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Official website download address: Community DL Page
Windows 10 installation ignores (third-party and graphical visualization tools are selected for installation)
1. Start using
1. Start the postgreSQL service
Enter the service installation location/bin, execute the cmd command, and start the service through the command
pg_ctl.exe -D "D:\Program Files\PostgreSQL\12\data" start
#Description: Replace D:\Program Files\PostgreSQL\12\data with the actual /data storage directory during installation
If the following results appear during execution, the startup is successful!
Startup exception, solution:
1. Delete the existing /data directory
2. Reinitialize the /data storage file and execute
initdb.exe -D "data storage location" -E UTF-8 --locale=chs -U postgres -W
Example: C:\Program Files\PostgreSQL\12\data #This is the default location
2. Connect to the database locally and create test libraries and tables. This time, Navicat Premium 15 version is used to connect.
Create a test database - test_db
Create a test data table - test sets the table to auto-increment the primary key
(1) Create a test data table
CREATE TABLE "public"."test" ( "id" int4 NOT NULL, "name" varchar(255) COLLATE "pg_catalog"."default", "create_time" timestamp(6), CONSTRAINT "test_pkey" PRIMARY KEY ("id") ) ; ALTER TABLE "public"."test" OWNER TO "postgres"; COMMENT ON COLUMN "public"."test"."id" IS '主键'; COMMENT ON COLUMN "public"."test"."name" IS '姓名'; COMMENT ON COLUMN "public"."test"."create_time" IS '时间';
(2) Create a primary key auto-increment sequence (select table—>Others—>New sequence)
(3) Primary key column association sequence settings
nextval('sequence name'::regclass)
(4) Support data type description
| name |
Alias |
describe |
| bigint |
you8 |
Signed 8-byte integer |
| bigserial |
serial8 |
Auto-increasing 8-byte integer |
| bit [ (n) ] |
Fixed length bit string |
|
| bit varying [ (n) ] |
wander [ (n) ] |
variable length bit string |
| boolean |
bool |
Logical boolean (true/false) |
| box |
Ordinary box on plane |
|
| bytea |
binary data ( "byte array" ） |
|
| character [ (n) ] |
char [ (n) ] |
Fixed length string |
| character varying [ (n) ] |
varchar [ (n) ] |
variable length string |
| cidr |
IPv4 or IPv6 network address |
|
| circle |
circle on plane |
|
| date |
Calendar date (year, month, day) |
|
| double precision |
float8 |
Double precision floating point number (8 bytes) |
| inet |
IPv4 or IPv6 host address |
|
| integer |
int int4 you8 |
-32768~ +32767 -21474836478 ~ 2147483647 -9223372036854775808 ~ +9223372036854775807 |
| interval [ fields ] [ (p) ] |
period |
|
| json |
Text JSON data |
|
| jsonb |
Binary JSON data, decomposed |
|
| line |
Infinitely long line on the plane |
|
| lsg |
line segment on plane |
|
| macadr |
MAC (Media Access Control) address |
|
| Macaddr8 |
MAC (Media Access Control) address (EUI-64 format) |
|
| money |
currency quantity |
|
| numeric [ (p, s) ] |
decimal [ (p, s) ] |
Exact numbers with selectable precision |
| path |
geometric path on plane |
|
| pg_lsn |
PostgreSQL Log sequence number |
|
| point |
Geometric points on the plane |
|
| polygon |
