- About MogDB
- Quick Start
- MogDB Playground
- Container-based MogDB Installation
- Installation on a Single Node
- MogDB Access
- Use CLI to Access MogDB
- Use GUI to Access MogDB
- Use Middleware to Access MogDB
- Use Programming Language to Access MogDB
- Using Sample Dataset Mogila
- Characteristic Description
- Overview
- High Performance
- CBO Optimizer
- LLVM
- Vectorized Engine
- Hybrid Row-Column Store
- Adaptive Compression
- SQL by pass
- Kunpeng NUMA Architecture Optimization
- High Concurrency of Thread Pools
- SMP for Parallel Execution
- Xlog no Lock Flush
- Parallel Page-based Redo For Ustore
- Row-Store Execution to Vectorized Execution
- Astore Row Level Compression
- BTree Index Compression
- Tracing SQL Function
- Parallel Index Scan
- Enhancement of Tracing Backend Key Thread
- Ordering Operator Optimization
- High Availability (HA)
- Primary/Standby
- Logical Replication
- Logical Backup
- Physical Backup
- Automatic Job Retry upon Failure
- Ultimate RTO
- High Availability Based on the Paxos Protocol
- Cascaded Standby Server
- Delayed Replay
- Adding or Deleting a Standby Server
- Delaying Entering the Maximum Availability Mode
- Parallel Logical Decoding
- DCF
- CM(Cluster Manager)
- Global SysCache
- Using a Standby Node to Build a Standby Node
- Two City and Three Center DR
- CM Cluster Management Component Supporting Two Node Deployment
- Maintainability
- Database Security
- Access Control Model
- Separation of Control and Access Permissions
- Database Encryption Authentication
- Data Encryption and Storage
- Database Audit
- Network Communication Security
- Resource Label
- Unified Audit
- Dynamic Data Anonymization
- Row-Level Access Control
- Password Strength Verification
- Equality Query in a Fully-encrypted Database
- Ledger Database Mechanism
- Transparent Data Encryption
- Enterprise-Level Features
- Support for Functions and Stored Procedures
- SQL Hints
- Full-Text Indexing
- Copy Interface for Error Tolerance
- Partitioning
- Support for Advanced Analysis Functions
- Materialized View
- HyperLogLog
- Creating an Index Online
- Autonomous Transaction
- Global Temporary Table
- Pseudocolumn ROWNUM
- Stored Procedure Debugging
- JDBC Client Load Balancing and Read/Write Isolation
- In-place Update Storage Engine
- Publication-Subscription
- Foreign Key Lock Enhancement
- Data Compression in OLTP Scenarios
- Transaction Async Submit
- Index Creation Parallel Control
- Dynamic Partition Pruning
- COPY Import Optimization
- SQL Running Status Observation
- BRIN Index
- BLOOM Index
- Application Development Interfaces
- AI Capabilities
- AI4DB: Autonomous Database O&M
- DB4AI: Database-driven AI
- AI in DB
- ABO Optimizer
- Middleware
- Installation Guide
- Installation Preparation
- Container Installation
- PTK-based Installation
- OM-based Installation
- Manual Installation
- Recommended Parameter Settings
- Administrator Guide
- Localization
- Routine Maintenance
- Starting and Stopping MogDB
- Using the gsql Client for Connection
- Routine Maintenance
- Checking OS Parameters
- Checking MogDB Health Status
- Checking Database Performance
- Checking and Deleting Logs
- Checking Time Consistency
- Checking The Number of Application Connections
- Routinely Maintaining Tables
- Routinely Recreating an Index
- Exporting and Viewing the WDR
- Data Security Maintenance Suggestions
- Slow SQL Diagnosis
- Log Reference
- Primary and Standby Management
- MOT Engine
- Introducing MOT
- Using MOT
- Concepts of MOT
- Appendix
- Column-store Tables Management
- Backup and Restoration
- Two City and Three Center DR
- Importing and Exporting Data
- Importing Data
- Exporting Data
- Upgrade Guide
- AI Features Guide
- AI Features Overview
- AI4DB: Autonomous Database O&M
- DBMind Mode
- Components that Support DBMind
- AI Sub-functions of the DBMind
- X-Tuner: Parameter Tuning and Diagnosis
- Index-advisor: Index Recommendation
- Slow Query Diagnosis: Root Cause Analysis for Slow SQL Statements
- Forecast: Trend Prediction
- SQLdiag: Slow SQL Discovery
- SQL Rewriter
- Anomaly Detection
- DB4AI: Database-driven AI
- AI in DB
- Intelligence Explain: SQL Statement Query Time Prediction
- ABO Optimizer
- Intelligent Cardinality Estimation
