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Google Cloud Documentation
  • Documentation
    • More
    • Overview
    • Guides
    • Reference
    • Samples
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  • Console
  • Discover
  • Product overview
  • Spanner editions overview
  • Security, privacy, risk, and compliance overview
  • PostgreSQL interface
  • Spanner for non-relational workloads
    • Non-relational overview
    • Cassandra interface
  • Get started
  • Spanner proof of concept playbook
  • Set up your environment
  • Create and query a database
    • Use the Google Cloud console
    • Use the gcloud CLI
  • Manage your data using the Google Cloud console
  • Client libraries
    • C++ quickstart
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    • Go quickstart
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  • Drivers
    • Set up with drivers
    • JDBC quickstart
    • Go database/sql quickstart
    • ADO.NET quickstart
    • PostgreSQL drivers quickstart
  • Spanner CLI
    • Spanner CLI quickstart
    • Spanner CLI commands
  • Free trial instances
    • Free trial instances overview
    • Create a free trial instance
  • Data residency overview
  • Create and manage
  • Instances
    • Instances overview
    • Nodes and processing units
    • Regional, dual-region, and multi-region configurations
    • Region types
    • Replication
    • Geo-partition data
      • Geo-partitioning overview
      • Create and manage instance partitions
      • Create and manage data placements
      • Indexes and geo-partitioning
    • Leader-aware routing
    • Global and regional service endpoints
    • Tiered storage
    • Create and manage instances
    • Create and manage instance configurations
    • Change dual-region quorum
    • Move an instance
    • Autoscale instances
      • Autoscaling overview
      • Managed autoscaler
      • Open source Autoscaler tool
        • Autoscaler tool overview
        • Deploy the Autoscaler tool to Cloud Run functions
        • Deploy the Autoscaler tool to GKE
    • Control access and organize instances using tags
    • Organize instances and view costs using labels
  • Databases
    • Databases overview
    • Choose between GoogleSQL and PostgreSQL
    • Create and manage databases
    • Prevent accidental database deletion
    • Schema object drop protection
    • Modify the leader region of a database
    • Set the default time zone for a database
  • Manage resources using Data Catalog
  • Design and manage a database schema
    • Schemas overview
    • Schema design best practices
    • Make schema updates
    • Schema update best practices
    • Create and manage named schemas
    • Views overview
    • Create and manage views
    • Secondary indexes
    • Foreign keys
    • Primary key default values management
    • Create and manage foreign key relationships
    • Create and manage check constraints
    • Create and manage generated columns
    • Store arbitrary precision numeric data
    • Create and manage sequences
    • Manage table names
    • Create and manage locality groups
  • Routines
    • Remote functions
  • Manage and observe long-running operations
  • Configure time to live (TTL)
    • TTL overview
    • Manage data retention with TTL
    • TTL metrics and monitoring
  • Connect
  • Connect to a PostgreSQL-dialect database
  • Connect PostgreSQL clients to Spanner using PGAdapter
    • PGAdapter overview
    • Get PGAdapter
    • Start PGAdapter
    • PGAdapter session management commands
    • Connect PGAdapter to the emulator
  • Connect to Spanner using the Cassandra Adapter
  • Create and connect a Compute Engine VM instance to access Spanner
  • Connect to Spanner with a GKE cluster
  • Connect to Spanner from other Google Cloud services
  • Authenticate to Spanner
  • Secure and control access
  • Access control with IAM
    • IAM overview
    • Apply IAM roles
  • Fine-grained access control
    • Fine-grained access control overview
    • Fine-grained access control for change streams
    • Fine-grained access control for sequences
    • Fine-grained access control for models
    • Configure fine-grained access control
    • Access a database with fine-grained access control
    • Fine-grained access control privileges
    • Fine-grained access control system roles
  • Add a custom organization policy
  • Data encryption
    • Customer-managed encryption keys (CMEK)
      • CMEK overview
      • Secure a database using CMEK
    • Data encryption in transit
  • Migrate
  • Migration process
    • Migration overview
    • Assess your migration
    • Migrate your schema
    • Migrate your application
    • Optimize your schema and application performance
    • Migrate your data
    • Validate your data
    • Configure cutover and fallback mechanisms
  • Migration tools
    • Migration tools overview
    • Set up Spanner migration tool (SMT)
  • Primary key migration
    • Primary key migration overview
    • Migrate primary keys
  • Migrate from MySQL
    • MySQL migration overview
    • MySQL schema migration
      • Migrate schema from MySQL overview
      • Use SMT to migrate schema from MySQL
    • Migrate your MySQL data
    • Configure fallback for MySQL
  • Load sample data
  • Migrate from DynamoDB
  • Migrate from Oracle
  • Migrate from PostgreSQL
