Crie agentes inteligentes e seguros com o AlloyDB

1. Introdução

Neste codelab, você vai criar um sistema inteligente de pesquisa e recomendação de sessões de conferência usando o AlloyDB para PostgreSQL e os recursos de IA dele. Você vai aprender a combinar a pesquisa tradicional de palavras-chave com a pesquisa semântica avançada de vetores, usar o QueryData para gerar instruções SQL previsíveis em linguagem natural e utilizar funções de operador inteligentes.

Atividades deste laboratório

• Implante um cluster do AlloyDB e ative os recursos de IA.
• Carregar um conjunto de dados de conferência e entender a estrutura dele.
• Ative a API de acesso aos dados do AlloyDB.
• Use os operadores de IA do AlloyDB, como ai.if e ai.rank, para ações semânticas.
• Implemente a pesquisa híbrida, combinando pesquisas semânticas vetoriais (ScaNN) e de texto (RUM).
• Ativar o QueryData para o AlloyDB
• Gerar modelos de QueryData
• Usar QueryData com agentes de IA

O que é necessário

• Um navegador da web, como o Chrome
• Tenha um projeto do Google Cloud com o faturamento ativado.

Este codelab é destinado a desenvolvedores de todos os níveis, incluindo iniciantes.

Duração total estimada: 60 a 70 minutos. Custo estimado: menos de US $3. Os recursos criados neste codelab estão qualificados para o nível sem custo financeiro padrão ou uso de teste.

2. Configuração e requisitos

Configuração do projeto

Faça login no Console do Google Cloud. Crie uma conta do Gmail ou do Google Workspace, se ainda não tiver uma.

Use uma conta pessoal em vez de uma conta escolar ou de trabalho.

Atenção: as contas escolares e de trabalho podem ter restrições que impedem a ativação das APIs necessárias para este laboratório ou o acesso a alguns recursos.

Criar um projeto do Google Cloud

1. No console do Google Cloud, na página do seletor de projetos, selecione ou crie um projeto na nuvem do Google Cloud.
2. Verifique se o faturamento está ativado para seu projeto do Cloud. Saiba como verificar se o faturamento está ativado em um projeto.

Atenção: o ID do projeto é globalmente exclusivo e não pode ser usado por outras pessoas após a seleção. Você é o único usuário com esse ID. Mesmo que um projeto seja excluído, o ID não poderá ser usado novamente.

Observação: se você usa uma conta do Gmail, defina o local padrão como Sem organização. Se você usa uma conta do Google Workspace, escolha um local adequado para a organização.

Inicie o Cloud Shell

Embora o Google Cloud e o Spanner possam ser operados remotamente do seu laptop, neste codelab usaremos o Google Cloud Shell, um ambiente de linha de comando executado no Cloud.

1. Clique em Ativar o Cloud Shell na parte de cima do console do Google Cloud.
2. Verificar a autenticação:

gcloud auth list

3. Confirme seu projeto:

gcloud config get project

4. Defina se necessário:

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

3. Antes de começar

Ativar APIs

Execute este comando para ativar todas as APIs necessárias:

gcloud services enable alloydb.googleapis.com \
                       compute.googleapis.com \
                       cloudresourcemanager.googleapis.com \
                       servicenetworking.googleapis.com \
                       aiplatform.googleapis.com \
                       geminidataanalytics.googleapis.com

Apresentação das APIs

• A API AlloyDB (alloydb.googleapis.com) permite criar, gerenciar e escalonar clusters do AlloyDB para PostgreSQL. Ele oferece um serviço de banco de dados totalmente gerenciado e compatível com PostgreSQL, projetado para cargas de trabalho empresariais transacionais e analíticas exigentes.
• A API Compute Engine (compute.googleapis.com) permite criar e gerenciar máquinas virtuais (VMs), discos permanentes e configurações de rede. Ela fornece a base principal de infraestrutura como serviço (IaaS) necessária para executar suas cargas de trabalho e hospedar a infraestrutura subjacente de muitos serviços gerenciados.
• A API Resource Manager (cloudresourcemanager.googleapis.com) permite gerenciar de forma programática os metadados e a configuração do seu projeto do Google Cloud. Ele permite organizar recursos, processar políticas de gerenciamento de identidade e acesso (IAM) e validar permissões em toda a hierarquia do projeto.
• A API Service Networking (servicenetworking.googleapis.com) permite automatizar a configuração da conectividade particular entre sua rede de nuvem privada virtual (VPC) e os serviços gerenciados do Google. Ele é especificamente necessário para estabelecer o acesso a IP particular para serviços como o AlloyDB, para que eles possam se comunicar com segurança com seus outros recursos.
• A API Vertex AI (aiplatform.googleapis.com) permite que seus aplicativos criem, implantem e escalonem modelos de machine learning. Ela oferece a interface unificada para todos os serviços de IA do Google Cloud, incluindo acesso a modelos de IA generativa (como o Gemini) e treinamento de modelos personalizados.
• A API Data Analytics (geminidataanalytics.googleapis.com) permite que seu aplicativo use recursos gerais de IA em produtos de BI.

4. Provisionar o AlloyDB

Crie um cluster do AlloyDB e uma instância principal.

Criar intervalo de IP privado

O AlloyDB exige um intervalo de IP privado na sua VPC. Supondo que você esteja usando a rede VPC default:

1. Crie o intervalo de IP privado:

gcloud compute addresses create psa-range \
    --global \
    --purpose=VPC_PEERING \
    --prefix-length=24 \
    --description="VPC private service access" \
    --network=default

2. Estabelecer conexão particular:

gcloud services vpc-peerings connect \
    --service=servicenetworking.googleapis.com \
    --ranges=psa-range \
    --network=default

Criar cluster do AlloyDB

1. Crie uma senha para o usuário postgres:

export PGPASSWORD=`openssl rand -hex 12`
echo $PGPASSWORD

Anote essa senha! Você vai precisar dele para se conectar ao banco de dados mais tarde.

2. Crie um cluster de teste sem custo financeiro ("TRIAL") ou um cluster padrão ("STANDARD") se não for a primeira vez:

Observação:se você não estiver usando o AlloyDB, crie um cluster de teste sem custos financeiros.

export REGION=us-central1
export ADBCLUSTER=alloydb-next26-ai-demo-01

gcloud alloydb clusters create $ADBCLUSTER \
    --password=$PGPASSWORD \
    --network=default \
    --region=$REGION \
    --subscription-type=TRIAL

3. Crie a instância principal:

gcloud alloydb instances create $ADBCLUSTER-pr \
    --instance-type=PRIMARY \
    --cpu-count=8 \
    --region=$REGION \
    --cluster=$ADBCLUSTER

A criação da instância leva de 6 a 10 minutos para ser concluída.

5. Configurar permissões de banco de dados

Ativar as permissões da Vertex AI para geração de incorporações

PROJECT_ID=$(gcloud config get-value project)
gcloud projects add-iam-policy-binding $PROJECT_ID \
  --member="serviceAccount:service-$(gcloud projects describe $PROJECT_ID --format="value(projectNumber)")@gcp-sa-alloydb.iam.gserviceaccount.com" \
  --role="roles/aiplatform.user"

Ativar a API Data Access

É necessário ativar a API Data Access no cluster do AlloyDB para usar contextos QueryData e criar modelos que ajudam a criar instruções SQL previsíveis com base em linguagem natural.

Na mesma guia do terminal, execute:

PROJECT_ID=$(gcloud config get-value project)
REGION=us-central1
ADBCLUSTER=alloydb-next26-ai-demo-01
curl -X PATCH \
 -H "Authorization: Bearer $(gcloud auth print-access-token)" \
 -H "Content-Type: application/json" \
 https://alloydb.googleapis.com/v1alpha/projects/$PROJECT_ID/locations/$REGION/clusters/$ADBCLUSTER/instances/$ADBCLUSTER-pr?updateMask=dataApiAccess \
 -d '{
   "dataApiAccess": "ENABLED",
 }'

Ativar a autenticação do IAM

Para nossas ferramentas de agente, é necessário ativar a autenticação do IAM na instância e se adicionar como usuário.

Ative o IAM na instância executando o seguinte na mesma guia do terminal:

PROJECT_ID=$(gcloud config get-value project)
REGION=us-central1
ADBCLUSTER=alloydb-next26-ai-demo-01
gcloud beta alloydb instances update $ADBCLUSTER-pr \
   --database-flags alloydb.iam_authentication=on \
   --region=$REGION \
   --cluster=$ADBCLUSTER \
   --project=$PROJECT_ID \
   --update-mode=FORCE_APPLY

Adicione você mesmo como usuário do AlloyDB:

REGION=us-central1
ADBCLUSTER=alloydb-next26-ai-demo-01
gcloud alloydb users create $(gcloud config get-value account) \
--cluster=$ADBCLUSTER \
--region=$REGION \
--type=IAM_BASED \
--db-roles=alloydbsuperuser

6. Preparar o banco de dados de amostra

Conectar-se ao AlloyDB Studio

1. Acesse a página AlloyDB para Postgres no console do Google Cloud.
2. Clique na instância principal.
3. Na navegação à esquerda, clique em AlloyDB Studio.
4. Selecione o banco de dados postgres.
5. Autenticar com IAM database authentication

Criar um banco de dados

Execute o seguinte SQL no editor de consultas:

CREATE DATABASE conference_db;

Mude para o banco de dados conference_db fazendo o seguinte:

1. Clique no botão Current user no canto superior esquerdo da tela AlloyDB studio.
2. Clique no botão Switch user/database.
3. Selecione o banco de dados conference_db recém-criado.