- Adaptive Plan Selection
- Security Guide
- Developer Guide
- Application Development Guide
- Development Specifications
- Development Based on JDBC
- Overview
- JDBC Package, Driver Class, and Environment Class
- Development Process
- Loading the Driver
- Connecting to a Database
- Connecting to the Database (Using SSL)
- Connecting to the Database (Using UDS)
- Running SQL Statements
- Processing Data in a Result Set
- Closing a Connection
- Managing Logs
- Example: Common Operations
- Example: Retrying SQL Queries for Applications
- Example: Importing and Exporting Data Through Local Files
- Example 2: Migrating Data from a MY Database to MogDB
- Example: Logic Replication Code
- Example: Parameters for Connecting to the Database in Different Scenarios
- JDBC API Reference
- java.sql.Connection
- java.sql.CallableStatement
- java.sql.DatabaseMetaData
- java.sql.Driver
- java.sql.PreparedStatement
- java.sql.ResultSet
- java.sql.ResultSetMetaData
- java.sql.Statement
- javax.sql.ConnectionPoolDataSource
- javax.sql.DataSource
- javax.sql.PooledConnection
- javax.naming.Context
- javax.naming.spi.InitialContextFactory
- CopyManager
- JDBC-based Common Parameter Reference
- Development Based on ODBC
- Development Based on libpq
- Dependent Header Files of libpq
- Development Process
- Example
- Link Parameters
- libpq API Reference
- Database Connection Control Functions
- Database Statement Execution Functions
- Functions for Asynchronous Command Processing
- Functions for Canceling Queries in Progress
- Psycopg-Based Development
- Commissioning
- Stored Procedure
- User Defined Functions
- PL/pgSQL-SQL Procedural Language
- Scheduled Jobs
- Autonomous Transaction
- Logical Replication
- Extension
- Materialized View
- Materialized View Overview
- Full Materialized View
- Incremental Materialized View
- Partition Management
- Partition Pruning
- Recommendations For Choosing A Partitioning Strategy
- Application Development Guide
- Performance Tuning Guide
- System Optimization
- SQL Optimization
- WDR Snapshot
- Using the Vectorized Executor for Tuning
- TPC-C Performance Tunning Guide
- Reference Guide
- System Catalogs and System Views
- Overview of System Catalogs and System Views
- System Catalogs
- GS_ASP
- GS_AUDITING_POLICY
- GS_AUDITING_POLICY_ACCESS
- GS_AUDITING_POLICY_FILTERS
- GS_AUDITING_POLICY_PRIVILEGES
- GS_CLIENT_GLOBAL_KEYS
- GS_CLIENT_GLOBAL_KEYS_ARGS
- GS_COLUMN_KEYS
- GS_COLUMN_KEYS_ARGS
- GS_DB_PRIVILEGE
- GS_ENCRYPTED_COLUMNS
- GS_ENCRYPTED_PROC
- GS_GLOBAL_CHAIN
- GS_GLOBAL_CONFIG
- GS_MASKING_POLICY
- GS_MASKING_POLICY_ACTIONS
- GS_MASKING_POLICY_FILTERS
- GS_MATVIEW
- GS_MATVIEW_DEPENDENCY
- GS_MODEL_WAREHOUSE
- GS_OPT_MODEL
- GS_PACKAGE
- GS_POLICY_LABEL
- GS_RECYCLEBIN
- GS_TXN_SNAPSHOT
- GS_UID
- GS_WLM_EC_OPERATOR_INFO
- GS_WLM_INSTANCE_HISTORY
- GS_WLM_OPERATOR_INFO
- GS_WLM_PLAN_ENCODING_TABLE
- GS_WLM_PLAN_OPERATOR_INFO
- GS_WLM_SESSION_QUERY_INFO_ALL
- GS_WLM_USER_RESOURCE_HISTORY
- PG_AGGREGATE
- PG_AM
- PG_AMOP
- PG_AMPROC
- PG_APP_WORKLOADGROUP_MAPPING
- PG_ATTRDEF
- PG_ATTRIBUTE
- PG_AUTH_HISTORY
- PG_AUTH_MEMBERS
- PG_AUTHID
- PG_CAST
- PG_CLASS
- PG_COLLATION
- PG_CONSTRAINT
- PG_CONVERSION
- PG_DATABASE
- PG_DB_ROLE_SETTING
- PG_DEFAULT_ACL
- PG_DEPEND
- PG_DESCRIPTION
- PG_DIRECTORY
- PG_ENUM
- PG_EXTENSION
- PG_EXTENSION_DATA_SOURCE
- PG_FOREIGN_DATA_WRAPPER
- PG_FOREIGN_SERVER
- PG_FOREIGN_TABLE
- PG_HASHBUCKET
- PG_INDEX
- PG_INHERITS
- PG_JOB
- PG_JOB_PROC
- PG_LANGUAGE
- PG_LARGEOBJECT
- PG_LARGEOBJECT_METADATA
- PG_NAMESPACE
- PG_OBJECT
- PG_OPCLASS
- PG_OPERATOR
- PG_OPFAMILY
- PG_PARTITION
- PG_PLTEMPLATE
- PG_PROC
- PG_PUBLICATION
- PG_PUBLICATION_REL
- PG_RANGE
- PG_REPLICATION_ORIGIN
- PG_RESOURCE_POOL
- PG_REWRITE
- PG_RLSPOLICY
- PG_SECLABEL
- PG_SET
- PG_SHDEPEND
- PG_SHDESCRIPTION
- PG_SHSECLABEL
- PG_STATISTIC
- PG_STATISTIC_EXT
- PG_SUBSCRIPTION
- PG_SYNONYM
- PG_TABLESPACE
- PG_TRIGGER
- PG_TS_CONFIG
- PG_TS_CONFIG_MAP
- PG_TS_DICT
- PG_TS_PARSER
- PG_TS_TEMPLATE
- PG_TYPE
- PG_USER_MAPPING
- PG_USER_STATUS
- PG_WORKLOAD_GROUP
- PGXC_CLASS
- PGXC_GROUP
- PGXC_NODE
- PGXC_SLICE
- PLAN_TABLE_DATA
- STATEMENT_HISTORY
- System Views
- DV_SESSION_LONGOPS
- DV_SESSIONS
- GET_GLOBAL_PREPARED_XACTS(Discarded)
- GS_AUDITING