    • Migrate to a GoogleSQL-dialect database
    • Migrate to a PostgreSQL-dialect database
  • Migrate from Cassandra
  • Migrate Spanner to a PostgreSQL database
  • Import and export data
  • Import and export overview
  • Import, export, and modify data using Dataflow
  • Import and export data in Avro format
    • Import Spanner Avro files
    • Export data from Spanner to Avro
    • Import data from non-Spanner databases
  • Import and export data in CSV format
  • Import a database from Cloud SQL
  • Import data from PostgreSQL using COPY
  • Bulk loading best practices
  • Disaster recovery
  • Disaster recovery overview
  • Back up databases
    • Backups overview
    • Create backups
    • Create and manage backup schedules
    • Manage backups
  • Restore databases
    • Restore overview
    • Restore from a backup
  • Point-in-time recovery (PITR)
    • PITR overview
    • Recover data using PITR
  • Develop
  • Write SQL with Gemini assistance
  • Use case best practices
    • Spanner as a gaming database
  • Integrate language frameworks
    • Spanner with Hibernate
      • Integrate with Hibernate ORM (GoogleSQL)
      • Integrate with Hibernate ORM (PostgreSQL)
      • Write a Hibernate app that connects to Spanner
    • Spanner with Spring Data JPA
      • Integrate with Spring Data JPA (GoogleSQL)
      • Integrate with Spring Data JPA (PostgreSQL)
    • Spanner with Spring Data JDBC
      • Integrate with Spring Data JDBC (GoogleSQL)
      • Integrate with Spring Data JDBC (PostgreSQL)
    • Spanner with MyBatis
      • Integrate with MyBatis and Spring Boot (GoogleSQL)
      • Integrate with MyBatis and Spring Boot (PostgreSQL)
    • Spanner with Spring Data
    • Write a Spring Boot app that connects to Spanner
    • Spanner with GORM
      • Integrate with GORM (GoogleSQL)
      • Integrate with GORM (PostgreSQL)
    • Spanner with Django ORM
    • Spanner with SQLAlchemy
      • Integrate with SQLAlchemy (GoogleSQL)
      • Integrate with SQLAlchemy (PostgreSQL)
    • Spanner with Active Record
    • Spanner with Entity Framework Core
  • Use transactions
    • Transactions overview
    • Timestamp bounds
    • Commit timestamps
      • In GoogleSQL-dialect databases
      • In PostgreSQL-dialect databases
    • TrueTime and external consistency
    • Isolation levels
      • Isolation levels overview
      • Use repeatable read isolation
      • Use SELECT FOR UPDATE in serializable isolation
      • Use SELECT FOR UPDATE in repeatable read isolation
    • Concurrency control
    • Throughput optimized writes
    • Retrieve commit statistics for a transaction
  • Sessions
  • SQL best practices
  • Work with pipe query syntax
  • Read data
    • Reads outside of transactions
    • Directed reads
    • Read lease
    • Use Data Boost independent compute resources for reads
      • Data Boost overview
      • Run federated queries with Data Boost
      • Export data with Data Boost
      • Use Data Boost in your applications
      • Monitor Data Boost usage
      • Monitor and manage Data Boost quota usage
    • Use saved queries
      • Saved queries overview
      • Create and manage saved queries
  • Modify data
    • Modify data using the Google Cloud console
    • Modify data using the gcloud CLI
    • Modify data using DML
      • Insert, update, and delete data using DML
      • Partitioned DML
      • DML best practices
    • Modify data using mutations
    • Compare DML with mutations
    • Modify data using batch write
  • Work with data types
    • Work with arrays
      • In GoogleSQL-dialect databases
      • In PostgreSQL-dialect databases
    • Work with STRUCT objects
    • Work with NUMERIC data
    • Work with JSON data
    • Work with JSONB data
    • Work with protocol buffers in GoogleSQL
  • Develop and test
    • Emulate Spanner locally
    • Use Terraform with Spanner
    • Configure custom timeouts and retries
    • Configure statement timeout
    • Configure transaction timeout
  • Process and view data
    • Dataflow templates
    • Stream out data changes
      • Change streams overview
      • Create and manage change streams
      • Build change streams connections using Dataflow
      • Build change streams connections to Kafka
      • Change streams partitions, records, and queries
    • Integrate Spanner with IntelliJ
    • Integrate Spanner with Looker
    • Integrate Spanner with Liquibase
  • Full-text search
    • Full-text search overview
    • Tokenization and Search Indexes
      • Tokenization
      • Search indexes
      • Numeric search indexes
      • JSON search indexes
      • Partition search indexes
      • Combine TOKENLISTs
    • Full-text search queries
      • Query overview
      • Search multiple columns
      • Mix full-text and non-text queries
      • Rank search results
      • Perform a substring search
      • Search with query enhancement
      • Accelerate pattern-matching functions
      • Find approximate matches with fuzzy search
      • Perform top-k pattern matching
      • Perform a search using facets
      • Paginate search results
    • Hybrid full-text and vector search patterns
    • Search versus secondary indexes
  • Install MySQL functions in Spanner
  • Implement multi-tenancy in Spanner
  • Build data agents with conversational analytics
