Spanner e BigQuery: scudo di difesa antifrode in tempo reale

1. Introduzione

Ti diamo il benvenuto nel backend di Petverse, un gioco online multiplayer in cui i giocatori creano avatar di animali, esplorano il mondo e scambiano valuta in-game.

Di recente, l'economia del gioco è stata minacciata. Ingenti somme di denaro vengono sottratte dai conti dei ricchi giocatori di Dog, convertite interamente in scorte di tonno premium. Sospettiamo che un gruppo di "gatti Robin Hood" rubi ai cani ricchi per nutrire le masse feline.

In questo codelab, creerai uno scudo di difesa dalle frodi in tempo reale per catturare il capo e la sua rete di bot automatizzati. Vedrai come i dati operativi in Spanner convergono con l'analisi in BigQuery per rilevare e analizzare pattern di frode complessi con query grafiche (GQL) e relazionali.

In questo lab proverai a:

  • Rileva un'anomalia nel flusso in tempo reale utilizzando le query continue di BigQuery e inviala a Spanner.
  • Esamina la rete di frode utilizzando Spanner Graph per tracciare i rapporti finanziari.
  • Identifica gli account bot utilizzando la ricerca vettoriale di Spanner per trovare descrizioni di profili simili.
  • Scopri il grafico di coordinamento utilizzando BigQuery Graph per analizzare enormi log di comunicazione.

Che cosa ti serve

  • Un progetto Google Cloud con la fatturazione abilitata.
  • Conoscenza di base di SQL, comandi del terminale e Python.
  • Potresti aver bisogno di un account GitHub (il codice è ospitato su GitHub).

Pubblico: sviluppatori, data engineer e architetti di livello intermedio.

Durata totale stimata: da 45 a 60 minuti.

Stima dei costi: le risorse create in questo codelab dovrebbero costare meno di 5 $.

2. Prima di iniziare / Configurazione

Crea o seleziona un progetto Google Cloud

Per utilizzare i servizi richiesti per questo lab, devi disporre di un progetto Google Cloud con la fatturazione abilitata.

  1. Nella console Google Cloud, nella pagina di selezione del progetto, seleziona o crea un progetto Google Cloud.
  2. Assicurati che la fatturazione sia attivata per il tuo progetto Cloud. Scopri come verificare se la fatturazione è attivata.
  3. Trova l'ID progetto nella home page di Cloud Console.

Home page della console Cloud

Avvia Cloud Shell

Utilizzerai Google Cloud Shell come ambiente di esecuzione. Cloud Shell è preinstallato con gcloud, git e altri strumenti di cui avrai bisogno.

  1. Vai a Google Cloud Shell.
  2. Se richiesto, fai clic su Autorizza.
  3. Assicurati di lavorare nel tuo progetto impostando la variabile di ambiente nel terminale Cloud Shell:
export PROJECT_ID=<YOUR_PROJECT_ID>
gcloud config set project $PROJECT_ID

Cloud Shell: usa gcloud config per impostare il progetto

Abilita le API necessarie

Esegui il seguente comando per abilitare le API per Spanner, BigQuery e Vertex AI:

gcloud services enable spanner.googleapis.com \
    bigquery.googleapis.com \
    aiplatform.googleapis.com \
    run.googleapis.com

Clona il repository

Clona il repository contenente il codice dell'applicazione e gli schemi di esempio:

git clone https://github.com/GoogleCloudPlatform/cloud-spanner-samples.git
cd cloud-spanner-samples/spanner-bq-fraud-defense

3. Esegui il provisioning dell'infrastruttura

Ora configurerai il data warehouse in BigQuery e il database operativo in Spanner.

Configura il set di dati e la connessione BigQuery

BigQuery analizzerà il flusso di telemetria del gioco.

Sempre all'interno della console in Google Cloud Shell, esegui i seguenti comandi per assicurarti che l'ID progetto sia ancora impostato:

export PROJECT_ID=<YOUR_PROJECT_ID>
gcloud config set project $PROJECT_ID
  1. Crea un set di dati BigQuery game_analytics:
bq mk -d --location=US game_analytics
  1. Crea una connessione per connetterti ai bucket Storage e (facoltativamente) a Spanner:
bq mk --connection --location=US --project_id=$PROJECT_ID \
    --connection_type=CLOUD_RESOURCE unicorn-connection
  1. Crea gli schemi per le tabelle GameplayTelemetry, AccountSignals, Players e ChatLogs utilizzando il file dello schema:
bq query --use_legacy_sql=false < bq_schema.sql

Configura Spanner

Google Cloud Spanner gestirà le transazioni operative in tempo reale. Per questo lab, utilizzeremo un'istanza da 100 unità di elaborazione (PU) conveniente.

  1. Crea un'istanza di Spanner:
gcloud spanner instances create game-instance \
    --config=regional-us-central1 \
    --description="Game Instance" \
    --processing-units=100 \
    --edition=ENTERPRISE
  1. Crea il database Spanner game-db:
gcloud spanner databases create game-db --instance=game-instance
  1. Aggiorna lo schema Spanner con le tabelle dell'applicazione (Players, Transactions, AccountSignals) e il grafico delle proprietà (PlayerNetwork):
gcloud spanner databases ddl update game-db --instance=game-instance --ddl-file=spanner_schema.sql
  1. Crea l'AvatarSearchIndex per la nostra ricerca vettoriale multimodale:
gcloud spanner databases ddl update game-db --instance=game-instance \
    --ddl="CREATE SEARCH INDEX AvatarSearchIndex ON Players(AvatarDescriptionTokens)"

Importare i dati in BigQuery

  1. Importa i dati demo in BigQuery:
bq load --source_format=AVRO game_analytics.GameplayTelemetry gs://sample-data-and-media/spanner-bq-fraud-heist/GameplayTelemetry
bq load --source_format=AVRO game_analytics.AccountSignals gs://sample-data-and-media/spanner-bq-fraud-heist/AccountSignals
bq load --source_format=AVRO game_analytics.Players gs://sample-data-and-media/spanner-bq-fraud-heist/Players
bq load --source_format=AVRO game_analytics.ChatLogs gs://sample-data-and-media/spanner-bq-fraud-heist/ChatLogs
  1. Vai alla console BigQuery ed esplora i dati nel set di dati game_analytics.

Console BigQuery

Importa dati in Spanner

Vai alla console Spanner ed esplora i dati nel database game-db.

Fai clic su Spanner Studio e apri una Nuova query (+).

Console Spanner

Incolla le seguenti istruzioni INSERT nell'editor di query e fai clic su Esegui:

-- Table: Players
INSERT INTO Players (
  PlayerId,
  Name,
  Species,
  Clan,
  AvatarDescription,
  ProfilePictureUrl,
  CreatedAt
) VALUES
  ('dc8cf07a-ac0f-48da-9f64-4f379492b1e7', 'Pixel', 'Cat', 'CatClan', 'A heroic cat wearing a green tunic and a feathered cap', 'gs://sample-data-and-media/pixel_profile_booth.png', '2026-03-02T05:11:28.077335+00:00'),
  ('e82df4fb-0b6d-44dc-8609-70b41430af38', 'Rocky_1', 'Dog', 'DogClan', 'A robot dog with metal plating', 'gs://sample-data-and-media/wheaten_terrier_102.jpg', '2026-03-02T05:11:28.077374+00:00'),
  ('ea3afac7-54f0-4f68-8ed5-a5b6bd386c59', 'Whiskers_2', 'Cat', 'CatClan', 'A sneaky black cat hiding in the shadows', 'gs://sample-data-and-media/Bengal_100.jpg', '2026-03-02T05:11:28.077389+00:00'),
  ('f37d558b-fd0a-404c-a193-bc3a8a2edfba', 'Felix_3', 'Cat', 'CatClan', 'A cyber-punk cat with neon glasses', 'gs://sample-data-and-media/Abyssinian_1.jpg', '2026-03-02T05:11:28.077407+00:00'),
  ('f3687206-405e-43b6-afb0-8ca73eee5dd1', 'Luna_4', 'Cat', 'CatClan', 'A tabby cat with a red bandana', 'gs://sample-data-and-media/Bengal_100.jpg', '2026-03-02T05:11:28.077419+00:00'),
  ('82383e2d-d3a2-481d-b0cf-bfe165ed9bfd', 'Luna_5', 'Cat', 'CatClan', 'A fluffy persian cat with a golden collar', 'gs://sample-data-and-media/Abyssinian_114.jpg', '2026-03-02T05:11:28.077429+00:00'),
  ('755c7aff-e538-4681-9b90-4b870a42ac72', 'Buddy_6', 'Dog', 'DogClan', 'A tough bulldog with a spiked collar', 'gs://sample-data-and-media/yorkshire_terrier_101.jpg', '2026-03-02T05:11:28.077439+00:00'),
  ('8a034e84-26b3-4198-8ec9-3749b1f60537', 'Charlie_7', 'Dog', 'DogClan', 'A police german shepherd with a badge', 'gs://sample-data-and-media/wheaten_terrier_102.jpg', '2026-03-02T05:11:28.077462+00:00'),
  ('ca288a07-2bf8-46fa-a121-9bd0d0f44c64', 'Rocky_8', 'Dog', 'DogClan', 'A robot dog with metal plating', 'gs://sample-data-and-media/yorkshire_terrier_101.jpg', '2026-03-02T05:11:28.077474+00:00'),
  ('7b2881f0-289b-4ea4-9c0e-c1748249b70a', 'Bella_9', 'Dog', 'DogClan', 'A robot dog with metal plating', 'gs://sample-data-and-media/yorkshire_terrier_101.jpg', '2026-03-02T05:11:28.077484+00:00'),
  ('153f4022-a4ce-404a-8544-25d004fd34ad', 'Simba_10', 'Cat', 'CatClan', 'A tabby cat with a red bandana', 'gs://sample-data-and-media/Bengal_100.jpg', '2026-03-02T05:11:28.077494+00:00'),
  ('3fb82b8e-75a1-49fd-8691-a9dabb42bc4b', 'Charlie_11', 'Dog', 'DogClan', 'A police german shepherd with a badge', 'gs://sample-data-and-media/staffordshire_bull_terrier_116.jpg', '2026-03-02T05:11:28.077507+00:00'),
  ('e37b6dcf-7ccb-47d0-8b9d-0da2fa30ad09', 'Felix_12', 'Cat', 'CatClan', 'A cyber-punk cat with neon glasses', 'gs://sample-data-and-media/Bengal_105.jpg', '2026-03-02T05:11:28.077516+00:00'),
  ('0b395a7b-0673-4348-afd0-7cea9252629f', 'Bella_13', 'Dog', 'DogClan', 'A police german shepherd with a badge', 'gs://sample-data-and-media/yorkshire_terrier_101.jpg', '2026-03-02T05:11:28.077527+00:00'),
  ('64921a63-bea6-4a5c-9e49-7a817678c94f', 'Charlie_14', 'Dog', 'DogClan', 'A tough bulldog with a spiked collar', 'gs://sample-data-and-media/yorkshire_terrier_101.jpg', '2026-03-02T05:11:28.077537+00:00'),
  ('0d9040df-34a3-4e54-b660-a85e3c60a6fe', 'Felix_15', 'Cat', 'CatClan', 'A fluffy persian cat with a golden collar', 'gs://sample-data-and-media/Abyssinian_114.jpg', '2026-03-02T05:11:28.077546+00:00'),
  ('188c23a6-4c3b-4c25-9b40-9ec8ad7712a3', 'Max_16', 'Dog', 'DogClan', 'A fast greyhound wearing a racing vest', 'gs://sample-data-and-media/wheaten_terrier_102.jpg', '2026-03-02T05:11:28.077556+00:00'),
  ('a2eaefc9-dbff-4704-b908-74518d687e17', 'Rocky_17', 'Dog', 'DogClan', 'A tough bulldog with a spiked collar', 'gs://sample-data-and-media/shiba_inu_105.jpg', '2026-03-02T05:11:28.077565+00:00'),
  ('b59d9b9a-a169-43c1-832d-7e7d4acfa19c', 'Felix_18', 'Cat', 'CatClan', 'A sneaky black cat hiding in the shadows', 'gs://sample-data-and-media/Abyssinian_1.jpg', '2026-03-02T05:11:28.077581+00:00'),
  ('7019b91a-d908-4c93-8ed2-d1c60e518630', 'Nala_19', 'Cat', 'CatClan', 'A royal siamese cat wearing a crown', 'gs://sample-data-and-media/Abyssinian_1.jpg', '2026-03-02T05:11:28.077595+00:00'),
  ('1a972a71-a530-407a-b3f7-1dd9b2532cec', 'Luna_20', 'Cat', 'CatClan', 'A sneaky black cat hiding in the shadows', 'gs://sample-data-and-media/Bengal_105.jpg', '2026-03-02T05:11:28.077604+00:00'),
  ('3bd0489d-3f43-428d-be2d-0434f0e04ed8', 'Luna_21', 'Cat', 'CatClan', 'A cyber-punk cat with neon glasses', 'gs://sample-data-and-media/Bombay_104.jpg', '2026-03-02T05:11:28.077613+00:00'),
  ('28d7ab21-7ca7-435b-bdc4-5266a381ef89', 'Whiskers_22', 'Cat', 'CatClan', 'A fluffy persian cat with a golden collar', 'gs://sample-data-and-media/Bombay_104.jpg', '2026-03-02T05:11:28.077623+00:00'),
  ('87d880d4-c949-40e3-8d76-9307b45d57fe', 'Rocky_23', 'Dog', 'DogClan', 'A robot dog with metal plating', 'gs://sample-data-and-media/wheaten_terrier_102.jpg', '2026-03-02T05:11:28.077632+00:00'),
  ('b49a4523-83ff-4f59-8fca-54356928a18b', 'Nala_24', 'Cat', 'CatClan', 'A tabby cat with a red bandana', 'gs://sample-data-and-media/Bengal_105.jpg', '2026-03-02T05:11:28.077641+00:00'),
  ('1e049026-1231-4763-bc50-82cb51950fa2', 'Nala_25', 'Cat', 'CatClan', 'A fluffy persian cat with a golden collar', 'gs://sample-data-and-media/Abyssinian_1.jpg', '2026-03-02T05:11:28.077650+00:00'),
  ('e83caccd-e81e-454a-bf92-9d9a5a509e25', 'Simba_26', 'Cat', 'CatClan', 'A royal siamese cat wearing a crown', 'gs://sample-data-and-media/Bengal_105.jpg', '2026-03-02T05:11:28.077659+00:00'),
  ('45650b49-9701-4415-92a9-79073243d198', 'Simba_27', 'Cat', 'CatClan', 'A royal siamese cat wearing a crown', 'gs://sample-data-and-media/Bombay_104.jpg', '2026-03-02T05:11:28.077668+00:00'),
  ('2eb95b36-c9c3-4720-849b-fc240c9434da', 'Bella_28', 'Dog', 'DogClan', 'A robot dog with metal plating', 'gs://sample-data-and-media/samoyed_97.jpg', '2026-03-02T05:11:28.077677+00:00'),
  ('491943d2-8aa3-4484-9d6d-afcab7ec579a', 'Buddy_29', 'Dog', 'DogClan', 'A robot dog with metal plating', 'gs://sample-data-and-media/wheaten_terrier_102.jpg', '2026-03-02T05:11:28.077687+00:00'),
  ('004ac8b2-a37d-42c8-aba3-35b204f596f0', 'Max_30', 'Dog', 'DogClan', 'A police german shepherd with a badge', 'gs://sample-data-and-media/wheaten_terrier_102.jpg', '2026-03-02T05:11:28.077697+00:00'),
  ('5cf1a55e-7904-4937-a4bd-bf3d1fc1c839', 'Whiskers_31', 'Cat', 'CatClan', 'A royal siamese cat wearing a crown', 'gs://sample-data-and-media/Bengal_100.jpg', '2026-03-02T05:11:28.077706+00:00'),
  ('4736fc20-1c22-49c2-af87-c35802302507', 'Luna_32', 'Cat', 'CatClan', 'A fluffy persian cat with a golden collar', 'gs://sample-data-and-media/Bengal_100.jpg', '2026-03-02T05:11:28.077715+00:00'),
  ('d98fc7ff-dd92-4723-994c-6267ef951bcc', 'Buddy_33', 'Dog', 'DogClan', 'A police german shepherd with a badge', 'gs://sample-data-and-media/staffordshire_bull_terrier_116.jpg', '2026-03-02T05:11:28.077797+00:00'),
  ('3de80488-e1b6-4908-a6ec-9c51f46f43b9', 'Luna_34', 'Cat', 'CatClan', 'A sneaky black cat hiding in the shadows', 'gs://sample-data-and-media/Bombay_104.jpg', '2026-03-02T05:11:28.077821+00:00'),
  ('710128e0-4e1d-479c-acbc-497bbc5bc802', 'Bella_35', 'Dog', 'DogClan', 'A tough bulldog with a spiked collar', 'gs://sample-data-and-media/scottish_terrier_108.jpg', '2026-03-02T05:11:28.077836+00:00'),
  ('7e5d416f-f42c-410e-8e2a-19be0cdfc1e5', 'Simba_36', 'Cat', 'CatClan', 'A royal siamese cat wearing a crown', 'gs://sample-data-and-media/Abyssinian_114.jpg', '2026-03-02T05:11:28.077850+00:00'),
  ('b5af580c-4998-4f68-b52f-5c5b6a9d0aab', 'Buddy_37', 'Dog', 'DogClan', 'A robot dog with metal plating', 'gs://sample-data-and-media/scottish_terrier_108.jpg', '2026-03-02T05:11:28.077864+00:00'),
  ('145cc805-810a-4320-864d-ba6b5c6fbc33', 'Max_38', 'Dog', 'DogClan', 'A tough bulldog with a spiked collar', 'gs://sample-data-and-media/staffordshire_bull_terrier_116.jpg', '2026-03-02T05:11:28.077884+00:00'),
  ('34fa84c8-3356-4ed6-9ac5-967cd2baabac', 'Whiskers_39', 'Cat', 'CatClan', 'A royal siamese cat wearing a crown', 'gs://sample-data-and-media/Bengal_105.jpg', '2026-03-02T05:11:28.077894+00:00'),
  ('a50c967b-2e89-448d-be47-4df628c51572', 'Luna_40', 'Cat', 'CatClan', 'A royal siamese cat wearing a crown', 'gs://sample-data-and-media/Bengal_105.jpg', '2026-03-02T05:11:28.077906+00:00'),
  ('64aeeb22-42db-46bf-85bd-b21b135c9803', 'Simba_41', 'Cat', 'CatClan', 'A cyber-punk cat with neon glasses', 'gs://sample-data-and-media/Bombay_104.jpg', '2026-03-02T05:11:28.077915+00:00'),
  ('dec825d6-91f4-4f8f-b44b-74cf6b4b78f6', 'Felix_42', 'Cat', 'CatClan', 'A sneaky black cat hiding in the shadows', 'gs://sample-data-and-media/Bengal_100.jpg', '2026-03-02T05:11:28.077924+00:00'),
  ('d9380e8d-8949-4849-af57-7a91a1a2b953', 'Bella_43', 'Dog', 'DogClan', 'A police german shepherd with a badge', 'gs://sample-data-and-media/staffordshire_bull_terrier_116.jpg', '2026-03-02T05:11:28.077933+00:00'),
  ('88a425a0-b499-4825-8a16-3d33b85feec9', 'Whiskers_44', 'Cat', 'CatClan', 'A fluffy persian cat with a golden collar', 'gs://sample-data-and-media/Abyssinian_114.jpg', '2026-03-02T05:11:28.077942+00:00'),
  ('e17ae312-37c6-4a66-9172-2d20d8528033', 'Simba_45', 'Cat', 'CatClan', 'A cyber-punk cat with neon glasses', 'gs://sample-data-and-media/Abyssinian_1.jpg', '2026-03-02T05:11:28.077958+00:00'),
  ('ae82282e-d380-4500-99e0-2dc4e276c0cf', 'Nala_46', 'Cat', 'CatClan', 'A cyber-punk cat with neon glasses', 'gs://sample-data-and-media/Bombay_104.jpg', '2026-03-02T05:11:28.077967+00:00'),
  ('9ce13d41-dede-4658-a7e4-7bc00372d65c', 'Simba_47', 'Cat', 'CatClan', 'A cyber-punk cat with neon glasses', 'gs://sample-data-and-media/Bengal_105.jpg', '2026-03-02T05:11:28.077976+00:00'),
  ('8db26b5c-2c09-4578-89bf-f9afaf765e36', 'Whiskers_48', 'Cat', 'CatClan', 'A fluffy persian cat with a golden collar', 'gs://sample-data-and-media/Bengal_100.jpg', '2026-03-02T05:11:28.077989+00:00'),
  ('eb113965-6ee6-459e-ba0f-fb6cb1d0ae34', 'Luna_49', 'Cat', 'CatClan', 'A tabby cat with a red bandana', 'gs://sample-data-and-media/Bombay_104.jpg', '2026-03-02T05:11:28.078002+00:00'),
  ('3f064471-24a0-47cd-8927-925cb3e5df7f', 'Felix_50', 'Cat', 'CatClan', 'A tabby cat with a red bandana', 'gs://sample-data-and-media/Bengal_100.jpg', '2026-03-02T05:11:28.078012+00:00'),
  ('ed20f879-2d42-4ba7-8df7-d696c4b6aafd', 'Whiskers_51', 'Cat', 'CatClan', 'A sneaky black cat hiding in the shadows', 'gs://sample-data-and-media/Bengal_105.jpg', '2026-03-02T05:11:28.078021+00:00'),
  ('7e9bbec4-e2aa-4d67-b1c0-35f7db1d0dae', 'Buddy_52', 'Dog', 'DogClan', 'A fast greyhound wearing a racing vest', 'gs://sample-data-and-media/yorkshire_terrier_101.jpg', '2026-03-02T05:11:28.078030+00:00'),
  ('398de7e0-8f4f-44ba-adfe-503a157cfe7c', 'Rocky_53', 'Dog', 'DogClan', 'A fast greyhound wearing a racing vest', 'gs://sample-data-and-media/staffordshire_bull_terrier_116.jpg', '2026-03-02T05:11:28.078040+00:00'),
  ('0f2948c8-f5ba-4546-bdba-567a27b6b4f0', 'Bella_54', 'Dog', 'DogClan', 'A loyal golden retriever with a happy smile', 'gs://sample-data-and-media/wheaten_terrier_102.jpg', '2026-03-02T05:11:28.078049+00:00'),
  ('0b1e7a03-2922-4d53-8871-290520e6bb76', 'Max_55', 'Dog', 'DogClan', 'A fast greyhound wearing a racing vest', 'gs://sample-data-and-media/wheaten_terrier_102.jpg', '2026-03-02T05:11:28.078059+00:00'),
  ('d0ad6342-88fd-443f-82ba-919fc1d652d0', 'Luna_56', 'Cat', 'CatClan', 'A cyber-punk cat with neon glasses', 'gs://sample-data-and-media/Abyssinian_1.jpg', '2026-03-02T05:11:28.078068+00:00'),
  ('73e9a7c4-09e6-46d8-a093-b241d7d1d5df', 'Charlie_57', 'Dog', 'DogClan', 'A loyal golden retriever with a happy smile', 'gs://sample-data-and-media/wheaten_terrier_102.jpg', '2026-03-02T05:11:28.078081+00:00'),
  ('55a1207d-a029-48da-a79d-c1f3f6824a37', 'Buddy_58', 'Dog', 'DogClan', 'A tough bulldog with a spiked collar', 'gs://sample-data-and-media/wheaten_terrier_102.jpg', '2026-03-02T05:11:28.078090+00:00'),
  ('61dd4370-bff0-4d09-be31-19f19c4dad5d', 'Max_59', 'Dog', 'DogClan', 'A tough bulldog with a spiked collar', 'gs://sample-data-and-media/wheaten_terrier_102.jpg', '2026-03-02T05:11:28.078099+00:00'),
  ('4e9dfce6-555b-434a-81b6-237c61b9b530', 'Merry_Cat_0', 'Cat', 'RobinHoods', 'A sneaky rebel cat wearing a green tunic and a feathered cap', 'gs://sample-data-and-media/Bombay_104.jpg', '2026-03-02T05:11:28.078112+00:00'),
  ('686337b0-304e-4270-89c3-d015f9039294', 'Merry_Cat_1', 'Cat', 'RobinHoods', 'A sneaky rebel cat wearing a green tunic and a feathered cap', 'gs://sample-data-and-media/Abyssinian_114.jpg', '2026-03-02T05:11:28.078165+00:00'),
  ('1627bc18-c42e-4599-b5f1-6f3d52669edb', 'Merry_Cat_2', 'Cat', 'RobinHoods', 'A sneaky rebel cat wearing a green tunic and a feathered cap', 'gs://sample-data-and-media/Bengal_100.jpg', '2026-03-02T05:11:28.078212+00:00'),
  ('215b3d04-402a-4ac2-83ed-1edb9a421691', 'Merry_Cat_3', 'Cat', 'RobinHoods', 'A sneaky rebel cat wearing a green tunic and a feathered cap', 'gs://sample-data-and-media/Bengal_105.jpg', '2026-03-02T05:11:28.078258+00:00'),
  ('78d66ff4-0519-4157-9d95-76c2900ba7f9', 'Merry_Cat_4', 'Cat', 'RobinHoods', 'A sneaky rebel cat wearing a green tunic and a feathered cap', 'gs://sample-data-and-media/Abyssinian_114.jpg', '2026-03-02T05:11:28.078301+00:00'),
  ('822a8aae-57bd-460e-9643-69815990bec8', 'Merry_Cat_5', 'Cat', 'RobinHoods', 'A sneaky rebel cat wearing a green tunic and a feathered cap', 'gs://sample-data-and-media/Bombay_104.jpg', '2026-03-02T05:11:28.078349+00:00'),
  ('9f223b65-41a3-495e-940a-5a07d2ba4ba7', 'Merry_Cat_6', 'Cat', 'RobinHoods', 'A sneaky rebel cat wearing a green tunic and a feathered cap', 'gs://sample-data-and-media/Abyssinian_114.jpg', '2026-03-02T05:11:28.078390+00:00'),
  ('3910b199-caf7-4822-8346-1ba9bd750c8e', 'Merry_Cat_7', 'Cat', 'RobinHoods', 'A sneaky rebel cat wearing a green tunic and a feathered cap', 'gs://sample-data-and-media/Bengal_105.jpg', '2026-03-02T05:11:28.078427+00:00'),
  ('78c129b6-21e5-40c6-b9cf-d25ad5193e68', 'Merry_Cat_8', 'Cat', 'RobinHoods', 'A sneaky rebel cat wearing a green tunic and a feathered cap', 'gs://sample-data-and-media/Bengal_100.jpg', '2026-03-02T05:11:28.078463+00:00'),
  ('eba84e9d-bd10-466e-8fcd-899c0a868149', 'Merry_Cat_9', 'Cat', 'RobinHoods', 'A sneaky rebel cat wearing a green tunic and a feathered cap', 'gs://sample-data-and-media/Bombay_104.jpg', '2026-03-02T05:11:28.078508+00:00'),
  ('37a1e15c-a38c-4763-a2bd-042741bce012', 'Merry_Cat_10', 'Cat', 'RobinHoods', 'A sneaky rebel cat wearing a green tunic and a feathered cap', 'gs://sample-data-and-media/Bombay_104.jpg', '2026-03-02T05:11:28.078544+00:00'),
  ('c5337857-3b58-4b0c-8814-4585dcbf765f', 'Merry_Cat_11', 'Cat', 'RobinHoods', 'A sneaky rebel cat wearing a green tunic and a feathered cap', 'gs://sample-data-and-media/Bombay_104.jpg', '2026-03-02T05:11:28.078587+00:00');

