在运用CAS做Lock-Free操作中有一个经典的ABA问题: 线程1准备用CAS将变量的由A替换为B,在此之前,线程2将变量的由A替换为C,又由C替换为A,然后线程1执行CAS时发现变量的仍然为A,所以CAS成功。但实际上这时的现场已经和最初不同了,尽管CAS成功,但可能存
在运用CAS做Lock-Free操作中有一个经典的ABA问题:
线程1准备用CAS将变量的值由A替换为B,在此之前,线程2将变量的值由A替换为C,又由C替换为A,然后线程1执行CAS时发现变量的值仍然为A,所以CAS成功。但实际上这时的现场已经和最初不同了,尽管CAS成功,但可能存在潜藏的问题,例如下面的例子:
现有一个用单向链表实现的堆栈,栈顶为A,这时线程T1已经知道A.next为B,然后希望用CAS将栈顶替换为B:
head.compareAndSet(A,B);
在T1执行上面这条指令之前,线程T2介入,将A、B出栈,再pushD、C、A,此时堆栈结构如下图,而对象B此时处于游离状态:
此时轮到线程T1执行CAS操作,检测发现栈顶仍为A,所以CAS成功,栈顶变为B,但实际上B.next为null,所以此时的情况变为:
其中堆栈中只有B一个元素,C和D组成的链表不再存在于堆栈中,平白无故就把C、D丢掉了。
以上就是由于ABA问题带来的隐患,各种乐观锁的实现中通常都会用版本戳version来对记录或对象标记,避免并发操作带来的问题,在Java中,AtomicStampedReference
public class Test { private static AtomicInteger atomicInt = new AtomicInteger(100); private static AtomicStampedReference atomicStampedRef = new AtomicStampedReference( 100, 0); public static void main(String[] args) throws InterruptedException { Thread intT1 = new Thread(new Runnable() { @Override public void run() { atomicInt.compareAndSet(100, 101); atomicInt.compareAndSet(101, 100); } }); Thread intT2 = new Thread(new Runnable() { @Override public void run() { try { TimeUnit.SECONDS.sleep(1); } catch (InterruptedException e) { } boolean c3 = atomicInt.compareAndSet(100, 101); System.out.println(c3); // true } }); intT1.start(); intT2.start(); intT1.join(); intT2.join(); Thread refT1 = new Thread(new Runnable() { @Override public void run() { try { TimeUnit.SECONDS.sleep(1); } catch (InterruptedException e) { } atomicStampedRef.compareAndSet(100, 101, atomicStampedRef.getStamp(), atomicStampedRef.getStamp() + 1); atomicStampedRef.compareAndSet(101, 100, atomicStampedRef.getStamp(), atomicStampedRef.getStamp() + 1); } }); Thread refT2 = new Thread(new Runnable() { @Override public void run() { int stamp = atomicStampedRef.getStamp(); try { TimeUnit.SECONDS.sleep(2); } catch (InterruptedException e) { } boolean c3 = atomicStampedRef.compareAndSet(100, 101, stamp, stamp + 1); System.out.println(c3); // false } }); refT1.start(); refT2.start(); } }

ACID attributes include atomicity, consistency, isolation and durability, and are the cornerstone of database design. 1. Atomicity ensures that the transaction is either completely successful or completely failed. 2. Consistency ensures that the database remains consistent before and after a transaction. 3. Isolation ensures that transactions do not interfere with each other. 4. Persistence ensures that data is permanently saved after transaction submission.

MySQL is not only a database management system (DBMS) but also closely related to programming languages. 1) As a DBMS, MySQL is used to store, organize and retrieve data, and optimizing indexes can improve query performance. 2) Combining SQL with programming languages, embedded in Python, using ORM tools such as SQLAlchemy can simplify operations. 3) Performance optimization includes indexing, querying, caching, library and table division and transaction management.

MySQL uses SQL commands to manage data. 1. Basic commands include SELECT, INSERT, UPDATE and DELETE. 2. Advanced usage involves JOIN, subquery and aggregate functions. 3. Common errors include syntax, logic and performance issues. 4. Optimization tips include using indexes, avoiding SELECT* and using LIMIT.

MySQL is an efficient relational database management system suitable for storing and managing data. Its advantages include high-performance queries, flexible transaction processing and rich data types. In practical applications, MySQL is often used in e-commerce platforms, social networks and content management systems, but attention should be paid to performance optimization, data security and scalability.

The relationship between SQL and MySQL is the relationship between standard languages and specific implementations. 1.SQL is a standard language used to manage and operate relational databases, allowing data addition, deletion, modification and query. 2.MySQL is a specific database management system that uses SQL as its operating language and provides efficient data storage and management.

InnoDB uses redologs and undologs to ensure data consistency and reliability. 1.redologs record data page modification to ensure crash recovery and transaction persistence. 2.undologs records the original data value and supports transaction rollback and MVCC.

Key metrics for EXPLAIN commands include type, key, rows, and Extra. 1) The type reflects the access type of the query. The higher the value, the higher the efficiency, such as const is better than ALL. 2) The key displays the index used, and NULL indicates no index. 3) rows estimates the number of scanned rows, affecting query performance. 4) Extra provides additional information, such as Usingfilesort prompts that it needs to be optimized.

Usingtemporary indicates that the need to create temporary tables in MySQL queries, which are commonly found in ORDERBY using DISTINCT, GROUPBY, or non-indexed columns. You can avoid the occurrence of indexes and rewrite queries and improve query performance. Specifically, when Usingtemporary appears in EXPLAIN output, it means that MySQL needs to create temporary tables to handle queries. This usually occurs when: 1) deduplication or grouping when using DISTINCT or GROUPBY; 2) sort when ORDERBY contains non-index columns; 3) use complex subquery or join operations. Optimization methods include: 1) ORDERBY and GROUPB


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