Schema Rules for UBL…and Maybe for You

mysql prometheus规则MySQL Prometheus规则Prometheus是一种开源的监控系统和时间序列数据库，它被广泛用于监控和警报系统。

而MySQL是一种流行的关系型数据库，被广泛应用于各种应用程序中。

本文将探讨如何使用Prometheus规则来监控和管理MySQL数据库。

一、什么是Prometheus规则Prometheus规则是一种用于定义告警规则的方式，它可以根据一组表达式和条件来生成告警。

这些规则可以用于监控和警报系统，以便在出现问题时及时通知管理员。

二、为什么使用Prometheus规则监控MySQLMySQL是一个常见的数据库，但在生产环境中，它可能会遇到各种问题，如性能下降、连接超时、磁盘空间不足等。

使用Prometheus规则可以实时监控和警报这些问题，帮助管理员及时发现和解决问题，提高系统的可靠性和稳定性。

三、如何配置Prometheus规则来监控MySQL1. 安装和配置Prometheus：首先需要安装和配置Prometheus，具体操作可以参考官方文档或相关教程。

2. 创建MySQL监控规则文件：在Prometheus的配置文件中，可以定义一个名为mysql.rules的规则文件，用于监控和管理MySQL数据库。

3. 定义MySQL告警规则：在mysql.rules文件中，可以定义一系列告警规则，例如：- 监控MySQL连接数：可以定义一个告警规则，当MySQL连接数超过阈值时，生成告警。

- 监控MySQL查询响应时间：可以定义一个告警规则，当MySQL查询响应时间超过预设阈值时，生成告警。

- 监控MySQL磁盘空间：可以定义一个告警规则，当MySQL磁盘空间不足时，生成告警。

- 监控MySQL慢查询：可以定义一个告警规则，当MySQL出现慢查询时，生成告警。

4. 配置告警通知方式：在Prometheus的配置文件中，可以配置告警通知方式，例如通过邮件、短信或Slack等方式通知管理员。

postgresql schema 命名规则PostgreSQL Schema 命名规则在PostgreSQL 中，Schema 是一种将数据库对象组织起来的机制。

它可以用于划分不同模块、部门或项目的数据库对象，并提供了更好的管理和安全性控制。

当使用Schema 时，一般情况下需要遵循一些命名规则，以确保数据库结构的一致性和可维护性。

本文将详细介绍PostgreSQL Schema 命名规则，并提供一些最佳实践建议。

一、Schema 命名规则的重要性正确命名数据库对象是良好数据库设计的基础。

Schema 命名规则的重要性在于：1. 清晰的架构设计：一个好的Schema 命名约定可以帮助开发人员和管理人员更好地理解数据库的结构和设计。

2. 组织和分类对象：通过使用Schema，可以将相关的数据库对象分组并进行分类，提升数据库的可维护性和管理性。

3. 权限管理：Schema 可以用于实现数据库对象的访问控制和权限管理。

通过合理的Schema 命名规则，可以更加方便地设置和管理权限。

二、Schema 命名规则的一般准则1. 使用小写字母：在PostgreSQL 中，Schema 名称默认是不区分大小写的，但为了提高可读性和可维护性，建议使用小写字母命名Schema。

2. 避免特殊字符：尽量避免在Schema 名称中使用特殊字符，如空格、连字符、斜杠等。

这样可以避免在查询和引用Schema 名称时产生困难。

3. 使用可读性强的名称：选择一个能够清晰表达Schema 功能和意义的名称。

避免使用缩写或简写，以免造成困扰和误解。

4. 命名一致性：保持Schema 命名的一致性很重要。

在整个数据库中使用相同的命名规则可以减少混淆和错误。

5. 避免使用保留词：避免将保留词用作Schema 名称，以防止与PostgreSQL 关键字冲突。

三、具体的命名约定除了上述一般准则外，还可以参考以下具体的命名约定来命名PostgreSQL Schema：1. 基于业务逻辑：根据业务逻辑和应用需求来命名Schema，将相关的对象放在同一个Schema 下。

mysql数据库可重复读、幻读事务基本特性ACID分别是：原⼦性（Atomicity）指的是⼀个事务中的操作要么全部成功，要么全部失败。

⼀致性（Consistency）指的是数据库总是从⼀个⼀致性的状态转换到另外⼀个⼀致性的状态。

⽐如A转账给B100块钱，假设中间sql执⾏过程中系统崩溃A也不会损失100块，因为事务没有提交，修改也就不会保存到数据库。

隔离性（Isolation）指的是⼀个事务的修改在最终提交前，对其他事务是不可见的。

持久性（Durability）指的是⼀旦事务提交，所做的修改就会永久保存到数据库中。

ACID靠什么保证的呢A原⼦性由undo log⽇志保证，它记录了需要回滚的⽇志信息，事务回滚时撤销已经执⾏成功的sql；C⼀致性⼀般由代码层⾯来保证；（如tcc两阶段提交，事务回滚）I隔离性由MVCC来保证；（多版本并发控制，保存当前时间快照）D持久性由内存+redo log来保证，mysql修改数据同时在内存和redo log记录这次操作，事务提交的时候通过redo log刷盘，宕机的时候可以从redo log恢复；⽽隔离性有4个隔离级别，分别是：1、read uncommit 读未提交，可能会读到其他事务未提交的数据，也叫做脏读。

⽤户本来应该读取到id=1的⽤户age应该是10，结果读取到了其他事务还没有提交的事务，结果读取结果age=20，这就是脏读。

2、read commit 读已提交，两次读取结果不⼀致，叫做不可重复读。

不可重复读解决了脏读的问题，他只会读取已经提交的事务。

⽤户开启事务读取id=1⽤户，查询到age=10，再次读取发现结果=20，在同⼀个事务⾥同⼀个查询读取到不同的结果叫做不可重复读。

3、repeatable read 可重复复读，这是mysql的默认级别，就是每次读取结果都⼀样，但是有可能产⽣幻读。

4、serializable 串⾏，⼀般是不会使⽤的，他会给每⼀⾏读取的数据加锁，会导致⼤量超时和锁竞争的问题。

obfuscate的混淆加密规则英文回答：Obfuscation is a technique used to make code or data difficult to understand or reverse engineer. It involves modifying the code or data in such a way that it becomes more complex and harder to comprehend. The purpose of obfuscation is to deter unauthorized access, protect intellectual property, and prevent software piracy.There are several common techniques used in obfuscation. One such technique is renaming variables and functions to meaningless or confusing names. For example, a variable named "password" could be renamed to something like"x1a2b3c4d". This makes it harder for someone to understand the purpose of the variable and its role in the code.Another technique is code restructuring, where the code is rearranged in a way that makes it more difficult tofollow the logic. This can involve adding unnecessary code,removing whitespace and comments, or splitting code into multiple files. The goal is to make the code appear more convoluted and confusing.Obfuscation can also involve encrypting sensitive data or using encryption algorithms to hide important parts of the code. This makes it harder for someone to extract sensitive information or understand the inner workings of the software.Additionally, obfuscation can include the use of anti-debugging techniques to make it harder for someone to analyze the code while it is running. This can involve detecting if a debugger is attached and taking actions to prevent it from functioning properly.Overall, the goal of obfuscation is to make itdifficult for someone to understand or modify the code, while still allowing it to function correctly. It is important to note that obfuscation is not foolproof and can be bypassed by determined attackers. However, it can provide an additional layer of protection and make it moretime-consuming for someone to reverse engineer the code.中文回答：混淆加密是一种用于使代码或数据难以理解或逆向工程的技术。

