System catalog tables and views

本文详细介绍了Greenplum数据库中的系统表和视图,包括以gp_为前缀的并行特性相关表和以pg_为前缀的标准PostgreSQL系统目录表。这些表对于理解Greenplum的数据仓库工作负载至关重要。

摘要生成于 C知道 ,由 DeepSeek-R1 满血版支持, 前往体验 >

System Catalog Reference : This is a reference of the system catalog tables and views of Greenplum Database. All system tables related to the parallel features of Greenplum Database are prefixed with gp_. Tables prefixed with pg_ are either standard PostgreSQL system catalog tables (which are also used in Greenplum Database), or are related to features Greenplum has added to enhance PostgreSQL for data warehousing workloads. Note that the global system catalog for Greenplum Database resides on the master instance.
System Tables - Greenplum
•gp_configuration (no longer used, see gp_segment_configuration)
•gp_configuration_history
•gp_db_interfaces
•gp_distribution_policy
•gp_fastsequence
•gp_fault_strategy
•gp_global_sequence
•gp_id
•gp_interfaces
•gp_master_mirroring
•gp_persistent_database_node
•gp_persistent_filespace_node
•gp_persistent_relation_node
•gp_persistent_tablespace_node
•gp_relation_node
•gp_san_configuration
•gp_segment_configuration
•gp_version_at_initdb
•gpexpand.status
•gpexpand.status_detail

System Views - Greenplum

•gp_distributed_log
•gp_distributed_xacts
•gp_pgdatabase
•gp_resqueue_status
•gp_transaction_log
•gpexpand.expansion_progress

System Views

Greenplum Database also contains the following system views currently not available in PostgreSQL.
•pg_max_external_files (shows number of external table files allowed per segment host when using the file protocol)
•pg_partition_columns
•pg_partition_templates
•pg_partitions
•pg_resqueue_attributes
•pg_resqueue_status deprecated (use gp_toolkit.gp_resqueue_status)
•pg_stat_resqueues
•pg_user_mappings (not implemented in 4.1 - for a future release)
System Tables
•pg_aggregate
•pg_am
•pg_amop
•pg_amproc
•pg_appendonly
•pg_appendonly_alter_column (not implemented in 4.1 - for a future release)
•pg_attrdef
•pg_attribute
•pg_auth_members
•pg_authid
•pg_autovacuum
•pg_cast
•pg_class
•pg_constraint
•pg_conversion
•pg_database
•pg_depend
•pg_description
•pg_exttable
•pg_filespace
•pg_filespace_entry
•pg_foreign_data_wrapper (not implemented in 4.1 - for a future release)
•pg_foreign_server (not implemented in 4.1 - for a future release)
•pg_foreign_table (not implemented in 4.1 - for a future release)
•pg_index
•pg_inherits
•pg_language
•pg_largeobject
•pg_listener
•pg_namespace
•pg_opclass
•pg_operator
•pg_partition
•pg_partition_rule
•pg_pltemplate
•pg_proc
•pg_resourcetype
•pg_resqueue
•pg_resqueuecapability
•pg_rewrite
•pg_shdepend
•pg_shdescription
•pg_stat_last_operation
•pg_stat_last_shoperation
•pg_statistic
•pg_tablespace
•pg_trigger
•pg_type
•pg_user_mapping (not implemented in 4.1 - for a future release)
•pg_window




pg_tables
### MySQL Schema Management and Operations In the context of managing schemas within a MySQL database, several critical operations can be performed to ensure efficient data organization and retrieval. A schema in MySQL refers to a set of objects such as tables, views, stored procedures, etc., that are logically grouped together. #### Creating Schemas To create a new schema or database, one uses the `CREATE DATABASE` statement: ```sql CREATE DATABASE IF NOT EXISTS my_database; ``` This command creates a new schema named `my_database`, only if it does not already exist[^1]. #### Selecting Schemas Once multiple databases have been created, switching between them is achieved using the `USE` keyword followed by the name of the desired database: ```sql USE my_database; ``` After executing this command, all subsequent SQL commands will operate on `my_database`. #### Managing Tables Within Schemas Creating tables inside a specific schema involves specifying column definitions along with any constraints required for maintaining integrity rules: ```sql CREATE TABLE employees ( id INT AUTO_INCREMENT PRIMARY KEY, first_name VARCHAR(50), last_name VARCHAR(50), hire_date DATE ); ``` Altering existing table structures also falls under schema management activities. For instance, adding an index might improve query performance significantly when searching through large datasets: ```sql ALTER TABLE employees ADD INDEX idx_hire_date (hire_date); ``` Dropping unnecessary indexes helps reduce overhead during insertions while ensuring optimal storage usage: ```sql DROP INDEX idx_hire_date ON employees; ``` Similarly, dropping entire tables removes both structure and content associated with those entities permanently from the system catalog: ```sql DROP TABLE employees; ``` #### Query Optimization Using Indexes Indexes play a crucial role in optimizing queries involving joins across different relations or filtering based upon certain criteria. However, misuse may lead to degraded write performances due to additional maintenance costs incurred whenever records get inserted/updated/deleted. For example, creating composite keys over frequently accessed columns ensures faster lookups without sacrificing too much space efficiency: ```sql CREATE UNIQUE INDEX uk_employee_email ON employees(email); ``` #### Handling Data Integrity Constraints Defining foreign key relationships guarantees referential consistency among related pieces of information spread out throughout various parts of your application's domain model: ```sql CREATE TABLE departments ( dept_id INT AUTO_INCREMENT PRIMARY KEY, department_name VARCHAR(100) NOT NULL ); CREATE TABLE employee_departments ( emp_dept_id INT AUTO_INCREMENT PRIMARY KEY, emp_id INT, dept_id INT, FOREIGN KEY fk_emp(emp_id) REFERENCES employees(id), FOREIGN KEY fk_dept(dept_id) REFERENCES departments(dept_id) ); ``` These examples illustrate how proper planning around logical divisions like schemas contributes towards building robust applications capable of handling complex business requirements efficiently.
评论 1
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值