Spanner y BigQuery: Escudo de defensa contra el fraude en tiempo real

1. Introducción

Te damos la bienvenida al backend de Petverse, un juego multijugador en línea en el que los jugadores crean avatares de animales, exploran el mundo y comercian con la moneda del juego.

Recientemente, la economía del juego se vio amenazada. Se están drenando enormes sumas de dinero de las cuentas de los jugadores ricos de Dog, que se convierten por completo en reservas de atún premium. Sospechamos que hay un grupo de "gatos Robin Hood" que les roban a los perros ricos para alimentar a las masas felinas.

En este codelab, compilarás un escudo de defensa contra el fraude en tiempo real para atrapar al cabecilla y a su red de bots automatizados. Experimentarás cómo los datos operativos en Spanner convergen con los análisis en BigQuery para detectar e investigar patrones de fraude complejos con consultas relacionales y de gráficos (GQL).

Actividades

Requisitos

  • Un proyecto de Google Cloud con la facturación habilitada
  • Conocimientos básicos de SQL, comandos de terminal y Python
  • Es posible que necesites una cuenta de GitHub (el código está alojado en GitHub).

Público: Desarrolladores, ingenieros de datos y arquitectos de nivel intermedio.

Duración total estimada: De 45 a 60 minutos

Estimación de costos: Los recursos creados en este codelab deberían costar menos de USD 5.

2. Antes de comenzar / Configuración

Crea o selecciona un proyecto de Google Cloud

Para usar los servicios necesarios para este lab, necesitas un proyecto de Google Cloud con la facturación habilitada.

  1. En la consola de Google Cloud, en la página del selector de proyectos, selecciona o crea un proyecto de Google Cloud.
  2. Confirma que la facturación está habilitada para tu proyecto de Cloud. Obtén más información para verificar si la facturación está habilitada.
  3. Busca el ID de tu proyecto en la página principal de la consola de Cloud.

Página principal de la consola de Cloud

Inicie Cloud Shell

Usarás Google Cloud Shell como tu entorno de ejecución. Cloud Shell viene preinstalado con gcloud, git y otras herramientas que necesitarás.

  1. Navega a Google Cloud Shell.
  2. Si se te solicita, haz clic en Autorizar.
  3. Asegúrate de estar trabajando en tu proyecto configurando la variable de entorno en la terminal de Cloud Shell:
export PROJECT_ID=<YOUR_PROJECT_ID>
gcloud config set project $PROJECT_ID

Cloud Shell: Usa gcloud config para establecer el proyecto

Habilita las APIs necesarias

Ejecuta el siguiente comando para habilitar las APIs de Spanner, BigQuery y Vertex AI:

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

Clona el repositorio

Clona el repositorio que contiene el código de la aplicación y los esquemas de muestra:

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

3. Aprovisione la infraestructura

Ahora configurarás el almacén de datos en BigQuery y la base de datos operativa en Spanner.

Configura el conjunto de datos y la conexión de BigQuery

BigQuery analizará el flujo de telemetría del juego.

Aún en la consola de Cloud Shell, ejecuta los siguientes comandos para asegurarte de que tu ID del proyecto siga configurado:

export PROJECT_ID=<YOUR_PROJECT_ID>
gcloud config set project $PROJECT_ID
  1. Crea un conjunto de datos de game_analytics BigQuery:
bq mk -d --location=US game_analytics
  1. Crea una conexión para conectarte a buckets de Storage y, de manera opcional, a Spanner:
bq mk --connection --location=US --project_id=$PROJECT_ID \
    --connection_type=CLOUD_RESOURCE unicorn-connection
  1. Crea los esquemas para las tablas GameplayTelemetry, AccountSignals, Players y ChatLogs con el archivo de esquema:
bq query --use_legacy_sql=false < bq_schema.sql

Configura Spanner

Google Cloud Spanner controlará las transacciones operativas en tiempo real. Para este lab, usaremos una instancia rentable de 100 unidades de procesamiento (PU).