Ativar pgvector

Verifique se a extensão padrão vector está ativada:

CREATE EXTENSION IF NOT EXISTS vector;

Carregar dados de amostra

Execute os seguintes scripts SQL para criar o esquema e preenchê-lo com dados de amostra:

1. Limpar tabelas conflitantes anteriores

DROP TABLE IF EXISTS public.attendees_sessions CASCADE;
DROP TABLE IF EXISTS public.session_speaker_mapping CASCADE;
DROP TABLE IF EXISTS public.session_topic_mapping CASCADE;
DROP TABLE IF EXISTS public.session CASCADE;
DROP TABLE IF EXISTS public.attendees CASCADE;
DROP TABLE IF EXISTS public.speaker CASCADE;
DROP TABLE IF EXISTS public.session_topic CASCADE;

2. crie tabelas

CREATE TABLE public.attendees (
    username character varying(100) NOT NULL PRIMARY KEY,
    name character varying(100),
    company character varying(150),
    job_title character varying(100),
    area_of_interest character varying(100),
    street_address text,
    city character varying(100),
    state_province character varying(100),
    country character varying(100),
    created_at timestamp without time zone DEFAULT CURRENT_TIMESTAMP
);

CREATE TABLE public.attendees_sessions (
    username character varying(100) NOT NULL REFERENCES public.attendees(username),
    session_id character varying(50) NOT NULL,
    registration_date timestamp without time zone DEFAULT CURRENT_TIMESTAMP,
    PRIMARY KEY (username, session_id)
);

CREATE TABLE public.session (
    session_id character varying(50) NOT NULL PRIMARY KEY,
    session_name character varying(255) NOT NULL,
    full_description text,
    full_description_embedding vector(768) GENERATED ALWAYS AS (embedding('text-embedding-005', full_description)) STORED,
    description_tsvector tsvector GENERATED ALWAYS AS (to_tsvector('english', full_description)) STORED,
    session_format character varying(50),
    learning_level character varying(50),
    session_url character varying(255),
    for_job_role character varying(250),
    session_date date,
    session_start_time time without time zone,
    session_end_time time without time zone,
    session_location character varying(100),
    capacity integer,
    remaining_capacity integer,
    interest_area character varying(100),
    industry character varying(100)
);

COMMENT ON COLUMN public.session.session_format IS 'The format of a session. Possible values are Keynotes, Breakouts, Lightning Talks.';

CREATE TABLE public.speaker (
    speaker_id integer NOT NULL PRIMARY KEY,
    speaker_name character varying(100) NOT NULL,
    job_title character varying(100),
    company character varying(100),
    type character varying(50),
    profile_pic character varying(100),
    speaker_url character varying(100)
);

CREATE TABLE public.session_speaker_mapping (
    session_id character varying(50) NOT NULL REFERENCES public.session(session_id),
    speaker_id integer NOT NULL REFERENCES public.speaker(speaker_id),
    PRIMARY KEY (session_id, speaker_id)
);

CREATE TABLE public.session_topic (
    topic character varying(100) NOT NULL PRIMARY KEY,
    topic_desc text,
    embedding vector(768) GENERATED ALWAYS AS (embedding('text-embedding-005', topic_desc)) STORED
);

CREATE TABLE public.session_topic_mapping (
    session_id character varying(50) NOT NULL REFERENCES public.session(session_id),
    topic character varying(100) NOT NULL REFERENCES public.session_topic(topic),
    PRIMARY KEY (session_id, topic)
);

3. Preencher tabelas com dados de amostra

3.1 Preencher tópicos da sessão

-- Insert Topics
INSERT INTO public.session_topic (topic, topic_desc) VALUES
('Databases', 'Relational and non-relational database technologies.'),
('AI & Machine Learning', 'Generative AI, LLMs, and ML infrastructure.'),
('Cloud Architecture', 'Designing scalable and resilient cloud systems.'),
('Security', 'Identity, compliance, and network security.'),
('DevOps', 'CI/CD, platform engineering, and automation.') ON CONFLICT DO NOTHING;

3.2 Preencher alto-falantes

-- Insert Speakers
INSERT INTO public.speaker (speaker_id, speaker_name, job_title, company, type, profile_pic, speaker_url) VALUES
(1, 'Speaker 1', 'Director of Engineering', 'DeepMind', 'External', 'pic_1.png', 'http://speakers.com/1'),
(2, 'Speaker 2', 'Cloud Architect', 'Verily', 'External', 'pic_2.png', 'http://speakers.com/2'),
(3, 'Speaker 3', 'Product Manager', 'GlobalEnterprises', 'External', 'pic_3.png', 'http://speakers.com/3'),
(4, 'Speaker 4', 'Tech Lead', 'Google', 'Internal', 'pic_4.png', 'http://speakers.com/4'),
(5, 'Speaker 5', 'Security Engineer', 'DeepMind', 'External', 'pic_5.png', 'http://speakers.com/5'),
(6, 'Speaker 6', 'DevOps Engineer', 'DeepMind', 'External', 'pic_6.png', 'http://speakers.com/6'),
(7, 'Speaker 7', 'Product Manager', 'DataSystems', 'External', 'pic_7.png', 'http://speakers.com/7'),
(8, 'Speaker 8', 'Director of Engineering', 'Google', 'Internal', 'pic_8.png', 'http://speakers.com/8'),
(9, 'Speaker 9', 'Cloud Architect', 'Google', 'Internal', 'pic_9.png', 'http://speakers.com/9'),
(10, 'Speaker 10', 'DevOps Engineer', 'Alphabet', 'Internal', 'pic_10.png', 'http://speakers.com/10'),
(11, 'Speaker 11', 'Tech Lead', 'Alphabet', 'External', 'pic_11.png', 'http://speakers.com/11'),
(12, 'Speaker 12', 'Product Manager', 'Alphabet', 'External', 'pic_12.png', 'http://speakers.com/12'),
(13, 'Speaker 13', 'Tech Lead', 'SoftSolutions', 'Internal', 'pic_13.png', 'http://speakers.com/13'),
(14, 'Speaker 14', 'Director of Engineering', 'Verily', 'Internal', 'pic_14.png', 'http://speakers.com/14'),
(15, 'Speaker 15', 'DevOps Engineer', 'CloudNative', 'External', 'pic_15.png', 'http://speakers.com/15'),
(16, 'Speaker 16', 'Software Engineer', 'Waymo', 'External', 'pic_16.png', 'http://speakers.com/16'),
(17, 'Speaker 17', 'DevOps Engineer', 'Google', 'External', 'pic_17.png', 'http://speakers.com/17'),
(18, 'Speaker 18', 'Data Scientist', 'GlobalEnterprises', 'External', 'pic_18.png', 'http://speakers.com/18'),
(19, 'Speaker 19', 'Security Engineer', 'Waymo', 'Internal', 'pic_19.png', 'http://speakers.com/19'),
(20, 'Speaker 20', 'Tech Lead', 'SoftSolutions', 'Internal', 'pic_20.png', 'http://speakers.com/20') ON CONFLICT (speaker_id) DO NOTHING;

3.3 Preencher participantes

-- Insert Attendees
INSERT INTO public.attendees (username, name, company, job_title, area_of_interest, street_address, city, state_province, country) VALUES
('user_1', 'Attendee 1', 'GlobalEnterprises', 'Data Scientist', 'DevOps', '1 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_2', 'Attendee 2', 'Alphabet', 'Director of Engineering', 'DevOps', '2 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_3', 'Attendee 3', 'CloudNative', 'Data Scientist', 'AI & Machine Learning', '3 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_4', 'Attendee 4', 'SoftSolutions', 'Product Manager', 'DevOps', '4 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_5', 'Attendee 5', 'DataSystems', 'Software Engineer', 'DevOps', '5 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_6', 'Attendee 6', 'Google', 'Director of Engineering', 'Security', '6 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_7', 'Attendee 7', 'Waymo', 'Product Manager', 'AI & Machine Learning', '7 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_8', 'Attendee 8', 'Verily', 'Product Manager', 'DevOps', '8 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_9', 'Attendee 9', 'Waymo', 'Software Engineer', 'DevOps', '9 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_10', 'Attendee 10', 'Waymo', 'DevOps Engineer', 'Databases', '10 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_11', 'Attendee 11', 'GlobalEnterprises', 'Tech Lead', 'Cloud Architecture', '11 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_12', 'Attendee 12', 'Google', 'Tech Lead', 'DevOps', '12 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_13', 'Attendee 13', 'DeepMind', 'Software Engineer', 'Cloud Architecture', '13 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_14', 'Attendee 14', 'DataSystems', 'Security Engineer', 'DevOps', '14 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_15', 'Attendee 15', 'DeepMind', 'Security Engineer', 'Cloud Architecture', '15 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_16', 'Attendee 16', 'Verily', 'Security Engineer', 'Cloud Architecture', '16 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_17', 'Attendee 17', 'Google', 'Software Engineer', 'Cloud Architecture', '17 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_18', 'Attendee 18', 'GlobalEnterprises', 'Security Engineer', 'DevOps', '18 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_19', 'Attendee 19', 'CloudNative', 'Data Scientist', 'Databases', '19 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_20', 'Attendee 20', 'DataSystems', 'Cloud Architect', 'AI & Machine Learning', '20 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_21', 'Attendee 21', 'Google', 'Data Scientist', 'Databases', '21 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_22', 'Attendee 22', 'TechCorp', 'Data Scientist', 'DevOps', '22 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_23', 'Attendee 23', 'DeepMind', 'Product Manager', 'Databases', '23 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_24', 'Attendee 24', 'Google', 'Cloud Architect', 'AI & Machine Learning', '24 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_25', 'Attendee 25', 'GlobalEnterprises', 'Software Engineer', 'AI & Machine Learning', '25 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_26', 'Attendee 26', 'Verily', 'Security Engineer', 'Security', '26 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_27', 'Attendee 27', 'GlobalEnterprises', 'Tech Lead', 'Databases', '27 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_28', 'Attendee 28', 'Google', 'Tech Lead', 'Databases', '28 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_29', 'Attendee 29', 'SoftSolutions', 'Software Engineer', 'Databases', '29 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_30', 'Attendee 30', 'Verily', 'DevOps Engineer', 'Databases', '30 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_31', 'Attendee 31', 'DeepMind', 'Data Scientist', 'Databases', '31 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_32', 'Attendee 32', 'SoftSolutions', 'Software Engineer', 'Cloud Architecture', '32 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_33', 'Attendee 33', 'DeepMind', 'Tech Lead', 'Databases', '33 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_34', 'Attendee 34', 'Alphabet', 'Security Engineer', 'DevOps', '34 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_35', 'Attendee 35', 'TechCorp', 'DevOps Engineer', 'Cloud Architecture', '35 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_36', 'Attendee 36', 'DataSystems', 'Director of Engineering', 'Security', '36 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_37', 'Attendee 37', 'Google', 'Cloud Architect', 'Databases', '37 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_38', 'Attendee 38', 'Google', 'Product Manager', 'Security', '38 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_39', 'Attendee 39', 'SoftSolutions', 'Security Engineer', 'Cloud Architecture', '39 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_40', 'Attendee 40', 'Waymo', 'Director of Engineering', 'Cloud Architecture', '40 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_41', 'Attendee 41', 'SoftSolutions', 'Tech Lead', 'Security', '41 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_42', 'Attendee 42', 'DeepMind', 'Cloud Architect', 'Security', '42 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_43', 'Attendee 43', 'TechCorp', 'Cloud Architect', 'Databases', '43 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_44', 'Attendee 44', 'Alphabet', 'Security Engineer', 'AI & Machine Learning', '44 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_45', 'Attendee 45', 'CloudNative', 'Cloud Architect', 'AI & Machine Learning', '45 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_46', 'Attendee 46', 'CloudNative', 'Data Scientist', 'Security', '46 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_47', 'Attendee 47', 'DeepMind', 'Data Scientist', 'Security', '47 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_48', 'Attendee 48', 'Verily', 'DevOps Engineer', 'AI & Machine Learning', '48 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_49', 'Attendee 49', 'Verily', 'Director of Engineering', 'AI & Machine Learning', '49 Main St', 'CityVille', 'StateName', 'CountryName'),
('user_50', 'Attendee 50', 'Google', 'Director of Engineering', 'DevOps', '50 Main St', 'CityVille', 'StateName', 'CountryName') ON CONFLICT (username) DO NOTHING;

