INV_TXN_MANAGER_PUB 0. 这个package 处理MTI 的数据, 包含下面一些 Procedure 和 Function 1. Procedure validate_group(), 输入参数 p_header_id, 这个存储过程会批次的处理同一个 p_header_id 的 MTI 数据. 被 process_transaction() 调用. 2. Procedure
INV_TXN_MANAGER_PUB
0. 这个package 处理MTI 的数据, 包含下面一些 Procedure 和 Function
1. Procedure validate_group(), 输入参数 p_header_id, 这个存储过程会批次的处理同一个 p_header_id 的 MTI 数据. 被 process_transaction() 调用.
2. Procedure validate_lines(), 输入参数 p_header_id, p_validation_level, 这个存储过程会验证 MTI 的单个record. 会调用 process_transaction().
3. Function post_temp_validation(), 输入参数 p_line_rec_type, 这个函数验证 MMTT 的record, 被 process_transaction() 调用.
4. Function get_open_period(), 输入参数 p_org_id, p_trans_date, 这个函数决定了Account Period, 被 validate_lines() 调用.
5. Function process_transaction(), 输入参数 p_table, p_header_id, p_commit, 输出 x_trans_count. 这个函数是 INV Transaction Manager 的接口 API, 负责处理 MTI MTT 的数据.
6. Function tmpinsert(), 输入参数 p_rowid, 这个函数负责把 MTI 的数据插入 MMTT, 被 process_transaction() 调用.
7. Procedure rel_reservations_mrp_update(), 输入参数 p_header_id, p_transaction_temp_id, 这个存储过程负责为MMTT 释放保留量并update MRP 表. 被 BaseTransaction.java 调用.
INV_LPN_TRX_PUB
0. 这个package 只包含 个函数, process_lpn_trx(), process_lpn_trx_line().
1. Function process_lpn_trx(), 输入参数 p_trx_hdr_id(MMTT header id), p_commit, p_proc_mode, p_process_trx, p_atomic, 输出参数 p_proc_msg, return_status, 这个API 是用来处理基于 LPN 的 transaction, 这个 API pack/unpack LPN, 更新 LPN 状态, 并调用 INV txn manager 更新数量.
2. Procedure process_trx_lpn_line(), 这个存储过程被 BaseTransaction.java 调用, 用来处理单个的 MMTT record.

Stored procedures are precompiled SQL statements in MySQL for improving performance and simplifying complex operations. 1. Improve performance: After the first compilation, subsequent calls do not need to be recompiled. 2. Improve security: Restrict data table access through permission control. 3. Simplify complex operations: combine multiple SQL statements to simplify application layer logic.

The working principle of MySQL query cache is to store the results of SELECT query, and when the same query is executed again, the cached results are directly returned. 1) Query cache improves database reading performance and finds cached results through hash values. 2) Simple configuration, set query_cache_type and query_cache_size in MySQL configuration file. 3) Use the SQL_NO_CACHE keyword to disable the cache of specific queries. 4) In high-frequency update environments, query cache may cause performance bottlenecks and needs to be optimized for use through monitoring and adjustment of parameters.

The reasons why MySQL is widely used in various projects include: 1. High performance and scalability, supporting multiple storage engines; 2. Easy to use and maintain, simple configuration and rich tools; 3. Rich ecosystem, attracting a large number of community and third-party tool support; 4. Cross-platform support, suitable for multiple operating systems.

The steps for upgrading MySQL database include: 1. Backup the database, 2. Stop the current MySQL service, 3. Install the new version of MySQL, 4. Start the new version of MySQL service, 5. Recover the database. Compatibility issues are required during the upgrade process, and advanced tools such as PerconaToolkit can be used for testing and optimization.

MySQL backup policies include logical backup, physical backup, incremental backup, replication-based backup, and cloud backup. 1. Logical backup uses mysqldump to export database structure and data, which is suitable for small databases and version migrations. 2. Physical backups are fast and comprehensive by copying data files, but require database consistency. 3. Incremental backup uses binary logging to record changes, which is suitable for large databases. 4. Replication-based backup reduces the impact on the production system by backing up from the server. 5. Cloud backups such as AmazonRDS provide automation solutions, but costs and control need to be considered. When selecting a policy, database size, downtime tolerance, recovery time, and recovery point goals should be considered.

MySQLclusteringenhancesdatabaserobustnessandscalabilitybydistributingdataacrossmultiplenodes.ItusestheNDBenginefordatareplicationandfaulttolerance,ensuringhighavailability.Setupinvolvesconfiguringmanagement,data,andSQLnodes,withcarefulmonitoringandpe

Optimizing database schema design in MySQL can improve performance through the following steps: 1. Index optimization: Create indexes on common query columns, balancing the overhead of query and inserting updates. 2. Table structure optimization: Reduce data redundancy through normalization or anti-normalization and improve access efficiency. 3. Data type selection: Use appropriate data types, such as INT instead of VARCHAR, to reduce storage space. 4. Partitioning and sub-table: For large data volumes, use partitioning and sub-table to disperse data to improve query and maintenance efficiency.

TooptimizeMySQLperformance,followthesesteps:1)Implementproperindexingtospeedupqueries,2)UseEXPLAINtoanalyzeandoptimizequeryperformance,3)Adjustserverconfigurationsettingslikeinnodb_buffer_pool_sizeandmax_connections,4)Usepartitioningforlargetablestoi


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