Spanner ve BigQuery: Anlık Sahtekarlık Savunma Kalkanı

1. Giriş

Oyuncuların hayvan avatarı oluşturduğu, dünyayı keşfettiği ve oyun içi para birimiyle takas yaptığı çok oyunculu online oyun Petverse'ün arka ucuna hoş geldiniz.

Son zamanlarda oyunun ekonomisi tehdit altında. Zengin köpek oyuncuların hesaplarından büyük miktarlarda para çekiliyor ve bu paralar tamamen premium ton balığı stoklarına dönüştürülüyor. "Robin Hood Kedileri" adlı bir grubun, zengin köpeklerden çalarak kedi kitlelerini beslediğinden şüpheleniyoruz.

Bu codelab'de, elebaşını ve otomatik bot ağını yakalamak için gerçek zamanlı bir sahtekarlık savunma kalkanı oluşturacaksınız. Spanner'daki operasyonel verilerin BigQuery'deki analizlerle nasıl birleştiğini deneyimleyerek grafik (GQL) ve ilişkisel sorgularla karmaşık sahtekarlık kalıplarını tespit edip inceleyeceksiniz.

Yapacaklarınız

• BigQuery sürekli sorgularını kullanarak gerçek zamanlı akışta anormallik tespit edin ve Spanner'a aktarın.
• Finansal ilişkileri izlemek için Spanner Graph'ı kullanarak sahtekarlık şebekesini araştırın.
• Benzer profil açıklamalarını bulmak için Spanner vektör aramasını kullanarak bot hesaplarını tespit edin.
• Büyük iletişim günlüklerini analiz etmek için BigQuery Graph'ı kullanarak koordinasyon planını ortaya çıkarın.

İhtiyacınız olanlar

• Faturalandırmanın etkin olduğu bir Google Cloud projesi.
• SQL, terminal komutları ve Python hakkında temel düzeyde bilgi
• GitHub hesabınızın olması gerekebilir (kod, GitHub'da barındırılır).

Kitle: Orta seviye geliştiriciler, veri mühendisleri ve mimarlar.

Tahmini Toplam Süre: 45-60 dakika

Maliyet Tahmini: Bu codelab'de oluşturulan kaynakların maliyeti 5 ABD dolarından az olmalıdır.

2. Başlamadan Önce/Kurulum

Google Cloud projesi oluşturma veya seçme

Bu laboratuvar için gereken hizmetleri kullanmak üzere faturalandırmanın etkin olduğu bir Google Cloud projeniz olmalıdır.

1. Google Cloud Console'da, proje seçici sayfasında bir Google Cloud projesi seçin veya oluşturun.
2. Cloud projeniz için faturalandırmanın etkinleştirildiğinden emin olun. Faturalandırmanın etkin olup olmadığını nasıl doğrulayacağınızı öğrenin.
3. Proje kimliğinizi Cloud Console ana sayfasında bulabilirsiniz.

Cloud Shell'i Başlatma

Yürütme ortamınız olarak Google Cloud Shell'i kullanacaksınız. Cloud Shell'de gcloud, git ve ihtiyacınız olan diğer araçlar önceden yüklenmiştir.

1. Google Cloud Shell'e gidin.
2. İstenirse Yetkilendir'i tıklayın.
3. Cloud Shell terminalinde ortam değişkenini ayarlayarak projenizde çalıştığınızdan emin olun:

<YOUR_PROJECT_ID> ifadesini gerçek proje kimliğinizle değiştirin. Terminalde yapıştırmak için Ctrl veya Command + v tuşlarını kullanın.

export PROJECT_ID=<YOUR_PROJECT_ID>
gcloud config set project $PROJECT_ID

Gerekli API'leri etkinleştirme

Spanner, BigQuery ve Vertex AI API'lerini etkinleştirmek için aşağıdaki komutu çalıştırın:

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

Depoyu klonlama

Uygulama kodunu ve örnek şemaları içeren depoyu klonlayın:

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

3. Altyapı Temini

Şimdi BigQuery'de veri ambarını ve Spanner'da operasyonel veritabanını oluşturacaksınız.

BigQuery veri kümesini ve bağlantısını oluşturma

BigQuery, oyundan gelen telemetri akışını analiz eder.

Google Cloud Shell'deki konsolda, proje kimliğinizin hâlâ ayarlanmış olduğundan emin olmak için aşağıdaki komutları çalıştırın:

<YOUR_PROJECT_ID> ifadesini gerçek proje kimliğinizle değiştirin. Terminalde yapıştırmak için Ctrl veya Command + v tuşlarını kullanın.

export PROJECT_ID=<YOUR_PROJECT_ID>
gcloud config set project $PROJECT_ID

1. game_analytics BigQuery veri kümesi oluşturun:

bq mk -d --location=US game_analytics

2. Storage paketlerine ve (isteğe bağlı olarak) Spanner'a bağlanmak için bir bağlantı oluşturun:

bq mk --connection --location=US --project_id=$PROJECT_ID \
    --connection_type=CLOUD_RESOURCE unicorn-connection

3. Şema dosyasını kullanarak GameplayTelemetry, AccountSignals, Players ve ChatLogs tabloları için şemaları oluşturun:

bq query --use_legacy_sql=false < bq_schema.sql

Spanner'ı ayarlama

Google Cloud Spanner, operasyonel gerçek zamanlı işlemleri yönetir. Bu laboratuvarda, uygun maliyetli 100 işleme birimi (PU) örneği kullanacağız.