- GS_AUDITING_ACCESS
- GS_AUDITING_PRIVILEGE
- GS_ASYNC_SUBMIT_SESSIONS_STATUS
- GS_CLUSTER_RESOURCE_INFO
- GS_COMPRESSION
- GS_DB_PRIVILEGES
- GS_FILE_STAT
- GS_GSC_MEMORY_DETAIL
- GS_INSTANCE_TIME
- GS_LABELS
- GS_LSC_MEMORY_DETAIL
- GS_MASKING
- GS_MATVIEWS
- GS_OS_RUN_INFO
- GS_REDO_STAT
- GS_SESSION_CPU_STATISTICS
- GS_SESSION_MEMORY
- GS_SESSION_MEMORY_CONTEXT
- GS_SESSION_MEMORY_DETAIL
- GS_SESSION_MEMORY_STATISTICS
- GS_SESSION_STAT
- GS_SESSION_TIME
- GS_SQL_COUNT
- GS_STAT_SESSION_CU
- GS_THREAD_MEMORY_CONTEXT
- GS_TOTAL_MEMORY_DETAIL
- GS_WLM_CGROUP_INFO
- GS_WLM_EC_OPERATOR_STATISTICS
- GS_WLM_OPERATOR_HISTORY
- GS_WLM_OPERATOR_STATISTICS
- GS_WLM_PLAN_OPERATOR_HISTORY
- GS_WLM_REBUILD_USER_RESOURCE_POOL
- GS_WLM_RESOURCE_POOL
- GS_WLM_SESSION_HISTORY
- GS_WLM_SESSION_INFO
- GS_WLM_SESSION_INFO_ALL
- GS_WLM_SESSION_STATISTICS
- GS_WLM_USER_INFO
- GS_WRITE_TERM_LOG
- MPP_TABLES
- PG_AVAILABLE_EXTENSION_VERSIONS
- PG_AVAILABLE_EXTENSIONS
- PG_COMM_DELAY
- PG_COMM_RECV_STREAM
- PG_COMM_SEND_STREAM
- PG_COMM_STATUS
- PG_CONTROL_GROUP_CONFIG
- PG_CURSORS
- PG_EXT_STATS
- PG_GET_INVALID_BACKENDS
- PG_GET_SENDERS_CATCHUP_TIME
- PG_GROUP
- PG_GTT_ATTACHED_PIDS
- PG_GTT_RELSTATS
- PG_GTT_STATS
- PG_INDEXES
- PG_LOCKS
- PG_NODE_ENV
- PG_OS_THREADS
- PG_PREPARED_STATEMENTS
- PG_PREPARED_XACTS
- PG_PUBLICATION_TABLES
- PG_REPLICATION_ORIGIN_STATUS
- PG_REPLICATION_SLOTS
- PG_RLSPOLICIES
- PG_ROLES
- PG_RULES
- PG_RUNNING_XACTS
- PG_SECLABELS
- PG_SESSION_IOSTAT
- PG_SESSION_WLMSTAT
- PG_SETTINGS
- PG_SHADOW
- PG_STAT_ACTIVITY
- PG_STAT_ACTIVITY_NG
- PG_STAT_ALL_INDEXES
- PG_STAT_ALL_TABLES
- PG_STAT_BAD_BLOCK
- PG_STAT_BGWRITER
- PG_STAT_DATABASE
- PG_STAT_DATABASE_CONFLICTS
- PG_STAT_REPLICATION
- PG_STAT_SUBSCRIPTION
- PG_STAT_SYS_INDEXES
- PG_STAT_SYS_TABLES
- PG_STAT_USER_FUNCTIONS
- PG_STAT_USER_INDEXES
- PG_STAT_USER_TABLES
- PG_STAT_XACT_ALL_TABLES
- PG_STAT_XACT_SYS_TABLES
- PG_STAT_XACT_USER_FUNCTIONS
- PG_STAT_XACT_USER_TABLES
- PG_STATIO_ALL_INDEXES
- PG_STATIO_ALL_SEQUENCES
- PG_STATIO_ALL_TABLES
- PG_STATIO_SYS_INDEXES
- PG_STATIO_SYS_SEQUENCES
- PG_STATIO_SYS_TABLES
- PG_STATIO_USER_INDEXES
- PG_STATIO_USER_SEQUENCES
- PG_STATIO_USER_TABLES
- PG_STATS
- PG_TABLES
- PG_TDE_INFO
- PG_THREAD_WAIT_STATUS
- PG_TIMEZONE_ABBREVS
- PG_TIMEZONE_NAMES
- PG_TOTAL_MEMORY_DETAIL
- PG_TOTAL_USER_RESOURCE_INFO
- PG_TOTAL_USER_RESOURCE_INFO_OID
- PG_USER
- PG_USER_MAPPINGS
- PG_VARIABLE_INFO
- PG_VIEWS
- PG_WLM_STATISTICS
- PGXC_PREPARED_XACTS
- PLAN_TABLE
- Functions and Operators
- Logical Operators
- Comparison Operators
- Character Processing Functions and Operators
- Binary String Functions and Operators
- Bit String Functions and Operators
- Mode Matching Operators
- Mathematical Functions and Operators
- Date and Time Processing Functions and Operators
- Type Conversion Functions
- Geometric Functions and Operators
- Network Address Functions and Operators
- Text Search Functions and Operators
- JSON/JSONB Functions and Operators
- HLL Functions and Operators
- SEQUENCE Functions
- Array Functions and Operators
- Range Functions and Operators
- Aggregate Functions
- Window Functions(Analysis Functions)
- Security Functions
- Ledger Database Functions
- Encrypted Equality Functions
- Set Returning Functions
- Conditional Expression Functions
- System Information Functions
- System Administration Functions
- Configuration Settings Functions
- Universal File Access Functions
- Server Signal Functions
- Backup and Restoration Control Functions
- Snapshot Synchronization Functions
- Database Object Functions
- Advisory Lock Functions
- Logical Replication Functions
- Segment-Page Storage Functions
- Other Functions
- Undo System Functions
- Row-Store Compression System Functions
- Statistics Information Functions
- Trigger Functions
- Hash Function
- Prompt Message Function
- Global Temporary Table Functions
- Fault Injection System Function
- AI Feature Functions
- Dynamic Data Masking Functions
- Other System Functions
- Internal Functions
- Global SysCache Feature Functions
- Data Damage Detection and Repair Functions
- Obsolete Functions
- Supported Data Types
- Numeric Types
- Monetary Types
- Boolean Types
- Enumerated Types
- Character Types
- Binary Types