-- Table: Transactions
INSERT INTO Transactions (
  TransactionId,
  SenderId,
  ReceiverId,
  Amount,
  Timestamp,
  IsSuspicious
) VALUES
  ('83086ce9-1813-40c7-8e60-624662e7dff8', '0f2948c8-f5ba-4546-bdba-567a27b6b4f0', '4e9dfce6-555b-434a-81b6-237c61b9b530', 13481, '2026-03-02T05:11:28.078136+00:00', TRUE),
  ('8c8f38a8-424f-4752-b662-78800e04b137', '4e9dfce6-555b-434a-81b6-237c61b9b530', 'dc8cf07a-ac0f-48da-9f64-4f379492b1e7', 7327, '2026-03-02T05:11:28.078145+00:00', TRUE),
  ('e4b88c5e-ad32-4fa7-87d7-7e7e70ab133a', '3fb82b8e-75a1-49fd-8691-a9dabb42bc4b', '686337b0-304e-4270-89c3-d015f9039294', 11283, '2026-03-02T05:11:28.078182+00:00', TRUE),
  ('8fe11946-c0ef-4b84-a259-11850955a3ea', '686337b0-304e-4270-89c3-d015f9039294', 'dc8cf07a-ac0f-48da-9f64-4f379492b1e7', 8181, '2026-03-02T05:11:28.078191+00:00', TRUE),
  ('c2d024eb-9131-47ce-84c0-3404e5a01db0', '145cc805-810a-4320-864d-ba6b5c6fbc33', '1627bc18-c42e-4599-b5f1-6f3d52669edb', 11086, '2026-03-02T05:11:28.078228+00:00', TRUE),
  ('7a51d50f-63ac-4406-b4df-2d6fd862977f', '1627bc18-c42e-4599-b5f1-6f3d52669edb', 'dc8cf07a-ac0f-48da-9f64-4f379492b1e7', 9443, '2026-03-02T05:11:28.078237+00:00', TRUE),
  ('edc980d0-539e-4951-9eaf-4ba98b88b40c', '2eb95b36-c9c3-4720-849b-fc240c9434da', '215b3d04-402a-4ac2-83ed-1edb9a421691', 10438, '2026-03-02T05:11:28.078274+00:00', TRUE),
  ('0e98eb5f-a942-4bb3-931a-1de1bdbb2e03', '215b3d04-402a-4ac2-83ed-1edb9a421691', 'dc8cf07a-ac0f-48da-9f64-4f379492b1e7', 7612, '2026-03-02T05:11:28.078286+00:00', TRUE),
  ('13cf3599-f18a-47a5-8b7d-71f9eda250ab', 'ca288a07-2bf8-46fa-a121-9bd0d0f44c64', '78d66ff4-0519-4157-9d95-76c2900ba7f9', 14301, '2026-03-02T05:11:28.078318+00:00', TRUE),
  ('db7051ef-aa4b-47fa-a54e-54ff03dbabf1', '78d66ff4-0519-4157-9d95-76c2900ba7f9', 'dc8cf07a-ac0f-48da-9f64-4f379492b1e7', 10294, '2026-03-02T05:11:28.078330+00:00', TRUE),
  ('9080d8a1-def2-4b95-bc9f-56c25ec9c3ba', 'e82df4fb-0b6d-44dc-8609-70b41430af38', '822a8aae-57bd-460e-9643-69815990bec8', 9613, '2026-03-02T05:11:28.078365+00:00', TRUE),
  ('06593b48-2546-4a52-a078-cf4ddfaed856', '822a8aae-57bd-460e-9643-69815990bec8', 'dc8cf07a-ac0f-48da-9f64-4f379492b1e7', 9787, '2026-03-02T05:11:28.078376+00:00', TRUE),
  ('d540b1d5-5e20-4252-985c-275b82fdad80', '491943d2-8aa3-4484-9d6d-afcab7ec579a', '9f223b65-41a3-495e-940a-5a07d2ba4ba7', 11403, '2026-03-02T05:11:28.078406+00:00', TRUE),
  ('6ba654b3-4c04-48ed-9975-1aae3f557a38', '9f223b65-41a3-495e-940a-5a07d2ba4ba7', 'dc8cf07a-ac0f-48da-9f64-4f379492b1e7', 13564, '2026-03-02T05:11:28.078413+00:00', TRUE),
  ('da73004f-a9e6-4078-af54-4dc7a697a0e4', '710128e0-4e1d-479c-acbc-497bbc5bc802', '3910b199-caf7-4822-8346-1ba9bd750c8e', 10088, '2026-03-02T05:11:28.078442+00:00', TRUE),
  ('ac25cfd6-1c64-483a-8b36-5fe4c6c36e36', '3910b199-caf7-4822-8346-1ba9bd750c8e', 'dc8cf07a-ac0f-48da-9f64-4f379492b1e7', 11354, '2026-03-02T05:11:28.078450+00:00', TRUE),
  ('3f09bdb0-5831-44f8-b293-98cbdb953c9d', 'd98fc7ff-dd92-4723-994c-6267ef951bcc', '78c129b6-21e5-40c6-b9cf-d25ad5193e68', 12426, '2026-03-02T05:11:28.078479+00:00', TRUE),
  ('65803100-7b84-4ff5-a273-b54fe48d5ad2', '78c129b6-21e5-40c6-b9cf-d25ad5193e68', 'dc8cf07a-ac0f-48da-9f64-4f379492b1e7', 13858, '2026-03-02T05:11:28.078490+00:00', TRUE),
  ('7caeab6c-eb5c-4284-9857-87ab6ba744d1', '398de7e0-8f4f-44ba-adfe-503a157cfe7c', 'eba84e9d-bd10-466e-8fcd-899c0a868149', 14851, '2026-03-02T05:11:28.078523+00:00', TRUE),
  ('441b31cd-1c7b-4385-a5da-490a6c98d58d', 'eba84e9d-bd10-466e-8fcd-899c0a868149', 'dc8cf07a-ac0f-48da-9f64-4f379492b1e7', 12481, '2026-03-02T05:11:28.078530+00:00', TRUE),
  ('ea509bae-75a0-4878-b73c-0688efd2808e', 'd9380e8d-8949-4849-af57-7a91a1a2b953', '37a1e15c-a38c-4763-a2bd-042741bce012', 8042, '2026-03-02T05:11:28.078564+00:00', TRUE),
  ('7ac7d043-2744-4689-835a-20b21dca962b', '37a1e15c-a38c-4763-a2bd-042741bce012', 'dc8cf07a-ac0f-48da-9f64-4f379492b1e7', 11248, '2026-03-02T05:11:28.078572+00:00', TRUE),
  ('1fdfc9a6-af31-4151-a96e-6df93e8fafff', '3fb82b8e-75a1-49fd-8691-a9dabb42bc4b', 'c5337857-3b58-4b0c-8814-4585dcbf765f', 11357, '2026-03-02T05:11:28.078603+00:00', TRUE),
  ('3408e82d-61c5-49e1-a037-b8e25422d9ca', 'c5337857-3b58-4b0c-8814-4585dcbf765f', 'dc8cf07a-ac0f-48da-9f64-4f379492b1e7', 13411, '2026-03-02T05:11:28.078612+00:00', TRUE),
  ('a63fa5df-9d00-44e4-bd00-3d993c737a99', '82383e2d-d3a2-481d-b0cf-bfe165ed9bfd', '28d7ab21-7ca7-435b-bdc4-5266a381ef89', 312, '2026-03-02T05:11:28.078658+00:00', FALSE),
  ('26b8b704-7b50-4ce5-894f-452741649286', 'e17ae312-37c6-4a66-9172-2d20d8528033', '7b2881f0-289b-4ea4-9c0e-c1748249b70a', 52, '2026-03-02T05:11:28.078679+00:00', FALSE),
  ('9d8197de-888c-42ce-8bcf-ef0fe6fccc39', '82383e2d-d3a2-481d-b0cf-bfe165ed9bfd', '188c23a6-4c3b-4c25-9b40-9ec8ad7712a3', 65, '2026-03-02T05:11:28.078700+00:00', FALSE),
  ('b0fd1afe-871a-4afc-be00-5c203b147a90', 'eb113965-6ee6-459e-ba0f-fb6cb1d0ae34', '61dd4370-bff0-4d09-be31-19f19c4dad5d', 292, '2026-03-02T05:11:28.078715+00:00', FALSE),
  ('b7be0c34-2d44-4d48-8cef-ddb74dd11260', 'ea3afac7-54f0-4f68-8ed5-a5b6bd386c59', '45650b49-9701-4415-92a9-79073243d198', 199, '2026-03-02T05:11:28.078730+00:00', FALSE),
  ('0baea611-d24a-43d6-be24-49286f4b80bc', 'c5337857-3b58-4b0c-8814-4585dcbf765f', 'e17ae312-37c6-4a66-9172-2d20d8528033', 313, '2026-03-02T05:11:28.078739+00:00', FALSE),
  ('936234c3-3d96-4649-8679-cdc7a35c7c14', '28d7ab21-7ca7-435b-bdc4-5266a381ef89', 'e83caccd-e81e-454a-bf92-9d9a5a509e25', 306, '2026-03-02T05:11:28.078748+00:00', FALSE),
  ('f29c2881-9ce1-47e3-8934-be21250d807b', '55a1207d-a029-48da-a79d-c1f3f6824a37', '1e049026-1231-4763-bc50-82cb51950fa2', 356, '2026-03-02T05:11:28.078757+00:00', FALSE),
  ('aea90ceb-8669-48b2-ad20-903fa2592cc4', '78c129b6-21e5-40c6-b9cf-d25ad5193e68', 'ca288a07-2bf8-46fa-a121-9bd0d0f44c64', 320, '2026-03-02T05:11:28.078766+00:00', FALSE),
  ('e5cb67d4-7fb5-4788-b705-e4b156846cf1', '37a1e15c-a38c-4763-a2bd-042741bce012', '45650b49-9701-4415-92a9-79073243d198', 96, '2026-03-02T05:11:28.078780+00:00', FALSE),
  ('1484d14a-4ece-4c60-8760-aca02d8912d3', 'b49a4523-83ff-4f59-8fca-54356928a18b', '4e9dfce6-555b-434a-81b6-237c61b9b530', 286, '2026-03-02T05:11:28.078797+00:00', FALSE),
  ('55bfca86-c16e-4d83-a3be-4a9339b5ca90', '7e9bbec4-e2aa-4d67-b1c0-35f7db1d0dae', 'e82df4fb-0b6d-44dc-8609-70b41430af38', 94, '2026-03-02T05:11:28.078812+00:00', FALSE),
  ('626b175d-7954-4b48-bfc3-47e1759eb62e', '4e9dfce6-555b-434a-81b6-237c61b9b530', '2eb95b36-c9c3-4720-849b-fc240c9434da', 364, '2026-03-02T05:11:28.078826+00:00', FALSE),
  ('657b64cd-eb82-47f7-af15-c485f09e4c6a', 'dec825d6-91f4-4f8f-b44b-74cf6b4b78f6', '9ce13d41-dede-4658-a7e4-7bc00372d65c', 180, '2026-03-02T05:11:28.078835+00:00', FALSE),
  ('45a3d118-9ada-400f-8007-f90f6573012f', 'f3687206-405e-43b6-afb0-8ca73eee5dd1', 'c5337857-3b58-4b0c-8814-4585dcbf765f', 21, '2026-03-02T05:11:28.078844+00:00', FALSE),
  ('bad0c577-9063-4315-a923-609b55354aec', '28d7ab21-7ca7-435b-bdc4-5266a381ef89', '0f2948c8-f5ba-4546-bdba-567a27b6b4f0', 96, '2026-03-02T05:11:28.078852+00:00', FALSE),