3.4 Preencher sessões

-- Insert Sessions
INSERT INTO public.session (session_id, session_name, full_description, session_format, learning_level, session_url, for_job_role, session_date, session_start_time, session_end_time, session_location, capacity, remaining_capacity, interest_area, industry) VALUES
('S001', 'AlloyDB Deep Dive: Advanced Performance Tuning', 'Learn how to squeeze every drop of performance out of AlloyDB. This session covers index tuning, memory management, and advanced query optimization techniques.', 'Lightning Talks', 'Beginner', 'http://sessions.com/S001', 'Cloud Architect', '2026-04-11', '15:00:00', '15:00:00', 'Room C', 500, 192, 'Databases', 'Technology'),
('S002', 'Vector Search at Scale with ScaNN in AlloyDB', 'Discover how to use ScaNN for fast approximate nearest neighbor search in AlloyDB. Perfect for building high-scale recommendation systems.', 'Breakouts', 'Intermediate', 'http://sessions.com/S002', 'Cloud Architect', '2026-04-10', '14:00:00', '14:00:00', 'Auditorium', 100, 16, 'Databases', 'Retail'),
('S003', 'Building Gen AI Apps with Vertex AI and AlloyDB', 'A practical guide to integrating Vertex AI embeddings and LLMs with your operational data in AlloyDB to build intelligent applications.', 'Lightning Talks', 'Advanced', 'http://sessions.com/S003', 'Director of Engineering', '2026-04-11', '11:00:00', '11:00:00', 'Auditorium', 50, 28, 'Databases', 'Healthcare'),
('S004', 'Spanner: Architecting for Global Consistency', 'Learn how Spanner achieves global scale without sacrificing strong consistency. We will cover multi-region deployment patterns.', 'Keynotes', 'Intermediate', 'http://sessions.com/S004', 'Cloud Architect', '2026-04-11', '11:00:00', '11:00:00', 'Room B', 500, 441, 'Databases', 'Healthcare'),
('S005', 'BigQuery + Vertex AI: Predictive Analytics Made Easy', 'See how to combine the power of BigQuery for data warehousing with Vertex AI for machine learning to build predictive models directly on your data.', 'Breakouts', 'Advanced', 'http://sessions.com/S005', 'Product Manager', '2026-04-11', '14:00:00', '14:00:00', 'Room C', 100, 96, 'AI & Machine Learning', 'Retail'),
('S006', 'Securing Your Data: Best Practices in AlloyDB', 'Deep dive into the security features of AlloyDB, including IAM integration, encryption at rest and in transit, and audit logging.', 'Keynotes', 'Beginner', 'http://sessions.com/S006', 'Product Manager', '2026-04-09', '15:00:00', '15:00:00', 'Room C', 200, 199, 'Databases', 'Healthcare'),
('S007', 'Kubernetes for Databases: Running PostgreSQL on GKE', 'Best practices for running stateful workloads like PostgreSQL on Google Kubernetes Engine (GKE).', 'Lightning Talks', 'Intermediate', 'http://sessions.com/S007', 'Software Engineer', '2026-04-09', '16:00:00', '16:00:00', 'Room C', 100, 63, 'Databases', 'Retail'),
('S008', 'Real-time Analytics with BigQuery and Pub/Sub', 'Learn how to build real-time data pipelines using Pub/Sub and stream data directly into BigQuery for instant insights.', 'Keynotes', 'Beginner', 'http://sessions.com/S008', 'Security Engineer', '2026-04-10', '14:00:00', '14:00:00', 'Room C', 200, 65, 'Databases', 'Finance'),
('S009', 'Microservices Architecture with Spanner', 'How to design microservices that leverage Spanner''s unique capabilities for distributed transactions and scalability.', 'Keynotes', 'Beginner', 'http://sessions.com/S009', 'Software Engineer', '2026-04-11', '10:00:00', '10:00:00', 'Auditorium', 100, 25, 'Databases', 'Technology'),
('S010', 'AI-Powered Search with ScaNN and LLMs', 'Learn how to combine ScaNN vector search with Large Language Models to create powerful, context-aware search experiences.', 'Keynotes', 'Intermediate', 'http://sessions.com/S010', 'Tech Lead', '2026-04-11', '11:00:00', '11:00:00', 'Room C', 50, 27, 'AI & Machine Learning', 'Healthcare'),
('S011', 'AlloyDB Omni: Run AlloyDB Anywhere', 'Explore AlloyDB Omni, the downloadable edition of AlloyDB that lets you run the same high-performance database in your own data center or on the edge.', 'Breakouts', 'Intermediate', 'http://sessions.com/S011', 'Cloud Architect', '2026-04-09', '10:00:00', '10:00:00', 'Room B', 200, 195, 'Databases', 'Technology'),
('S012', 'Data Mesh on Google Cloud: Best Practices', 'How to implement a decentralized data mesh architecture using BigQuery, Dataplex, and other Google Cloud tools.', 'Lightning Talks', 'Intermediate', 'http://sessions.com/S012', 'Data Scientist', '2026-04-10', '16:00:00', '16:00:00', 'Room C', 100, 46, 'Cloud Architecture', 'Technology'),
('S013', 'Serverless Databases: When to use Cloud SQL vs AlloyDB', 'A comparison of Cloud SQL and AlloyDB, helping you choose the right database for your serverless and traditional applications.', 'Lightning Talks', 'Beginner', 'http://sessions.com/S013', 'DevOps Engineer', '2026-04-10', '11:00:00', '11:00:00', 'Room C', 500, 458, 'Databases', 'Manufacturing'),
('S014', 'Graph Databases on Google Cloud', 'Explore options for graph data processing on Google Cloud, including integrations with existing database services.', 'Breakouts', 'Advanced', 'http://sessions.com/S014', 'DevOps Engineer', '2026-04-11', '09:00:00', '09:00:00', 'Room C', 500, 338, 'DevOps', 'Finance'),
('S015', 'Automating DB Ops with Gemini', 'See how Gemini can help DBA and developers write better SQL, optimize queries, and manage database infrastructure.', 'Breakouts', 'Advanced', 'http://sessions.com/S015', 'Cloud Architect', '2026-04-11', '14:00:00', '14:00:00', 'Room C', 100, 53, 'AI & Machine Learning', 'Retail'),
('S016', 'High Availability and Disaster Recovery in AlloyDB', 'A deep dive into how AlloyDB ensures your data is always available, covering failover mechanisms and backup strategies.', 'Breakouts', 'Advanced', 'http://sessions.com/S016', 'Cloud Architect', '2026-04-11', '11:00:00', '11:00:00', 'Room A', 200, 52, 'Databases', 'Technology'),
('S017', 'Optimizing Costs in BigQuery', 'Practical tips for reducing your BigQuery bill without sacrificing performance, covering slot management and query optimization.', 'Lightning Talks', 'Beginner', 'http://sessions.com/S017', 'Security Engineer', '2026-04-11', '15:00:00', '15:00:00', 'Room B', 100, 65, 'Databases', 'Manufacturing'),
('S018', 'Continuous Integration for Database Schemas', 'How to apply CI/CD principles to database schema changes using tools like Liquibase or Flyway on Google Cloud.', 'Breakouts', 'Beginner', 'http://sessions.com/S018', 'Cloud Architect', '2026-04-11', '09:00:00', '09:00:00', 'Room B', 50, 30, 'Security', 'Technology'),
('S019', 'Data Governance in the Age of AI', 'Learn how to maintain data quality, privacy, and compliance when feeding enterprise data into AI models.', 'Breakouts', 'Beginner', 'http://sessions.com/S019', 'Product Manager', '2026-04-10', '10:00:00', '10:00:00', 'Room A', 100, 39, 'DevOps', 'Retail'),
('S020', 'Hybrid Search: Combining Vector and Keyword Search', 'Learn how to implement hybrid search in AlloyDB to get the best of both worlds: semantic understanding and precise keyword matching.', 'Breakouts', 'Intermediate', 'http://sessions.com/S020', 'Data Scientist', '2026-04-09', '14:00:00', '14:00:00', 'Auditorium', 500, 176, 'Databases', 'Manufacturing'),
('S021', 'Deep Dive into ScaNN for High Availability', 'Join this session to explore how ScaNN can be used for High Availability. We will cover best practices, real-world use cases, and advanced configuration options.', 'Breakouts', 'Advanced', 'http://sessions.com/S021', 'Software Engineer', '2026-04-11', '14:00:00', '14:00:00', 'Room B', 200, 18, 'AI & Machine Learning', 'Finance'),
('S022', 'Understanding Vertex AI for Modernization', 'Join this session to explore how Vertex AI can be used for Modernization. We will cover best practices, real-world use cases, and advanced configuration options.', 'Lightning Talks', 'Beginner', 'http://sessions.com/S022', 'Tech Lead', '2026-04-09', '09:00:00', '09:00:00', 'Room A', 50, 48, 'AI & Machine Learning', 'Finance'),
('S023', 'Securing Vertex AI for Modernization', 'Join this session to explore how Vertex AI can be used for Modernization. We will cover best practices, real-world use cases, and advanced configuration options.', 'Lightning Talks', 'Intermediate', 'http://sessions.com/S023', 'Tech Lead', '2026-04-10', '10:00:00', '10:00:00', 'Auditorium', 200, 96, 'AI & Machine Learning', 'Manufacturing'),
('S024', 'Mastering Kubernetes for Security', 'Join this session to explore how Kubernetes can be used for Security. We will cover best practices, real-world use cases, and advanced configuration options.', 'Lightning Talks', 'Beginner', 'http://sessions.com/S024', 'DevOps Engineer', '2026-04-09', '09:00:00', '09:00:00', 'Auditorium', 200, 160, 'Security', 'Technology'),
('S025', 'Mastering AlloyDB for Modernization', 'Join this session to explore how AlloyDB can be used for Modernization. We will cover best practices, real-world use cases, and advanced configuration options.', 'Breakouts', 'Advanced', 'http://sessions.com/S025', 'Director of Engineering', '2026-04-11', '16:00:00', '16:00:00', 'Room B', 200, 74, 'Databases', 'Healthcare'),
('S026', 'Securing Vertex AI for Automation', 'Join this session to explore how Vertex AI can be used for Automation. We will cover best practices, real-world use cases, and advanced configuration options.', 'Keynotes', 'Advanced', 'http://sessions.com/S026', 'Cloud Architect', '2026-04-11', '16:00:00', '16:00:00', 'Room A', 50, 25, 'AI & Machine Learning', 'Manufacturing'),
('S027', 'Mastering BigQuery for Analytics', 'Join this session to explore how BigQuery can be used for Analytics. We will cover best practices, real-world use cases, and advanced configuration options.', 'Breakouts', 'Intermediate', 'http://sessions.com/S027', 'Security Engineer', '2026-04-11', '10:00:00', '10:00:00', 'Room B', 200, 117, 'Databases', 'Healthcare'),
('S028', 'Deep Dive into Spanner for Integration', 'Join this session to explore how Spanner can be used for Integration. We will cover best practices, real-world use cases, and advanced configuration options.', 'Lightning Talks', 'Advanced', 'http://sessions.com/S028', 'Tech Lead', '2026-04-09', '10:00:00', '10:00:00', 'Auditorium', 50, 32, 'Databases', 'Retail'),
('S029', 'Scaling Generative AI for Automation', 'Join this session to explore how Generative AI can be used for Automation. We will cover best practices, real-world use cases, and advanced configuration options.', 'Keynotes', 'Intermediate', 'http://sessions.com/S029', 'Tech Lead', '2026-04-09', '10:00:00', '10:00:00', 'Room A', 200, 157, 'AI & Machine Learning', 'Healthcare'),
('S030', 'Deploying Generative AI for Analytics', 'Join this session to explore how Generative AI can be used for Analytics. We will cover best practices, real-world use cases, and advanced configuration options.', 'Keynotes', 'Advanced', 'http://sessions.com/S030', 'Director of Engineering', '2026-04-09', '16:00:00', '16:00:00', 'Room B', 500, 462, 'DevOps', 'Healthcare'),
('S031', 'Mastering ScaNN for High Availability', 'Join this session to explore how ScaNN can be used for High Availability. We will cover best practices, real-world use cases, and advanced configuration options.', 'Breakouts', 'Beginner', 'http://sessions.com/S031', 'Director of Engineering', '2026-04-10', '09:00:00', '09:00:00', 'Room C', 500, 140, 'AI & Machine Learning', 'Finance'),
('S032', 'Deploying Kubernetes for Integration', 'Join this session to explore how Kubernetes can be used for Integration. We will cover best practices, real-world use cases, and advanced configuration options.', 'Breakouts', 'Advanced', 'http://sessions.com/S032', 'Cloud Architect', '2026-04-11', '14:00:00', '14:00:00', 'Auditorium', 200, 22, 'Databases', 'Retail'),
('S033', 'Securing Gemini for Performance', 'Join this session to explore how Gemini can be used for Performance. We will cover best practices, real-world use cases, and advanced configuration options.', 'Keynotes', 'Intermediate', 'http://sessions.com/S033', 'Cloud Architect', '2026-04-09', '16:00:00', '16:00:00', 'Room B', 200, 84, 'AI & Machine Learning', 'Technology'),
('S034', 'Deploying Vertex AI for Scale', 'Join this session to explore how Vertex AI can be used for Scale. We will cover best practices, real-world use cases, and advanced configuration options.', 'Breakouts', 'Intermediate', 'http://sessions.com/S034', 'Director of Engineering', '2026-04-10', '10:00:00', '10:00:00', 'Room B', 500, 222, 'AI & Machine Learning', 'Finance'),