- Date/Time Types
- Geometric
- Network Address Types
- Bit String Types
- Text Search Types
- UUID
- JSON/JSONB Types
- HLL
- Array Types
- Range
- OID Types
- Pseudo-Types
- Data Types Supported by Column-store Tables
- XML Types
- Data Type Used by the Ledger Database
- SET Type
- SQL Syntax
- ABORT
- ALTER AGGREGATE
- ALTER AUDIT POLICY
- ALTER DATABASE
- ALTER DATA SOURCE
- ALTER DEFAULT PRIVILEGES
- ALTER DIRECTORY
- ALTER EXTENSION
- ALTER FOREIGN TABLE
- ALTER FUNCTION
- ALTER GLOBAL CONFIGURATION
- ALTER GROUP
- ALTER INDEX
- ALTER LANGUAGE
- ALTER LARGE OBJECT
- ALTER MASKING POLICY
- ALTER MATERIALIZED VIEW
- ALTER PACKAGE
- ALTER PROCEDURE
- ALTER PUBLICATION
- ALTER RESOURCE LABEL
- ALTER RESOURCE POOL
- ALTER ROLE
- ALTER ROW LEVEL SECURITY POLICY
- ALTER RULE
- ALTER SCHEMA
- ALTER SEQUENCE
- ALTER SERVER
- ALTER SESSION
- ALTER SUBSCRIPTION
- ALTER SYNONYM
- ALTER SYSTEM KILL SESSION
- ALTER SYSTEM SET
- ALTER TABLE
- ALTER TABLE PARTITION
- ALTER TABLE SUBPARTITION
- ALTER TABLESPACE
- ALTER TEXT SEARCH CONFIGURATION
- ALTER TEXT SEARCH DICTIONARY
- ALTER TRIGGER
- ALTER TYPE
- ALTER USER
- ALTER USER MAPPING
- ALTER VIEW
- ANALYZE | ANALYSE
- BEGIN
- CALL
- CHECKPOINT
- CLEAN CONNECTION
- CLOSE
- CLUSTER
- COMMENT
- COMMIT | END
- COMMIT PREPARED
- CONNECT BY
- COPY
- CREATE AGGREGATE
- CREATE AUDIT POLICY
- CREATE CAST
- CREATE CLIENT MASTER KEY
- CREATE COLUMN ENCRYPTION KEY
- CREATE DATABASE
- CREATE DATA SOURCE
- CREATE DIRECTORY
- CREATE EXTENSION
- CREATE FOREIGN TABLE
- CREATE FUNCTION
- CREATE GROUP
- CREATE INCREMENTAL MATERIALIZED VIEW
- CREATE INDEX
- CREATE LANGUAGE
- CREATE MASKING POLICY
- CREATE MATERIALIZED VIEW
- CREATE MODEL
- CREATE OPERATOR
- CREATE PACKAGE
- CREATE PROCEDURE
- CREATE PUBLICATION
- CREATE RESOURCE LABEL
- CREATE RESOURCE POOL
- CREATE ROLE
- CREATE ROW LEVEL SECURITY POLICY
- CREATE RULE
- CREATE SCHEMA
- CREATE SEQUENCE
- CREATE SERVER
- CREATE SUBSCRIPTION
- CREATE SYNONYM
- CREATE TABLE
- CREATE TABLE AS
- CREATE TABLE PARTITION
- CREATE TABLE SUBPARTITION
- CREATE TABLESPACE
- CREATE TEXT SEARCH CONFIGURATION
- CREATE TEXT SEARCH DICTIONARY
- CREATE TRIGGER
- CREATE TYPE
- CREATE USER
- CREATE USER MAPPING
- CREATE VIEW
- CREATE WEAK PASSWORD DICTIONARY
- CURSOR
- DEALLOCATE
- DECLARE
- DELETE
- DO
- DROP AGGREGATE
- DROP AUDIT POLICY
- DROP CAST
- DROP CLIENT MASTER KEY
- DROP COLUMN ENCRYPTION KEY
- DROP DATABASE
- DROP DATA SOURCE
- DROP DIRECTORY
- DROP EXTENSION
- DROP FOREIGN TABLE
- DROP FUNCTION
- DROP GLOBAL CONFIGURATION
- DROP GROUP
- DROP INDEX
- DROP LANGUAGE
- DROP MASKING POLICY
- DROP MATERIALIZED VIEW
- DROP MODEL
- DROP OPERATOR
- DROP OWNED
- DROP PACKAGE
- DROP PROCEDURE
- DROP PUBLICATION
- DROP RESOURCE LABEL
- DROP RESOURCE POOL
- DROP ROLE
- DROP ROW LEVEL SECURITY POLICY
- DROP RULE
- DROP SCHEMA
- DROP SEQUENCE
- DROP SERVER
- DROP SUBSCRIPTION
- DROP SYNONYM
- DROP TABLE
- DROP TABLESPACE
- DROP TEXT SEARCH CONFIGURATION
- DROP TEXT SEARCH DICTIONARY
- DROP TRIGGER
- DROP TYPE
- DROP USER
- DROP USER MAPPING
- DROP VIEW
- DROP WEAK PASSWORD DICTIONARY
- EXECUTE
- EXECUTE DIRECT
- EXPLAIN
- EXPLAIN PLAN
- FETCH
- GRANT
- INSERT
- LOCK
- MERGE INTO
- MOVE
- PREDICT BY
- PREPARE
- PREPARE TRANSACTION
- PURGE
- REASSIGN OWNED
- REFRESH INCREMENTAL MATERIALIZED VIEW
- REFRESH MATERIALIZED VIEW
- REINDEX
- RELEASE SAVEPOINT
- RESET
- REVOKE
- ROLLBACK
- ROLLBACK PREPARED
- ROLLBACK TO SAVEPOINT
- SAVEPOINT
- SELECT
- SELECT INTO
- SET
- SET CONSTRAINTS
- SET ROLE
- SET SESSION AUTHORIZATION
- SET TRANSACTION
- SHOW
- SHUTDOWN
- SNAPSHOT
- START TRANSACTION
- TIMECAPSULE TABLE
- TRUNCATE
- UPDATE
- VACUUM
- VALUES
- SHRINK
- SQL Reference
- MogDB SQL
- Keywords
- Constant and Macro
- Expressions
- Type Conversion
- Full Text Search
- Introduction
- Tables and Indexes
- Controlling Text Search
- Additional Features
- Parser
- Dictionaries
- Configuration Examples
- Testing and Debugging Text Search
- Limitations
- System Operation
- Controlling Transactions
- DDL Syntax Overview
- DML Syntax Overview
- DCL Syntax Overview
- Appendix
- GUC Parameters
- GUC Parameter Usage
- GUC Parameter List
- File Location
- Connection and Authentication
- Resource Consumption
- Write Ahead Log
- HA Replication
