mirror of
https://gitee.com/dromara/mayfly-go
synced 2025-11-04 08:20:25 +08:00
272 lines
9.0 KiB
Go
272 lines
9.0 KiB
Go
package postgres
|
||
|
||
import (
|
||
"database/sql"
|
||
"fmt"
|
||
"mayfly-go/internal/db/dbm/dbi"
|
||
"mayfly-go/pkg/utils/anyx"
|
||
"mayfly-go/pkg/utils/collx"
|
||
"regexp"
|
||
"strings"
|
||
"time"
|
||
)
|
||
|
||
type PgsqlDialect struct {
|
||
dc *dbi.DbConn
|
||
}
|
||
|
||
func (pd *PgsqlDialect) GetMetaData() dbi.MetaData {
|
||
return &PgsqlMetaData{dc: pd.dc}
|
||
}
|
||
|
||
// GetDbProgram 获取数据库程序模块，用于数据库备份与恢复
|
||
func (pd *PgsqlDialect) GetDbProgram() (dbi.DbProgram, error) {
|
||
return nil, fmt.Errorf("该数据库类型不支持数据库备份与恢复: %v", pd.dc.Info.Type)
|
||
}
|
||
|
||
func (pd *PgsqlDialect) BatchInsert(tx *sql.Tx, tableName string, columns []string, values [][]any, duplicateStrategy int) (int64, error) {
|
||
// 执行批量insert sql，跟mysql一样 pg或高斯支持批量insert语法
|
||
// insert into table_name (column1, column2, ...) values (value1, value2, ...), (value1, value2, ...), ...
|
||
|
||
// 把二维数组转为一维数组
|
||
var args []any
|
||
for _, v := range values {
|
||
args = append(args, v...)
|
||
}
|
||
|
||
// 构建占位符字符串 "($1, $2, $3), ($4, $5, $6), ..." 用于指定参数
|
||
var placeholders []string
|
||
for i := 0; i < len(args); i += len(columns) {
|
||
var placeholder []string
|
||
for j := 0; j < len(columns); j++ {
|
||
placeholder = append(placeholder, fmt.Sprintf("$%d", i+j+1))
|
||
}
|
||
placeholders = append(placeholders, "("+strings.Join(placeholder, ", ")+")")
|
||
}
|
||
|
||
// 根据冲突策略生成后缀
|
||
suffix := ""
|
||
if pd.dc.Info.Type == dbi.DbTypeGauss {
|
||
// 高斯db使用ON DUPLICATE KEY UPDATE 语法参考 https://support.huaweicloud.com/distributed-devg-v3-gaussdb/gaussdb-12-0607.html#ZH-CN_TOPIC_0000001633948138
|
||
suffix = pd.gaussOnDuplicateStrategySql(duplicateStrategy, tableName, columns)
|
||
} else {
|
||
// pgsql 默认使用 on conflict 语法参考 http://www.postgres.cn/docs/12/sql-insert.html
|
||
// vastbase语法参考 https://docs.vastdata.com.cn/zh/docs/VastbaseE100Ver3.0.0/doc/SQL%E8%AF%AD%E6%B3%95/INSERT.html
|
||
// kingbase语法参考 https://help.kingbase.com.cn/v8/development/sql-plsql/sql/SQL_Statements_9.html#insert
|
||
suffix = pd.pgsqlOnDuplicateStrategySql(duplicateStrategy, tableName, columns)
|
||
}
|
||
|
||
sqlStr := fmt.Sprintf("insert into %s (%s) values %s %s", pd.dc.Info.Type.QuoteIdentifier(tableName), strings.Join(columns, ","), strings.Join(placeholders, ", "), suffix)
|
||
// 执行批量insert sql
|
||
|
||
return pd.dc.TxExec(tx, sqlStr, args...)
|
||
}
|
||
|
||
// pgsql默认唯一键冲突策略
|
||
func (pd PgsqlDialect) pgsqlOnDuplicateStrategySql(duplicateStrategy int, tableName string, columns []string) string {
|
||
suffix := ""
|
||
if duplicateStrategy == dbi.DuplicateStrategyIgnore {
|
||
suffix = " \n on conflict do nothing"
|
||
} else if duplicateStrategy == dbi.DuplicateStrategyUpdate {
|
||
// 生成 on conflict () do update set column1 = excluded.column1, column2 = excluded.column2, ...