MIPS32™ Architecture For Programmers Volume I: Introduction to the MIPS32™ArchitectureDocument Number: MD00082Revision 2.00June 8, 2003MIPS Technologies, Inc.1225 Charleston RoadMountain View, CA 94043-1353Copyright © 2001-2003 MIPS Technologies Inc. All rights reserved.Copyright ©2001-2003 MIPS Technologies, Inc. All rights reserved.Unpublished rights (if any) reserved under the copyright laws of the United States of America and other countries.This document contains information that is proprietary to MIPS Technologies, Inc. ("MIPS Technologies"). Any copying,reproducing,modifying or use of this information(in whole or in part)that is not expressly permitted in writing by MIPS Technologies or an authorized third party is strictly prohibited. At a minimum, this information is protected under unfair competition and copyright laws. Violations thereof may result in criminal penalties and fines.Any document provided in source format(i.e.,in a modifiable form such as in FrameMaker or Microsoft Word format) is subject to use and distribution restrictions that are independent of and supplemental to any and all confidentiality restrictions. UNDER NO CIRCUMSTANCES MAY A DOCUMENT PROVIDED IN SOURCE FORMAT BE DISTRIBUTED TO A THIRD PARTY IN SOURCE FORMAT WITHOUT THE EXPRESS WRITTEN PERMISSION OF MIPS TECHNOLOGIES, INC.MIPS Technologies reserves the right to change the information contained in this document to improve function,design or otherwise.MIPS Technologies does not assume any liability arising out of the application or use of this information, or of any error or omission in such information. Any warranties, whether express, statutory, implied or otherwise, including but not limited to the implied warranties of merchantability orfitness for a particular purpose,are excluded. Except as expressly provided in any written license agreement from MIPS Technologies or an authorized third party,the furnishing of this document does not give recipient any license to any intellectual property rights,including any patent rights, that cover the information in this document.The information contained in this document shall not be exported or transferred for the purpose of reexporting in violation of any U.S. or non-U.S. regulation, treaty, Executive Order, law, statute, amendment or supplement thereto. The information contained in this document constitutes one or more of the following: commercial computer software, commercial computer software documentation or other commercial items.If the user of this information,or any related documentation of any kind,including related technical data or manuals,is an agency,department,or other entity of the United States government ("Government"), the use, duplication, reproduction, release, modification, disclosure, or transfer of this information, or any related documentation of any kind, is restricted in accordance with Federal Acquisition Regulation12.212for civilian agencies and Defense Federal Acquisition Regulation Supplement227.7202 for military agencies.The use of this information by the Government is further restricted in accordance with the terms of the license agreement(s) and/or applicable contract terms and conditions covering this information from MIPS Technologies or an authorized third party.MIPS,R3000,R4000,R5000and R10000are among the registered trademarks of MIPS Technologies,Inc.in the United States and other countries,and MIPS16,MIPS16e,MIPS32,MIPS64,MIPS-3D,MIPS-based,MIPS I,MIPS II,MIPS III,MIPS IV,MIPS V,MIPSsim,SmartMIPS,MIPS Technologies logo,4K,4Kc,4Km,4Kp,4KE,4KEc,4KEm,4KEp, 4KS, 4KSc, 4KSd, M4K, 5K, 5Kc, 5Kf, 20Kc, 25Kf, ASMACRO, ATLAS, At the Core of the User Experience., BusBridge, CoreFPGA, CoreLV, EC, JALGO, MALTA, MDMX, MGB, PDtrace, Pipeline, Pro, Pro Series, SEAD, SEAD-2, SOC-it and YAMON are among the trademarks of MIPS Technologies, Inc.All other trademarks referred to herein are the property of their respective owners.Template: B1.08, Built with tags: 2B ARCH MIPS32MIPS32™ Architecture For Programmers Volume I, Revision 2.00 Copyright © 2001-2003 MIPS Technologies Inc. All rights reserved.Table of ContentsChapter 1 About This Book (1)1.1 Typographical Conventions (1)1.1.1 Italic Text (1)1.1.2 Bold Text (1)1.1.3 Courier Text (1)1.2 UNPREDICTABLE and UNDEFINED (2)1.2.1 UNPREDICTABLE (2)1.2.2 UNDEFINED (2)1.3 Special Symbols in Pseudocode Notation (2)1.4 For More Information (4)Chapter 2 The MIPS Architecture: An Introduction (7)2.1 MIPS32 and MIPS64 Overview (7)2.1.1 Historical Perspective (7)2.1.2 Architectural Evolution (7)2.1.3 Architectural Changes Relative to the MIPS I through MIPS V Architectures (9)2.2 Compliance and Subsetting (9)2.3 Components of the MIPS Architecture (10)2.3.1 MIPS Instruction Set Architecture (ISA) (10)2.3.2 MIPS Privileged Resource Architecture (PRA) (10)2.3.3 MIPS Application Specific Extensions (ASEs) (10)2.3.4 MIPS User Defined Instructions (UDIs) (11)2.4 Architecture Versus Implementation (11)2.5 Relationship between the MIPS32 and MIPS64 Architectures (11)2.6 Instructions, Sorted by ISA (12)2.6.1 List of MIPS32 Instructions (12)2.6.2 List of MIPS64 Instructions (13)2.7 Pipeline Architecture (13)2.7.1 Pipeline Stages and Execution Rates (13)2.7.2 Parallel Pipeline (14)2.7.3 Superpipeline (14)2.7.4 Superscalar Pipeline (14)2.8 Load/Store Architecture (15)2.9 Programming Model (15)2.9.1 CPU Data Formats (16)2.9.2 FPU Data Formats (16)2.9.3 Coprocessors (CP0-CP3) (16)2.9.4 CPU Registers (16)2.9.5 FPU Registers (18)2.9.6 Byte Ordering and Endianness (21)2.9.7 Memory Access Types (25)2.9.8 Implementation-Specific Access Types (26)2.9.9 Cache Coherence Algorithms and Access Types (26)2.9.10 Mixing Access Types (26)Chapter 3 Application Specific Extensions (27)3.1 Description of ASEs (27)3.2 List of Application Specific Instructions (28)3.2.1 The MIPS16e Application Specific Extension to the MIPS32Architecture (28)3.2.2 The MDMX Application Specific Extension to the MIPS64 Architecture (28)3.2.3 The MIPS-3D Application Specific Extension to the MIPS64 Architecture (28)MIPS32™ Architecture For Programmers Volume I, Revision 2.00i Copyright © 2001-2003 MIPS Technologies Inc. All rights reserved.3.2.4 The SmartMIPS Application Specific Extension to the MIPS32 Architecture (28)Chapter 4 Overview of the CPU Instruction Set (29)4.1 CPU Instructions, Grouped By Function (29)4.1.1 CPU Load and Store Instructions (29)4.1.2 Computational Instructions (32)4.1.3 Jump and Branch Instructions (35)4.1.4 Miscellaneous Instructions (37)4.1.5 Coprocessor Instructions (40)4.2 CPU Instruction Formats (41)Chapter 5 Overview of the FPU Instruction Set (43)5.1 Binary Compatibility (43)5.2 Enabling the Floating Point Coprocessor (44)5.3 IEEE Standard 754 (44)5.4 FPU Data Types (44)5.4.1 Floating Point Formats (44)5.4.2 Fixed Point Formats (48)5.5 Floating Point Register Types (48)5.5.1 FPU Register Models (49)5.5.2 Binary Data Transfers (32-Bit and 64-Bit) (49)5.5.3 FPRs and Formatted Operand Layout (50)5.6 Floating Point Control Registers (FCRs) (50)5.6.1 Floating Point Implementation Register (FIR, CP1 Control Register 0) (51)5.6.2 Floating Point Control and Status Register (FCSR, CP1 Control Register 31) (53)5.6.3 Floating Point Condition Codes Register (FCCR, CP1 Control Register 25) (55)5.6.4 Floating Point Exceptions Register (FEXR, CP1 Control Register 26) (56)5.6.5 Floating Point Enables Register (FENR, CP1 Control Register 28) (56)5.7 Formats of Values Used in FP Registers (57)5.8 FPU Exceptions (58)5.8.1 Exception Conditions (59)5.9 FPU Instructions (62)5.9.1 Data Transfer Instructions (62)5.9.2 Arithmetic Instructions (63)5.9.3 Conversion Instructions (65)5.9.4 Formatted Operand-Value Move Instructions (66)5.9.5 Conditional Branch Instructions (67)5.9.6 Miscellaneous Instructions (68)5.10 Valid Operands for FPU Instructions (68)5.11 FPU Instruction Formats (70)5.11.1 Implementation Note (71)Appendix A Instruction Bit Encodings (75)A.1 Instruction Encodings and Instruction Classes (75)A.2 Instruction Bit Encoding Tables (75)A.3 Floating Point Unit Instruction Format Encodings (82)Appendix B Revision History (85)ii MIPS32™ Architecture For Programmers Volume I, Revision 2.00 Copyright © 2001-2003 MIPS Technologies Inc. All rights reserved.Figure 2-1: Relationship between the MIPS32 and MIPS64 Architectures (11)Figure 2-2: One-Deep Single-Completion Instruction Pipeline (13)Figure 2-3: Four-Deep Single-Completion Pipeline (14)Figure 2-4: Four-Deep Superpipeline (14)Figure 2-5: Four-Way Superscalar Pipeline (15)Figure 2-6: CPU Registers (18)Figure 2-7: FPU Registers for a 32-bit FPU (20)Figure 2-8: FPU Registers for a 64-bit FPU if Status FR is 1 (21)Figure 2-9: FPU Registers for a 64-bit FPU if Status FR is 0 (22)Figure 2-10: Big-Endian Byte Ordering (23)Figure 2-11: Little-Endian Byte Ordering (23)Figure 2-12: Big-Endian Data in Doubleword Format (24)Figure 2-13: Little-Endian Data in Doubleword Format (24)Figure 2-14: Big-Endian Misaligned Word Addressing (25)Figure 2-15: Little-Endian Misaligned Word Addressing (25)Figure 3-1: MIPS ISAs and ASEs (27)Figure 3-2: User-Mode MIPS ISAs and Optional ASEs (27)Figure 4-1: Immediate (I-Type) CPU Instruction Format (42)Figure 4-2: Jump (J-Type) CPU Instruction Format (42)Figure 4-3: Register (R-Type) CPU Instruction Format (42)Figure 5-1: Single-Precisions Floating Point Format (S) (45)Figure 5-2: Double-Precisions Floating Point Format (D) (45)Figure 5-3: Paired Single Floating Point Format (PS) (46)Figure 5-4: Word Fixed Point Format (W) (48)Figure 5-5: Longword Fixed Point Format (L) (48)Figure 5-6: FPU Word Load and Move-to Operations (49)Figure 5-7: FPU Doubleword Load and Move-to Operations (50)Figure 5-8: Single Floating Point or Word Fixed Point Operand in an FPR (50)Figure 5-9: Double Floating Point or Longword Fixed Point Operand in an FPR (50)Figure 5-10: Paired-Single Floating Point Operand in an FPR (50)Figure 5-11: FIR Register Format (51)Figure 5-12: FCSR Register Format (53)Figure 5-13: FCCR Register Format (55)Figure 5-14: FEXR Register Format (56)Figure 5-15: FENR Register Format (56)Figure 5-16: Effect of FPU Operations on the Format of Values Held in FPRs (58)Figure 5-17: I-Type (Immediate) FPU Instruction Format (71)Figure 5-18: R-Type (Register) FPU Instruction Format (71)Figure 5-19: Register-Immediate FPU Instruction Format (71)Figure 5-20: Condition Code, Immediate FPU Instruction Format (71)Figure 5-21: Formatted FPU Compare Instruction Format (71)Figure 5-22: FP RegisterMove, Conditional Instruction Format (71)Figure 5-23: Four-Register Formatted Arithmetic FPU Instruction Format (72)Figure 5-24: Register Index FPU Instruction Format (72)Figure 5-25: Register Index Hint FPU Instruction Format (72)Figure 5-26: Condition Code, Register Integer FPU Instruction Format (72)Figure A-1: Sample Bit Encoding Table (76)MIPS32™ Architecture For Programmers Volume I, Revision 2.00iii Copyright © 2001-2003 MIPS Technologies Inc. All rights reserved.Table 1-1: Symbols Used in Instruction Operation Statements (2)Table 2-1: MIPS32 Instructions (12)Table 2-2: MIPS64 Instructions (13)Table 2-3: Unaligned Load and Store Instructions (24)Table 4-1: Load and Store Operations Using Register + Offset Addressing Mode (30)Table 4-2: Aligned CPU Load/Store Instructions (30)Table 4-3: Unaligned CPU Load and Store Instructions (31)Table 4-4: Atomic Update CPU Load and Store Instructions (31)Table 4-5: Coprocessor Load and Store Instructions (31)Table 4-6: FPU Load and Store Instructions Using Register+Register Addressing (32)Table 4-7: ALU Instructions With an Immediate Operand (33)Table 4-8: Three-Operand ALU Instructions (33)Table 4-9: Two-Operand ALU Instructions (34)Table 4-10: Shift Instructions (34)Table 4-11: Multiply/Divide Instructions (35)Table 4-12: Unconditional Jump Within a 256 Megabyte Region (36)Table 4-13: PC-Relative Conditional Branch Instructions Comparing Two Registers (36)Table 4-14: PC-Relative Conditional Branch Instructions Comparing With Zero (37)Table 4-15: Deprecated Branch Likely Instructions (37)Table 4-16: Serialization Instruction (38)Table 4-17: System Call and Breakpoint Instructions (38)Table 4-18: Trap-on-Condition Instructions Comparing Two Registers (38)Table 4-19: Trap-on-Condition Instructions Comparing an Immediate Value (38)Table 4-20: CPU Conditional Move Instructions (39)Table 4-21: Prefetch Instructions (39)Table 4-22: NOP Instructions (40)Table 4-23: Coprocessor Definition and Use in the MIPS Architecture (40)Table 4-24: CPU Instruction Format Fields (42)Table 5-1: Parameters of Floating Point Data Types (45)Table 5-2: Value of Single or Double Floating Point DataType Encoding (46)Table 5-3: Value Supplied When a New Quiet NaN Is Created (47)Table 5-4: FIR Register Field Descriptions (51)Table 5-5: FCSR Register Field Descriptions (53)Table 5-6: Cause, Enable, and Flag Bit Definitions (55)Table 5-7: Rounding Mode Definitions (55)Table 5-8: FCCR Register Field Descriptions (56)Table 5-9: FEXR Register Field Descriptions (56)Table 5-10: FENR Register Field Descriptions (57)Table 5-11: Default Result for IEEE Exceptions Not Trapped Precisely (60)Table 5-12: FPU Data Transfer Instructions (62)Table 5-13: FPU Loads and Stores Using Register+Offset Address Mode (63)Table 5-14: FPU Loads and Using Register+Register Address Mode (63)Table 5-15: FPU Move To and From Instructions (63)Table 5-16: FPU IEEE Arithmetic Operations (64)Table 5-17: FPU-Approximate Arithmetic Operations (64)Table 5-18: FPU Multiply-Accumulate Arithmetic Operations (65)Table 5-19: FPU Conversion Operations Using the FCSR Rounding Mode (65)Table 5-20: FPU Conversion Operations Using a Directed Rounding Mode (65)Table 5-21: FPU Formatted Operand Move Instructions (66)Table 5-22: FPU Conditional Move on True/False Instructions (66)iv MIPS32™ Architecture For Programmers Volume I, Revision 2.00 Copyright © 2001-2003 MIPS Technologies Inc. All rights reserved.Table 5-23: FPU Conditional Move on Zero/Nonzero Instructions (67)Table 5-24: FPU Conditional Branch Instructions (67)Table 5-25: Deprecated FPU Conditional Branch Likely Instructions (67)Table 5-26: CPU Conditional Move on FPU True/False Instructions (68)Table 5-27: FPU Operand Format Field (fmt, fmt3) Encoding (68)Table 5-28: Valid Formats for FPU Operations (69)Table 5-29: FPU Instruction Format Fields (72)Table A-1: Symbols Used in the Instruction Encoding Tables (76)Table A-2: MIPS32 Encoding of the Opcode Field (77)Table A-3: MIPS32 SPECIAL Opcode Encoding of Function Field (78)Table A-4: MIPS32 REGIMM Encoding of rt Field (78)Table A-5: MIPS32 SPECIAL2 Encoding of Function Field (78)Table A-6: MIPS32 SPECIAL3 Encoding of Function Field for Release 2 of the Architecture (78)Table A-7: MIPS32 MOVCI Encoding of tf Bit (79)Table A-8: MIPS32 SRL Encoding of Shift/Rotate (79)Table A-9: MIPS32 SRLV Encoding of Shift/Rotate (79)Table A-10: MIPS32 BSHFL Encoding of sa Field (79)Table A-11: MIPS32 COP0 Encoding of rs Field (79)Table A-12: MIPS32 COP0 Encoding of Function Field When rs=CO (80)Table A-13: MIPS32 COP1 Encoding of rs Field (80)Table A-14: MIPS32 COP1 Encoding of Function Field When rs=S (80)Table A-15: MIPS32 COP1 Encoding of Function Field When rs=D (81)Table A-16: MIPS32 COP1 Encoding of Function Field When rs=W or L (81)Table A-17: MIPS64 COP1 Encoding of Function Field When rs=PS (81)Table A-18: MIPS32 COP1 Encoding of tf Bit When rs=S, D, or PS, Function=MOVCF (81)Table A-19: MIPS32 COP2 Encoding of rs Field (82)Table A-20: MIPS64 COP1X Encoding of Function Field (82)Table A-21: Floating Point Unit Instruction Format Encodings (82)MIPS32™ Architecture For Programmers Volume I, Revision 2.00v Copyright © 2001-2003 MIPS Technologies Inc. All rights reserved.vi MIPS32™ Architecture For Programmers Volume I, Revision 2.00 Copyright © 2001-2003 MIPS Technologies Inc. All rights reserved.Chapter 1About This BookThe MIPS32™ Architecture For Programmers V olume I comes as a multi-volume set.•V olume I describes conventions used throughout the document set, and provides an introduction to the MIPS32™Architecture•V olume II provides detailed descriptions of each instruction in the MIPS32™ instruction set•V olume III describes the MIPS32™Privileged Resource Architecture which defines and governs the behavior of the privileged resources included in a MIPS32™ processor implementation•V olume IV-a describes the MIPS16e™ Application-Specific Extension to the MIPS32™ Architecture•V olume IV-b describes the MDMX™ Application-Specific Extension to the MIPS32™ Architecture and is notapplicable to the MIPS32™ document set•V olume IV-c describes the MIPS-3D™ Application-Specific Extension to the MIPS64™ Architecture and is notapplicable to the MIPS32™ document set•V olume IV-d describes the SmartMIPS™Application-Specific Extension to the MIPS32™ Architecture1.1Typographical ConventionsThis section describes the use of italic,bold and courier fonts in this book.1.1.1Italic Text•is used for emphasis•is used for bits,fields,registers, that are important from a software perspective (for instance, address bits used bysoftware,and programmablefields and registers),and variousfloating point instruction formats,such as S,D,and PS •is used for the memory access types, such as cached and uncached1.1.2Bold Text•represents a term that is being defined•is used for bits andfields that are important from a hardware perspective (for instance,register bits, which are not programmable but accessible only to hardware)•is used for ranges of numbers; the range is indicated by an ellipsis. For instance,5..1indicates numbers 5 through 1•is used to emphasize UNPREDICTABLE and UNDEFINED behavior, as defined below.1.1.3Courier TextCourier fixed-width font is used for text that is displayed on the screen, and for examples of code and instruction pseudocode.MIPS32™ Architecture For Programmers Volume I, Revision 2.001 Copyright © 2001-2003 MIPS Technologies Inc. All rights reserved.Chapter 1 About This Book1.2UNPREDICTABLE and UNDEFINEDThe terms UNPREDICTABLE and UNDEFINED are used throughout this book to describe the behavior of theprocessor in certain cases.UNDEFINED behavior or operations can occur only as the result of executing instructions in a privileged mode (i.e., in Kernel Mode or Debug Mode, or with the CP0 usable bit set in the Status register).Unprivileged software can never cause UNDEFINED behavior or operations. Conversely, both privileged andunprivileged software can cause UNPREDICTABLE results or operations.1.2.1UNPREDICTABLEUNPREDICTABLE