- Memory Table
- Query Planning
- Error Reporting and Logging
- Alarm Detection
- Statistics During the Database Running
- Load Management
- Automatic Vacuuming
- Default Settings of Client Connection
- Lock Management
- Version and Platform Compatibility
- Faut Tolerance
- Connection Pool Parameters
- MogDB Transaction
- Replication Parameters of Two Database Instances
- Developer Options
- Auditing
- CM Parameters
- Upgrade Parameters
- Miscellaneous Parameters
- Wait Events
- Query
- System Performance Snapshot
- Security Configuration
- Global Temporary Table
- HyperLogLog
- Scheduled Task
- Thread Pool
- User-defined Functions
- Backup and Restoration
- Undo
- DCF Parameters Settings
- Flashback
- Rollback Parameters
- Reserved Parameters
- AI Features
- Global SysCache Parameters
- Parameters Related to Efficient Data Compression Algorithms
- Appendix
- Schema
- Overview
- Information Schema
- DBE_PERF
- Overview
- OS
- Instance
- Memory
- File
- Object
- STAT_USER_TABLES
- SUMMARY_STAT_USER_TABLES
- GLOBAL_STAT_USER_TABLES
- STAT_USER_INDEXES
- SUMMARY_STAT_USER_INDEXES
- GLOBAL_STAT_USER_INDEXES
- STAT_SYS_TABLES
- SUMMARY_STAT_SYS_TABLES
- GLOBAL_STAT_SYS_TABLES
- STAT_SYS_INDEXES
- SUMMARY_STAT_SYS_INDEXES
- GLOBAL_STAT_SYS_INDEXES
- STAT_ALL_TABLES
- SUMMARY_STAT_ALL_TABLES
- GLOBAL_STAT_ALL_TABLES
- STAT_ALL_INDEXES
- SUMMARY_STAT_ALL_INDEXES
- GLOBAL_STAT_ALL_INDEXES
- STAT_DATABASE
- SUMMARY_STAT_DATABASE
- GLOBAL_STAT_DATABASE
- STAT_DATABASE_CONFLICTS
- SUMMARY_STAT_DATABASE_CONFLICTS
- GLOBAL_STAT_DATABASE_CONFLICTS
- STAT_XACT_ALL_TABLES
- SUMMARY_STAT_XACT_ALL_TABLES
- GLOBAL_STAT_XACT_ALL_TABLES
- STAT_XACT_SYS_TABLES
- SUMMARY_STAT_XACT_SYS_TABLES
- GLOBAL_STAT_XACT_SYS_TABLES
- STAT_XACT_USER_TABLES
- SUMMARY_STAT_XACT_USER_TABLES
- GLOBAL_STAT_XACT_USER_TABLES
- STAT_XACT_USER_FUNCTIONS
- SUMMARY_STAT_XACT_USER_FUNCTIONS
- GLOBAL_STAT_XACT_USER_FUNCTIONS
- STAT_BAD_BLOCK
- SUMMARY_STAT_BAD_BLOCK
- GLOBAL_STAT_BAD_BLOCK
- STAT_USER_FUNCTIONS
- SUMMARY_STAT_USER_FUNCTIONS
- GLOBAL_STAT_USER_FUNCTIONS
- Workload
- Session/Thread
- SESSION_STAT
- GLOBAL_SESSION_STAT
- SESSION_TIME
- GLOBAL_SESSION_TIME
- SESSION_MEMORY
- GLOBAL_SESSION_MEMORY
- SESSION_MEMORY_DETAIL
- GLOBAL_SESSION_MEMORY_DETAIL
- SESSION_STAT_ACTIVITY
- GLOBAL_SESSION_STAT_ACTIVITY
- THREAD_WAIT_STATUS
- GLOBAL_THREAD_WAIT_STATUS
- LOCAL_THREADPOOL_STATUS
- GLOBAL_THREADPOOL_STATUS
- SESSION_CPU_RUNTIME
- SESSION_MEMORY_RUNTIME
- STATEMENT_IOSTAT_COMPLEX_RUNTIME
- LOCAL_ACTIVE_SESSION
- Transaction
- Query
- STATEMENT
- SUMMARY_STATEMENT
- STATEMENT_COUNT
- GLOBAL_STATEMENT_COUNT
- SUMMARY_STATEMENT_COUNT
- GLOBAL_STATEMENT_COMPLEX_HISTORY
- GLOBAL_STATEMENT_COMPLEX_HISTORY_TABLE
- GLOBAL_STATEMENT_COMPLEX_RUNTIME
- STATEMENT_RESPONSETIME_PERCENTILE
- STATEMENT_COMPLEX_RUNTIME
- STATEMENT_COMPLEX_HISTORY_TABLE
- STATEMENT_COMPLEX_HISTORY
- STATEMENT_WLMSTAT_COMPLEX_RUNTIME
- STATEMENT_HISTORY
- Cache/IO
- STATIO_USER_TABLES
- SUMMARY_STATIO_USER_TABLES
- GLOBAL_STATIO_USER_TABLES
- STATIO_USER_INDEXES
- SUMMARY_STATIO_USER_INDEXES
- GLOBAL_STATIO_USER_INDEXES
- STATIO_USER_SEQUENCES
- SUMMARY_STATIO_USER_SEQUENCES
- GLOBAL_STATIO_USER_SEQUENCES
- STATIO_SYS_TABLES
- SUMMARY_STATIO_SYS_TABLES
- GLOBAL_STATIO_SYS_TABLES
- STATIO_SYS_INDEXES
- SUMMARY_STATIO_SYS_INDEXES
- GLOBAL_STATIO_SYS_INDEXES
- STATIO_SYS_SEQUENCES
- SUMMARY_STATIO_SYS_SEQUENCES
- GLOBAL_STATIO_SYS_SEQUENCES
- STATIO_ALL_TABLES
- SUMMARY_STATIO_ALL_TABLES
- GLOBAL_STATIO_ALL_TABLES
- STATIO_ALL_INDEXES
- SUMMARY_STATIO_ALL_INDEXES
- GLOBAL_STATIO_ALL_INDEXES
- STATIO_ALL_SEQUENCES
- SUMMARY_STATIO_ALL_SEQUENCES
- GLOBAL_STATIO_ALL_SEQUENCES
- GLOBAL_STAT_DB_CU
- GLOBAL_STAT_SESSION_CU
- Utility
- REPLICATION_STAT
- GLOBAL_REPLICATION_STAT
- REPLICATION_SLOTS
- GLOBAL_REPLICATION_SLOTS
- BGWRITER_STAT
- GLOBAL_BGWRITER_STAT
- GLOBAL_CKPT_STATUS
- GLOBAL_DOUBLE_WRITE_STATUS
- GLOBAL_PAGEWRITER_STATUS
- GLOBAL_RECORD_RESET_TIME
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Array Types
MogDB allows columns of a table to be defined as variable-length multidimensional arrays. Arrays of any built-in or user-defined base type, enum type, or composite type can be created. Arrays of domains are not yet supported.