Closed geometric path on plane |
|
| real |
float4 |
Single precision floating point number (4 bytes) |
| smallint |
int2 |
Signed 2-byte integer |
| smallserial |
serial2 |
Auto-increasing 2-byte integer |
| serial |
serial4 |
Auto-increasing 4-byte integer |
| text |
variable length string |
|
| time [ (p) ] [ without time zone ] |
Time of day (no time zone) |
|
| time [ (p) ] with time zone |
timetz |
Time of day, including time zone |
| timestamp [ (p) ] [ without time zone ] |
Date and time (no time zone) |
|
| timestamp [ (p) ] with time zone |
timestamptz |
Date and time, including time zone |
| tsquery |
Text search query |
|
| tsvector |
文本搜索文档 |
|
| txid_snapshot |
用户级别事务ID快照 |
|
| uuid |
通用唯一标识码 |
|
| xml |
XML数据 |
（5）、事务说明
在PostgreSQL中，开启一个事务需要将SQL命令用BEGIN和COMMIT命令包围起来。事务提交
BEGIN; UPDATE accounts SET balance = balance - 100.00 WHERE name = 'Alice'; -- etc etc COMMIT;
记住那个银行数据库，假设我们从Alice的账户扣款100美元，然后存款到Bob的账户，结果直到最后才发现我们应该存到Wally的账户。我们可以通过使用保存点来做这件事：
事务回退 SAVEPOINT和 ROLLBACK
BEGIN; UPDATE accounts SET balance = balance - 100.00 WHERE name = 'Alice'; SAVEPOINT my_savepoint; UPDATE accounts SET balance = balance + 100.00 WHERE name = 'Bob'; -- oops ... forget that and use Wally's account ROLLBACK TO my_savepoint; UPDATE accounts SET balance = balance + 100.00 WHERE name = 'Wally'; COMMIT;
（6）、索引说明
Btree索引
Btree索引使用Btree数据结构来存储索引数据，可用于处理等值查询和范围查询，包括＜、＜=、=、＞=、＞等运算符，以及BETWEEN、IN、IS NULL、IS NOT NULL 等条件。
Btree索引可用于模式匹配查询，如“col LIKE′foo%′”或“col～′^foo′”，但是不能用于“col LIKE′%bar′”之类的后缀模糊匹配查询。Btree索引还可以用于查询结果集排序，如ORDER BY排序。
Hash索引
Hash索引根据每一行数据的索引字段计算哈希码，并维护哈希码、记录指针对应关系。对于哈希码相同的数据来说，可以采用链表来解决冲突。Hash索引的查询速度很快。
GiST索引
GiST（Generalized Search Tree）是一种平衡的树型结构访问方法，可作为一种基础模板来实现任意索引模式。B-tree索引和许多其他的索引模式都可以用GiST索引来实现。GiST 索引适用于多维数据类型和集合数据类型。GiST 多列索引支持在查询条件中包含索引字段的子集。PostgreSQL包含了全文检索、几何数据类型等多个用GiST实现的索引方法。
SP-GiST索引
SP-GiST索引与GiST索引类似，可作为一种基础模板来实现多种搜索方法。SP-GiST索引主要实现非平衡的基于硬盘的数据结构，如四叉树、k-d树和radix树。
GIN索引
GIN索引是一种通用倒排索引（GIN stands for generalized inverted indexes），可以处理包含多个键值，如 hstore, array，jsonb, 和 range 类型。用它来全文搜索或JSON键值的效率很高。GIN 允许用户开发自定义访问方法的数据类型索引，可以支持多种不同用户定义的索引策略。
BRIN索引
BRIN索引BRIN表示块范围索引。BRIN索引存储连续相邻的数据块统计信息，可以大大缩小索引占用空间。对于数据量比较大的表来说，BRIN索引比B-Tree索引插入数据的速度要快，两者的范围查询效率相当。BRIN索引通常用于线性顺序排列的列，如订单表的创建日期。
布尔过滤索引
Bloom Filter is a space-efficient random data structure that uses a bit array to represent a set concisely and can determine whether an element belongs to the set. This high efficiency of Bloom Filter comes at a certain cost: when determining whether an element belongs to a certain set, elements that do not belong to this set may be mistaken for belonging to this set (false positive). Therefore, Bloom Filter is not suitable for those "zero error" applications. In applications that can tolerate low error rates, Bloom Filter exchanges very few errors for great savings in storage space.
It is not recommended to use indexes in the following scenarios:
Do not use indexes for tables with small data volumes
Tables with frequent large-volume insert and update operations do not need to be indexed
There are a large number of null values on the column and the index should not be built.
Column values are frequently maintained and indexes should not be built.