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https://github.com/nosqlbench/nosqlbench.git
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Initial working draft
This commit is contained in:
Madhavan Sridharan
parent
78ff0a3fde
commit
5667e0570a
@ -42,7 +42,7 @@
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<dependency>
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<groupId>org.mongodb</groupId>
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<artifactId>mongodb-driver-sync</artifactId>
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<version>4.10.2</version>
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<version>4.11.0</version>
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</dependency>
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</dependencies>
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@ -18,8 +18,11 @@ package io.nosqlbench.adapter.mongodb.core;
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import com.mongodb.ConnectionString;
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import com.mongodb.MongoClientSettings;
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import com.mongodb.ServerApi;
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import com.mongodb.ServerApiVersion;
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import com.mongodb.client.MongoClient;
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import com.mongodb.client.MongoClients;
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import com.mongodb.client.MongoDatabase;
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import io.nosqlbench.api.config.NBNamedElement;
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import io.nosqlbench.api.config.standard.ConfigModel;
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import io.nosqlbench.api.config.standard.NBConfigModel;
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@ -27,6 +30,7 @@ import io.nosqlbench.api.config.standard.NBConfiguration;
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import io.nosqlbench.api.config.standard.Param;
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import org.apache.logging.log4j.LogManager;
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import org.apache.logging.log4j.Logger;
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import org.bson.Document;
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import org.bson.UuidRepresentation;
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import org.bson.codecs.UuidCodec;
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import org.bson.codecs.configuration.CodecRegistry;
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@ -80,12 +84,26 @@ public class MongoSpace implements NBNamedElement, AutoCloseable {
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MongoClientSettings.getDefaultCodecRegistry()
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);
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// https://www.mongodb.com/docs/v7.0/reference/stable-api
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ServerApi serverApi = ServerApi.builder()
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.version(ServerApiVersion.V1)
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.deprecationErrors(true)
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.strict(true)
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.build();
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MongoClientSettings settings = MongoClientSettings.builder()
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.applyConnectionString(new ConnectionString(connectionURL))
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.codecRegistry(codecRegistry)
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.serverApi(serverApi)
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.uuidRepresentation(UuidRepresentation.STANDARD)
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.applicationName("NoSQLBench")
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.build();
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this.mongoClient = MongoClients.create(settings);
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// Send a ping to confirm a successful connection
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MongoDatabase mdb = this.mongoClient.getDatabase("admin");
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mdb.runCommand(new Document("ping", 1));
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logger.info(() -> "Connection ping test to the cluster successful.");
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}
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public MongoClient getClient() {
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@ -0,0 +1,163 @@
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# Connection Guide: https://www.mongodb.com/docs/drivers/java/sync/current/fundamentals/connection/
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# Troubleshoot connection: https://www.mongodb.com/docs/atlas/troubleshoot-connection/#special-characters-in-connection-string-password
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# nb5 run driver=mongodb workload=/path/to/mongodb_verctor_search.yaml tags=block:"schema.*" connection='mongodb+srv://user:pass@sample-db.host.mongodb.net/?retryWrites=true&w=majority' database=baselines -vv --show-stacktraces
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# nb5 run driver=mongodb workload=/path/to/mongodb_verctor_search.yaml tags=block:rampup cycles=25 connection='mongodb+srv://user:pass@sample-db.host.mongodb.net/?retryWrites=true&w=majority' database=baselines -vv --show-stacktraces
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# nb5 run driver=mongodb workload=/path/to/mongodb_verctor_search.yaml tags='block:main-.*' cycles=25 connection='mongodb+srv://user:pass@sample-db.host.mongodb.net/?retryWrites=true&w=majority' database=baselines -vv --show-stacktraces
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min_version: "5.17.5"
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description: |
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This workload is analogous to the cql-keyvalue2 workload, just implemented for MongoDB Atlas Vector Search.