  • Query database in natural language with QueryData
  • Spanner AI and machine learning
  • Spanner AI overview
  • Get started using Spanner for generative AI applications
  • Spanner integration with Agent Platform
  • Vector search
    • Vector search overview
    • Generate embeddings
      • Get Agent Platform text embeddings
      • Generate vector embeddings in bulk using partitioned DML
    • Perform K-nearest neighbors search
    • Choose the best vector distance function
    • Approximate nearest neighbors (ANN)
      • Perform ANN search with vector indexes
      • Create and manage vector indexes
      • Vector indexing best practices
    • Export embeddings to Agent Platform Vector Search
    • Vector search best practices
    • Troubleshoot vector search
  • Generate predictions
    • Generate ML predictions using SQL
    • Use Generative AI with a sample ecommerce application
    • Generate ML predictions using the Spanner emulator
  • Integrate with AI technologies
    • Build LLM-powered applications using LangChain
    • Use Spanner with agents
    • Best practices for securing agent interactions with MCP
    • Build applications using LlamaIndex
    • Use the Spanner remote MCP server
  • Spanner Graph
  • Product overview
  • Set up and query Spanner Graph
  • Spanner Graph schema
    • Schema overview
    • Create and manage a Spanner Graph schema with DDL
    • Create and manage a Spanner Graph schema visually
    • Best practices for designing a schema
    • Use SQL views to create a property graph
      • Overview of graphs created from SQL views
      • Create a graph from SQL views
  • Manage Spanner Graph data
  • Spanner Graph queries
    • Queries overview
    • Work with paths
    • Best practices for tuning queries
    • Use full-text search with Spanner Graph
    • Use vector search with Spanner Graph
  • Spanner Graph algorithms
    • Graph algorithms overview
    • Run algorithms
    • Algorithm schema requirements and feature compatibility
    • Algorithms catalog
    • Best practices for running algorithms on Spanner Graph
  • Spanner Graph visualizations
    • Use Spanner Graph visualizations
    • Work with Spanner Graph visualization integrations
  • Manage schemaless data with Spanner Graph
  • Load BigQuery data into Spanner Graph
  • Migrate to Spanner Graph
  • Spanner Graph reference for openCypher users
  • Troubleshoot Spanner Graph
  • Monitor
  • Capture telemetry signals
    • Signal capture overview
    • Trace collection
      • Trace collection overview
      • Set up trace collection using OpenTelemetry
    • Monitor Spanner using the Database insights MCP server
    • Metrics
      • Metrics list
      • Client-side metric collection
        • View and manage client-side metrics
        • Client-side metrics description
      • Custom client-side metric collection
        • Capture custom client-side metrics using OpenTelemetry
        • Capture custom client-side metrics using OpenCensus
    • Audit logs
  • Monitor instances
    • Monitor instance performance using insights
    • Monitor instances using Cloud Monitoring
  • Optimize and troubleshoot
  • Optimize Spanner performance
    • Performance overview
    • Analyze query performance
    • Monitor active queries
    • Query optimizer
      • Query optimizer overview
      • Query optimizer versions
      • List query optimizer versions
      • Manage the query optimizer
    • Query execution plans
    • Tune a query using the query plan visualizer
    • Accelerate analytical queries using the columnar engine
      • Spanner columnar engine overview
      • Configure Spanner columnar engine
      • Query columnar data
      • Monitor columnar engine
    • Find hotspots in your database
    • Use the index advisor
  • Manage split points for anticipated traffic increase
    • Pre-splitting overview
    • Create and manage split points
  • Manually trigger major compaction in a Spanner database
  • Analyze usage patterns with Key Visualizer
    • Key Visualizer overview
    • Access Key Visualizer
    • Explore Key Visualizer heatmaps
    • Key Visualizer heatmap patterns
  • Troubleshoot latency
    • Latency points in a Spanner request
    • Identify where latency occurs
    • Use metrics to diagnose latency
    • Calculate streaming and partition request latency
    • Identify transactions that cause high latencies
  • Troubleshoot issues using built-in statistics tables
    • Built-in statistics tables overview
    • Active partitioned DMLs statistics
    • Columns operations statistics
    • Lock statistics
    • Oldest active queries statistics
    • Query statistics
    • Read statistics
    • Split statistics
    • Table operations statistics
    • Table sizes statistics
    • Transaction statistics
    • Vector index statistics
  • Troubleshoot instance utilization
    • CPU utilization overview
    • Troubleshoot high CPU utilization
    • Storage utilization
  • Troubleshoot performance regressions
  • Monitor and troubleshoot with Gemini assistance
  • Troubleshoot CMEK org policy violations
  • Troubleshoot with request tags and transaction tags
  • Troubleshoot deadline exceeded errors
  • Troubleshoot Agent Platform integration errors
  • Error codes
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Compute capacity, nodes and processing units