results may vary from processor implementation to implementation,instruction to instruction,or as a function of time on the same implementation or instruction. Software can never depend on results that areUNPREDICTABLE.UNPREDICTABLE operations may cause a result to be generated or not.If a result is generated, it is UNPREDICTABLE.UNPREDICTABLE operations may cause arbitrary exceptions.UNPREDICTABLE results or operations have several implementation restrictions:•Implementations of operations generating UNPREDICTABLE results must not depend on any data source(memory or internal state) which is inaccessible in the current processor mode•UNPREDICTABLE operations must not read, write, or modify the contents of memory or internal state which is inaccessible in the current processor mode. For example,UNPREDICTABLE operations executed in user modemust not access memory or internal state that is only accessible in Kernel Mode or Debug Mode or in another process •UNPREDICTABLE operations must not halt or hang the processor1.2.2UNDEFINEDUNDEFINED operations or behavior may vary from processor implementation to implementation, instruction toinstruction, or as a function of time on the same implementation or instruction.UNDEFINED operations or behavior may vary from nothing to creating an environment in which execution can no longer continue.UNDEFINED operations or behavior may cause data loss.UNDEFINED operations or behavior has one implementation restriction:•UNDEFINED operations or behavior must not cause the processor to hang(that is,enter a state from which there is no exit other than powering down the processor).The assertion of any of the reset signals must restore the processor to an operational state1.3Special Symbols in Pseudocode NotationIn this book, algorithmic descriptions of an operation are described as pseudocode in a high-level language notation resembling Pascal. Special symbols used in the pseudocode notation are listed in Table 1-1.Table 1-1 Symbols Used in Instruction Operation StatementsSymbol Meaning←Assignment=, ≠Tests for equality and inequality||Bit string concatenationx y A y-bit string formed by y copies of the single-bit value x2MIPS32™ Architecture For Programmers Volume I, Revision 2.00 Copyright © 2001-2003 MIPS Technologies Inc. All rights reserved.1.3Special Symbols in Pseudocode Notationb#n A constant value n in base b.For instance10#100represents the decimal value100,2#100represents the binary value 100 (decimal 4), and 16#100 represents the hexadecimal value 100 (decimal 256). If the "b#" prefix is omitted, the default base is 10.x y..z Selection of bits y through z of bit string x.Little-endian bit notation(rightmost bit is0)is used.If y is less than z, this expression is an empty (zero length) bit string.+, −2’s complement or floating point arithmetic: addition, subtraction∗, ×2’s complement or floating point multiplication (both used for either)div2’s complement integer divisionmod2’s complement modulo/Floating point division<2’s complement less-than comparison>2’s complement greater-than comparison≤2’s complement less-than or equal comparison≥2’s complement greater-than or equal comparisonnor Bitwise logical NORxor Bitwise logical XORand Bitwise logical ANDor Bitwise logical ORGPRLEN The length in bits (32 or 64) of the CPU general-purpose registersGPR[x]CPU general-purpose register x. The content of GPR[0] is always zero.SGPR[s,x]In Release 2 of the Architecture, multiple copies of the CPU general-purpose registers may be implemented.SGPR[s,x] refers to GPR set s, register x. GPR[x] is a short-hand notation for SGPR[ SRSCtl CSS, x].FPR[x]Floating Point operand register xFCC[CC]Floating Point condition code CC.FCC[0] has the same value as COC[1].FPR[x]Floating Point (Coprocessor unit 1), general register xCPR[z,x,s]Coprocessor unit z, general register x,select sCP2CPR[x]Coprocessor unit 2, general register xCCR[z,x]Coprocessor unit z, control register xCP2CCR[x]Coprocessor unit 2, control register xCOC[z]Coprocessor unit z condition signalXlat[x]Translation of the MIPS16e GPR number x into the corresponding 32-bit GPR numberBigEndianMem Endian mode as configured at chip reset (0→Little-Endian, 1→ Big-Endian). Specifies the endianness of the memory interface(see LoadMemory and StoreMemory pseudocode function descriptions),and the endianness of Kernel and Supervisor mode execution.BigEndianCPU The endianness for load and store instructions (0→ Little-Endian, 1→ Big-Endian). In User mode, this endianness may be switched by setting the RE bit in the Status register.Thus,BigEndianCPU may be computed as (BigEndianMem XOR ReverseEndian).Table 1-1 Symbols Used in Instruction Operation StatementsSymbol MeaningChapter 1 About This Book1.4For More InformationVarious MIPS RISC processor manuals and additional information about MIPS products can be found at the MIPS URL:ReverseEndianSignal to reverse the endianness of load and store instructions.This feature is available in User mode only,and is implemented by setting the RE bit of the Status register.Thus,ReverseEndian may be computed as (SR RE and User mode).LLbitBit of virtual state used to specify operation for instructions that provide atomic read-modify-write.LLbit is set when a linked load occurs; it is tested and cleared by the conditional store. It is cleared, during other CPU operation,when a store to the location would no longer be atomic.In particular,it is cleared by exception return instructions.I :,I+n :,I-n :This occurs as a prefix to Operation description lines and functions as a label. It indicates the instruction time during which the pseudocode appears to “execute.” Unless otherwise indicated, all effects of the currentinstruction appear to occur during the instruction time of the current instruction.No label is equivalent to a time label of I . Sometimes effects of an instruction appear to occur either earlier or later — that is, during theinstruction time of another instruction.When this happens,the instruction operation is written in sections labeled with the instruction time,relative to the current instruction I ,in which the effect of that pseudocode appears to occur.For example,an instruction may have a result that is not available until after the next instruction.Such an instruction has the portion of the instruction operation description that writes the result register in a section labeled I +1.The effect of pseudocode statements for the current instruction labelled I +1appears to occur “at the same time”as the effect of pseudocode statements labeled I for the following instruction.Within one pseudocode sequence,the effects of the statements take place in order. However, between sequences of statements for differentinstructions that occur “at the same time,” there is no defined order. Programs must not depend on a particular order of evaluation between such sections.PCThe Program Counter value.During the instruction time of an instruction,this is the address of the instruction word. The address of the instruction that occurs during the next instruction time is determined by assigning a value to PC during an instruction time. If no value is assigned to PC during an instruction time by anypseudocode statement,it is automatically incremented by either 2(in the case of a 16-bit MIPS16e instruction)or 4before the next instruction time.A taken branch assigns the target address to the PC during the instruction time of the instruction in the branch delay slot.PABITSThe number of physical address bits implemented is represented by the symbol PABITS.As such,if 36physical address bits were implemented, the size of the physical address space would be 2PABITS = 236 bytes.FP32RegistersModeIndicates whether the FPU has 32-bit or 64-bit floating point registers (FPRs).In MIPS32,the FPU has 3232-bit FPRs in which 64-bit data types are stored in even-odd pairs of FPRs.In MIPS64,the FPU has 3264-bit FPRs in which 64-bit data types are stored in any FPR.In MIPS32implementations,FP32RegistersMode is always a 0.MIPS64implementations have a compatibility mode in which the processor references the FPRs as if it were a MIPS32 implementation. In such a caseFP32RegisterMode is computed from the FR bit in the Status register.If this bit is a 0,the processor operates as if it had 32 32-bit FPRs. If this bit is a 1, the processor operates with 32 64-bit FPRs.The value of FP32RegistersMode is computed from the FR bit in the Status register.InstructionInBranchDelaySlotIndicates whether the instruction at the Program Counter address was executed in the delay slot of a branch or jump. This condition reflects the dynamic state of the instruction, not the static state. That is, the value is false if a branch or jump occurs to an instruction whose PC immediately follows a branch or jump, but which is not executed in the delay slot of a branch or jump.SignalException(exce ption, argument)Causes an exception to be signaled, using the exception parameter as the type of exception and the argument parameter as an exception-specific argument). Control does not return from this pseudocode function - the exception is signaled at the point of the call.Table 1-1 Symbols Used in Instruction Operation StatementsSymbolMeaning。