('S035', 'Deep Dive into BigQuery for Analytics', 'Join this session to explore how BigQuery can be used for Analytics. We will cover best practices, real-world use cases, and advanced configuration options.', 'Breakouts', 'Intermediate', 'http://sessions.com/S035', 'Security Engineer', '2026-04-11', '15:00:00', '15:00:00', 'Room A', 500, 408, 'Databases', 'Healthcare'),
('S036', 'Deploying Kubernetes for Security', 'Join this session to explore how Kubernetes can be used for Security. We will cover best practices, real-world use cases, and advanced configuration options.', 'Keynotes', 'Advanced', 'http://sessions.com/S036', 'Tech Lead', '2026-04-10', '09:00:00', '09:00:00', 'Room A', 200, 54, 'Security', 'Healthcare'),
('S037', 'Understanding Spanner for Integration', 'Join this session to explore how Spanner can be used for Integration. We will cover best practices, real-world use cases, and advanced configuration options.', 'Lightning Talks', 'Beginner', 'http://sessions.com/S037', 'Tech Lead', '2026-04-10', '14:00:00', '14:00:00', 'Room C', 200, 89, 'Databases', 'Technology'),
('S038', 'Deep Dive into Kubernetes for Automation', 'Join this session to explore how Kubernetes can be used for Automation. We will cover best practices, real-world use cases, and advanced configuration options.', 'Lightning Talks', 'Beginner', 'http://sessions.com/S038', 'Product Manager', '2026-04-11', '09:00:00', '09:00:00', 'Room C', 50, 47, 'AI & Machine Learning', 'Healthcare'),
('S039', 'Optimizing BigQuery for Reliability', 'Join this session to explore how BigQuery can be used for Reliability. We will cover best practices, real-world use cases, and advanced configuration options.', 'Keynotes', 'Beginner', 'http://sessions.com/S039', 'Director of Engineering', '2026-04-10', '14:00:00', '14:00:00', 'Auditorium', 200, 38, 'Databases', 'Retail'),
('S040', 'Deep Dive into Spanner for Cost Efficiency', 'Join this session to explore how Spanner can be used for Cost Efficiency. We will cover best practices, real-world use cases, and advanced configuration options.', 'Lightning Talks', 'Advanced', 'http://sessions.com/S040', 'Software Engineer', '2026-04-09', '14:00:00', '14:00:00', 'Auditorium', 50, 2, 'Databases', 'Healthcare'),
('S041', 'Exploring Gemini for Cost Efficiency', 'Join this session to explore how Gemini can be used for Cost Efficiency. We will cover best practices, real-world use cases, and advanced configuration options.', 'Keynotes', 'Intermediate', 'http://sessions.com/S041', 'Product Manager', '2026-04-10', '15:00:00', '15:00:00', 'Room A', 100, 73, 'AI & Machine Learning', 'Healthcare'),
('S042', 'Mastering ScaNN for Performance', 'Join this session to explore how ScaNN can be used for Performance. We will cover best practices, real-world use cases, and advanced configuration options.', 'Breakouts', 'Beginner', 'http://sessions.com/S042', 'Tech Lead', '2026-04-09', '11:00:00', '11:00:00', 'Auditorium', 100, 50, 'AI & Machine Learning', 'Manufacturing'),
('S043', 'Mastering ScaNN for Analytics', 'Join this session to explore how ScaNN can be used for Analytics. We will cover best practices, real-world use cases, and advanced configuration options.', 'Breakouts', 'Advanced', 'http://sessions.com/S043', 'Data Scientist', '2026-04-10', '09:00:00', '09:00:00', 'Room B', 200, 111, 'AI & Machine Learning', 'Technology'),
('S044', 'Securing Gemini for Integration', 'Join this session to explore how Gemini can be used for Integration. We will cover best practices, real-world use cases, and advanced configuration options.', 'Lightning Talks', 'Advanced', 'http://sessions.com/S044', 'Cloud Architect', '2026-04-09', '14:00:00', '14:00:00', 'Auditorium', 500, 281, 'AI & Machine Learning', 'Healthcare'),
('S045', 'Architecting Cloud SQL for Integration', 'Join this session to explore how Cloud SQL can be used for Integration. We will cover best practices, real-world use cases, and advanced configuration options.', 'Lightning Talks', 'Advanced', 'http://sessions.com/S045', 'Product Manager', '2026-04-11', '11:00:00', '11:00:00', 'Room C', 50, 6, 'AI & Machine Learning', 'Retail'),
('S046', 'Securing Kubernetes for Scale', 'Join this session to explore how Kubernetes can be used for Scale. We will cover best practices, real-world use cases, and advanced configuration options.', 'Lightning Talks', 'Beginner', 'http://sessions.com/S046', 'Security Engineer', '2026-04-11', '14:00:00', '14:00:00', 'Room B', 100, 80, 'AI & Machine Learning', 'Manufacturing'),
('S047', 'Mastering PostgreSQL for Integration', 'Join this session to explore how PostgreSQL can be used for Integration. We will cover best practices, real-world use cases, and advanced configuration options.', 'Lightning Talks', 'Advanced', 'http://sessions.com/S047', 'Tech Lead', '2026-04-10', '14:00:00', '14:00:00', 'Auditorium', 200, 134, 'Databases', 'Manufacturing'),
('S048', 'Deep Dive into Kubernetes for Cost Efficiency', 'Join this session to explore how Kubernetes can be used for Cost Efficiency. We will cover best practices, real-world use cases, and advanced configuration options.', 'Breakouts', 'Intermediate', 'http://sessions.com/S048', 'Data Scientist', '2026-04-11', '09:00:00', '09:00:00', 'Room C', 500, 102, 'AI & Machine Learning', 'Retail'),
('S049', 'Deep Dive into Cloud SQL for Scale', 'Join this session to explore how Cloud SQL can be used for Scale. We will cover best practices, real-world use cases, and advanced configuration options.', 'Breakouts', 'Beginner', 'http://sessions.com/S049', 'Security Engineer', '2026-04-09', '14:00:00', '14:00:00', 'Auditorium', 200, 127, 'AI & Machine Learning', 'Healthcare'),
('S050', 'Scaling Cloud SQL for Reliability', 'Join this session to explore how Cloud SQL can be used for Reliability. We will cover best practices, real-world use cases, and advanced configuration options.', 'Keynotes', 'Intermediate', 'http://sessions.com/S050', 'Software Engineer', '2026-04-10', '15:00:00', '15:00:00', 'Room A', 100, 40, 'Cloud Architecture', 'Finance'),
('S051', 'Building Vertex AI for Security', 'Join this session to explore how Vertex AI can be used for Security. We will cover best practices, real-world use cases, and advanced configuration options.', 'Keynotes', 'Beginner', 'http://sessions.com/S051', 'Director of Engineering', '2026-04-09', '15:00:00', '15:00:00', 'Room C', 500, 138, 'AI & Machine Learning', 'Retail'),
('S052', 'Exploring Vertex AI for Modernization', 'Join this session to explore how Vertex AI can be used for Modernization. We will cover best practices, real-world use cases, and advanced configuration options.', 'Breakouts', 'Intermediate', 'http://sessions.com/S052', 'DevOps Engineer', '2026-04-09', '09:00:00', '09:00:00', 'Room C', 200, 27, 'AI & Machine Learning', 'Finance'),
('S053', 'Optimizing Generative AI for Automation', 'Join this session to explore how Generative AI can be used for Automation. We will cover best practices, real-world use cases, and advanced configuration options.', 'Keynotes', 'Beginner', 'http://sessions.com/S053', 'Director of Engineering', '2026-04-10', '11:00:00', '11:00:00', 'Room C', 500, 65, 'Databases', 'Healthcare'),
('S054', 'Architecting PostgreSQL for Performance', 'Join this session to explore how PostgreSQL can be used for Performance. We will cover best practices, real-world use cases, and advanced configuration options.', 'Breakouts', 'Beginner', 'http://sessions.com/S054', 'Data Scientist', '2026-04-09', '11:00:00', '11:00:00', 'Auditorium', 200, 103, 'Databases', 'Healthcare'),
('S055', 'Mastering Generative AI for Automation', 'Join this session to explore how Generative AI can be used for Automation. We will cover best practices, real-world use cases, and advanced configuration options.', 'Breakouts', 'Intermediate', 'http://sessions.com/S055', 'Data Scientist', '2026-04-11', '11:00:00', '11:00:00', 'Room C', 50, 31, 'AI & Machine Learning', 'Technology'),
('S056', 'Exploring ScaNN for Reliability', 'Join this session to explore how ScaNN can be used for Reliability. We will cover best practices, real-world use cases, and advanced configuration options.', 'Breakouts', 'Intermediate', 'http://sessions.com/S056', 'Security Engineer', '2026-04-11', '15:00:00', '15:00:00', 'Room A', 500, 351, 'AI & Machine Learning', 'Healthcare'),
('S057', 'Deep Dive into BigQuery for Performance', 'Join this session to explore how BigQuery can be used for Performance. We will cover best practices, real-world use cases, and advanced configuration options.', 'Breakouts', 'Intermediate', 'http://sessions.com/S057', 'DevOps Engineer', '2026-04-11', '11:00:00', '11:00:00', 'Room B', 200, 200, 'Databases', 'Finance'),
('S058', 'Scaling Generative AI for Reliability', 'Join this session to explore how Generative AI can be used for Reliability. We will cover best practices, real-world use cases, and advanced configuration options.', 'Breakouts', 'Beginner', 'http://sessions.com/S058', 'Cloud Architect', '2026-04-10', '11:00:00', '11:00:00', 'Room C', 100, 61, 'Databases', 'Finance'),
('S059', 'Securing Vertex AI for High Availability', 'Join this session to explore how Vertex AI can be used for High Availability. We will cover best practices, real-world use cases, and advanced configuration options.', 'Keynotes', 'Beginner', 'http://sessions.com/S059', 'Data Scientist', '2026-04-11', '16:00:00', '16:00:00', 'Room B', 500, 224, 'AI & Machine Learning', 'Manufacturing'),
('S060', 'Architecting AlloyDB for Integration', 'Join this session to explore how AlloyDB can be used for Integration. We will cover best practices, real-world use cases, and advanced configuration options.', 'Breakouts', 'Beginner', 'http://sessions.com/S060', 'Tech Lead', '2026-04-09', '14:00:00', '14:00:00', 'Room A', 500, 223, 'Databases', 'Technology'),
('S061', 'Understanding Spanner for High Availability', 'Join this session to explore how Spanner can be used for High Availability. We will cover best practices, real-world use cases, and advanced configuration options.', 'Keynotes', 'Advanced', 'http://sessions.com/S061', 'Tech Lead', '2026-04-09', '16:00:00', '16:00:00', 'Room C', 100, 52, 'Databases', 'Manufacturing'),
('S062', 'Scaling Kubernetes for Cost Efficiency', 'Join this session to explore how Kubernetes can be used for Cost Efficiency. We will cover best practices, real-world use cases, and advanced configuration options.', 'Breakouts', 'Advanced', 'http://sessions.com/S062', 'Product Manager', '2026-04-10', '16:00:00', '16:00:00', 'Room B', 100, 0, 'Cloud Architecture', 'Retail'),
('S063', 'Architecting Kubernetes for High Availability', 'Join this session to explore how Kubernetes can be used for High Availability. We will cover best practices, real-world use cases, and advanced configuration options.', 'Breakouts', 'Beginner', 'http://sessions.com/S063', 'Security Engineer', '2026-04-09', '10:00:00', '10:00:00', 'Auditorium', 200, 0, 'Security', 'Finance'),
('S064', 'Mastering Gemini for Integration', 'Join this session to explore how Gemini can be used for Integration. We will cover best practices, real-world use cases, and advanced configuration options.', 'Keynotes', 'Advanced', 'http://sessions.com/S064', 'Security Engineer', '2026-04-10', '15:00:00', '15:00:00', 'Room B', 100, 8, 'AI & Machine Learning', 'Technology'),
('S065', 'Optimizing Generative AI for Security', 'Join this session to explore how Generative AI can be used for Security. We will cover best practices, real-world use cases, and advanced configuration options.', 'Breakouts', 'Beginner', 'http://sessions.com/S065', 'Tech Lead', '2026-04-09', '15:00:00', '15:00:00', 'Room C', 500, 230, 'AI & Machine Learning', 'Retail'),
('S066', 'Optimizing BigQuery for Scale', 'Join this session to explore how BigQuery can be used for Scale. We will cover best practices, real-world use cases, and advanced configuration options.', 'Keynotes', 'Intermediate', 'http://sessions.com/S066', 'Tech Lead', '2026-04-11', '10:00:00', '10:00:00', 'Room C', 500, 186, 'Databases', 'Healthcare'),
('S067', 'Scaling PostgreSQL for Automation', 'Join this session to explore how PostgreSQL can be used for Automation. We will cover best practices, real-world use cases, and advanced configuration options.', 'Keynotes', 'Beginner', 'http://sessions.com/S067', 'Product Manager', '2026-04-10', '11:00:00', '11:00:00', 'Auditorium', 100, 17, 'Databases', 'Retail'),