  1. Crea una instancia de Spanner:
gcloud spanner instances create game-instance \
    --config=regional-us-central1 \
    --description="Game Instance" \
    --processing-units=100 \
    --edition=ENTERPRISE
  1. Crea la base de datos de Spanner game-db:
gcloud spanner databases create game-db --instance=game-instance
  1. Actualiza el esquema de Spanner con las tablas de la aplicación (Players, Transactions, AccountSignals) y el gráfico de propiedades (PlayerNetwork):
gcloud spanner databases ddl update game-db --instance=game-instance --ddl-file=spanner_schema.sql
  1. Crea el AvatarSearchIndex para nuestra búsqueda de vectores multimodal:
gcloud spanner databases ddl update game-db --instance=game-instance \
    --ddl="CREATE SEARCH INDEX AvatarSearchIndex ON Players(AvatarDescriptionTokens)"

Importa datos a BigQuery

  1. Importa los datos de demostración a 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. Navega a la consola de BigQuery y explora los datos en el conjunto de datos game_analytics.

Consola de BigQuery

Importa datos a Spanner

Navega a la consola de Spanner y explora los datos en la base de datos game-db.

Haz clic en Spanner Studio y abre una Nueva consulta (+).

Consola de Spanner

Pega las siguientes instrucciones INSERT en el editor de consultas y haz clic en Ejecutar:

-- 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),
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  ('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),
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  ('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');

Este proceso puede tardar unos minutos en ejecutarse. Deberías poder obtener una vista previa de los datos después de que se complete el proceso.

Vista previa de los datos de Spanner Studio

4. El Watchdog (consultas continuas de BigQuery y sincronización de Spanner)

Nuestra primera línea de defensa son los datos de telemetría que se transmiten a BigQuery. Queremos supervisar los movimientos sospechosos (p.ej., distancias imposibles) y enviar una alerta a Spanner en tiempo real.

En una situación real, usarías consultas continuas de BigQuery y ETL inverso para transmitir estos datos. Sin embargo, esto requiere una reserva con la edición ENTERPRISE o una superior.

Así se vería el comando si la reserva estuviera disponible. No es necesario que copies esto en la consola si no configuraste reservas:

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);

Para crear la consulta continua, haz clic en Más > Crear consulta continua en el espacio de trabajo de SQL de la consola de BigQuery.

Esta consulta actúa como un motor de ETL inverso, lo que garantiza que nuestro sistema transaccional (Spanner) detecte de inmediato las anomalías detectadas en nuestro sistema analítico (BigQuery).

Para este lab, insertamos artificialmente algunas transacciones en Spanner.

5. El detective multimodal (Spanner Graph y Vector Search)

Ahora que Spanner tiene el indicador "Alto riesgo", puedes investigar el anillo de fraude. Usaremos Spanner Graph para visualizar la Web financiera y encontrar al cabecilla.

Ejecuta estas consultas en Spanner Studio

Gráfico: Encuentra al líder

Esta consulta rastrea la red financiera de transacciones en la que las víctimas transfieren dinero a un ladrón, quien luego lo transfiere a un nodo principal. Agrupa por jefe y suma el botín.

Cópiala en Spanner Studio y haz clic en Ejecutar.

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;

Deberías ver "Pixel" como el principal destinatario de los tributos.

Investigación de varios indicadores

Unamos los resultados del gráfico con los indicadores de comportamiento en tiempo real que enviamos desde BigQuery anteriormente. Queremos encontrar a los jugadores que envían dinero a "Pixel" Y que se marcaron por movimientos sospechosos.

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;

Búsqueda de vectores: Identifica cuentas de bots

¿Son jugadores reales o una red coordinada de bots? Usa la búsqueda vectorial para identificar cuentas con descripciones de perfil sospechosamente similares 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;

Una puntuación de similitud más baja significa que están más cerca del vector de "Pixel". Si tienen descripciones similares, es probable que sean bots.