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scenarios:
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default:
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schema: run driver=mongodb tags==block:"schema.*" threads==1 cycles==UNDEF database=baselines
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rampup: run driver=mongodb tags==block:rampup cycles===TEMPLATE(rampup-cycles,100000) threads=auto database=baselines
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main: run driver=mongodb tags==block:'main-.*' cycles===TEMPLATE(main-cycles,100000) threads=auto database=baselines
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drop: run driver=mongodb tags==block:drop-collection threads==1 cycles==UNDEF database=baselines
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params:
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instrument: true
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bindings:
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#seq_key: Mod(TEMPLATE(keycount,1000000000)); ToString();
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#seq_value: >-
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# Hash();
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# Mod(TEMPLATE(valuecount,1000000000));
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# CharBufImage('A-Za-z0-9 _|/',16000000,HashRange(TEMPLATE(mintext,50000)TEMPLATE(addzeroes,),TEMPLATE(maxtext,150000)TEMPLATE(addzeroes,)));
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# ToString();
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rw_key: TEMPLATE(keydist,Uniform(0,1000000000)); ToString() -> String
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#rw_value: Hash(); TEMPLATE(valdist,Uniform(0,1000000000)); CharBufImage('A-Za-z0-9 _|/',16000000,HashRange(TEMPLATE(mintext,50000)TEMPLATE(addzeros,),TEMPLATE(maxtext,150000)TEMPLATE(addzeros,))); ToString();
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#WRITE
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train_floatlist: HdfFileToFloatList("testdata/TEMPLATE(dataset).hdf5", "/train"); ToCqlVector();
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#READ
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test_floatlist: HdfFileToFloatList("testdata/TEMPLATE(dataset).hdf5", "/test"); ToCqlVector();
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blocks:
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schema:
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params:
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prepared: false
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ops:
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# https://www.mongodb.com/docs/manual/reference/method/db.createCollection/
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# https://www.mongodb.com/docs/manual/core/schema-validation/specify-json-schema/
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# `clusteredIndex` only support creation of an index on `_id` field (as shown below) so its optional
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create_collection: |
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{
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create: "TEMPLATE(collection,keyvalue)",
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clusteredIndex: {
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key: { "_id": 1 },
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unique: true,
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name: "_id_idx"
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},
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writeConcern: { w: "majority" },
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validator: {
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$jsonSchema: {
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bsonType: "object",
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title: "Key/Value collection schema validation",
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required: [ "key" ],
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properties: {
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key: {
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bsonType: "string",
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description: "'key' must be a string and is required"
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},
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value: {
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bsonType: "array",
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description: "'value' must be an array of numbers of BSON double type and is optional but, recommended"
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}
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}
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}
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},
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validationLevel: "off",
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validationAction: "warn",
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comment: "keyvalue collection creation with strict types and a required 'key' field."
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}
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create_key_index: |
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{
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createIndexes: "TEMPLATE(collection,keyvalue)",
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indexes: [
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{
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key: {
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key: 1,
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},
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name: "kv_key_idx",
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unique: true
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}
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],
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writeConcern: { w: "majority" },
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comment: "'key' index creation for keyvalue collection. Values should be unique.",
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commitQuorum: "majority"
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}
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create_vector_search_index: |
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{
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createSearchIndexes: "TEMPLATE(collection,keyvalue)",
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indexes: [
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{
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name: "kv_value_vector_search_idx",
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definition: {
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mappings: {
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dynamic: true,
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fields: {
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value: {
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type: "knnVector",
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dimensions: TEMPLATE(dimensions,1536),
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similarity: "TEMPLATE(similarity_function,cosine)"
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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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rampup:
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ops:
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rampup-insert: |
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{
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insert: "TEMPLATE(collection,keyvalue)",
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documents: [
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{
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key: "{rw_key}",
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value: {train_floatlist}
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}
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],
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comment: "Insert documents into keyvalue collection."
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}
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main-read:
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params:
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ratio: 5
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ops:
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main-select: |
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{
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aggregate: "TEMPLATE(collection,keyvalue)",
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pipeline: [
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$vectorSearch: {
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index: "kv_value_vector_search_idx",
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path: "value",
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queryVector: {test_floatlist},
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numCandidates: TEMPLATE(num_candidates,1000)
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limit: TEMPLATE(top_k,100)
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}
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],
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readConcern: { level: "majority" },
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comment: "Find the results for the given 'value' vector search embedding."
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}
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main-write:
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params:
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ratio: 5
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ops:
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main-insert: |
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{
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insert: "TEMPLATE(collection,keyvalue)",
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documents: [
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{
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key: "{rw_key}",
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value: {train_floatlist}
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}
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],
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writeConcern: { w: "majority" },
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comment: "Insert documents into keyvalue collection."
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}
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drop-collection:
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ops:
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drop-collection: |
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{
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drop: "TEMPLATE(collection,keyvalue)",
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comment: "Drop keyvalue collection to start afresh."
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}
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