('S068', 'Exploring AlloyDB for Automation', 'Join this session to explore how AlloyDB can be used for Automation. We will cover best practices, real-world use cases, and advanced configuration options.', 'Lightning Talks', 'Beginner', 'http://sessions.com/S068', 'Director of Engineering', '2026-04-11', '16:00:00', '16:00:00', 'Room B', 100, 77, 'Databases', 'Retail'),
('S069', 'Securing BigQuery for Cost Efficiency', 'Join this session to explore how BigQuery can be used for Cost Efficiency. We will cover best practices, real-world use cases, and advanced configuration options.', 'Breakouts', 'Advanced', 'http://sessions.com/S069', 'Cloud Architect', '2026-04-09', '14:00:00', '14:00:00', 'Room A', 500, 437, 'Databases', 'Manufacturing'),
('S070', 'Deep Dive into Kubernetes for Integration', 'Join this session to explore how Kubernetes can be used for Integration. We will cover best practices, real-world use cases, and advanced configuration options.', 'Lightning Talks', 'Intermediate', 'http://sessions.com/S070', 'Cloud Architect', '2026-04-11', '11:00:00', '11:00:00', 'Room A', 50, 46, 'AI & Machine Learning', 'Technology'),
('S071', 'Architecting ScaNN for Cost Efficiency', 'Join this session to explore how ScaNN can be used for Cost Efficiency. We will cover best practices, real-world use cases, and advanced configuration options.', 'Lightning Talks', 'Intermediate', 'http://sessions.com/S071', 'Cloud Architect', '2026-04-11', '14:00:00', '14:00:00', 'Auditorium', 100, 97, 'AI & Machine Learning', 'Finance'),
('S072', 'Scaling ScaNN for Analytics', 'Join this session to explore how ScaNN can be used for Analytics. We will cover best practices, real-world use cases, and advanced configuration options.', 'Lightning Talks', 'Beginner', 'http://sessions.com/S072', 'Cloud Architect', '2026-04-09', '11:00:00', '11:00:00', 'Room C', 100, 96, 'AI & Machine Learning', 'Manufacturing'),
('S073', 'Securing Cloud SQL for Modernization', 'Join this session to explore how Cloud SQL can be used for Modernization. We will cover best practices, real-world use cases, and advanced configuration options.', 'Keynotes', 'Advanced', 'http://sessions.com/S073', 'Tech Lead', '2026-04-10', '16:00:00', '16:00:00', 'Room C', 200, 195, 'Security', 'Technology'),
('S074', 'Deploying ScaNN for Scale', 'Join this session to explore how ScaNN can be used for Scale. We will cover best practices, real-world use cases, and advanced configuration options.', 'Breakouts', 'Beginner', 'http://sessions.com/S074', 'Data Scientist', '2026-04-10', '10:00:00', '10:00:00', 'Room A', 500, 215, 'AI & Machine Learning', 'Technology'),
('S075', 'Architecting BigQuery for Automation', 'Join this session to explore how BigQuery can be used for Automation. We will cover best practices, real-world use cases, and advanced configuration options.', 'Breakouts', 'Advanced', 'http://sessions.com/S075', 'Product Manager', '2026-04-09', '09:00:00', '09:00:00', 'Room A', 200, 110, 'Databases', 'Healthcare'),
('S076', 'Understanding Vertex AI for Scale', 'Join this session to explore how Vertex AI can be used for Scale. We will cover best practices, real-world use cases, and advanced configuration options.', 'Breakouts', 'Advanced', 'http://sessions.com/S076', 'Software Engineer', '2026-04-11', '15:00:00', '15:00:00', 'Room B', 200, 15, 'AI & Machine Learning', 'Finance'),
('S077', 'Architecting PostgreSQL for Reliability', 'Join this session to explore how PostgreSQL can be used for Reliability. We will cover best practices, real-world use cases, and advanced configuration options.', 'Keynotes', 'Advanced', 'http://sessions.com/S077', 'Director of Engineering', '2026-04-09', '11:00:00', '11:00:00', 'Room C', 200, 133, 'Databases', 'Finance'),
('S078', 'Deploying Generative AI for Analytics', 'Join this session to explore how Generative AI can be used for Analytics. We will cover best practices, real-world use cases, and advanced configuration options.', 'Lightning Talks', 'Intermediate', 'http://sessions.com/S078', 'Product Manager', '2026-04-11', '16:00:00', '16:00:00', 'Room A', 200, 190, 'AI & Machine Learning', 'Manufacturing'),
('S079', 'Deploying ScaNN for Analytics', 'Join this session to explore how ScaNN can be used for Analytics. We will cover best practices, real-world use cases, and advanced configuration options.', 'Lightning Talks', 'Advanced', 'http://sessions.com/S079', 'Cloud Architect', '2026-04-11', '16:00:00', '16:00:00', 'Room B', 200, 95, 'AI & Machine Learning', 'Technology'),
('S080', 'Securing Spanner for Security', 'Join this session to explore how Spanner can be used for Security. We will cover best practices, real-world use cases, and advanced configuration options.', 'Lightning Talks', 'Intermediate', 'http://sessions.com/S080', 'Tech Lead', '2026-04-11', '14:00:00', '14:00:00', 'Room A', 500, 310, 'Databases', 'Healthcare'),
('S081', 'Optimizing Cloud SQL for Performance', 'Join this session to explore how Cloud SQL can be used for Performance. We will cover best practices, real-world use cases, and advanced configuration options.', 'Keynotes', 'Beginner', 'http://sessions.com/S081', 'Security Engineer', '2026-04-11', '11:00:00', '11:00:00', 'Room B', 100, 76, 'Databases', 'Finance'),
('S082', 'Exploring Spanner for Cost Efficiency', 'Join this session to explore how Spanner can be used for Cost Efficiency. We will cover best practices, real-world use cases, and advanced configuration options.', 'Keynotes', 'Advanced', 'http://sessions.com/S082', 'Tech Lead', '2026-04-11', '15:00:00', '15:00:00', 'Room C', 50, 1, 'Databases', 'Manufacturing'),
('S083', 'Understanding Kubernetes for Performance', 'Join this session to explore how Kubernetes can be used for Performance. We will cover best practices, real-world use cases, and advanced configuration options.', 'Keynotes', 'Beginner', 'http://sessions.com/S083', 'Product Manager', '2026-04-11', '14:00:00', '14:00:00', 'Auditorium', 100, 49, 'Security', 'Retail'),
('S084', 'Exploring Cloud SQL for Cost Efficiency', 'Join this session to explore how Cloud SQL can be used for Cost Efficiency. We will cover best practices, real-world use cases, and advanced configuration options.', 'Breakouts', 'Intermediate', 'http://sessions.com/S084', 'Tech Lead', '2026-04-09', '16:00:00', '16:00:00', 'Room C', 500, 91, 'Cloud Architecture', 'Healthcare'),
('S085', 'Scaling Kubernetes for Automation', 'Join this session to explore how Kubernetes can be used for Automation. We will cover best practices, real-world use cases, and advanced configuration options.', 'Lightning Talks', 'Intermediate', 'http://sessions.com/S085', 'Director of Engineering', '2026-04-10', '10:00:00', '10:00:00', 'Room B', 500, 204, 'Databases', 'Finance'),
('S086', 'Deep Dive into BigQuery for Cost Efficiency', 'Join this session to explore how BigQuery can be used for Cost Efficiency. We will cover best practices, real-world use cases, and advanced configuration options.', 'Lightning Talks', 'Beginner', 'http://sessions.com/S086', 'Product Manager', '2026-04-09', '16:00:00', '16:00:00', 'Room B', 100, 89, 'Databases', 'Finance'),
('S087', 'Deep Dive into Vertex AI for Automation', 'Join this session to explore how Vertex AI can be used for Automation. We will cover best practices, real-world use cases, and advanced configuration options.', 'Breakouts', 'Beginner', 'http://sessions.com/S087', 'Data Scientist', '2026-04-10', '14:00:00', '14:00:00', 'Auditorium', 100, 74, 'AI & Machine Learning', 'Retail'),
('S088', 'Mastering AlloyDB for Modernization', 'Join this session to explore how AlloyDB can be used for Modernization. We will cover best practices, real-world use cases, and advanced configuration options.', 'Breakouts', 'Beginner', 'http://sessions.com/S088', 'Security Engineer', '2026-04-09', '16:00:00', '16:00:00', 'Room C', 100, 39, 'Databases', 'Healthcare'),
('S089', 'Exploring AlloyDB for High Availability', 'Join this session to explore how AlloyDB can be used for High Availability. We will cover best practices, real-world use cases, and advanced configuration options.', 'Breakouts', 'Advanced', 'http://sessions.com/S089', 'Data Scientist', '2026-04-10', '15:00:00', '15:00:00', 'Room A', 100, 94, 'Databases', 'Healthcare'),
('S090', 'Exploring Vertex AI for Security', 'Join this session to explore how Vertex AI can be used for Security. We will cover best practices, real-world use cases, and advanced configuration options.', 'Breakouts', 'Intermediate', 'http://sessions.com/S090', 'Security Engineer', '2026-04-11', '10:00:00', '10:00:00', 'Room B', 50, 27, 'AI & Machine Learning', 'Retail'),
('S091', 'Mastering ScaNN for Cost Efficiency', 'Join this session to explore how ScaNN can be used for Cost Efficiency. We will cover best practices, real-world use cases, and advanced configuration options.', 'Keynotes', 'Advanced', 'http://sessions.com/S091', 'DevOps Engineer', '2026-04-09', '14:00:00', '14:00:00', 'Auditorium', 100, 21, 'AI & Machine Learning', 'Technology'),
('S092', 'Mastering BigQuery for Scale', 'Join this session to explore how BigQuery can be used for Scale. We will cover best practices, real-world use cases, and advanced configuration options.', 'Breakouts', 'Advanced', 'http://sessions.com/S092', 'Cloud Architect', '2026-04-09', '16:00:00', '16:00:00', 'Room C', 200, 67, 'Databases', 'Manufacturing'),
('S093', 'Exploring AlloyDB for Performance', 'Join this session to explore how AlloyDB can be used for Performance. We will cover best practices, real-world use cases, and advanced configuration options.', 'Lightning Talks', 'Beginner', 'http://sessions.com/S093', 'Security Engineer', '2026-04-09', '10:00:00', '10:00:00', 'Room B', 200, 171, 'Databases', 'Finance'),
('S094', 'Deploying Cloud SQL for Modernization', 'Join this session to explore how Cloud SQL can be used for Modernization. We will cover best practices, real-world use cases, and advanced configuration options.', 'Lightning Talks', 'Advanced', 'http://sessions.com/S094', 'Product Manager', '2026-04-09', '14:00:00', '14:00:00', 'Room B', 100, 71, 'DevOps', 'Healthcare'),
('S095', 'Building Spanner for Analytics', 'Join this session to explore how Spanner can be used for Analytics. We will cover best practices, real-world use cases, and advanced configuration options.', 'Lightning Talks', 'Beginner', 'http://sessions.com/S095', 'Product Manager', '2026-04-10', '15:00:00', '15:00:00', 'Room B', 500, 334, 'Databases', 'Manufacturing'),
('S096', 'Deep Dive into Vertex AI for Analytics', 'Join this session to explore how Vertex AI can be used for Analytics. We will cover best practices, real-world use cases, and advanced configuration options.', 'Keynotes', 'Intermediate', 'http://sessions.com/S096', 'DevOps Engineer', '2026-04-11', '14:00:00', '14:00:00', 'Room C', 100, 27, 'AI & Machine Learning', 'Healthcare'),
('S097', 'Deploying PostgreSQL for Analytics', 'Join this session to explore how PostgreSQL can be used for Analytics. We will cover best practices, real-world use cases, and advanced configuration options.', 'Breakouts', 'Beginner', 'http://sessions.com/S097', 'Cloud Architect', '2026-04-09', '11:00:00', '11:00:00', 'Room C', 50, 36, 'Databases', 'Healthcare'),
('S098', 'Architecting Kubernetes for Reliability', 'Join this session to explore how Kubernetes can be used for Reliability. We will cover best practices, real-world use cases, and advanced configuration options.', 'Lightning Talks', 'Beginner', 'http://sessions.com/S098', 'Cloud Architect', '2026-04-10', '11:00:00', '11:00:00', 'Room A', 50, 29, 'AI & Machine Learning', 'Finance'),
('S099', 'Scaling Cloud SQL for Analytics', 'Join this session to explore how Cloud SQL can be used for Analytics. We will cover best practices, real-world use cases, and advanced configuration options.', 'Keynotes', 'Beginner', 'http://sessions.com/S099', 'DevOps Engineer', '2026-04-09', '09:00:00', '09:00:00', 'Auditorium', 50, 21, 'Security', 'Finance'),
('S100', 'Deploying PostgreSQL for Analytics', 'Join this session to explore how PostgreSQL can be used for Analytics. We will cover best practices, real-world use cases, and advanced configuration options.', 'Keynotes', 'Advanced', 'http://sessions.com/S100', 'DevOps Engineer', '2026-04-11', '09:00:00', '09:00:00', 'Room B', 500, 141, 'Databases', 'Technology') ON CONFLICT (session_id) DO NOTHING;