  ('f3f3c44c-29e5-4356-bcdb-34fceead7277', '4e9dfce6-555b-434a-81b6-237c61b9b530', '45650b49-9701-4415-92a9-79073243d198', 206, '2026-03-02T05:11:28.078863+00:00', FALSE),
  ('89e9f697-6cfe-4a11-ada1-2846a9a0e815', '7b2881f0-289b-4ea4-9c0e-c1748249b70a', '1627bc18-c42e-4599-b5f1-6f3d52669edb', 62, '2026-03-02T05:11:28.078878+00:00', FALSE),
  ('2d980b9e-ec93-4d4c-98b1-4f9440489e0e', '28d7ab21-7ca7-435b-bdc4-5266a381ef89', 'e17ae312-37c6-4a66-9172-2d20d8528033', 379, '2026-03-02T05:11:28.078894+00:00', FALSE),
  ('1eabdf25-5b41-4773-8870-bb3e71ad320a', '0b395a7b-0673-4348-afd0-7cea9252629f', '7b2881f0-289b-4ea4-9c0e-c1748249b70a', 10, '2026-03-02T05:11:28.078911+00:00', FALSE),
  ('eeb9524c-5aa7-4c5a-a8b6-b96fea0c0502', '1a972a71-a530-407a-b3f7-1dd9b2532cec', '78d66ff4-0519-4157-9d95-76c2900ba7f9', 200, '2026-03-02T05:11:28.079050+00:00', FALSE),
  ('2c38f9e6-97fe-477f-8ceb-a6e29880c926', '188c23a6-4c3b-4c25-9b40-9ec8ad7712a3', '0f2948c8-f5ba-4546-bdba-567a27b6b4f0', 197, '2026-03-02T05:11:28.079063+00:00', FALSE),
  ('a85ab466-5c6d-4863-b5fd-ec5418a52534', 'a50c967b-2e89-448d-be47-4df628c51572', '9f223b65-41a3-495e-940a-5a07d2ba4ba7', 215, '2026-03-02T05:11:28.079079+00:00', FALSE),
  ('b273c634-1b47-492e-9651-d32e54bdcbb8', 'ae82282e-d380-4500-99e0-2dc4e276c0cf', '491943d2-8aa3-4484-9d6d-afcab7ec579a', 298, '2026-03-02T05:11:28.079088+00:00', FALSE),
  ('93956d3c-c44b-4624-87d8-ac139b1310d0', 'dec825d6-91f4-4f8f-b44b-74cf6b4b78f6', '2eb95b36-c9c3-4720-849b-fc240c9434da', 495, '2026-03-02T05:11:28.079096+00:00', FALSE),
  ('1d827b0f-710e-4af6-8492-4e8753c11584', '153f4022-a4ce-404a-8544-25d004fd34ad', '9ce13d41-dede-4658-a7e4-7bc00372d65c', 242, '2026-03-02T05:11:28.079107+00:00', FALSE),
  ('226c5063-77e1-4888-90f1-a1f23cfb7461', '004ac8b2-a37d-42c8-aba3-35b204f596f0', 'c5337857-3b58-4b0c-8814-4585dcbf765f', 63, '2026-03-02T05:11:28.079115+00:00', FALSE),
  ('11584808-fc90-4f7f-bbb0-d9b444bf09b9', '3de80488-e1b6-4908-a6ec-9c51f46f43b9', 'a50c967b-2e89-448d-be47-4df628c51572', 385, '2026-03-02T05:11:28.079124+00:00', FALSE),
  ('69ac1396-8377-4e44-9257-d14eafdd8c3d', 'b59d9b9a-a169-43c1-832d-7e7d4acfa19c', '4e9dfce6-555b-434a-81b6-237c61b9b530', 331, '2026-03-02T05:11:28.079133+00:00', FALSE),
  ('c0400153-b737-4c54-8ae3-c6958c481aa5', '4e9dfce6-555b-434a-81b6-237c61b9b530', 'f3687206-405e-43b6-afb0-8ca73eee5dd1', 254, '2026-03-02T05:11:28.079142+00:00', FALSE),
  ('80ca0f0e-6a9d-446a-adeb-16a4388120f4', '755c7aff-e538-4681-9b90-4b870a42ac72', '0b1e7a03-2922-4d53-8871-290520e6bb76', 183, '2026-03-02T05:11:28.079150+00:00', FALSE),
  ('289f79a4-5743-4577-9880-85648f4e4c17', '8db26b5c-2c09-4578-89bf-f9afaf765e36', '1a972a71-a530-407a-b3f7-1dd9b2532cec', 344, '2026-03-02T05:11:28.079159+00:00', FALSE),
  ('fcea8d5f-c180-480d-83eb-45bd0801e1f3', 'a50c967b-2e89-448d-be47-4df628c51572', '78d66ff4-0519-4157-9d95-76c2900ba7f9', 416, '2026-03-02T05:11:28.079167+00:00', FALSE),
  ('a142f26e-c281-44d7-b7f2-e023a2362f56', '8a034e84-26b3-4198-8ec9-3749b1f60537', 'a2eaefc9-dbff-4704-b908-74518d687e17', 168, '2026-03-02T05:11:28.079176+00:00', FALSE),
  ('ad62fcc0-2bb3-430c-9dda-dd309e346f59', '0f2948c8-f5ba-4546-bdba-567a27b6b4f0', 'e83caccd-e81e-454a-bf92-9d9a5a509e25', 18, '2026-03-02T05:11:28.079185+00:00', FALSE),
  ('2ba99e26-8967-4cc0-b024-4545ea3220d9', '61dd4370-bff0-4d09-be31-19f19c4dad5d', 'dec825d6-91f4-4f8f-b44b-74cf6b4b78f6', 489, '2026-03-02T05:11:28.079194+00:00', FALSE),
  ('7c8c664b-5491-47f2-bd93-c5ad2a263e87', 'b5af580c-4998-4f68-b52f-5c5b6a9d0aab', '7e9bbec4-e2aa-4d67-b1c0-35f7db1d0dae', 175, '2026-03-02T05:11:28.079202+00:00', FALSE),
  ('3e5b5fae-26c5-44ff-97c0-e1b0624e208d', '7019b91a-d908-4c93-8ed2-d1c60e518630', '9ce13d41-dede-4658-a7e4-7bc00372d65c', 272, '2026-03-02T05:11:28.079211+00:00', FALSE),
  ('6995eaea-b5f3-4291-a1e4-68450d25b19b', 'd98fc7ff-dd92-4723-994c-6267ef951bcc', '88a425a0-b499-4825-8a16-3d33b85feec9', 186, '2026-03-02T05:11:28.079219+00:00', FALSE),
  ('9c50c700-e887-4336-b092-d5e37120d304', 'f37d558b-fd0a-404c-a193-bc3a8a2edfba', '3de80488-e1b6-4908-a6ec-9c51f46f43b9', 15, '2026-03-02T05:11:28.079232+00:00', FALSE),
  ('9e27bc69-bb96-4392-8e2c-a911db3e9dcb', 'e37b6dcf-7ccb-47d0-8b9d-0da2fa30ad09', 'd9380e8d-8949-4849-af57-7a91a1a2b953', 81, '2026-03-02T05:11:28.079241+00:00', FALSE),
  ('ba31c88c-49ec-4934-bc99-f036aa1e3cb5', '0d9040df-34a3-4e54-b660-a85e3c60a6fe', 'f37d558b-fd0a-404c-a193-bc3a8a2edfba', 208, '2026-03-02T05:11:28.079259+00:00', FALSE),
  ('93e0c429-0788-492a-935a-4674a4cf1522', '4736fc20-1c22-49c2-af87-c35802302507', '5cf1a55e-7904-4937-a4bd-bf3d1fc1c839', 244, '2026-03-02T05:11:28.079268+00:00', FALSE),
  ('9f001cbb-a6fb-4192-a0ae-892219b99444', '4736fc20-1c22-49c2-af87-c35802302507', 'eba84e9d-bd10-466e-8fcd-899c0a868149', 239, '2026-03-02T05:11:28.079277+00:00', FALSE),
  ('0ee4d029-3905-49ab-98cb-c7e5ffcd08bc', 'c5337857-3b58-4b0c-8814-4585dcbf765f', 'f37d558b-fd0a-404c-a193-bc3a8a2edfba', 204, '2026-03-02T05:11:28.079290+00:00', FALSE),
  ('e39956dd-af1f-4cc9-8831-cabbfbf5bec6', '61dd4370-bff0-4d09-be31-19f19c4dad5d', '398de7e0-8f4f-44ba-adfe-503a157cfe7c', 129, '2026-03-02T05:11:28.079310+00:00', FALSE),
  ('2404c2d3-4738-40f3-a169-9af84c909a79', '1e049026-1231-4763-bc50-82cb51950fa2', '87d880d4-c949-40e3-8d76-9307b45d57fe', 14, '2026-03-02T05:11:28.079319+00:00', FALSE),
  ('c9ba7281-5b78-4fe2-ad7c-105fafaad0b4', '8db26b5c-2c09-4578-89bf-f9afaf765e36', '82383e2d-d3a2-481d-b0cf-bfe165ed9bfd', 232, '2026-03-02T05:11:28.079327+00:00', FALSE),
  ('b848f820-a6d9-4f2b-b7e1-13ddfd887fe1', '61dd4370-bff0-4d09-be31-19f19c4dad5d', 'dec825d6-91f4-4f8f-b44b-74cf6b4b78f6', 426, '2026-03-02T05:11:28.079336+00:00', FALSE),
  ('db409655-050a-41e1-be6b-52c9d792deb2', '1a972a71-a530-407a-b3f7-1dd9b2532cec', 'eba84e9d-bd10-466e-8fcd-899c0a868149', 448, '2026-03-02T05:11:28.079344+00:00', FALSE),
  ('79811268-69cf-4542-8258-ad795155964c', '73e9a7c4-09e6-46d8-a093-b241d7d1d5df', '4e9dfce6-555b-434a-81b6-237c61b9b530', 244, '2026-03-02T05:11:28.079353+00:00', FALSE),
  ('71b40f64-aef1-4a83-a021-3118c6404475', 'd0ad6342-88fd-443f-82ba-919fc1d652d0', '9ce13d41-dede-4658-a7e4-7bc00372d65c', 223, '2026-03-02T05:11:28.079361+00:00', FALSE),
  ('06b9f40d-2988-446f-9eaf-7222198b7c52', '0b395a7b-0673-4348-afd0-7cea9252629f', '37a1e15c-a38c-4763-a2bd-042741bce012', 290, '2026-03-02T05:11:28.079374+00:00', FALSE),
  ('d3a2bd8f-5796-48bd-82bb-1c94f89b24a4', '0b1e7a03-2922-4d53-8871-290520e6bb76', 'b5af580c-4998-4f68-b52f-5c5b6a9d0aab', 411, '2026-03-02T05:11:28.079385+00:00', FALSE),
  ('1b8d50ce-4083-4b0b-b12d-b94529d200f3', '0b395a7b-0673-4348-afd0-7cea9252629f', '9f223b65-41a3-495e-940a-5a07d2ba4ba7', 237, '2026-03-02T05:11:28.079393+00:00', FALSE),
  ('d6ed7dff-b106-42cf-99c7-4f15bf114b79', 'e82df4fb-0b6d-44dc-8609-70b41430af38', '215b3d04-402a-4ac2-83ed-1edb9a421691', 205, '2026-03-02T05:11:28.079402+00:00', FALSE),
  ('de837bd6-5b12-47a3-ac05-c8fa4ac02ca3', '78c129b6-21e5-40c6-b9cf-d25ad5193e68', '73e9a7c4-09e6-46d8-a093-b241d7d1d5df', 251, '2026-03-02T05:11:28.079411+00:00', FALSE),