|
||
var updateColumns []string
|
||
for _, col := range columns {
|
||
updateColumns = append(updateColumns, fmt.Sprintf("%s = excluded.%s", col, col))
|
||
}
|
||
// 查询唯一键名,拼接冲突sql
|
||
_, keyRes, _ := pd.dc.Query("SELECT constraint_name FROM information_schema.table_constraints WHERE constraint_schema = $1 AND table_name = $2 AND constraint_type in ('PRIMARY KEY', 'UNIQUE') ", pd.currentSchema(), tableName)
|
||
if len(keyRes) > 0 {
|
||
for _, re := range keyRes {
|
||
key := anyx.ToString(re["constraint_name"])
|
||
if key != "" {
|
||
suffix += fmt.Sprintf(" \n on conflict on constraint %s do update set %s \n", key, strings.Join(updateColumns, ", "))
|
||
}
|
||
}
|
||
}
|
||
}
|
||
return suffix
|
||
}
|
||
|
||
// 高斯db唯一键冲突策略,使用ON DUPLICATE KEY UPDATE 参考：https://support.huaweicloud.com/distributed-devg-v3-gaussdb/gaussdb-12-0607.html#ZH-CN_TOPIC_0000001633948138
|
||
func (pd PgsqlDialect) gaussOnDuplicateStrategySql(duplicateStrategy int, tableName string, columns []string) string {
|
||
suffix := ""
|
||
if duplicateStrategy == dbi.DuplicateStrategyIgnore {
|
||
suffix = " \n ON DUPLICATE KEY UPDATE NOTHING"
|
||
} else if duplicateStrategy == dbi.DuplicateStrategyUpdate {
|
||
|
||
// 查出表里的唯一键涉及的字段
|
||
var uniqueColumns []string
|
||
indexs, err := pd.GetMetaData().GetTableIndex(tableName)
|
||
if err == nil {
|
||
for _, index := range indexs {
|
||
if index.IsUnique {
|
||
cols := strings.Split(index.ColumnName, ",")
|
||
for _, col := range cols {
|
||
if !collx.ArrayContains(uniqueColumns, strings.ToLower(col)) {
|
||
uniqueColumns = append(uniqueColumns, strings.ToLower(col))
|
||
}
|
||
}
|
||
}
|
||
}
|
||
}
|
||
|
||
suffix = " \n ON DUPLICATE KEY UPDATE "
|
||
for i, col := range columns {
|
||
// ON DUPLICATE KEY UPDATE语句不支持更新唯一键字段，所以得去掉
|
||
if !collx.ArrayContains(uniqueColumns, pd.dc.Info.Type.RemoveQuote(strings.ToLower(col))) {
|
||
suffix += fmt.Sprintf("%s = excluded.%s", col, col)
|
||
if i < len(columns)-1 {
|
||
suffix += ", "
|
||
}
|
||
}
|
||
}
|
||
}
|
||
return suffix
|
||
}
|
||
|
||
// 从连接信息中获取数据库和schema信息
|
||
func (pd *PgsqlDialect) currentSchema() string {
|
||
dbName := pd.dc.Info.Database
|
||
schema := ""
|
||
arr := strings.Split(dbName, "/")
|
||
if len(arr) == 2 {
|
||
schema = arr[1]
|
||
}
|
||
return schema
|
||
}
|
||
|
||
func (pd *PgsqlDialect) GetDataConverter() dbi.DataConverter {
|
||
return converter
|
||
}
|
||
|
||
var (
|
||
// 数字类型
|
||
numberRegexp = regexp.MustCompile(`(?i)int|double|float|number|decimal|byte|bit`)
|
||
// 日期时间类型
|
||
datetimeRegexp = regexp.MustCompile(`(?i)datetime|timestamp`)
|
||
// 日期类型
|
||
dateRegexp = regexp.MustCompile(`(?i)date`)
|
||
// 时间类型
|
||
timeRegexp = regexp.MustCompile(`(?i)time`)
|
||
|
||
converter = new(DataConverter)
|
||
)
|
||
|
||
type DataConverter struct {
|
||
}
|
||
|
||
func (dc *DataConverter) GetDataType(dbColumnType string) dbi.DataType {
|
||
if numberRegexp.MatchString(dbColumnType) {
|
||
return dbi.DataTypeNumber
|
||
}
|
||
// 日期时间类型
|
||
if datetimeRegexp.MatchString(dbColumnType) {
|
||
return dbi.DataTypeDateTime
|
||
}
|
||
// 日期类型
|
||
if dateRegexp.MatchString(dbColumnType) {
|
||
return dbi.DataTypeDate
|
||
}
|
||
// 时间类型
|
||
if timeRegexp.MatchString(dbColumnType) {
|
||
return dbi.DataTypeTime