1. Spanner örneği oluşturun:

gcloud spanner instances create game-instance \
    --config=regional-us-central1 \
    --description="Game Instance" \
    --processing-units=100 \
    --edition=ENTERPRISE

2. Spanner veritabanını (game-db) oluşturun:

gcloud spanner databases create game-db --instance=game-instance

3. Spanner şemasını uygulama tabloları (Players, Transactions, AccountSignals) ve özellik grafiğiyle (PlayerNetwork) güncelleyin:

gcloud spanner databases ddl update game-db --instance=game-instance --ddl-file=spanner_schema.sql

4. Çok formatlı vektör aramamız için AvatarSearchIndex oluşturun:

gcloud spanner databases ddl update game-db --instance=game-instance \
    --ddl="CREATE SEARCH INDEX AvatarSearchIndex ON Players(AvatarDescriptionTokens)"

BigQuery'ye veri aktarma

1. Demo verilerini BigQuery'ye aktarın:

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

3. BigQuery Console'a gidin ve game_analytics veri kümesindeki verileri inceleyin.

Verileri Spanner'a aktarma

Spanner Console'a gidin ve game-db veritabanındaki verileri inceleyin.

Spanner Studio'yu tıklayın ve Yeni Sorgu (+)'yu açın.

Aşağıdaki INSERT ifadelerini sorgu düzenleyiciye yapıştırın ve Çalıştır'ı tıklayın:

-- 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),
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-- 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');

Bu işlemin çalışması birkaç dakika sürebilir. İşlem tamamlandıktan sonra verileri önizleyebilirsiniz.

4. Watchdog (BigQuery Sürekli Sorguları ve Spanner Senkronizasyonu)

İlk savunma hattımız, BigQuery'ye aktarılan telemetri verileridir. Şüpheli hareketleri (ör. imkansız mesafeler) izlemek ve Spanner'a gerçek zamanlı olarak uyarı göndermek istiyoruz.

Gerçek hayatta bu verileri aktarmak için BigQuery sürekli sorgularını ve ters ETL'yi kullanırsınız. Ancak bunun için ENTERPRISE veya daha yüksek bir sürümle rezervasyon yapılması gerekir.

Rezervasyonun müsait olması durumunda komut bu şekilde görünür. Rezervasyon oluşturmadıysanız bu kodu konsola kopyalamanız gerekmez:

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);

Sürekli sorguyu oluşturmak için BigQuery Console SQL Workspace'te Diğer > Sürekli sorgu oluştur'u tıklayın.

Bu sorgu, ters ETL motoru görevi görerek işlem sistemimizin (Spanner), analiz sistemimizde (BigQuery) algılanan anormalliklerden anında haberdar olmasını sağlar.

Bu laboratuvarda, Spanner'a yapay olarak bazı işlemler ekledik.

5. Çok Modlu Dedektif (Spanner Graph ve Vector Search)

Spanner'da "Yüksek Risk" sinyali olduğuna göre sahtekarlık şebekesini inceleyebilirsiniz. Finansal ağı görselleştirmek ve elebaşını bulmak için Spanner Graph'i kullanacağız.

Bu sorguları Spanner Studio'da çalıştırın.

Grafik: Elebaşını Bulma

Bu sorgu, mağdurların hırsıza, hırsızın da patron düğümüne para aktardığı finansal işlem ağını izler. Boss'a göre gruplandırır ve ganimeti toplar.

Sorguyu Spanner Studio'ya kopyalayıp Run'ı (Çalıştır) tıklayın.

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;

En çok övgü alan cihaz olarak "Pixel"i görmeniz gerekir.

Çoklu Sinyal İncelemesi

Grafik sonuçlarını, daha önce BigQuery'den gönderdiğimiz gerçek zamanlı davranış sinyalleriyle birleştirelim. "Pixel"e para gönderen VE şüpheli hareket nedeniyle işaretlenmiş oyuncuları bulmak istiyoruz.

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;

Vektör arama: Bot hesapları tanımlama

Bunlar gerçek oyuncular mı yoksa koordineli bir bot ağı mı? Profil açıklamaları "Pixel"e şüpheli bir şekilde benzeyen hesapları belirlemek için vektör aramayı kullanın.

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;

Benzerlik puanının düşük olması, "Pixel" vektörüne daha yakın oldukları anlamına gelir. Açıklamaları benzerse muhtemelen botturlar.

MATCH yan tümcesinde skaler işlevler de uygulayabiliriz:

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. Uncovering the Plot (BigQuery Property Graph & GCS Integration)

Elebaşını yakaladık ancak bu devasa "ton balığı soygununu" nasıl koordine ettiğini anlamamız gerekiyor. Oyun sohbet günlüklerini sorgulamak için BigQuery Property Graph'i kullanarak BigQuery'deki iletişim kalıplarını izleyeceğiz.