  ('56080f4e-a404-4340-b119-8f82a1f2d6d0', '3fb82b8e-75a1-49fd-8691-a9dabb42bc4b', '755c7aff-e538-4681-9b90-4b870a42ac72', 334, '2026-03-02T05:11:28.079419+00:00', FALSE),
  ('db94e731-6ed8-42a4-a62d-2227814c95f7', '78d66ff4-0519-4157-9d95-76c2900ba7f9', '87d880d4-c949-40e3-8d76-9307b45d57fe', 477, '2026-03-02T05:11:28.079428+00:00', FALSE),
  ('cf051085-4625-44aa-bf03-e4529f1324d8', '3de80488-e1b6-4908-a6ec-9c51f46f43b9', '34fa84c8-3356-4ed6-9ac5-967cd2baabac', 285, '2026-03-02T05:11:28.079441+00:00', FALSE),
  ('137f933b-40a1-441d-b547-d296bc977244', '82383e2d-d3a2-481d-b0cf-bfe165ed9bfd', '822a8aae-57bd-460e-9643-69815990bec8', 34, '2026-03-02T05:11:28.079449+00:00', FALSE),
  ('164295cd-bb80-4c24-bbfa-29b582aa8e0f', '3f064471-24a0-47cd-8927-925cb3e5df7f', 'b59d9b9a-a169-43c1-832d-7e7d4acfa19c', 311, '2026-03-02T05:11:28.079458+00:00', FALSE),
  ('2b3a7e6b-7474-439e-b387-baa708683ca8', 'e83caccd-e81e-454a-bf92-9d9a5a509e25', '755c7aff-e538-4681-9b90-4b870a42ac72', 432, '2026-03-02T05:11:28.079466+00:00', FALSE),
  ('fcecd45c-f950-4704-9405-8ff6cc34f3fc', 'ea3afac7-54f0-4f68-8ed5-a5b6bd386c59', 'b5af580c-4998-4f68-b52f-5c5b6a9d0aab', 368, '2026-03-02T05:11:28.079474+00:00', FALSE),
  ('c2d81a86-0c03-4495-a1e8-702e1754f424', '2eb95b36-c9c3-4720-849b-fc240c9434da', '34fa84c8-3356-4ed6-9ac5-967cd2baabac', 353, '2026-03-02T05:11:28.079483+00:00', FALSE),
  ('462f5078-6df6-4f57-843e-47d0b51bc7ea', '8a034e84-26b3-4198-8ec9-3749b1f60537', '1a972a71-a530-407a-b3f7-1dd9b2532cec', 173, '2026-03-02T05:11:28.079496+00:00', FALSE),
  ('059a2a27-e019-4f5f-8e24-8208898c723f', '4e9dfce6-555b-434a-81b6-237c61b9b530', '5cf1a55e-7904-4937-a4bd-bf3d1fc1c839', 411, '2026-03-02T05:11:28.079507+00:00', FALSE),
  ('8ab52f88-d38c-4c60-b9ca-c2d08a337a33', '64921a63-bea6-4a5c-9e49-7a817678c94f', '5cf1a55e-7904-4937-a4bd-bf3d1fc1c839', 457, '2026-03-02T05:11:28.079516+00:00', FALSE),
  ('117ff05e-21d2-48ab-a3c8-29e61658c822', 'c5337857-3b58-4b0c-8814-4585dcbf765f', '7b2881f0-289b-4ea4-9c0e-c1748249b70a', 142, '2026-03-02T05:11:28.079525+00:00', FALSE),
  ('34e5ea80-59b4-4cb0-a8c1-552e2ba6ecc5', 'eb113965-6ee6-459e-ba0f-fb6cb1d0ae34', '3910b199-caf7-4822-8346-1ba9bd750c8e', 142, '2026-03-02T05:11:28.079533+00:00', FALSE),
  ('db1cfbb1-8555-492e-b6c9-45f8040c469b', '0f2948c8-f5ba-4546-bdba-567a27b6b4f0', 'ae82282e-d380-4500-99e0-2dc4e276c0cf', 478, '2026-03-02T05:11:28.079542+00:00', FALSE),
  ('370f50b3-e558-447e-bfbe-fe4eca7e9628', '9ce13d41-dede-4658-a7e4-7bc00372d65c', '3910b199-caf7-4822-8346-1ba9bd750c8e', 72, '2026-03-02T05:11:28.079550+00:00', FALSE),
  ('d08c71a3-bfde-4f95-895a-dc6fa810250f', 'b59d9b9a-a169-43c1-832d-7e7d4acfa19c', '822a8aae-57bd-460e-9643-69815990bec8', 330, '2026-03-02T05:11:28.079558+00:00', FALSE),
  ('81d6bb50-9127-4e2d-acd5-ecaaa797fcb1', '1a972a71-a530-407a-b3f7-1dd9b2532cec', '82383e2d-d3a2-481d-b0cf-bfe165ed9bfd', 149, '2026-03-02T05:11:28.079567+00:00', FALSE),
  ('6ac1ba71-9852-4f0c-97b2-0bb166057ef0', '3de80488-e1b6-4908-a6ec-9c51f46f43b9', '2eb95b36-c9c3-4720-849b-fc240c9434da', 479, '2026-03-02T05:11:28.079575+00:00', FALSE),
  ('9125a495-66f2-435b-8eab-8a2557f55820', '7b2881f0-289b-4ea4-9c0e-c1748249b70a', '9f223b65-41a3-495e-940a-5a07d2ba4ba7', 220, '2026-03-02T05:11:28.079670+00:00', FALSE),
  ('e11b19c9-6bf7-45e2-9831-bb42050b7e8e', '78c129b6-21e5-40c6-b9cf-d25ad5193e68', '4e9dfce6-555b-434a-81b6-237c61b9b530', 380, '2026-03-02T05:11:28.079687+00:00', FALSE),
  ('09b6649c-99a3-48c3-864b-9cbd3d57980a', '7e9bbec4-e2aa-4d67-b1c0-35f7db1d0dae', 'ed20f879-2d42-4ba7-8df7-d696c4b6aafd', 317, '2026-03-02T05:11:28.079696+00:00', FALSE),
  ('68940de9-65d3-4afb-b080-0354b5c6b1a5', '153f4022-a4ce-404a-8544-25d004fd34ad', '82383e2d-d3a2-481d-b0cf-bfe165ed9bfd', 284, '2026-03-02T05:11:28.079710+00:00', FALSE),
  ('050b1905-c72a-446d-81f7-087cddb24434', '1a972a71-a530-407a-b3f7-1dd9b2532cec', 'e17ae312-37c6-4a66-9172-2d20d8528033', 156, '2026-03-02T05:11:28.079870+00:00', FALSE),
  ('7d1bbcaf-69eb-4acc-855d-3174d659a430', '188c23a6-4c3b-4c25-9b40-9ec8ad7712a3', '755c7aff-e538-4681-9b90-4b870a42ac72', 210, '2026-03-02T05:11:28.079923+00:00', FALSE),
  ('07fb83e9-5818-4991-aeba-54f65239954e', 'e83caccd-e81e-454a-bf92-9d9a5a509e25', '3de80488-e1b6-4908-a6ec-9c51f46f43b9', 291, '2026-03-02T05:11:28.079938+00:00', FALSE),
  ('a8a3e69b-392d-4d59-a016-183152eda94a', '64aeeb22-42db-46bf-85bd-b21b135c9803', '8a034e84-26b3-4198-8ec9-3749b1f60537', 261, '2026-03-02T05:11:28.079948+00:00', FALSE),
  ('dcdbd81b-9c64-42cb-9960-4f10b13675ac', '398de7e0-8f4f-44ba-adfe-503a157cfe7c', 'a50c967b-2e89-448d-be47-4df628c51572', 104, '2026-03-02T05:11:28.079958+00:00', FALSE),
  ('df5490e1-cb3f-4109-be18-2aa10a52d848', '491943d2-8aa3-4484-9d6d-afcab7ec579a', '7019b91a-d908-4c93-8ed2-d1c60e518630', 302, '2026-03-02T05:11:28.079967+00:00', FALSE),
  ('801607a9-a4f7-424d-b80f-915094a6f389', '3de80488-e1b6-4908-a6ec-9c51f46f43b9', '55a1207d-a029-48da-a79d-c1f3f6824a37', 129, '2026-03-02T05:11:28.079979+00:00', FALSE),
  ('80851b7f-a1b5-4eb5-a54e-2c3c55e9dd2a', 'a50c967b-2e89-448d-be47-4df628c51572', '710128e0-4e1d-479c-acbc-497bbc5bc802', 450, '2026-03-02T05:11:28.079999+00:00', FALSE),
  ('b1b728aa-177f-4b2f-a5ff-0267898ff6b1', '145cc805-810a-4320-864d-ba6b5c6fbc33', '78c129b6-21e5-40c6-b9cf-d25ad5193e68', 490, '2026-03-02T05:11:28.080011+00:00', FALSE),
  ('bc2e3265-7349-4ef4-a47d-9cd004d8baa4', 'a50c967b-2e89-448d-be47-4df628c51572', '5cf1a55e-7904-4937-a4bd-bf3d1fc1c839', 82, '2026-03-02T05:11:28.080021+00:00', FALSE),
  ('1b51395e-1dc0-4201-9596-34f3dbac4a14', 'eb113965-6ee6-459e-ba0f-fb6cb1d0ae34', '1e049026-1231-4763-bc50-82cb51950fa2', 175, '2026-03-02T05:11:28.080032+00:00', FALSE),
  ('cb319fb3-2707-4712-a042-b58a51d5407a', 'a2eaefc9-dbff-4704-b908-74518d687e17', '188c23a6-4c3b-4c25-9b40-9ec8ad7712a3', 20, '2026-03-02T05:11:28.080041+00:00', FALSE),
  ('5339f7f9-fd7e-4dc5-861b-98121e3fd696', '2eb95b36-c9c3-4720-849b-fc240c9434da', 'd9380e8d-8949-4849-af57-7a91a1a2b953', 339, '2026-03-02T05:11:28.080050+00:00', FALSE),
  ('ae4424b0-27d2-43d3-89d7-a1d8c49f5ee0', '37a1e15c-a38c-4763-a2bd-042741bce012', 'a50c967b-2e89-448d-be47-4df628c51572', 342, '2026-03-02T05:11:28.080059+00:00', FALSE),
  ('92c39e1d-45a3-41c9-9583-cfcaca15c4a3', '1a972a71-a530-407a-b3f7-1dd9b2532cec', 'a50c967b-2e89-448d-be47-4df628c51572', 484, '2026-03-02T05:11:28.080067+00:00', FALSE),
  ('a7cf23d8-b178-4a65-ba03-3ece7b259d51', 'dec825d6-91f4-4f8f-b44b-74cf6b4b78f6', '4736fc20-1c22-49c2-af87-c35802302507', 400, '2026-03-02T05:11:28.080076+00:00', FALSE),
  ('1a1981a8-b63a-4a73-9b8a-ff517286745d', 'ed20f879-2d42-4ba7-8df7-d696c4b6aafd', '8a034e84-26b3-4198-8ec9-3749b1f60537', 72, '2026-03-02T05:11:28.080087+00:00', FALSE),
  ('473dbb0e-652c-43b3-b571-f88c1af1e8c5', '7e9bbec4-e2aa-4d67-b1c0-35f7db1d0dae', '5cf1a55e-7904-4937-a4bd-bf3d1fc1c839', 146, '2026-03-02T05:11:28.080095+00:00', FALSE),
  ('26ebb626-b5a4-4a23-b411-9428219bc8ae', 'b5af580c-4998-4f68-b52f-5c5b6a9d0aab', '2eb95b36-c9c3-4720-849b-fc240c9434da', 261, '2026-03-02T05:11:28.080104+00:00', FALSE);