|
||
}
|
||
return dbi.DataTypeString
|
||
}
|
||
|
||
func (dc *DataConverter) FormatData(dbColumnValue any, dataType dbi.DataType) string {
|
||
str := fmt.Sprintf("%v", dbColumnValue)
|
||
switch dataType {
|
||
case dbi.DataTypeDateTime: // "2024-01-02T22:16:28.545377+08:00"
|
||
res, _ := time.Parse(time.RFC3339, str)
|
||
return res.Format(time.DateTime)
|
||
case dbi.DataTypeDate: // "2024-01-02T00:00:00Z"
|
||
res, _ := time.Parse(time.RFC3339, str)
|
||
return res.Format(time.DateOnly)
|
||
case dbi.DataTypeTime: // "0000-01-01T22:16:28.545075+08:00"
|
||
res, _ := time.Parse(time.RFC3339, str)
|
||
return res.Format(time.TimeOnly)
|
||
}
|
||
return anyx.ConvString(dbColumnValue)
|
||
}
|
||
|
||
func (dc *DataConverter) ParseData(dbColumnValue any, dataType dbi.DataType) any {
|
||
// 如果dataType是datetime而dbColumnValue是string类型，则需要转换为time.Time类型
|
||
_, ok := dbColumnValue.(string)
|
||
if dataType == dbi.DataTypeDateTime && ok {
|
||
res, _ := time.Parse(time.RFC3339, anyx.ToString(dbColumnValue))
|
||
return res
|
||
}
|
||
if dataType == dbi.DataTypeDate && ok {
|
||
res, _ := time.Parse(time.DateOnly, anyx.ToString(dbColumnValue))
|
||
return res
|
||
}
|
||
if dataType == dbi.DataTypeTime && ok {
|
||
res, _ := time.Parse(time.TimeOnly, anyx.ToString(dbColumnValue))
|
||
return res
|
||
}
|
||
return dbColumnValue
|
||
}
|
||
|
||
func (pd *PgsqlDialect) IsGauss() bool {
|
||
return strings.Contains(pd.dc.Info.Params, "gauss")
|
||
}
|
||
|
||
func (pd *PgsqlDialect) CopyTable(copy *dbi.DbCopyTable) error {
|
||
tableName := copy.TableName
|
||
// 生成新表名,为老表明+_copy_时间戳
|
||
newTableName := tableName + "_copy_" + time.Now().Format("20060102150405")
|
||
// 执行根据旧表创建新表
|
||
_, err := pd.dc.Exec(fmt.Sprintf("create table %s (like %s)", newTableName, tableName))
|
||
if err != nil {
|
||
return err
|
||
}
|
||
|
||
// 复制数据
|
||
if copy.CopyData {
|
||
go func() {
|
||
_, _ = pd.dc.Exec(fmt.Sprintf("insert into %s select * from %s", newTableName, tableName))
|
||
}()
|
||
}
|
||
|
||
// 查询旧表的自增字段名 重新设置新表的序列序列器
|
||
_, res, err := pd.dc.Query(fmt.Sprintf("select column_name from information_schema.columns where table_name = '%s' and column_default like 'nextval%%'", tableName))
|
||
if err != nil {
|
||
return err
|
||
}
|
||
|
||
for _, re := range res {
|
||
colName := anyx.ConvString(re["column_name"])
|
||
if colName != "" {
|
||
|
||
// 查询自增列当前最大值
|
||
_, maxRes, err := pd.dc.Query(fmt.Sprintf("select max(%s) max_val from %s", colName, tableName))
|
||
if err != nil {
|
||
return err
|
||
}
|
||
maxVal := anyx.ConvInt(maxRes[0]["max_val"])
|
||
// 序列起始值为1或当前最大值+1
|
||
if maxVal <= 0 {
|
||
maxVal = 1
|
||
} else {
|
||
maxVal += 1
|
||
}
|
||
|
||
// 之所以不用tableName_colName_seq是因为gauss会自动创建同名的序列，且无法修改序列起始值，所以直接使用新序列值
|
||
newSeqName := fmt.Sprintf("%s_%s_copy_seq", newTableName, colName)
|
||
|
||
// 创建自增序列，当前最大值为旧表最大值
|
||
_, err = pd.dc.Exec(fmt.Sprintf("CREATE SEQUENCE %s START %d INCREMENT 1", newSeqName, maxVal))
|
||
if err != nil {
|
||
return err
|
||
}
|
||
// 将新表的自增主键序列与主键列相关联
|
||
_, err = pd.dc.Exec(fmt.Sprintf("alter table %s alter column %s set default nextval('%s')", newTableName, colName, newSeqName))
|
||
if err != nil {
|
||
return err
|
||
}
|
||
}
|
||
}
|
||
return err
|
||
}
|