在这之前我只接触过逆向考勤，没有用过正向考勤。

这次把二者都用到了，可以来做个比较。

两者的区别主要在以下几个方面：Infotype：正向考勤会用到IT0050和IT2011，而逆向不需要。

其他跟时间相关的我有用到IT2001, IT2002,IT2003, IT2006 和IT2007, IT2013, IT0416。

加班放在IT2002中，因为用时间评估生成Absence Quota，所以需要用到IT2013做一些调整。

错误检查：主要是正向考勤中，系统会对打卡时间进行配对，如果不匹配就有错误信息提示，而正向不存在这个问题。

那么相对应的错误检查Rule会有些不同。

Schema：从Schema来看，主要的差别在于导入时间数据，后面的处理其实是差不多了。

Table T555Z 和 T555Y的差别，T555Z是time determination，正向考勤中使用, 他根据time ID来给时间分配time type；而T555Y在逆向中使用，它是根据Processing type/time type class给时间(absenceand attendance type)分配time type。

这两者会同时影响到后面time wage type(T510S)的生成，所以在前面就最好能统一起来。

之前有人说做正向很难，做完后觉得没有想象的那么难。

细想一下，也许是因为我有逆向的基础，这能帮助我理解一下整个逻辑。

正如上面第二条说到的，只要把数据导入进来，后面处理是可以相似或相同的，而数据导入基本用系统标准的就可以，不需要做修改，所以我才会觉得难度没有想象中的大。

对于Time模块，一直不是很了解，尽我所能写一些吧。

对于考勤的处理，主要有2种：一是正向考勤，另外一个是逆向考勤。

正向考勤就是记录员工的上下班时间。

用Schema TM00逆向考勤是指只记录与计划工作时间相悖的时间。

用Schema TM04.Basic Concepts:1. User Exits: 是系统中预留的一些空的Form/Subroutine, 获得Access key后可以在Form中写入自己的逻辑.2. Customer Exits :a. FM Exits: 在FM中include customer namespace程序来提供功能扩展点b. Menu Exits: 在GUI status中预留+Fcode menu item, 在程序中预留对应的Handling FM Exitsc. Screen Exits: 在Screen 中预留 Subscreen, 在程序中预留transport data to subscreen &return / retrieve data from subscreen 的 FM Exits3. Enhancement & Enhancement Project :a. Enhancement: 把系统程序中的相关Customer Exits收集起来成为一个Enhancement, 一般情况是按功能和类型来收集的, 比方说几个相关的FM eixts组成一个enhancemnet, 或就一个screen 或 menuexits 形成一个enhancement. 查看/修改 Enhancement的t-code为: SMODb. Enhancement Project: 在使用Enhacement时, 要先建立一个Enhancement Project, 可以将多个Enhancement assign给一个enhancement project去管理, 对应t-code: CMOD.4. BADI (Business Add-in), 通过面向对象的方式来提供扩展点，它支持Customer Exits 所有的enhancement 类型，因目前Class中不能包含subscreen所以在用BADI enhance screen 时比用CustomerExits要复杂些．相关机制请参考我以前的blog.5. OtherUser Exits与Customer Exits的区别在于User Exits的使用需要Access Key但Customer Exits不要.FM exits在关联的Function Group中的命名规则为: EXIT_program name_nnnCustomer exits的调用方式为:a. FM Exits: CALL CUSTOMER-FUNCTION 'xxx' EXPORTING ... IMPORTING ...b. Subscreen: Call CUSTOMER-SUBSCREEN INCLUDINGHow to find user exits?Using t-code: SE93 and specify the transaction code. from here goto the main program andclick on the FIND button. Specify USEREXIT and select find in main program radio button andclick search... if any user exit is used, it will list all the places as in SAP if any userexit is used, a comment is been written above the user exit.How to find customer exits?1. 通过一些专门的程序，见附件2. Search string “call customer” i n the main program source code;3. SE80 -> Repository Infomation System -> Enhancements -> Customer Exits -> Inputsearch condition -> Execute4. SE11 -> Database table: MODSAPVIEW -> Display Contents -> Input "*program name*"into Enhancement field -> Execute -> 得到的SAP extension name 即为 Customer Exits Enhancement NameHow to find BADIs?1. 通过一些专门的程序，见附件2. Search string “type ref to” in the main program source code, then chec k if thereis BAdi used in the program;3. Set break-point in the method CL_EXITHANDLER=>GET_INSTANCE.4. SE80 -> Repository Infomation System -> Enhancements -> Business Add-ins Customer Exits and BADI implementation.1. Customer Exits: SMOD, CMOD2. BADI: SE18, SE19.Attachment is an ABAP program which can find customer exits and BADIs conveniently.Payroll Schemas and Personnel Calculation Rules (PCR's) Transaction Code: PE01Menu Path: Human Resources --> Payroll --> Europe --> Great Britain --> Tools --> Maintenance Tools --> SchemasDouble-clicking on a sub-schema will take you to the maintenance screen for that schema.Double-clicking on any of the rules (PCR's) will take you to the rule editor. You can tell the difference between sub-schemas a rules by looking at the parameters. The name of the sub-schema can be found in the Par 1 column. The main schema generally calls all the different sub-schemas. The sub-schemas will then call the payroll rules. In most cases, when a rule is called, there will be parameters in the Par 2 or Par 3 columns.In the main, most sub-schemas are called by the "copy" command.Schemas, rules and features in SAP use the following line editor commands. This allows you to move, delete, copy and insert lines. All the commands are entered in the area used for the line numbers. Overwrite any of the numbers with the commands shown below. For the commands using 1 letter - hit the return key once you have entered the letter. For the commands using 2 letters - hit the return key after the first 2 letters have been entered or after both sets have been entered.The most commonly used commands are:Once you have chosen the block to move or copy, you need to show where to move or copy it to in the schema. The following commands indicate where you can copy or move the lines to.Remember when calling the PCR from the schema: GEN means that the wagetype is **** i.e. you haven't specified one and NOAB means that it will look at any EE Sub-Grouping. If you want the rule to use specific wage types or groupings, then leave either blank.Use the print option and VAR (PAR 2) in the schema to output the variable table during processing.Position is very important for schemas. Look to see where a similar piece of processing has taken place. If in doubt, place the rule after the similar data has been read and processed.Commonly used FunctionsCommonly used ParametersPayroll PCR'sTransaction Code: PE02Menu Path: Human Resources --> Payroll --> Europe --> Great Britain --> Tools --> Maintenance Tools --> RulesCommonly used operations in payroll configurationWishing to retrieve previous payroll period results to be used in a PCR?You can do so by using the operation IMPRE with parameter NN (NN periods before current payroll period). Also have a look at the documentation of IMPRE.An example in using this operation is as follows (reading the period 6 months ago):D ZERO = NRA IMPRE 6 SUBRC?IMP *0 AMT = O 1001SETIN A=01SETIN R=3 ZERO= NR ADDWTI1001。

schema规则[schema规则]，以中括号内的内容为主题，写一篇1500-2000字文章，一步一步回答首先，让我们来了解一下什么是[schema规则]。

Schema规则是一种定义数据结构的标记语言，用于定义数据实体之间的关系和属性。

它用于描述数据的结构、数据类型、约束条件和关系等细节。

这种规则可以被应用于各种领域，例如数据库设计、API设计、网络通信等。

在本文中，我们将深入探讨[schema规则]的相关细节，包括它的基本概念、语法、常见的应用场景以及如何使用它来构建数据结构。

让我们一起来了解吧！1. 什么是[schema规则][schema规则]是一种用于定义数据结构的标记语言。

它定义了数据实体之间的关系和属性，以及它们之间的约束和限制。

通过使用[schema规则]，我们可以确保数据在应用程序中的一致性和完整性。

具体来说，它包括以下几个方面：- 数据结构：[schema规则]定义了数据实体的结构，包括属性名称、属性类型和属性之间的关系。

- 数据类型：[schema规则]规定了每个属性的数据类型，例如整数、字符串、日期等。

- 约束条件：[schema规则]可以定义属性的限制条件，例如必填、唯一性和范围等。

- 关系：[schema规则]可以定义实体之间的关系，例如一对一、一对多和多对多等。

通过使用[schema规则]，我们可以确保数据的一致性和有效性，并在应用程序中建立一个具有良好可维护性的数据结构。

2. [schema规则]的语法[schema规则]的语法通常有一定的标准和约定，下面是一个简单的示例：{"type": "object","properties": {"name": {"type": "string"},"age": {"type": "integer"},"email": {"type": "string","format": "email"}},"required": ["name", "email"]}在上面的示例中，我们定义了一个对象类型的[schema规则]，包含了三个属性：name、age和email。

