-4272-8a48-07568c4ed533", | |
| "3f28352d-9960-4251-aa05-ce4c612e1ab7", | |
| "4a08101e-f280-41f9-9e7b-fe12d7216c3c", | |
| "0dd7383f-c71b-483c-9253-e180f8763405", | |
| "cfb83c85-cf8f-49da-952f-5bd954b7e616", | |
| "b016bb0f-9e07-4d40-9878-a6bbaa67d866", | |
| "311d7423-552b-4d4c-b7b6-cdcd15e1009b", | |
| "895877d6-9cf3-4d79-989e-4d89f6867e09", | |
| "92bdb79c-6870-44e2-ab71-c3137c78cb2d", | |
| "b16cb9c4-5a6c-444c-bbf5-7b0ef2c1ac12", | |
| "efb09d97-09c4-4976-aa14-abfd520c114d", | |
| "6431f59d-9ed8-4963-9ed7-7336a5795d8b", | |
| "1ad26844-6f6b-4007-834d-09ec8668fe7b", | |
| "6d83b349-6ec8-49bb-b438-7f29a16216d3", | |
| "68156360-1cae-406e-8baf-177178f0815e", | |
| "3c726a50-ec82-4828-8967-f704477dfef7", | |
| "46f702b2-e1c3-4e4a-868e-10ec1e260c75", | |
| "51ff679a-87d8-4bef-830d-327e7b4c8f8e", | |
| "aea6fc5c-8eb0-4cd7-8cfe-1285239d16bd", | |
| "b70bbf68-5ebc-4315-9819-deb65b241f3f", | |
| "6069853f-8822-434f-9d59-c881800e0a27", | |
| "9a287ef6-6920-4d01-a44a-7561d2fb627d", | |
| "fa057d95-9ba8-418a-aeb2-fe4b2acd31b0", | |
| "9b0fb28f-21f1-4df1-a55b-67bf6be79911", | |
| "044403fb-25f6-461f-ad92-8f9533908070", | |
| "35d09151-c469-4901-8092-2114060cb86b", | |
| "85884aa2-5d0b-4dff-80f6-8ca7cbab9fef", | |
| "bd36a31a-f14e-4040-ad11-0ec5b6217b6a", | |
| "fe20620f-c612-4712-9475-d4cfc59e8bba", | |
| "09ba0773-e81d-4cb9-968a-552e1cbaf143", | |
| "7a7378a5-2d05-4457-b2d4-1fe068535167", | |
| "6867d1e5-2d30-4f91-90d2-2b453ffd5cd5", | |
| "2fef1b16-3dd1-4ad5-bc55-cf8f9783b40c", | |
| "0590f51b-7c9f-41a0-b81e-cdbc205ebdd9", | |
| "7ed55b94-86d5-440a-9a8a-5f83dabcb69b", | |
| "2daca92a-c8a6-4ab4-a528-3d99ce6f72f2", | |
| "24187e67-947d-436d-ae7f-d20b03874b56", | |
| "864ff42d-00fe-44a8-8163-8af459dc1c0c", | |
| "0c2cc9a5-089a-4d10-882a-837c154117ea", | |
| "fb256f18-e812-4355-b41a-c69d933f2a61", | |
| "b631c4df-8229-43c0-9e5e-189c5d666ac2", | |
| "8da03018-3272-4bd3-987c-1dd1e807bc1d", | |
| "bf736b76-fccc-4d1b-8d9f-2e78fdb0d972", | |
| "1fc9dffc-da23-4b99-8330-44c5598919db", | |
| "1ed74402-bc81-4245-8275-c2862a4d6a86", | |
| "6a91adb4-23df-43bd-9564-f97e76382a52", | |
| "d1661202-c568-4032-8ec6-99fe4238de84", | |
| "e4b4186d-f02e-47d7-8214-d3854ee475fd", | |
| "664e6157-bfcc-4513-8f04-c095d3ecb2d5", | |
| "b3b9951f-0867-453d-bf20-9f22bdb5a38b", | |
| "52adfeae-ab75-4250-ae45-61af9e231e86", | |
| "e994c378-ac0b-4f08-bd56-462990be36dd", | |
| "a012f65a-28a7-4005-95bb-f55783bcdda0", | |
| "0cbc7fb6-843c-4aad-b540-e37ddb7c84c6", | |
| } | |
| var arrayTypes = []map[string]interface{}{ | |
| { | |
| "strings": []string{"a", "b", "c"}, | |
| "numbers": []float64{1.0, 2.0, 2.0, 3.0, 3.0}, | |
| }, | |
| { | |
| "strings": []string{"a"}, | |
| "numbers": []float64{1.0, 2.0}, | |
| }, | |
| } | |
| var customers = []map[string]interface{}{ | |
| { | |
| "internalId": "customer 1", | |
| "countryOfOrigin": "US", | |
| "timeArrived": mustStringToTime("2022-06-16T17:30:17.231346Z"), | |
| "isNewCustomer": false, | |
| }, | |
| { | |
| "internalId": "customer 2", | |
| "countryOfOrigin": "US", | |
| "timeArrived": mustStringToTime("2022-06-16T17:30:17.231346Z"), | |
| "isNewCustomer": false, | |
| }, | |
| { | |
| "internalId": "customer 3", | |
| "countryOfOrigin": "US", | |
| "timeArrived": mustStringToTime("2022-06-16T17:30:17.231346Z"), | |
| "isNewCustomer": false, | |
| }, | |
| { | |
| "internalId": "customer 4", | |
| "countryOfOrigin": "US", | |
| "timeArrived": mustStringToTime("2022-06-16T17:30:20.123546Z"), | |
| "isNewCustomer": true, | |
| }, | |
| { | |
| "internalId": "customer 5", | |
| "countryOfOrigin": "US", | |
| "timeArrived": mustStringToTime("2022-06-16T17:30:20.123546Z"), | |
| "isNewCustomer": true, | |
| }, | |
| { | |
| "internalId": "customer 6", | |
| "countryOfOrigin": "US", | |
| "timeArrived": mustStringToTime("2022-06-16T17:30:22.112435Z"), | |
| "isNewCustomer": false, | |
| }, | |
| { | |
| "internalId": "customer 7", | |
| "countryOfOrigin": "US", | |
| "timeArrived": mustStringToTime("2022-06-16T17:30:23.754272Z"), | |
| "isNewCustomer": false, | |
| }, | |
| { | |
| "internalId": "customer 8", | |
| "countryOfOrigin": "US", | |
| "timeArrived": mustStringToTime("2022-06-16T17:30:24.325698Z"), | |
| "isNewCustomer": true, | |
| }, | |
| { | |
| "internalId": "customer 9", | |
| "countryOfOrigin": "US", | |
| "timeArrived": mustStringToTime("2022-06-16T17:30:25.524536Z"), | |
| "isNewCustomer": false, | |
| }, | |
| { | |
| "internalId": "customer 10", | |
| "countryOfOrigin": "US", | |
| "timeArrived": mustStringToTime("2022-06-16T17:30:26.451235Z"), | |
| "isNewCustomer": true, | |
| }, | |
| } | |