Declaration of Array Types
To illustrate the use of array types, we create this table:
CREATE TABLE sal_emp (
name text,
pay_by_quarter integer[],
schedule text[][]
);
As shown, an array data type is named by appending square brackets ([]
) to the data type name of the array elements. The above command will create a table named sal_emp
with a column of type text
(name
), a one-dimensional array of type integer
(pay_by_quarter
), which represents the employee's salary by quarter, and a two-dimensional array of text
(schedule
), which represents the employee's weekly schedule.
The syntax for CREATE TABLE
allows the exact size of arrays to be specified, for example:
CREATE TABLE tictactoe (
squares integer[3][3]
);
However, the current implementation ignores any supplied array size limits, i.e., the behavior is the same as for arrays of unspecified length.
The current implementation does not enforce the declared number of dimensions either. Arrays of a particular element type are all considered to be of the same type, regardless of size or number of dimensions. So, declaring the array size or number of dimensions in CREATE TABLE
is simply documentation; it does not affect run-time behavior.
An alternative syntax, which conforms to the SQL standard by using the keyword ARRAY
, can be used for one-dimensional arrays. pay_by_quarter
could have been defined as:
pay_by_quarter integer ARRAY[4],
Or, if no array size is to be specified:
pay_by_quarter integer ARRAY,
As before, however, MogDB does not enforce the size restriction in any case.
Array Value Input
To write an array value as a literal constant, enclose the element values within curly braces and separate them by commas. (If you know C, this is not unlike the C syntax for initializing structures.) You can put double quotes around any element value, and must do so if it contains commas or curly braces. (More details appear below.) Thus, the general format of an array constant is the following:
'{ val1 delim val2 delim ... }'
where delim
is the delimiter character for the type, as recorded in its pg_type
entry. Among the standard data types provided in the MogDB distribution, all use a comma (,
), except for type box
which uses a semicolon (;
). Each val
is either a constant of the array element type, or a subarray. An example of an array constant is:
'{{1,2,3},{4,5,6},{7,8,9}}'
This constant is a two-dimensional, 3-by-3 array consisting of three subarrays of integers.
To set an element of an array constant to NULL, write NULL
for the element value. (Any upper- or lower-case variant of NULL
will do.) If you want an actual string value "NULL", you must put double quotes around it.
The constant is initially treated as a string and passed to the array input conversion routine. An explicit type specification might be necessary.
Now we can show some INSERT
statements:
INSERT INTO sal_emp
VALUES ('Bill',
'{10000, 10000, 10000, 10000}',
'{{"meeting", "lunch"}, {"training", "presentation"}}');
INSERT INTO sal_emp
VALUES ('Carol',
'{20000, 25000, 25000, 25000}',
'{{"breakfast", "consulting"}, {"meeting", "lunch"}}');
The result of the previous two inserts looks like this:
SELECT * FROM sal_emp;
name | pay_by_quarter | schedule
-------+---------------------------+-------------------------------------------
Bill | {10000,10000,10000,10000} | {{meeting,lunch},{training,presentation}}
Carol | {20000,25000,25000,25000} | {{breakfast,consulting},{meeting,lunch}}
(2 rows)
Multidimensional arrays must have matching extents for each dimension. A mismatch causes an error, for example:
INSERT INTO sal_emp
VALUES ('Bill',
'{10000, 10000, 10000, 10000}',
'{{"meeting", "lunch"}, {"meeting"}}');
ERROR: multidimensional arrays must have array expressions with matching dimensions
The ARRAY
constructor syntax can also be used:
INSERT INTO sal_emp
VALUES ('Bill',
ARRAY[10000, 10000, 10000, 10000],
ARRAY[['meeting', 'lunch'], ['training', 'presentation']]);
INSERT INTO sal_emp
VALUES ('Carol',
ARRAY[20000, 25000, 25000, 25000],
ARRAY[['breakfast', 'consulting'], ['meeting', 'lunch']]);
Notice that the array elements are ordinary SQL constants or expressions; for instance, string literals are single quoted, instead of double quoted as they would be in an array literal.
Accessing Arrays
Now, we can run some queries on the table. First, we show how to access a single element of an array. This query retrieves the names of the employees whose pay changed in the second quarter:
SELECT name FROM sal_emp WHERE pay_by_quarter[1] <> pay_by_quarter[2];
name
-------
Carol
(1 row)
The array subscript numbers are written within square brackets. By default MogDB uses a one-based numbering convention for arrays, that is, an array of n
elements starts with array[1]
and ends with array[n]
.
This query retrieves the third quarter pay of all employees:
SELECT pay_by_quarter[3] FROM sal_emp;
pay_by_quarter
----------------
10000
25000
(2 rows)
We can also access arbitrary rectangular slices of an array, or subarrays. An array slice is denoted by writing lower-bound:upper-bound
for one or more array dimensions. For example, this query retrieves the first item on Bill's schedule for the first two days of the week:
SELECT schedule[1:2][1:1] FROM sal_emp WHERE name = 'Bill';
schedule
------------------------
{{meeting},{training}}
(1 row)
If any dimension is written as a slice, i.e., contains a colon, then all dimensions are treated as slices. Any dimension that has only a single number (no colon) is treated as being from 1 to the number specified. For example, [2]
is treated as [1:2]
, as in this example:
SELECT schedule[1:2][2] FROM sal_emp WHERE name = 'Bill';
schedule
-------------------------------------------
{{meeting,lunch},{training,presentation}}
(1 row)
To avoid confusion with the non-slice case, it's best to use slice syntax for all dimensions, e.g., [1:2][1:1]
, not [2][1:1]
.