BigQuery Studio'da aşağıdaki sorguyu çalıştırın:

BigQuery özellik grafiği

"Pixel" ile diğer oyuncular arasındaki iletişimi izleme:

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;

"Akvaryum Operasyonu başlıyor" ve "Fonlar merkezi ton balığı rezervine aktarılıyor" gibi mesajları inceleyin. BigQuery özellik grafiklerinin, yapılandırılmamış verilerle (ProfilePictureUrl.uri kullanan GCS resim referansları) zenginleştirilmiş iletişimleri analiz etmenize nasıl olanak tanıdığını görebilirsiniz.

Sonuçlardaki GCS bağlantısını takip ederseniz oyuncunun resmini görürsünüz:

Bu analitik sorgu, sahtekarlık şebekesi üyeleri arasındaki sohbet kalıplarını ve resimleri de karşılaştırır.

Bu kodu çalıştırmadan önce, Cloud Storage paketinde depolanan profil resimlerinin yerleştirmelerini oluşturmak için çok formatlı bir model tanımlayın. Bu model, ilk kurulumda oluşturulan bağlantı üzerinden bağlanır. Bu nedenle, söz konusu bağlantı için eklenen teknik kullanıcıya Vertex AI kullanıcı izinleri de vermeniz gerekir.

"PROJECT_ID" ifadesini proje kimliğinizle değiştirin.

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

Artık bağlantıyı oluşturabilirsiniz.

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

Bu işlem bir izin hatası nedeniyle başarısız olursa (ör. "[e-mail], uç noktaya erişme veya uç noktayı kullanma iznine sahip değil...") izinler yayılana kadar birkaç dakika bekleyip tekrar deneyin.

Aşağıdaki sorgu, depolama alanı paketindeki resimleri incelemek ve yerleştirmeler oluşturmak için AI.GENERATE_EMBEDDING işlevini kullanır. Bu yerleştirmeler daha sonra COSINE_DISTANCE kullanılarak karşılaştırılır. Böylece sohbet günlüklerinin ve profil resimlerinin ne kadar benzer olduğunu iyi bir şekilde anlayabiliriz.

-- 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;

Profil resimlerini açarsanız klan üyelerinin kendilerini tanıtma şeklindeki benzerliği fark edersiniz.

Sahtekarlık şebekesini görselleştirme

Sahtekarlık şebekesini görselleştirmek için not defterlerini ve Python Cell Magic'i kullanabilirsiniz. Bu sayede grafik sonuçlarını kolayca görselleştirebiliriz. Bu konu hakkında daha fazla bilgi için görselleştirmeyle ilgili belgelere bakın.

BigQuery Studio'da More (Diğer) > Notebook (Not Defteri) > Empty Notebook'u (Boş Not Defteri) tıklayın.

🗒️ Not defterlerini ilk kez kullanıyorsanız bölge seçmeniz istenir. Bu laboratuvarda US kullandığımız için US çoklu bölgesinde bir bölge seçmeniz gerekir. Notebooks API'yi de etkinleştirmeniz gerekebilir.

Aşağıdaki kodu bir kod hücresine yapıştırın:

!pip install bigquery-magics==0.12.1

Yeni bir hücre oluşturmak için + Code (+ Kod) düğmesini kullanın ve aşağıdakileri yapıştırın:

%%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

Run all'u (Tümünü çalıştır) tıklayın. Yaklaşık bir dakika sonra iletişim ağının grafik görselleştirmesini görürsünüz.

7. Temizleme

Bu codelab'de kullanılan kaynaklar için Google Cloud hesabınızdan ücret alınmasını önlemek amacıyla oluşturduğunuz kaynakları silin.

Spanner örneğini silme

gcloud spanner instances delete game-instance

BigQuery veri kümesini silme

bq rm -r -f -d game_analytics

Alternatif olarak projeyi silebilirsiniz.

Bu laboratuvar için yeni bir proje oluşturduysanız projenin tamamını silebilirsiniz:

gcloud projects delete <YOUR_PROJECT_ID>

8. Tebrikler!

Tebrikler! Spanner ve BigQuery'yi kullanarak gerçek zamanlı sahtekarlık savunma kalkanı oluşturma işlemini başarıyla tamamladınız.

Şunları öğrendiniz:

• Gerçek zamanlı analizleri Spanner'a aktarmak için BigQuery sürekli sorgularını kullanın.
• Finansal ilişkileri izlemek için Spanner Graph'ı kullanın.
• Yapılandırılmamış verilerdeki benzerlik sorguları için Spanner vektör aramasını kullanın.
• İletişim ağlarını izlemek için BigQuery Graph'i kullanın.

Sırada ne var?

• Spanner Graph belgelerini inceleyin.
• Spanner Graph GitHub deposunda daha fazla kod örneği bulabilirsiniz.
• BigQuery Graph hakkında daha fazla bilgi edinin.
• BigQuery sürekli sorguları'na göz atın.