3.5 Atribuir palestrantes às sessões

-- Insert Session-Speaker Mappings
INSERT INTO public.session_speaker_mapping (session_id, speaker_id) VALUES
('S001', 6),
('S001', 19),
('S002', 6),
('S002', 11),
('S003', 14),
('S003', 10),
('S004', 5),
('S004', 8),
('S005', 12),
('S005', 9),
('S006', 14),
('S007', 14),
('S007', 3),
('S008', 2),
('S008', 4),
('S009', 9),
('S009', 13),
('S010', 2),
('S010', 3),
('S011', 12),
('S012', 13),
('S013', 11),
('S014', 8),
('S015', 16),
('S016', 4),
('S016', 18),
('S017', 12),
('S018', 10),
('S019', 15),
('S020', 20),
('S020', 7),
('S021', 2),
('S021', 11),
('S022', 15),
('S022', 7),
('S023', 4),
('S023', 19),
('S024', 11),
('S025', 11),
('S025', 10),
('S026', 11),
('S027', 20),
('S028', 20),
('S028', 3),
('S029', 11),
('S029', 20),
('S030', 19),
('S030', 6),
('S031', 20),
('S031', 14),
('S032', 3),
('S033', 4),
('S033', 8),
('S034', 14),
('S035', 12),
('S035', 4),
('S036', 18),
('S037', 6),
('S038', 9),
('S038', 7),
('S039', 7),
('S040', 17),
('S041', 17),
('S042', 16),
('S042', 2),
('S043', 10),
('S043', 13),
('S044', 7),
('S045', 10),
('S046', 1),
('S046', 20),
('S047', 17),
('S048', 9),
('S048', 6),
('S049', 4),
('S049', 3),
('S050', 8),
('S050', 16),
('S051', 18),
('S051', 10),
('S052', 4),
('S053', 5),
('S053', 13),
('S054', 17),
('S055', 1),
('S056', 1),
('S056', 15),
('S057', 7),
('S058', 15),
('S059', 15),
('S059', 8),
('S060', 20),
('S060', 10),
('S061', 16),
('S062', 18),
('S062', 11),
('S063', 10),
('S064', 6),
('S065', 10),
('S066', 8),
('S066', 9),
('S067', 16),
('S067', 14),
('S068', 13),
('S068', 11),
('S069', 16),
('S070', 8),
('S071', 3),
('S072', 10),
('S072', 1),
('S073', 10),
('S073', 8),
('S074', 20),
('S074', 14),
('S075', 5),
('S076', 1),
('S076', 11),
('S077', 3),
('S078', 20),
('S078', 12),
('S079', 17),
('S079', 9),
('S080', 10),
('S081', 2),
('S082', 15),
('S082', 11),
('S083', 7),
('S083', 1),
('S084', 8),
('S085', 8),
('S085', 18),
('S086', 5),
('S087', 5),
('S088', 19),
('S088', 18),
('S089', 18),
('S090', 8),
('S091', 4),
('S092', 14),
('S093', 20),
('S093', 17),
('S094', 16),
('S094', 9),
('S095', 11),
('S095', 4),
('S096', 14),
('S096', 11),
('S097', 13),
('S097', 19),
('S098', 3),
('S099', 11),
('S099', 18),
('S100', 18),
('S100', 13) ON CONFLICT DO NOTHING;