It is possible to omit the lower-bound
and/or upper-bound
of a slice specifier; the missing bound is replaced by the lower or upper limit of the array's subscripts. For example:
SELECT schedule[:2][2:] FROM sal_emp WHERE name = 'Bill';
schedule
------------------------
{{lunch},{presentation}}
(1 row)
SELECT schedule[:][1:1] FROM sal_emp WHERE name = 'Bill';
schedule
------------------------
{{meeting},{training}}
(1 row)
An array subscript expression will return null if either the array itself or any of the subscript expressions are null. Also, null is returned if a subscript is outside the array bounds (this case does not raise an error). For example, if schedule
currently has the dimensions [1:3][1:2]
then referencing schedule[3][3]
yields NULL. Similarly, an array reference with the wrong number of subscripts yields a null rather than an error.
An array slice expression likewise yields null if the array itself or any of the subscript expressions are null. However, in other cases such as selecting an array slice that is completely outside the current array bounds, a slice expression yields an empty (zero-dimensional) array instead of null. (This does not match non-slice behavior and is done for historical reasons.) If the requested slice partially overlaps the array bounds, then it is silently reduced to just the overlapping region instead of returning null.
The current dimensions of any array value can be retrieved with the array_dims
function:
SELECT array_dims(schedule) FROM sal_emp WHERE name = 'Carol';
array_dims
------------
[1:2][1:2]
(1 row)
array_dims
produces a text
result, which is convenient for people to read but perhaps inconvenient for programs. Dimensions can also be retrieved with array_upper
and array_lower
, which return the upper and lower bound of a specified array dimension, respectively:
SELECT array_upper(schedule, 1) FROM sal_emp WHERE name = 'Carol';
array_upper
-------------
2
(1 row)
array_length
will return the length of a specified array dimension:
SELECT array_length(schedule, 1) FROM sal_emp WHERE name = 'Carol';
array_length
--------------
2
(1 row)
Modifying Arrays
An array value can be replaced completely:
UPDATE sal_emp SET pay_by_quarter = '{25000,25000,27000,27000}'
WHERE name = 'Carol';
or using the ARRAY
expression syntax:
UPDATE sal_emp SET pay_by_quarter = ARRAY[25000,25000,27000,27000]
WHERE name = 'Carol';
An array can also be updated at a single element:
UPDATE sal_emp SET pay_by_quarter[4] = 15000
WHERE name = 'Bill';
or updated in a slice:
UPDATE sal_emp SET pay_by_quarter[1:2] = '{27000,27000}'
WHERE name = 'Carol';
The slice syntaxes with omitted lower-bound
and/or upper-bound
can be used too, but only when updating an array value that is not NULL or zero-dimensional (otherwise, there is no existing subscript limit to substitute).
A stored array value can be enlarged by assigning to elements not already present. Any positions between those previously present and the newly assigned elements will be filled with nulls. For example, if array myarray
currently has 4 elements, it will have six elements after an update that assigns to myarray[6]
; myarray[5]
will contain null. Currently, enlargement in this fashion is only allowed for one-dimensional arrays, not multidimensional arrays.
Subscripted assignment allows creation of arrays that do not use one-based subscripts. For example one might assign to myarray[-2:7]
to create an array with subscript values from -2 to 7.
New array values can also be constructed using the concatenation operator, ||
:
SELECT ARRAY[1,2] || ARRAY[3,4];
?column?
-----------
{1,2,3,4}
(1 row)
SELECT ARRAY[5,6] || ARRAY[[1,2],[3,4]];
?column?
---------------------
{{5,6},{1,2},{3,4}}
(1 row)
The concatenation operator allows a single element to be pushed onto the beginning or end of a one-dimensional array. It also accepts two N
-dimensional arrays, or an N
-dimensional and an N+1
-dimensional array.
When a single element is pushed onto either the beginning or end of a one-dimensional array, the result is an array with the same lower bound subscript as the array operand. For example:
SELECT array_dims(1 || '[0:1]={2,3}'::int[]);
array_dims
------------
[0:2]
(1 row)
SELECT array_dims(ARRAY[1,2] || 3);
array_dims
------------
[1:3]
(1 row)
When two arrays with an equal number of dimensions are concatenated, the result retains the lower bound subscript of the left-hand operand's outer dimension. The result is an array comprising every element of the left-hand operand followed by every element of the right-hand operand. For example:
SELECT array_dims(ARRAY[1,2] || ARRAY[3,4,5]);
array_dims
------------
[1:5]
(1 row)
SELECT array_dims(ARRAY[[1,2],[3,4]] || ARRAY[[5,6],[7,8],[9,0]]);
array_dims
------------
[1:5][1:2]
(1 row)
When an N
-dimensional array is pushed onto the beginning or end of an N+1
-dimensional array, the result is analogous to the element-array case above. Each N
-dimensional sub-array is essentially an element of the N+1
-dimensional array's outer dimension. For example:
SELECT array_dims(ARRAY[1,2] || ARRAY[[3,4],[5,6]]);
array_dims
------------
[1:3][1:2]
(1 row)
An array can also be constructed by using the functions array_prepend
, array_append
, or array_cat
. The first two only support one-dimensional arrays, but array_cat
supports multidimensional arrays. Some examples:
SELECT array_prepend(1, ARRAY[2,3]);
array_prepend
---------------
{1,2,3}
(1 row)
SELECT array_append(ARRAY[1,2], 3);
array_append
--------------
{1,2,3}
(1 row)
SELECT array_cat(ARRAY[1,2], ARRAY[3,4]);
array_cat
-----------
{1,2,3,4}
(1 row)
SELECT array_cat(ARRAY[[1,2],[3,4]], ARRAY[5,6]);
array_cat
---------------------
{{1,2},{3,4},{5,6}}
(1 row)
SELECT array_cat(ARRAY[5,6], ARRAY[[1,2],[3,4]]);
array_cat
---------------------
{{5,6},{1,2},{3,4}}
In simple cases, the concatenation operator discussed above is preferred over direct use of these functions. However, because the concatenation operator is overloaded to serve all three cases, there are situations where use of one of the functions is helpful to avoid ambiguity. For example consider:
SELECT ARRAY[1, 2] || '{3, 4}'; -- the untyped literal is taken as an array
?column?