T his appendix derives various results for ordinary least squares estimation of themultiple linear regression model using matrix notation and matrix algebra (see Appendix D for a summary). The material presented here is much more ad-vanced than that in the text.E.1THE MODEL AND ORDINARY LEAST SQUARES ESTIMATIONThroughout this appendix,we use the t subscript to index observations and an n to denote the sample size. It is useful to write the multiple linear regression model with k parameters as follows:y t ϭ␤1ϩ␤2x t 2ϩ␤3x t 3ϩ… ϩ␤k x tk ϩu t ,t ϭ 1,2,…,n ,(E.1)where y t is the dependent variable for observation t ,and x tj ,j ϭ 2,3,…,k ,are the inde-pendent variables. Notice how our labeling convention here differs from the text:we call the intercept ␤1and let ␤2,…,␤k denote the slope parameters. This relabeling is not important,but it simplifies the matrix approach to multiple regression.For each t ,define a 1 ϫk vector,x t ϭ(1,x t 2,…,x tk ),and let ␤ϭ(␤1,␤2,…,␤k )Јbe the k ϫ1 vector of all parameters. Then,we can write (E.1) asy t ϭx t ␤ϩu t ,t ϭ 1,2,…,n .(E.2)[Some authors prefer to define x t as a column vector,in which case,x t is replaced with x t Јin (E.2). Mathematically,it makes more sense to define it as a row vector.] We can write (E.2) in full matrix notation by appropriately defining data vectors and matrices. Let y denote the n ϫ1 vector of observations on y :the t th element of y is y t .Let X be the n ϫk vector of observations on the explanatory variables. In other words,the t th row of X consists of the vector x t . Equivalently,the (t ,j )th element of X is simply x tj :755A p p e n d i x EThe Linear Regression Model inMatrix Formn X ϫ k ϵϭ .Finally,let u be the n ϫ 1 vector of unobservable disturbances. Then,we can write (E.2)for all n observations in matrix notation :y ϭX ␤ϩu .(E.3)Remember,because X is n ϫ k and ␤is k ϫ 1,X ␤is n ϫ 1.Estimation of ␤proceeds by minimizing the sum of squared residuals,as in Section3.2. Define the sum of squared residuals function for any possible k ϫ 1 parameter vec-tor b asSSR(b ) ϵ͚nt ϭ1(y t Ϫx t b )2.The k ϫ 1 vector of ordinary least squares estimates,␤ˆϭ(␤ˆ1,␤ˆ2,…,␤ˆk )؅,minimizes SSR(b ) over all possible k ϫ 1 vectors b . This is a problem in multivariable calculus.For ␤ˆto minimize the sum of squared residuals,it must solve the first order conditionѨSSR(␤ˆ)/Ѩb ϵ0.(E.4)Using the fact that the derivative of (y t Ϫx t b )2with respect to b is the 1ϫ k vector Ϫ2(y t Ϫx t b )x t ,(E.4) is equivalent to͚nt ϭ1xt Ј(y t Ϫx t ␤ˆ) ϵ0.(E.5)(We have divided by Ϫ2 and taken the transpose.) We can write this first order condi-tion as͚nt ϭ1(y t Ϫ␤ˆ1Ϫ␤ˆ2x t 2Ϫ… Ϫ␤ˆk x tk ) ϭ0͚nt ϭ1x t 2(y t Ϫ␤ˆ1Ϫ␤ˆ2x t 2Ϫ… Ϫ␤ˆk x tk ) ϭ0...͚nt ϭ1x tk (y t Ϫ␤ˆ1Ϫ␤ˆ2x t 2Ϫ… Ϫ␤ˆk x tk ) ϭ0,which,apart from the different labeling convention,is identical to the first order condi-tions in equation (3.13). We want to write these in matrix form to make them more use-ful. Using the formula for partitioned multiplication in Appendix D,we see that (E.5)is equivalent to΅1x 12x 13...x 1k1x 22x 23...x 2k...1x n 2x n 3...x nk ΄΅x 1x 2...x n ΄Appendix E The Linear Regression Model in Matrix Form756Appendix E The Linear Regression Model in Matrix FormXЈ(yϪX␤ˆ) ϭ0(E.6) or(XЈX)␤ˆϭXЈy.(E.7)It can be shown that (E.7) always has at least one solution. Multiple solutions do not help us,as we are looking for a unique set of OLS estimates given our data set. Assuming that the kϫ k symmetric matrix XЈX is nonsingular,we can premultiply both sides of (E.7) by (XЈX)Ϫ1to solve for the OLS estimator ␤ˆ:␤ˆϭ(XЈX)Ϫ1XЈy.(E.8)This is the critical formula for matrix analysis of the multiple linear regression model. The assumption that XЈX is invertible is equivalent to the assumption that rank(X) ϭk, which means that the columns of X must be linearly independent. This is the matrix ver-sion of MLR.4 in Chapter 3.Before we continue,(E.8) warrants a word of warning. It is tempting to simplify the formula for ␤ˆas follows:␤ˆϭ(XЈX)Ϫ1XЈyϭXϪ1(XЈ)Ϫ1XЈyϭXϪ1y.The flaw in this reasoning is that X is usually not a square matrix,and so it cannot be inverted. In other words,we cannot write (XЈX)Ϫ1ϭXϪ1(XЈ)Ϫ1unless nϭk,a case that virtually never arises in practice.The nϫ 1 vectors of OLS fitted values and residuals are given byyˆϭX␤ˆ,uˆϭyϪyˆϭyϪX␤ˆ.From (E.6) and the definition of uˆ,we can see that the first order condition for ␤ˆis the same asXЈuˆϭ0.(E.9) Because the first column of X consists entirely of ones,(E.9) implies that the OLS residuals always sum to zero when an intercept is included in the equation and that the sample covariance between each independent variable and the OLS residuals is zero. (We discussed both of these properties in Chapter 3.)The sum of squared residuals can be written asSSR ϭ͚n tϭ1uˆt2ϭuˆЈuˆϭ(yϪX␤ˆ)Ј(yϪX␤ˆ).(E.10)All of the algebraic properties from Chapter 3 can be derived using matrix algebra. For example,we can show that the total sum of squares is equal to the explained sum of squares plus the sum of squared residuals [see (3.27)]. The use of matrices does not pro-vide a simpler proof than summation notation,so we do not provide another derivation.757The matrix approach to multiple regression can be used as the basis for a geometri-cal interpretation of regression. This involves mathematical concepts that are even more advanced than those we covered in Appendix D. [See Goldberger (1991) or Greene (1997).]E.2FINITE SAMPLE PROPERTIES OF OLSDeriving the expected value and variance of the OLS estimator ␤ˆis facilitated by matrix algebra,but we must show some care in stating the assumptions.A S S U M P T I O N E.1(L I N E A R I N P A R A M E T E R S)The model can be written as in (E.3), where y is an observed nϫ 1 vector, X is an nϫ k observed matrix, and u is an nϫ 1 vector of unobserved errors or disturbances.A S S U M P T I O N E.2(Z E R O C O N D I T I O N A L M E A N)Conditional on the entire matrix X, each error ut has zero mean: E(ut͉X) ϭ0, tϭ1,2,…,n.In vector form,E(u͉X) ϭ0.(E.11) This assumption is implied by MLR.3 under the random sampling assumption,MLR.2.In time series applications,Assumption E.2 imposes strict exogeneity on the explana-tory variables,something discussed at length in Chapter 10. This rules out explanatory variables whose future values are correlated with ut; in particular,it eliminates laggeddependent variables. Under Assumption E.2,we can condition on the xtjwhen we com-pute the expected value of ␤ˆ.A S S U M P T I O N E.3(N O P E R F E C T C O L L I N E A R I T Y) The matrix X has rank k.This is a careful statement of the assumption that rules out linear dependencies among the explanatory variables. Under Assumption E.3,XЈX is nonsingular,and so ␤ˆis unique and can be written as in (E.8).T H E O R E M E.1(U N B I A S E D N E S S O F O L S)Under Assumptions E.1, E.2, and E.3, the OLS estimator ␤ˆis unbiased for ␤.P R O O F:Use Assumptions E.1 and E.3 and simple algebra to write␤ˆϭ(XЈX)Ϫ1XЈyϭ(XЈX)Ϫ1XЈ(X␤ϩu)ϭ(XЈX)Ϫ1(XЈX)␤ϩ(XЈX)Ϫ1XЈuϭ␤ϩ(XЈX)Ϫ1XЈu,(E.12)where we use the fact that (XЈX)Ϫ1(XЈX) ϭIk . Taking the expectation conditional on X givesAppendix E The Linear Regression Model in Matrix Form 758E(␤ˆ͉X)ϭ␤ϩ(XЈX)Ϫ1XЈE(u͉X)ϭ␤ϩ(XЈX)Ϫ1XЈ0ϭ␤,because E(u͉X) ϭ0under Assumption E.2. This argument clearly does not depend on the value of ␤, so we have shown that ␤ˆis unbiased.To obtain the simplest form of the variance-covariance matrix of ␤ˆ,we impose the assumptions of homoskedasticity and no serial correlation.A S S U M P T I O N E.4(H O M O S K E D A S T I C I T Y A N DN O S E R I A L C O R R E L A T I O N)(i) Var(ut͉X) ϭ␴2, t ϭ 1,2,…,n. (ii) Cov(u t,u s͉X) ϭ0, for all t s. In matrix form, we canwrite these two assumptions asVar(u͉X) ϭ␴2I n,(E.13)where Inis the nϫ n identity matrix.Part (i) of Assumption E.4 is the homoskedasticity assumption:the variance of utcan-not depend on any element of X,and the variance must be constant across observations, t. Part (ii) is the no serial correlation assumption:the errors cannot be correlated across observations. Under random sampling,and in any other cross-sectional sampling schemes with independent observations,part (ii) of Assumption E.4 automatically holds. For time series applications,part (ii) rules out correlation in the errors over time (both conditional on X and unconditionally).Because of (E.13),we often say that u has scalar variance-covariance matrix when Assumption E.4 holds. We can now derive the variance-covariance matrix of the OLS estimator.T H E O R E M E.2(V A R I A N C E-C O V A R I A N C EM A T R I X O F T H E O L S E S T I M A T O R)Under Assumptions E.1 through E.4,Var(␤ˆ͉X) ϭ␴2(XЈX)Ϫ1.(E.14)P R O O F:From the last formula in equation (E.12), we haveVar(␤ˆ͉X) ϭVar[(XЈX)Ϫ1XЈu͉X] ϭ(XЈX)Ϫ1XЈ[Var(u͉X)]X(XЈX)Ϫ1.Now, we use Assumption E.4 to getVar(␤ˆ͉X)ϭ(XЈX)Ϫ1XЈ(␴2I n)X(XЈX)Ϫ1ϭ␴2(XЈX)Ϫ1XЈX(XЈX)Ϫ1ϭ␴2(XЈX)Ϫ1.Appendix E The Linear Regression Model in Matrix Form759Formula (E.14) means that the variance of ␤ˆj (conditional on X ) is obtained by multi-plying ␴2by the j th diagonal element of (X ЈX )Ϫ1. For the slope coefficients,we gave an interpretable formula in equation (3.51). Equation (E.14) also tells us how to obtain the covariance between any two OLS estimates:multiply ␴2by the appropriate off diago-nal element of (X ЈX )Ϫ1. In Chapter 4,we showed how to avoid explicitly finding covariances for obtaining confidence intervals and hypotheses tests by appropriately rewriting the model.The Gauss-Markov Theorem,in its full generality,can be proven.T H E O R E M E .3 (G A U S S -M A R K O V T H E O R E M )Under Assumptions E.1 through E.4, ␤ˆis the best linear unbiased estimator.P R O O F :Any other linear estimator of ␤can be written as␤˜ ϭA Јy ,(E.15)where A is an n ϫ k matrix. In order for ␤˜to be unbiased conditional on X , A can consist of nonrandom numbers and functions of X . (For example, A cannot be a function of y .) To see what further restrictions on A are needed, write␤˜ϭA Ј(X ␤ϩu ) ϭ(A ЈX )␤ϩA Јu .