3.6 Temas anexados a sessões

-- Insert Session-Topic Mappings
INSERT INTO public.session_topic_mapping (session_id, topic) VALUES
('S001', 'Security'),
('S002', 'AI & Machine Learning'),
('S003', 'Cloud Architecture'),
('S003', 'AI & Machine Learning'),
('S004', 'Databases'),
('S004', 'DevOps'),
('S005', 'DevOps'),
('S005', 'Cloud Architecture'),
('S006', 'Security'),
('S006', 'AI & Machine Learning'),
('S007', 'Cloud Architecture'),
('S007', 'Databases'),
('S008', 'AI & Machine Learning'),
('S008', 'Databases'),
('S009', 'Security'),
('S009', 'DevOps'),
('S010', 'AI & Machine Learning'),
('S010', 'Cloud Architecture'),
('S011', 'Security'),
('S012', 'Databases'),
('S013', 'Cloud Architecture'),
('S014', 'Databases'),
('S015', 'DevOps'),
('S015', 'Security'),
('S016', 'AI & Machine Learning'),
('S016', 'Databases'),
('S017', 'Cloud Architecture'),
('S018', 'AI & Machine Learning'),
('S019', 'AI & Machine Learning'),
('S020', 'Security'),
('S021', 'Security'),
('S021', 'Databases'),
('S022', 'Security'),
('S022', 'Databases'),
('S023', 'DevOps'),
('S023', 'AI & Machine Learning'),
('S024', 'AI & Machine Learning'),
('S025', 'Databases'),
('S026', 'DevOps'),
('S027', 'DevOps'),
('S027', 'Cloud Architecture'),
('S028', 'DevOps'),
('S029', 'Databases'),
('S029', 'Security'),
('S030', 'DevOps'),
('S030', 'Security'),
('S031', 'Databases'),
('S032', 'Databases'),
('S033', 'Databases'),
('S034', 'AI & Machine Learning'),
('S035', 'Security'),
('S035', 'AI & Machine Learning'),
('S036', 'AI & Machine Learning'),
('S036', 'Databases'),
('S037', 'DevOps'),
('S037', 'Databases'),
('S038', 'Cloud Architecture'),
('S038', 'Security'),
('S039', 'Security'),
('S040', 'Security'),
('S040', 'AI & Machine Learning'),
('S041', 'AI & Machine Learning'),
('S042', 'Databases'),
('S043', 'AI & Machine Learning'),
('S043', 'Databases'),
('S044', 'Databases'),
('S044', 'DevOps'),
('S045', 'DevOps'),
('S045', 'Cloud Architecture'),
('S046', 'Cloud Architecture'),
('S046', 'Security'),
('S047', 'Cloud Architecture'),
('S047', 'Security'),
('S048', 'Databases'),
('S049', 'AI & Machine Learning'),
('S049', 'Databases'),
('S050', 'Cloud Architecture'),
('S050', 'AI & Machine Learning'),
('S051', 'DevOps'),
('S051', 'Databases'),
('S052', 'Databases'),
('S053', 'DevOps'),
('S053', 'Databases'),
('S054', 'Security'),
('S054', 'DevOps'),
('S055', 'AI & Machine Learning'),
('S056', 'Security'),
('S056', 'DevOps'),
('S057', 'AI & Machine Learning'),
('S058', 'Security'),
('S058', 'AI & Machine Learning'),
('S059', 'Security'),
('S060', 'AI & Machine Learning'),
('S060', 'DevOps'),
('S061', 'Security'),
('S061', 'AI & Machine Learning'),
('S062', 'DevOps'),
('S063', 'Security'),
('S063', 'DevOps'),
('S064', 'Databases'),
('S064', 'AI & Machine Learning'),
('S065', 'DevOps'),
('S066', 'AI & Machine Learning'),
('S066', 'Cloud Architecture'),
('S067', 'AI & Machine Learning'),
('S068', 'Security'),
('S069', 'Cloud Architecture'),
('S069', 'DevOps'),
('S070', 'AI & Machine Learning'),
('S071', 'AI & Machine Learning'),
('S071', 'DevOps'),
('S072', 'DevOps'),
('S072', 'Security'),
('S073', 'Security'),
('S074', 'AI & Machine Learning'),
('S074', 'Databases'),
('S075', 'AI & Machine Learning'),
('S076', 'DevOps'),
('S077', 'DevOps'),
('S077', 'AI & Machine Learning'),
('S078', 'Databases'),
('S079', 'Databases'),
('S080', 'AI & Machine Learning'),
('S080', 'Databases'),
('S081', 'Databases'),
('S082', 'Databases'),
('S083', 'Security'),
('S084', 'Security'),
('S084', 'AI & Machine Learning'),
('S085', 'AI & Machine Learning'),
('S085', 'Databases'),
('S086', 'DevOps'),
('S087', 'Databases'),
('S088', 'Security'),
('S088', 'Databases'),
('S089', 'Databases'),
('S090', 'DevOps'),
('S091', 'Databases'),
('S092', 'Databases'),
('S093', 'Security'),
('S093', 'AI & Machine Learning'),
('S094', 'Cloud Architecture'),
('S095', 'Cloud Architecture'),
('S095', 'AI & Machine Learning'),
('S096', 'AI & Machine Learning'),
('S097', 'Security'),
('S097', 'AI & Machine Learning'),
('S098', 'Databases'),
('S098', 'Security'),
('S099', 'Cloud Architecture'),
('S100', 'DevOps'),
('S100', 'Cloud Architecture') ON CONFLICT DO NOTHING;;

3.7 Atribuir participantes a sessões

-- Insert Attendee-Session Mappings
INSERT INTO public.attendees_sessions (username, session_id) VALUES
('user_1', 'S100'),
('user_1', 'S008'),
('user_1', 'S060'),
('user_1', 'S090'),
('user_1', 'S057'),
('user_2', 'S086'),
('user_2', 'S033'),
('user_2', 'S006'),
('user_2', 'S043'),
('user_2', 'S050'),
('user_3', 'S066'),
('user_3', 'S099'),
('user_4', 'S004'),
('user_4', 'S043'),
('user_4', 'S092'),
('user_4', 'S033'),
('user_4', 'S074'),
('user_5', 'S014'),
('user_5', 'S088'),
('user_5', 'S093'),
('user_6', 'S075'),
('user_6', 'S033'),
('user_7', 'S014'),
('user_7', 'S021'),
('user_7', 'S047'),
('user_8', 'S051'),
('user_8', 'S081'),
('user_9', 'S048'),
('user_9', 'S100'),
('user_10', 'S037'),
('user_10', 'S059'),
('user_10', 'S083'),
('user_11', 'S007'),
('user_11', 'S099'),
('user_11', 'S054'),
('user_12', 'S006'),
('user_12', 'S046'),
('user_12', 'S077'),
('user_12', 'S032'),
('user_13', 'S020'),
('user_13', 'S029'),
('user_13', 'S054'),
('user_14', 'S052'),
('user_14', 'S070'),
('user_14', 'S028'),
('user_15', 'S054'),
('user_15', 'S050'),
('user_15', 'S025'),
('user_15', 'S066'),
('user_15', 'S081'),
('user_16', 'S099'),
('user_16', 'S073'),
('user_16', 'S027'),
('user_16', 'S058'),
('user_17', 'S092'),
('user_17', 'S089'),
('user_17', 'S076'),
('user_17', 'S062'),
('user_18', 'S083'),
('user_18', 'S094'),
('user_18', 'S097'),
('user_18', 'S031'),
('user_18', 'S040'),
('user_19', 'S078'),
('user_19', 'S072'),
('user_19', 'S049'),
('user_19', 'S017'),
('user_19', 'S084'),
('user_20', 'S023'),
('user_20', 'S003'),
('user_20', 'S016'),
('user_20', 'S068'),
('user_21', 'S071'),
('user_21', 'S058'),
('user_21', 'S043'),
('user_21', 'S079'),
('user_21', 'S067'),
('user_22', 'S076'),
('user_22', 'S038'),
('user_22', 'S049'),
('user_22', 'S033'),
('user_22', 'S070'),
('user_23', 'S032'),
('user_23', 'S099'),
('user_24', 'S022'),
('user_24', 'S065'),
('user_24', 'S060'),
('user_24', 'S084'),
('user_25', 'S077'),
('user_25', 'S080'),
('user_25', 'S097'),
('user_25', 'S010'),
('user_26', 'S063'),
('user_26', 'S052'),
('user_26', 'S086'),
('user_27', 'S054'),
('user_27', 'S094'),
('user_27', 'S018'),
('user_27', 'S061'),
('user_27', 'S052'),
('user_28', 'S064'),
('user_28', 'S070'),
('user_28', 'S050'),
('user_29', 'S009'),
('user_29', 'S012'),
('user_30', 'S058'),
('user_30', 'S056'),
('user_30', 'S072'),
('user_30', 'S093'),
('user_30', 'S045'),
('user_31', 'S001'),
('user_31', 'S094'),
('user_31', 'S065'),
('user_31', 'S031'),
('user_32', 'S048'),
('user_32', 'S011'),
('user_32', 'S065'),
('user_33', 'S021'),
('user_33', 'S081'),
('user_33', 'S063'),
('user_34', 'S068'),
('user_34', 'S026'),
('user_35', 'S044'),
('user_35', 'S054'),
('user_36', 'S023'),
('user_36', 'S051'),
('user_36', 'S100'),
('user_37', 'S047'),
('user_37', 'S053'),
('user_37', 'S057'),
('user_37', 'S048'),
('user_37', 'S080'),
('user_38', 'S003'),
('user_38', 'S038'),
('user_38', 'S046'),
('user_38', 'S005'),
('user_38', 'S076'),
('user_39', 'S046'),
('user_39', 'S020'),
('user_39', 'S043'),
('user_39', 'S002'),
('user_39', 'S100'),
('user_40', 'S019'),
('user_40', 'S098'),
('user_40', 'S053'),
('user_40', 'S007'),
('user_41', 'S100'),
('user_41', 'S032'),
('user_41', 'S048'),
('user_41', 'S064'),
('user_42', 'S086'),
('user_42', 'S030'),
('user_42', 'S049'),
('user_43', 'S033'),
('user_43', 'S008'),
('user_43', 'S049'),
('user_43', 'S093'),
('user_44', 'S078'),
('user_44', 'S071'),
('user_44', 'S067'),
('user_44', 'S012'),
('user_45', 'S043'),
('user_45', 'S056'),
('user_45', 'S079'),
('user_45', 'S062'),
('user_45', 'S039'),
('user_46', 'S054'),
('user_46', 'S031'),
('user_46', 'S018'),
('user_47', 'S035'),
('user_47', 'S100'),
('user_47', 'S083'),
('user_47', 'S080'),
('user_47', 'S037'),
('user_48', 'S097'),
('user_48', 'S026'),
('user_48', 'S065'),
('user_48', 'S030'),
('user_48', 'S074'),
('user_49', 'S022'),
('user_49', 'S089'),
('user_49', 'S038'),
('user_49', 'S047'),
('user_49', 'S073'),
('user_50', 'S074'),
('user_50', 'S033'),
('user_50', 'S069'),
('user_50', 'S036') ON CONFLICT DO NOTHING;

Você vai ver uma saída indicando que a execução foi concluída. Verifique se as tabelas estão preenchidas. Por exemplo, verifique se você tem 100 sessões na tabela "sessions":

SELECT count(*) from public.session;

7. Ativar o mecanismo de consulta de IA

Antes de usar as funções de IA, ative o mecanismo de consulta de IA no seu banco de dados.

Execute o seguinte SQL no AlloyDB Studio (contexto conference_db):

CREATE EXTENSION IF NOT EXISTS google_ml_integration CASCADE;
ALTER DATABASE conference_db SET google_ml_integration.enable_ai_query_engine = 'on';

Verifique se a extensão está ativada:

SELECT extversion FROM pg_extension WHERE extname = 'google_ml_integration';

A saída esperada deve mostrar 1.5.9 ou mais recente.

8. Usar funções de IA (operadores)

Agora vamos usar a filtragem e a pontuação semânticas baseadas em IA com as funções ai.if e ai.rank.

Filtragem semântica com ai.if

A correspondência de texto padrão pode perder sessões se a palavra-chave exata não estiver presente. Vamos encontrar sessões sobre "IA generativa" usando ai.if.