-----------
{1,2,3,4}
SELECT ARRAY[1, 2] || '7'; -- so is this one
ERROR: malformed array literal: "7"
SELECT ARRAY[1, 2] || NULL; -- so is an undecorated NULL
?column?
----------
{1,2}
(1 row)
SELECT array_append(ARRAY[1, 2], NULL); -- this might have been meant
array_append
--------------
{1,2,NULL}
In the examples above, the parser sees an integer array on one side of the concatenation operator, and a constant of undetermined type on the other. The heuristic it uses to resolve the constant's type is to assume it's of the same type as the operator's other input - in this case, integer array. So the concatenation operator is presumed to represent array_cat
, not array_append
. When that's the wrong choice, it could be fixed by casting the constant to the array's element type; but explicit use of array_append
might be a preferable solution.
Searching in Arrays
To search for a value in an array, each value must be checked. This can be done manually, if you know the size of the array. For example:
SELECT * FROM sal_emp WHERE pay_by_quarter[1] = 10000 OR
pay_by_quarter[2] = 10000 OR
pay_by_quarter[3] = 10000 OR
pay_by_quarter[4] = 10000;
However, this quickly becomes tedious for large arrays, and is not helpful if the size of the array is unknown. The above query could be replaced by:
SELECT * FROM sal_emp WHERE 10000 = ANY (pay_by_quarter);
In addition, you can find rows where the array has all values equal to 10000 with:
SELECT * FROM sal_emp WHERE 10000 = ALL (pay_by_quarter);
Alternatively, the generate_subscripts
function can be used. For example:
SELECT * FROM
(SELECT pay_by_quarter,
generate_subscripts(pay_by_quarter, 1) AS s
FROM sal_emp) AS foo
WHERE pay_by_quarter[s] = 10000;
You can also search an array using the &&
operator, which checks whether the left operand overlaps with the right operand. For instance:
SELECT * FROM sal_emp WHERE pay_by_quarter && ARRAY[10000];
This and other array operators are further described in Array Functions and Operators.
You can also search for specific values in an array using the array_position
and array_positions
functions. The former returns the subscript of the first occurrence of a value in an array; the latter returns an array with the subscripts of all occurrences of the value in the array. For example:
SELECT array_position(ARRAY['sun','mon','tue','wed','thu','fri','sat'], 'mon');
array_positions
-----------------
2
SELECT array_positions(ARRAY[1, 4, 3, 1, 3, 4, 2, 1], 1);
array_positions
-----------------
{1,4,8}
Tip: Arrays are not sets; searching for specific array elements can be a sign of database misdesign. Consider using a separate table with a row for each item that would be an array element. This will be easier to search, and is likely to scale better for a large number of elements.
Array Input and Output Syntax
The external text representation of an array value consists of items that are interpreted according to the I/O conversion rules for the array's element type, plus decoration that indicates the array structure. The decoration consists of curly braces ({
and }
) around the array value plus delimiter characters between adjacent items. The delimiter character is usually a comma (,
) but can be something else: it is determined by the typdelim
setting for the array's element type. Among the standard data types provided in the MogDB distribution, all use a comma, except for type box
, which uses a semicolon (;
). In a multidimensional array, each dimension (row, plane, cube, etc.) gets its own level of curly braces, and delimiters must be written between adjacent curly-braced entities of the same level.
The array output routine will put double quotes around element values if they are empty strings, contain curly braces, delimiter characters, double quotes, backslashes, or white space, or match the word NULL
. Double quotes and backslashes embedded in element values will be backslash-escaped. For numeric data types it is safe to assume that double quotes will never appear, but for textual data types one should be prepared to cope with either the presence or absence of quotes.
By default, the lower bound index value of an array's dimensions is set to one. To represent arrays with other lower bounds, the array subscript ranges can be specified explicitly before writing the array contents. This decoration consists of square brackets ([]
) around each array dimension's lower and upper bounds, with a colon (:
) delimiter character in between. The array dimension decoration is followed by an equal sign (=
). For example:
SELECT f1[1][-2][3] AS e1, f1[1][-1][5] AS e2
FROM (SELECT '[1:1][-2:-1][3:5]={{{1,2,3},{4,5,6}}}'::int[] AS f1) AS ss;
e1 | e2
----+----
1 | 6
(1 row)
The array output routine will include explicit dimensions in its result only when there are one or more lower bounds different from one.
If the value written for an element is NULL
(in any case variant), the element is taken to be NULL. The presence of any quotes or backslashes disables this and allows the literal string value "NULL" to be entered. Also, for backward compatibility with pre-versions of MogDB, the array_nulls configuration parameter can be turned off
to suppress recognition of NULL
as a NULL.
As shown previously, when writing an array value you can use double quotes around any individual array element. You must do so if the element value would otherwise confuse the array-value parser. For example, elements containing curly braces, commas (or the data type's delimiter character), double quotes, backslashes, or leading or trailing whitespace must be double-quoted. Empty strings and strings matching the word NULL
must be quoted, too. To put a double quote or backslash in a quoted array element value, precede it with a backslash. Alternatively, you can avoid quotes and use backslash-escaping to protect all data characters that would otherwise be taken as array syntax.
You can add whitespace before a left brace or after a right brace. You can also add whitespace before or after any individual item string. In all of these cases the whitespace will be ignored. However, whitespace within double-quoted elements, or surrounded on both sides by non-whitespace characters of an element, is not ignored.
Tip: The
ARRAY
constructor syntax is often easier to work with than the array-literal syntax when writing array values in SQL commands. InARRAY
, individual element values are written the same way they would be written when not members of an array.