También podemos aplicar funciones escalares en la cláusula 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. Descubrir la trama (integración de BigQuery Property Graph y GCS)

Atrapamos al cabecilla, pero necesitamos entender cómo coordinó este enorme "robo de atún". Haremos un seguimiento de los patrones de comunicación en BigQuery con BigQuery Property Graph para consultar los registros de chat del juego.

Ejecuta la siguiente consulta en BigQuery Studio:

BigQuery Property Graph

Cómo rastrear la comunicación entre "Pixel" y otros jugadores:

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;

Observa mensajes como "La operación Fishbowl está en marcha" y "Desviando fondos a la reserva central de atún". Puedes ver cómo los gráficos de propiedades de BigQuery te permiten analizar comunicaciones enriquecidas con datos no estructurados (referencias de imágenes de GCS con ProfilePictureUrl.uri).

Si sigues el vínculo de GCS en los resultados, verás la imagen del jugador:

Foto de perfil de Pixel

Esta consulta analítica compara aún más los patrones de chat y las imágenes entre los miembros de la red de fraude.

Antes de ejecutar este código, declara un modelo multimodal para generar embeddings de las fotos de perfil almacenadas en el bucket de Cloud Storage. Este modelo se conecta a través de la conexión creada en la configuración inicial, por lo que también otorgarás permisos de usuario de Vertex AI al usuario técnico adjunto para esa conexión.

Reemplaza "PROJECT_ID" por el ID de tu proyecto.

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

Ahora puedes crear la conexión.

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

Si esto falla debido a un error de permiso (es decir,"The bqcx-12345745345345@gcp-sa-bigquery-condel.iam.gserviceaccount.com does not have the permission to access or use the endpoint…"), espera unos minutos hasta que se propaguen los permisos y vuelve a intentarlo.

La siguiente consulta usa la función AI.GENERATE_EMBEDDING para revisar las imágenes del bucket de almacenamiento y crear embeddings. Luego, se comparan estos embeddings con COSINE_DISTANCE para comprender mejor qué tan similares son los registros de chat y las fotos de perfil.

-- 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;

Si abres las fotos de perfil, notarás la similitud en la forma en que se presentan los miembros del clan.

Visualiza el anillo de fraude

Puedes usar notebooks y Cell Magic de Python para visualizar el anillo de fraude. Esto nos permite visualizar fácilmente los resultados del gráfico. Para obtener más información, consulta la documentación sobre visualización.

En BigQuery Studio, haz clic en Más > Notebook > Notebook vacío.

Crear notebook

Pega lo siguiente en una celda de código:

!pip install bigquery-magics==0.12.1

Usa el botón + Código para crear una celda nueva y pega lo siguiente:

%%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

Haz clic en Ejecutar todo. Después de aproximadamente un minuto, deberías ver una visualización gráfica de la red de comunicación.

Visualización de grafos

7. Limpieza

Para evitar que se generen cargos en tu cuenta de Google Cloud por los recursos que usaste en este codelab, borra los recursos que creaste.

Borra la instancia de Spanner

gcloud spanner instances delete game-instance

Borra el conjunto de datos de BigQuery

bq rm -r -f -d game_analytics

Como alternativa, borra el proyecto

Si creaste un proyecto nuevo para este lab, puedes borrarlo por completo:

gcloud projects delete <YOUR_PROJECT_ID>

8. ¡Felicitaciones!

¡Felicitaciones! Creaste correctamente un escudo de defensa contra el fraude en tiempo real con Spanner y BigQuery.

Aprendiste todo esto:

  • Usar consultas continuas de BigQuery para enviar estadísticas en tiempo real a Spanner
  • Usa Spanner Graph para rastrear relaciones financieras.
  • Usa la búsqueda de vectores de Spanner para realizar consultas de similitud en datos no estructurados.
  • Usa BigQuery Graph para rastrear redes de comunicación.

Próximos pasos