Execute o seguinte SQL no AlloyDB Studio:

SELECT session_name, full_description
FROM public.session
WHERE
  ai.if(
    prompt => 'Is this session description about Generative AI, LLMs or AI agents? ' || full_description
  );

Você vai encontrar sessões relevantes nos resultados, mesmo que elas usem terminologias diferentes.

Pontuação semântica com ai.rank

Vamos classificar as sessões com base na facilidade para iniciantes. Podemos usar ai.rank para pontuação semântica.

Execute o seguinte SQL:

SELECT session_name, full_description, 
  ai.rank(
    prompt => 'On a scale of 0 to 1, how suitable is this session for a beginner? 1 being very suitable, 0 being advanced. Session: ' || full_description
  ) as beginner_friendly_score
FROM public.session
ORDER BY beginner_friendly_score DESC;

Isso é útil para criar recomendações personalizadas para os participantes da conferência com base no perfil deles.

9. Implementar a pesquisa híbrida

A pesquisa híbrida combina a precisão da pesquisa por palavras-chave (lexical) com a compreensão contextual da pesquisa vetorial (semântica). Vamos criar índices para os dois e usar a Fusão de classificação recíproca (RRF) para mesclar os resultados.

Ativar a verificação

Verifique se as extensões scann e rum estão ativadas:

CREATE EXTENSION IF NOT EXISTS alloydb_scann;
CREATE EXTENSION IF NOT EXISTS rum;

Criar índices

Como nosso esquema usa uma coluna gerada para embeddings (full_description_embedding), eles são calculados automaticamente na inserção. Basta criar os índices adequados para uma recuperação rápida.

Crie um índice de RUM (índice de FTS) para pesquisa de palavra-chave de texto completo e um índice ScaNN para pesquisa rápida de similaridade de vetor.

Execute o seguinte SQL no AlloyDB Studio:

-- Create RUM index for text search on session descriptions
CREATE INDEX session_text_idx ON public.session USING RUM (description_tsvector rum_tsvector_ops);

-- Create ScaNN index for vector search on session embeddings
CREATE INDEX session_vector_idx ON public.session
  USING scann (full_description_embedding cosine)
  WITH (num_leaves=10);

Executar a pesquisa híbrida com RRF

Agora, vamos procurar a sessão em fast similarity search, mas focando no ScaNN do AlloyDB.

Vamos usar a pesquisa semântica e por palavras-chave e mesclar os resultados usando a RRF.

Execute o seguinte SQL:

-- Enable preview features for the AI Query Engine if not already set
SET google_ml_integration.enable_preview_ai_functions = true;
SELECT s.session_id, s.session_name, s.full_description
FROM public.session s
JOIN ai.hybrid_search(
  search_inputs => ARRAY[
      '{
        "data_type": "vector",
        "table_name": "session",
        "key_column": "session_id",
        "vec_column": "full_description_embedding",
        "distance_operator": "public.<=>",
        "limit": 5,
        "query_vector": "ai.embedding(''text-embedding-005'', ''fast similarity search'')::vector"
      }'::JSONB,
      '{
        "data_type": "text",
        "table_name": "session",
        "key_column": "session_id",
        "text_column": "description_tsvector",
        "limit": 5,
        "ranking_function": "<=>",
        "query_text_input": "ScaNN"
      }'::JSONB
  ]
) AS search_results
on s.session_id = search_results.id;

Você vai encontrar uma pesquisa de similaridade de sessões relevantes com a maioria dos resultados mostrando sessões relacionadas ao ScaNN.

10. Trabalhar com QueryData no AlloyDB Studio

Com a IA do AlloyDB, é possível usar QueryData para gerar instruções SQL precisas e previsíveis com base em entradas de linguagem natural. Nesta seção, você vai aprender a criar um contexto QueryData (modelos) e testá-lo diretamente no AlloyDB Studio.

Criar contexto do QueryData

O contexto QueryData é um arquivo JSON com modelos de consulta e facetas que fornecem os dados e as instruções necessários para o modelo de IA usar consultas SQL ou partes de consultas SQL corretas.

Vamos analisar um exemplo de contexto JSON projetado para nosso esquema de conferência. Os nomes das tabelas correspondem ao nosso esquema (por exemplo, public.session).

Este é o conteúdo JSON que vamos usar. Armazene-o em um arquivo .json local no seu laptop/computador :

{
  "templates": [
    {
      "nlQuery": "Advanced sessions that are almost full",
      "sql": "SELECT session_name, remaining_capacity, session_date, session_start_time FROM session WHERE learning_level = 'Advanced' AND remaining_capacity > 0 AND remaining_capacity < 5 ORDER BY remaining_capacity ASC",
      "intent": "Advanced sessions that are almost full (remaining capacity less than 5)",
      "manifest": "Advanced sessions that are almost full (remaining capacity less than 5)",
      "parameterized": {
        "parameterized_intent": "$1 sessions that are almost full (remaining capacity less than 5)",
        "parameterized_sql": "SELECT session_name, remaining_capacity, session_date, session_start_time FROM public.session WHERE learning_level = $1 AND remaining_capacity > 0 AND remaining_capacity < 5 ORDER BY remaining_capacity ASC"
      }
    },
    {
      "nlQuery": "Find sessions about Gemini",
      "sql": "SELECT name, format, session_date, description FROM ((SELECT s1.session_name AS name, s1.session_format AS format, s1.session_date AS session_date, s1.full_description AS description, (s1.full_description_embedding <=> public.embedding('text-embedding-005', 'Gemini')::public.vector) AS distance FROM public.session s1 ORDER BY distance LIMIT 10) UNION ALL (SELECT s2.session_name AS name, s2.session_format AS format, s2.session_date AS session_date, t.topic_desc AS description, (t.embedding <=> public.embedding('text-embedding-005', 'Gemini')::public.vector) AS distance FROM public.session s2 INNER JOIN public.session_topic_mapping stm ON s2.session_id = stm.session_id INNER JOIN public.session_topic t ON stm.topic = t.topic ORDER BY distance LIMIT 10)) AS combined_results ORDER BY distance LIMIT 10",
      "intent": "Find sessions about Gemini",
      "manifest": "Find sessions about a given topic",
      "parameterized": {
        "parameterized_intent": "Find sessions about $1",
        "parameterized_sql": "SELECT name, format, session_date, description FROM ((SELECT s1.session_name AS name, s1.session_format AS format, s1.session_date AS session_date, s1.full_description AS description, (s1.full_description_embedding <=> public.embedding('text-embedding-005', '$1')::public.vector) AS distance FROM public.session s1 ORDER BY distance LIMIT 10) UNION ALL (SELECT s2.session_name AS name, s2.session_format AS format, s2.session_date AS session_date, t.topic_desc AS description, (t.embedding <=> public.embedding('text-embedding-005', '$1')::public.vector) AS distance FROM public.session s2 INNER JOIN public.session_topic_mapping stm ON s2.session_id = stm.session_id INNER JOIN public.session_topic t ON stm.topic = t.topic ORDER BY distance LIMIT 10)) AS combined_results ORDER BY distance LIMIT 10"
      }
    }
  ]
}

Observação:no segundo modelo, usamos full_description_embedding, que é o nome da coluna no nosso esquema.

Carregar o contexto do QueryData no AlloyDB Studio

Para usar o contexto "Consultar dados", é necessário fazer upload dele para o banco de dados usando o AlloyDB Studio.

1. Abra o AlloyDB Studio no console do Google Cloud.
2. No painel esquerdo, na parte de baixo, você vai encontrar Conjuntos de contexto e três pontos.
3. Clique nele e escolha Criar conjunto de contexto.
4. Preencha a caixa de diálogo:
   • Nome: conference_context
   • Descrição: Conference Sessions QueryData Context
   • Fazer upload do arquivo de contexto: faça upload do arquivo JSON criado com o conteúdo acima.
5. Salvar os cards

A criação do contexto pode levar até 5 minutos.

Testar o contexto do QueryData

Depois de fazer upload, você pode testar diretamente no AlloyDB Studio.

1. Clique nos três pontos ao lado do contexto que você acabou de criar e escolha Testar conjunto de contexto (ou use a pílula do Gemini no editor de consultas e selecione esse contexto).
2. No comando de geração de SQL do Gemini, digite uma consulta em linguagem natural que corresponda ao nosso modelo:

   Advanced sessions that are almost full
   

3. Gere o SQL e verifique se ele corresponde ao modelo fornecido.
4. Tente uma consulta parametrizada mudando "Avançado" para "Iniciante" no comando de linguagem natural e veja se ela se adapta.

11. Limpar

Excluir cluster do AlloyDB

Para evitar cobranças contínuas na sua conta do Google Cloud, exclua os recursos criados durante este codelab.

Execute os comandos a seguir no Cloud Shell para excluir o cluster do AlloyDB (isso também vai excluir a instância):

export REGION=us-central1
export ADBCLUSTER=alloydb-next26-ai-demo-01

echo "=> Deleting AlloyDB Cluster (${ADBCLUSTER})..."
gcloud alloydb clusters delete $ADBCLUSTER --region=$REGION --force

Observação: o comando leva de 3 a 5 minutos para ser executado.

Se você criou um projeto especificamente para este codelab, exclua o projeto inteiro.

Excluir intervalo de IP e vpc-peering

⚠️ Aviso para projetos compartilhados:o script de limpeza abaixo também exclui a conexão de peering da VPC da rede de serviços (servicenetworking.googleapis.com). Isso é perfeitamente seguro e recomendado se você estiver usando um projeto descartável e isolado do codelab. No entanto, se você estiver executando isso em um projeto compartilhado ou de produção do Google Cloud, excluir esse peering vai desconectar instantaneamente outros bancos de dados gerenciados (como Cloud SQL ou Memorystore) que compartilham a mesma VPC. Se você tiver outros serviços que dependem dessa VPC, pule esta etapa.

PROJECT_ID=$(gcloud config get-value project)
echo "=> Deleting Service Networking VPC Peering..."
gcloud compute networks peerings delete servicenetworking-googleapis-com \
    --network=default \
    --project=${PROJECT_ID} --quiet || true

echo "=> Deleting Allocated IP Range for Managed Services..."
gcloud compute addresses delete psa-range \
    --global \
    --project=${PROJECT_ID} --quiet || true

Excluir arquivo local

Exclua o arquivo JSON local criado na etapa Work with QueryData in AlloyDB Studio.

12. Parabéns

Parabéns! Você aprendeu a usar vários recursos da IA do AlloyDB em um cenário unificado de sessões de conferência.

O que vimos

• Como ativar e usar funções de IA (ai.if, ai.rank) para filtragem e pontuação semânticas.
• Como implementar a Pesquisa híbrida usando índices ScaNN (vetor) e RUM (texto) com a fusão de classificação recíproca (RRF).
• Como usar o QueryData no AlloyDB Studio para gerar SQL previsível em linguagem natural.

Próximas etapas

• Consulte a documentação da IA do AlloyDB.
• Saiba mais sobre pgvector e ScaNN.

Documentos de referência

• Visão geral criada por IA do AlloyDB
• Consultas em linguagem natural