(E.16)Then,E(␤˜͉X )ϭA ЈX ␤ϩE(A Јu ͉X )ϭA ЈX ␤ϩA ЈE(u ͉X ) since A is a function of XϭA ЈX ␤since E(u ͉X ) ϭ0.For ␤˜to be an unbiased estimator of ␤, it must be true that E(␤˜͉X ) ϭ␤for all k ϫ 1 vec-tors ␤, that is,A ЈX ␤ϭ␤for all k ϫ 1 vectors ␤.(E.17)Because A ЈX is a k ϫ k matrix, (E.17) holds if and only if A ЈX ϭI k . Equations (E.15) and (E.17) characterize the class of linear, unbiased estimators for ␤.Next, from (E.16), we haveVar(␤˜͉X ) ϭA Ј[Var(u ͉X )]A ϭ␴2A ЈA ,by Assumption E.4. Therefore,Var(␤˜͉X ) ϪVar(␤ˆ͉X )ϭ␴2[A ЈA Ϫ(X ЈX )Ϫ1]ϭ␴2[A ЈA ϪA ЈX (X ЈX )Ϫ1X ЈA ] because A ЈX ϭI kϭ␴2A Ј[I n ϪX (X ЈX )Ϫ1X Ј]Aϵ␴2A ЈMA ,where M ϵI n ϪX (X ЈX )Ϫ1X Ј. Because M is symmetric and idempotent, A ЈMA is positive semi-definite for any n ϫ k matrix A . This establishes that the OLS estimator ␤ˆis BLUE. How Appendix E The Linear Regression Model in Matrix Form 760Appendix E The Linear Regression Model in Matrix Formis this significant? Let c be any kϫ 1 vector and consider the linear combination cЈ␤ϭc1␤1ϩc2␤2ϩ… ϩc k␤k, which is a scalar. The unbiased estimators of cЈ␤are cЈ␤ˆand cЈ␤˜. ButVar(c␤˜͉X) ϪVar(cЈ␤ˆ͉X) ϭcЈ[Var(␤˜͉X) ϪVar(␤ˆ͉X)]cՆ0,because [Var(␤˜͉X) ϪVar(␤ˆ͉X)] is p.s.d. Therefore, when it is used for estimating any linear combination of ␤, OLS yields the smallest variance. In particular, Var(␤ˆj͉X) ՅVar(␤˜j͉X) for any other linear, unbiased estimator of ␤j.The unbiased estimator of the error variance ␴2can be written as␴ˆ2ϭuˆЈuˆ/(n Ϫk),where we have labeled the explanatory variables so that there are k total parameters, including the intercept.T H E O R E M E.4(U N B I A S E D N E S S O F␴ˆ2)Under Assumptions E.1 through E.4, ␴ˆ2is unbiased for ␴2: E(␴ˆ2͉X) ϭ␴2for all ␴2Ͼ0. P R O O F:Write uˆϭyϪX␤ˆϭyϪX(XЈX)Ϫ1XЈyϭM yϭM u, where MϭI nϪX(XЈX)Ϫ1XЈ,and the last equality follows because MXϭ0. Because M is symmetric and idempotent,uˆЈuˆϭuЈMЈM uϭuЈM u.Because uЈM u is a scalar, it equals its trace. Therefore,ϭE(uЈM u͉X)ϭE[tr(uЈM u)͉X] ϭE[tr(M uuЈ)͉X]ϭtr[E(M uuЈ|X)] ϭtr[M E(uuЈ|X)]ϭtr(M␴2I n) ϭ␴2tr(M) ϭ␴2(nϪ k).The last equality follows from tr(M) ϭtr(I) Ϫtr[X(XЈX)Ϫ1XЈ] ϭnϪtr[(XЈX)Ϫ1XЈX] ϭnϪn) ϭnϪk. Therefore,tr(IkE(␴ˆ2͉X) ϭE(uЈM u͉X)/(nϪ k) ϭ␴2.E.3STATISTICAL INFERENCEWhen we add the final classical linear model assumption,␤ˆhas a multivariate normal distribution,which leads to the t and F distributions for the standard test statistics cov-ered in Chapter 4.A S S U M P T I O N E.5(N O R M A L I T Y O F E R R O R S)are independent and identically distributed as Normal(0,␴2). Conditional on X, the utEquivalently, u given X is distributed as multivariate normal with mean zero and variance-covariance matrix ␴2I n: u~ Normal(0,␴2I n).761Appendix E The Linear Regression Model in Matrix Form Under Assumption E.5,each uis independent of the explanatory variables for all t. Inta time series setting,this is essentially the strict exogeneity assumption.T H E O R E M E.5(N O R M A L I T Y O F␤ˆ)Under the classical linear model Assumptions E.1 through E.5, ␤ˆconditional on X is dis-tributed as multivariate normal with mean ␤and variance-covariance matrix ␴2(XЈX)Ϫ1.Theorem E.5 is the basis for statistical inference involving ␤. In fact,along with the properties of the chi-square,t,and F distributions that we summarized in Appendix D, we can use Theorem E.5 to establish that t statistics have a t distribution under Assumptions E.1 through E.5 (under the null hypothesis) and likewise for F statistics. We illustrate with a proof for the t statistics.T H E O R E M E.6Under Assumptions E.1 through E.5,(␤ˆjϪ␤j)/se(␤ˆj) ~ t nϪk,j ϭ 1,2,…,k.P R O O F:The proof requires several steps; the following statements are initially conditional on X. First, by Theorem E.5, (␤ˆjϪ␤j)/sd(␤ˆ) ~ Normal(0,1), where sd(␤ˆj) ϭ␴͙ෆc jj, and c jj is the j th diagonal element of (XЈX)Ϫ1. Next, under Assumptions E.1 through E.5, conditional on X,(n Ϫ k)␴ˆ2/␴2~ ␹2nϪk.(E.18)This follows because (nϪk)␴ˆ2/␴2ϭ(u/␴)ЈM(u/␴), where M is the nϫn symmetric, idem-potent matrix defined in Theorem E.4. But u/␴~ Normal(0,I n) by Assumption E.5. It follows from Property 1 for the chi-square distribution in Appendix D that (u/␴)ЈM(u/␴) ~ ␹2nϪk (because M has rank nϪk).We also need to show that ␤ˆand ␴ˆ2are independent. But ␤ˆϭ␤ϩ(XЈX)Ϫ1XЈu, and ␴ˆ2ϭuЈM u/(nϪk). Now, [(XЈX)Ϫ1XЈ]Mϭ0because XЈMϭ0. It follows, from Property 5 of the multivariate normal distribution in Appendix D, that ␤ˆand M u are independent. Since ␴ˆ2is a function of M u, ␤ˆand ␴ˆ2are also independent.Finally, we can write(␤ˆjϪ␤j)/se(␤ˆj) ϭ[(␤ˆjϪ␤j)/sd(␤ˆj)]/(␴ˆ2/␴2)1/2,which is the ratio of a standard normal random variable and the square root of a ␹2nϪk/(nϪk) random variable. We just showed that these are independent, and so, by def-inition of a t random variable, (␤ˆjϪ␤j)/se(␤ˆj) has the t nϪk distribution. Because this distri-bution does not depend on X, it is the unconditional distribution of (␤ˆjϪ␤j)/se(␤ˆj) as well.From this theorem,we can plug in any hypothesized value for ␤j and use the t statistic for testing hypotheses,as usual.Under Assumptions E.1 through E.5,we can compute what is known as the Cramer-Rao lower bound for the variance-covariance matrix of unbiased estimators of ␤(again762conditional on X ) [see Greene (1997,Chapter 4)]. This can be shown to be ␴2(X ЈX )Ϫ1,which is exactly the variance-covariance matrix of the OLS estimator. This implies that ␤ˆis the minimum variance unbiased estimator of ␤(conditional on X ):Var(␤˜͉X ) ϪVar(␤ˆ͉X ) is positive semi-definite for any other unbiased estimator ␤˜; we no longer have to restrict our attention to estimators linear in y .It is easy to show that the OLS estimator is in fact the maximum likelihood estima-tor of ␤under Assumption E.5. For each t ,the distribution of y t given X is Normal(x t ␤,␴2). Because the y t are independent conditional on X ,the likelihood func-tion for the sample is obtained from the product of the densities:͟nt ϭ1(2␲␴2)Ϫ1/2exp[Ϫ(y t Ϫx t ␤)2/(2␴2)].Maximizing this function with respect to ␤and ␴2is the same as maximizing its nat-ural logarithm:͚nt ϭ1[Ϫ(1/2)log(2␲␴2) Ϫ(yt Ϫx t ␤)2/(2␴2)].For obtaining ␤ˆ,this is the same as minimizing͚nt ϭ1(y t Ϫx t ␤)2—the division by 2␴2does not affect the optimization—which is just the problem that OLS solves. The esti-mator of ␴2that we have used,SSR/(n Ϫk ),turns out not to be the MLE of ␴2; the MLE is SSR/n ,which is a biased estimator. Because the unbiased estimator of ␴2results in t and F statistics with exact t and F distributions under the null,it is always used instead of the MLE.SUMMARYThis appendix has provided a brief discussion of the linear regression model using matrix notation. This material is included for more advanced classes that use matrix algebra,but it is not needed to read the text. In effect,this appendix proves some of the results that we either stated without proof,proved only in special cases,or proved through a more cumbersome method of proof. Other topics—such as asymptotic prop-erties,instrumental variables estimation,and panel data models—can be given concise treatments using matrices. Advanced texts in econometrics,including Davidson and MacKinnon (1993),Greene (1997),and Wooldridge (1999),can be consulted for details.KEY TERMSAppendix E The Linear Regression Model in Matrix Form 763First Order Condition Matrix Notation Minimum Variance Unbiased Scalar Variance-Covariance MatrixVariance-Covariance Matrix of the OLS EstimatorPROBLEMSE.1Let x t be the 1ϫ k vector of explanatory variables for observation t . Show that the OLS estimator ␤ˆcan be written as␤ˆϭΘ͚n tϭ1xt Јx t ΙϪ1Θ͚nt ϭ1xt Јy t Ι.Dividing each summation by n shows that ␤ˆis a function of sample averages.E.2Let ␤ˆbe the k ϫ 1 vector of OLS estimates.(i)Show that for any k ϫ 1 vector b ,we can write the sum of squaredresiduals asSSR(b ) ϭu ˆЈu ˆϩ(␤ˆϪb )ЈX ЈX (␤ˆϪb ).[Hint :Write (y Ϫ X b )Ј(y ϪX b ) ϭ[u ˆϩX (␤ˆϪb )]Ј[u ˆϩX (␤ˆϪb )]and use the fact that X Јu ˆϭ0.](ii)Explain how the expression for SSR(b ) in part (i) proves that ␤ˆuniquely minimizes SSR(b ) over all possible values of b ,assuming Xhas rank k .E.3Let ␤ˆbe the OLS estimate from the regression of y on X . Let A be a k ϫ k non-singular matrix and define z t ϵx t A ,t ϭ 1,…,n . Therefore,z t is 1ϫ k and is a non-singular linear combination of x t . Let Z be the n ϫ k matrix with rows z t . Let ␤˜denote the OLS estimate from a regression ofy on Z .(i)Show that ␤˜ϭA Ϫ1␤ˆ.(ii)Let y ˆt be the fitted values from the original regression and let y ˜t be thefitted values from regressing y on Z . Show that y ˜t ϭy ˆt ,for all t ϭ1,2,…,n . How do the residuals from the two regressions compare?(iii)Show that the estimated variance matrix for ␤˜is ␴ˆ2A Ϫ1(X ЈX )Ϫ1A Ϫ1؅,where ␴ˆ2is the usual variance estimate from regressing y on X .(iv)Let the ␤ˆj be the OLS estimates from regressing y t on 1,x t 2,…,x tk ,andlet the ␤˜j be the OLS estimates from the regression of yt on 1,a 2x t 2,…,a k x tk ,where a j 0,j ϭ 2,…,k . Use the results from part (i)to find the relationship between the ␤˜j and the ␤ˆj .(v)Assuming the setup of part (iv),use part (iii) to show that se(␤˜j ) ϭse(␤ˆj )/͉a j ͉.(vi)Assuming the setup of part (iv),show that the absolute values of the tstatistics for ␤˜j and ␤ˆj are identical.Appendix E The Linear Regression Model in Matrix Form 764。