-- Table: AccountSignals
-- This is pushed by BigQuery through a continuous query if it is configured
INSERT INTO AccountSignals (SignalId, PlayerId, AlertType, EventTime) VALUES ('50b64a6a-2e8f-4a0b-9742-c7e180949e82', '4e9dfce6-555b-434a-81b6-237c61b9b530', 'SUSPICIOUS_MOVEMENT', '2026-03-02T05:11:28.078156+00:00');
INSERT INTO AccountSignals (SignalId, PlayerId, AlertType, EventTime) VALUES ('d2659e80-bce0-46b0-9570-6bb8b3c99d34', '686337b0-304e-4270-89c3-d015f9039294', 'SUSPICIOUS_MOVEMENT', '2026-03-02T05:11:28.078198+00:00');
INSERT INTO AccountSignals (SignalId, PlayerId, AlertType, EventTime) VALUES ('10504018-b7a4-47a4-89b2-950fa492bbd4', '1627bc18-c42e-4599-b5f1-6f3d52669edb', 'SUSPICIOUS_MOVEMENT', '2026-03-02T05:11:28.078244+00:00');
INSERT INTO AccountSignals (SignalId, PlayerId, AlertType, EventTime) VALUES ('ccbba78a-0f45-49b9-a58b-21777de250cf', '215b3d04-402a-4ac2-83ed-1edb9a421691', 'SUSPICIOUS_MOVEMENT', '2026-03-02T05:11:28.078293+00:00');
INSERT INTO AccountSignals (SignalId, PlayerId, AlertType, EventTime) VALUES ('affa841d-0f9a-4b0f-ad6d-eb3e180263fe', '78d66ff4-0519-4157-9d95-76c2900ba7f9', 'SUSPICIOUS_MOVEMENT', '2026-03-02T05:11:28.078337+00:00');
INSERT INTO AccountSignals (SignalId, PlayerId, AlertType, EventTime) VALUES ('1fbdd097-b431-4a21-9a5c-a1f53db6d754', '822a8aae-57bd-460e-9643-69815990bec8', 'SUSPICIOUS_MOVEMENT', '2026-03-02T05:11:28.078383+00:00');
INSERT INTO AccountSignals (SignalId, PlayerId, AlertType, EventTime) VALUES ('0fc87891-dd4b-494b-8c47-f6ccc2c592c7', '9f223b65-41a3-495e-940a-5a07d2ba4ba7', 'SUSPICIOUS_MOVEMENT', '2026-03-02T05:11:28.078420+00:00');
INSERT INTO AccountSignals (SignalId, PlayerId, AlertType, EventTime) VALUES ('cc117869-7a6b-4e66-89bf-e3148ac8c6ea', '3910b199-caf7-4822-8346-1ba9bd750c8e', 'SUSPICIOUS_MOVEMENT', '2026-03-02T05:11:28.078456+00:00');
INSERT INTO AccountSignals (SignalId, PlayerId, AlertType, EventTime) VALUES ('c85a78c6-3cc8-4262-8fd2-2fb9661a1b96', '78c129b6-21e5-40c6-b9cf-d25ad5193e68', 'SUSPICIOUS_MOVEMENT', '2026-03-02T05:11:28.078499+00:00');
INSERT INTO AccountSignals (SignalId, PlayerId, AlertType, EventTime) VALUES ('ccdb20f8-cd05-42ae-b942-cb41396ec27d', 'eba84e9d-bd10-466e-8fcd-899c0a868149', 'SUSPICIOUS_MOVEMENT', '2026-03-02T05:11:28.078537+00:00');
INSERT INTO AccountSignals (SignalId, PlayerId, AlertType, EventTime) VALUES ('721511f1-ebc4-45dc-adb5-9dafc5426bc3', '37a1e15c-a38c-4763-a2bd-042741bce012', 'SUSPICIOUS_MOVEMENT', '2026-03-02T05:11:28.078579+00:00');
INSERT INTO AccountSignals (SignalId, PlayerId, AlertType, EventTime) VALUES ('4d8b0f0d-211a-4537-8c79-c2fd815812f3', 'c5337857-3b58-4b0c-8814-4585dcbf765f', 'SUSPICIOUS_MOVEMENT', '2026-03-02T05:11:28.078627+00:00');

L'operazione potrebbe richiedere alcuni minuti. Dovresti essere in grado di visualizzare l'anteprima dei dati al termine dell'operazione.

Anteprima dei dati da Spanner Studio

4. The Watchdog (query continue di BigQuery e sincronizzazione Spanner)

La nostra prima linea di difesa è lo streaming dei dati di telemetria in BigQuery. Vogliamo monitorare i movimenti sospetti (ad es. distanze impossibili) e inviare un avviso a Spanner in tempo reale.

In uno scenario reale, utilizzeresti le query continue di BigQuery e l'ETL inverso per trasmettere questi dati in streaming. Tuttavia, ciò richiede una prenotazione con la versione Enterprise o successive.

Ecco come apparirebbe il comando se la prenotazione fosse disponibile. Non devi copiarlo nella console se non hai configurato le prenotazioni:

EXPORT DATA
  OPTIONS (
    uri = 'https://spanner.googleapis.com/projects/<YOUR_PROJECT_ID>/instances/game-instance/databases/game-db',
    format='CLOUD_SPANNER',
    spanner_options="""{ "table": "AccountSignals" }"""
  ) AS
SELECT
  GENERATE_UUID() as SignalId,
  PlayerId,
  'SUSPICIOUS_MOVEMENT' as AlertType,
  CURRENT_TIMESTAMP() as EventTime
FROM `game_analytics.GameplayTelemetry`
WHERE
  EventType = 'player_move'
  AND (LocationX > 1000 OR LocationY > 1000);

Per creare la query continua, fai clic su Altro > Crea query continua nell'area di lavoro SQL della console BigQuery.

Questa query funge da motore ETL inverso, garantendo che il nostro sistema transazionale (Spanner) sia immediatamente a conoscenza delle anomalie rilevate nel nostro sistema analitico (BigQuery).

Per questo lab, abbiamo inserito artificialmente alcune transazioni in Spanner.

5. Il detective multimodale (Spanner Graph e ricerca vettoriale)

Ora che Spanner ha il segnale "Rischio elevato", puoi indagare sull'organizzazione fraudolenta. Utilizzeremo Spanner Graph per visualizzare la rete finanziaria e trovare il capo.

Esegui queste query in Spanner Studio

Grafico: trova il responsabile

Questa query traccia la rete finanziaria di transazioni in cui le vittime trasferiscono denaro a un ladro, che a sua volta lo trasferisce a un nodo principale. Raggruppa per boss e somma il bottino.

Copialo in Spanner Studio e fai clic su Esegui.