suricata 多个规则的关联-回复suricata 多个规则的关联是指在使用Suricata 进行网络入侵检测时，通过多个规则之间的关联性，提高检测准确性和可靠性。

在本文中，我将一步一步回答关于suricata 多个规则的关联的相关问题，并探讨如何使用suricata 实现规则关联来提升网络安全。

第一步：什么是Suricata？Suricata 是一个高性能的网络入侵检测系统，它可以监测网络中的流量，检测并阻止恶意的网络活动。

Suricata 使用规则库来描述不同类型的网络攻击和异常行为，当网络流量与规则匹配时，它将触发警报或进行其他特定操作。

第二步：为什么需要多个规则的关联？在现实世界中，网络攻击越来越复杂和隐蔽。

单独一个规则可能无法全面检测出所有类型的威胁。

通过多个规则的关联，可以减少误报率，并更好地检测潜在的网络攻击。

第三步：如何实现规则的关联？Suricata 提供了多种方式来实现规则的关联。

以下是几种常见的方式：1. 协议关联：某些攻击可能需要多个协议层级的信息才能进行准确检测。

Suricata 允许将多个规则与不同层级的协议相关联，以提高检测能力。

2. 时间窗口关联：某些攻击可能在一段时间内持续进行，例如暴力破解密码或扫描端口。

通过使用时间窗口关联，可以将多个规则应用于相同源或目标IP，在特定时间内触发的规则可以被视为相关规则。

3. 规则匹配顺序关联：Suricata 允许用户自定义规则的匹配顺序。

通过设置正确的匹配顺序，可以将多个规则关联起来，以减少误报或提高准确性。

第四步：如何优化规则关联？在实践中，优化规则关联非常重要，以避免过多的误报和漏报。

以下是一些优化规则关联的建议：1. 仔细审查规则：在构建规则关联之前，应对规则库进行仔细审查，并确保每个规则都符合实际需求。

不必要的规则会增加处理开销，并可能导致误报。

2. 分析攻击趋势：通过分析先前的攻击趋势，可以更好地理解攻击者的策略和手段，从而构建更好的规则关联。

create schema语句
嘿，朋友！你知道“create schema”语句吗？这就好比给一个杂乱无
章的房间搭建起合理的框架！比如说，你有一堆各种各样的物品，衣服、鞋子、书籍等等，乱七八糟地堆在一起。

这时候，“create schema”
语句就像是给这些物品划分出不同的区域，衣服放这边，鞋子放那边，书籍放另一个角落。

想象一下，如果没有这个语句，数据库就会像那个混乱的房间一样，数据到处乱飘，找都找不到！比如说你要找某个重要的客户信息，没
有“create schema”语句的规范，岂不是像大海捞针？
当我们使用“create schema”语句时，就好像是一个优秀的组织者，
把一切都安排得井井有条。

就像一个优秀的厨师，把各种食材分类放好，做菜的时候才能得心应手，不是吗？
它能让数据库变得清晰、有序，提高数据管理的效率。

这不就跟整
理好书包，学习起来更轻松是一个道理吗？
所以啊，“create schema”语句真的是太重要啦！。