GRAPH PlayerNetwork
MATCH (victim)-[:Transfers]->(thief)-[t:Transfers]->(boss)
RETURN
  boss.Name AS RingLeader, COUNT(t) AS TributesReceived,
  SUM(t.Amount) AS TotalLoot
GROUP BY RingLeader
ORDER BY TotalLoot DESC
LIMIT 5;

Dovresti vedere "Pixel" come il destinatario principale degli omaggi.

Indagine multi-indicatore

Uniamo i risultati del grafico ai segnali comportamentali in tempo reale che abbiamo inviato in precedenza da BigQuery. Vogliamo trovare i giocatori che inviano denaro a "Pixel" E che sono stati segnalati per movimenti sospetti.

SELECT DISTINCT
  p.Name,
  s.AlertType as BQ_Signal,
  s.EventTime as SignalTime
FROM GRAPH_TABLE (
  PlayerNetwork
  MATCH (associate:Players)-[:Transfers]->(boss:Players)
  WHERE boss.Name = 'Pixel'
  RETURN DISTINCT associate.Name
) as g
JOIN Players p
  ON p.Name = g.Name
JOIN AccountSignals s
  ON p.PlayerId = s.PlayerId
ORDER BY s.EventTime DESC;

Vector Search: identifica gli account bot

Si tratta di giocatori reali o di una rete di bot coordinata? Utilizza la ricerca vettoriale per identificare gli account con descrizioni del profilo sospettosamente simili a "Pixel".

SELECT
  Name, AvatarDescription,
  COSINE_DISTANCE(AvatarEmbedding, (SELECT AvatarEmbedding FROM Players WHERE Name = 'Pixel')) as Similarity
FROM Players
WHERE Name != 'Pixel'
ORDER BY Similarity ASC
LIMIT 5;

Un punteggio di similarità più basso significa che sono più vicini al vettore "Pixel". Se hanno descrizioni simili, è probabile che siano bot.

Possiamo anche applicare funzioni scalari nella clausola MATCH:

GRAPH PlayerNetwork
MATCH (associate:Players)-[:Transfers]->(boss:Players)
WHERE boss.Name = 'Pixel'
ORDER BY (
  COSINE_DISTANCE(associate.AvatarEmbedding, (SELECT AvatarEmbedding FROM Players WHERE Name = 'Pixel'))
) ASC
RETURN DISTINCT associate.Name

6. Scoprire la trama (integrazione di BigQuery Property Graph e GCS)

Abbiamo preso il capo della banda, ma dobbiamo capire come ha coordinato questo furto di tonno di massa. Tracciamo i pattern di comunicazione in BigQuery utilizzando BigQuery Property Graph per eseguire query sui log della chat di gioco.

Esegui la seguente query in BigQuery Studio:

BigQuery Property Graph

Tracciamento della comunicazione tra "Pixel" e altri giocatori:

GRAPH game_analytics.CatChatNetwork
MATCH (p1:Players)-[c:Communicates]->(p2:Players)
WHERE p1.Name = 'Pixel' OR p2.Name = 'Pixel'
RETURN
  p1.Name AS Sender,
  p2.Name AS Receiver,
  c.Message,
  -- Resolving structured metadata from ObjectRef
  p1.ProfilePictureUrl.uri AS SenderProfilePic
ORDER BY Message DESC;

Osserva messaggi come "Operazione Acquario in corso" e "Reindirizzamento dei fondi alla riserva centrale di tonno". Puoi vedere come BigQuery Property Graphs ti consente di analizzare le comunicazioni arricchite con dati non strutturati (riferimenti alle immagini GCS utilizzando ProfilePictureUrl.uri).

Se scarichi l'immagine o segui il link GCS autenticato nei risultati, vedrai l'immagine del giocatore:

Immagine del profilo Pixel

Questa query analitica confronta ulteriormente i pattern di chat e le immagini tra i membri dell'organizzazione fraudolenta.

Prima di poter eseguire questa operazione, dichiara un modello multimodale per generare incorporamenti delle immagini del profilo archiviate nel bucket Cloud Storage. Questo modello si connette tramite la connessione creata nella configurazione iniziale, pertanto concederai anche le autorizzazioni utente Vertex AI all'utente tecnico collegato per quella connessione.

Sostituisci <> con l'ID progetto.

GRANT `roles/aiplatform.user`
ON PROJECT `<<PROJECT_ID>>`
TO "connection:<<PROJECT_ID>>.us.unicorn-connection";

Ora puoi creare la connessione.

CREATE OR REPLACE MODEL `game_analytics.multimodal_model`
  REMOTE WITH CONNECTION `us.unicorn-connection`
  OPTIONS (ENDPOINT = 'multimodalembedding@001');

Se l'operazione non va a buon fine a causa di un errore di autorizzazione (ad es. "bqcx-12345745345345@gcp-sa-bigquery-condel.iam.gserviceaccount.com non dispone dell'autorizzazione per accedere o utilizzare l'endpoint..."), attendi qualche minuto affinché le autorizzazioni vengano propagate e riprova.

La query riportata di seguito utilizza la funzione AI.GENERATE_EMBEDDING per esaminare le immagini nel bucket di archiviazione e creare gli embedding. Questi incorporamenti vengono poi confrontati utilizzando una COSINE_DISTANCE, in modo da ottenere una buona comprensione della somiglianza tra i log delle chat e le immagini del profilo.

-- BigQuery Property Graph: Tracing communication patterns in chat logs
-- AND calculating distance between auto-embedded chat message and profile picture
-- BigQuery Property Graph: Tracing communication patterns
-- AND identifying similarity AMONG the fraudsters themselves
WITH GraphResults AS (
  SELECT *
  FROM GRAPH_TABLE(
  game_analytics.CatChatNetwork
   MATCH (p1:Players)-[c:Communicates]->(p2:Players)
   WHERE p1.Name = 'Pixel' OR p2.Name = 'Pixel'
   RETURN
    p1.Name AS Sender,
    c.Message,
    p1.ProfilePictureUrl.uri AS SenderProfilePic,
    c.MessageEmbedding.result AS MessageEmbedding
  )
),
UniquePics AS (
  SELECT DISTINCT SenderProfilePic AS uri FROM GraphResults
),
PicEmbeddings AS (
  SELECT embedding, uri
  FROM AI.GENERATE_EMBEDDING(
    MODEL game_analytics.multimodal_model,
    (
      SELECT OBJ.MAKE_REF(uri, 'us.unicorn-connection') as content, uri
      FROM UniquePics
    )
  )
),
CatData AS (
  -- Distinct list of players (excluding Pixel) with their embeddings and HTTPS Pic URLs
  SELECT DISTINCT
    g.Sender,
    g.MessageEmbedding,
    g.Message,
    p.embedding AS PicEmbedding,
    REPLACE( g.SenderProfilePic, 'gs://sample-data-and-media/spanner-bq-fraud-heist/profile_pics/', 'https://storage.mtls.cloud.google.com/sample-data-and-media/spanner-bq-fraud-heist/profile_pics/') AS SenderProfilePic
  FROM GraphResults g
  LEFT JOIN PicEmbeddings p ON g.SenderProfilePic = p.uri
  WHERE g.Sender != 'Pixel'
    AND g.MessageEmbedding IS NOT NULL
    AND p.embedding IS NOT NULL
)
SELECT
  c1.Sender AS Fraudster_A,
  c2.Sender AS Fraudster_B,
  c1.SenderProfilePic AS Pic_A,
  c2.SenderProfilePic AS Pic_B,
  c1.Message,
  -- Compare chat messages between Fraudster A and B
  COSINE_DISTANCE(c1.MessageEmbedding, c2.MessageEmbedding) AS MessageDistance,
  -- Compare profile pictures between Fraudster A and B
  COSINE_DISTANCE(c1.PicEmbedding, c2.PicEmbedding) AS PictureDistance
FROM CatData c1
CROSS JOIN CatData c2
WHERE c1.Sender < c2.Sender -- Avoid self-comparison and duplicate pairs (A-B and B-A)
  AND c1.SenderProfilePic <> c2.SenderProfilePic
ORDER BY PictureDistance ASC, MessageDistance ASC
LIMIT 10;

Se apri le immagini del profilo, noterai la somiglianza nel modo in cui i membri del clan si presentano.

Visualizzare l'anello di frode

Puoi utilizzare i notebook e Python Cell Magic per visualizzare la frode organizzata. In questo modo, possiamo visualizzare facilmente i risultati del grafico. Per saperne di più, consulta la documentazione relativa alla visualizzazione.

In BigQuery Studio, fai clic su Altro > Blocco note > Blocco note vuoto.

Crea notebook

Incolla il seguente codice in una cella di codice:

!pip install bigquery-magics==0.12.1

Utilizza il pulsante + Codice per creare una nuova cella e incolla quanto segue:

%%bigquery --graph
GRAPH game_analytics.CatChatNetwork
MATCH p=(p1:Players)-[c:Communicates]-(p2:Players)
WHERE p1.Name = 'Pixel' OR p2.Name = 'Pixel'
RETURN TO_JSON(p) AS full_path

Fai clic su Esegui tutto. Dopo circa un minuto, dovresti visualizzare un grafico della rete di comunicazione.

Visualizzazione del grafico

7. Elimina

Per evitare che al tuo account Google Cloud vengano addebitati costi relativi alle risorse utilizzate in questo codelab, elimina le risorse che hai creato.

Elimina l'istanza Spanner

gcloud spanner instances delete game-instance

Elimina il set di dati BigQuery

bq rm -r -f -d game_analytics

In alternativa, elimina il progetto

Se hai creato un nuovo progetto per questo lab, puoi eliminarlo completamente:

gcloud projects delete <YOUR_PROJECT_ID>

8. Complimenti!

Complimenti! Hai creato correttamente uno scudo di difesa dalle frodi in tempo reale utilizzando Spanner e BigQuery.

Hai imparato a:

  • Utilizza le query continue di BigQuery per inviare insight in tempo reale a Spanner.
  • Utilizza Spanner Graph per tracciare le relazioni finanziarie.
  • Utilizza la ricerca vettoriale di Spanner per le query di somiglianza sui dati non strutturati.
  • Utilizza BigQuery Graph per tracciare le reti di comunicazione.

Passaggi successivi