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Completeness and consistency issues with the Sub-database table

In a recent project, the database was kept in a sub-library due to the large amount of data being accounted for daily. When data is dispersed across libraries, there is a consistency and integrity of the data update operation. The following is a typical scenarioSuppose there are three physical libraries, now there is a file, there is 1W data, according to the rules of the library, you can divide the data in the file into three libraries, it is necessary to ensure that the 1W data to be fully sto

(turn) A large confession: I was so blown by two melts

, now I am afraid of assets tens of millions of it?Not to 11 points, the market diving, trading open, sell a single swarming out, directly hit 2 points on the flat,At this point, I noticed that there was a "fixed guarantee ratio" option in the credit account, which was already 1.47多 points, and in the morning, because of the participation in the auction, I did not pay attention to this option and saw that the guar

Memory Management _java Memory management

reading the value of x and the value of x to the working memory of the 2 operations are atomic operations, but together is not atomic operation.Similarly, X + + and × = x+1 include 3 operations: reads the value of x, adds 1 operations, and writes a new value.So the above 4 statements only have the atomicity of statement 1 operations.That is, only a simple read, assignment (and must assign a number to a variable, the reciprocal assignment of a variable is not an atomic operation) is the atomic O

Thread Synchronization (1): Atomic operation, memory barrier, lock overview

Atomic Operation , memory barrier , lock1. principle: TheCPU provides atomic operation, shutdown interrupt, lock memory bus , memory barrier and other mechanisms;OS based on these several CPU hardware mechanism, the lock can be implemented, and then a variety of synchronization mechanisms (semaphores, messages, Barrier and so on). 2. The most fundamental theory of all synchronization operations is atomic operations. Memory Barriers , locks are designed to gu

Introduction to common Collections in Java Collections Framework, their features, applicable scenarios, and implementation principles

ArrayList. The difference is that CopyOnWriteArrayList will first copy a copy during write operations and perform write operations on the new copy, then modify the reference. This mechanism allows CopyOnWriteArrayList to not lock read operations, which makes the Read efficiency of CopyOnWriteArrayList much higher than that of Vector. The CopyOnWriteArrayList concept is similar to read/write splitting, and is suitable for multi-threaded scenarios with more reads and less writes. Note that the Co

Java concurrent programming: volatile keyword Parsing

. After thread 1 modifies the variable I, thread 2 does not immediately see the value modified by thread 1. 3. orderliness: The program execution order is executed in the order of code. For a simple example, see the following code: int I = 0; boolean flag = false; I = 1; // Statement 1 flag = true; // Statement 2 the code above defines an int type variable, defines a boolean type variable, and then assigns values to the two variables respectively. In terms of code sequence, Statement 1 is prior

JVM Learning (3) -- Summary of the Java memory model, jvmjava

between atomic operations is allowed. When thread B modifies stop, it also invalidates the stop cache row in the working memory of thread! Because the cached row of the stop copy value of the JVM master memory in the working memory of thread A is invalid, the value of the stop read by thread A will be read from the JVM master memory. In this case, A gets the latest and correct stop value -- true. The program is perfectly interrupted. Many people also think that volatile is better than lock pe

Java concurrency in-depth analysis of the implementation principle of volatile

-Contains three operations: reads I, i + 1, assigns +1 results to I;4-Same as threeIn a single-threaded environment, we can assume that the entire step is atomic, but in a multithreaded environment, Java only guarantees that the basic data type of variables and assignment operations is atomic ( Note: In a 32-bit JDK environment, the reading of 64-bit data is not atomic operations *, such as Long, Double). To ensure atomicity in a multi-threaded environment, it can be ensured by locks and synchro

"Dead java Concurrency"-----In-depth analysis of the implementation principle of volatile

-threaded environment, we can assume that the entire step is atomic, but in a multithreaded environment, Java only guarantees that the basic data type of variables and assignment operations is atomic ( Note: In a 32-bit JDK environment, the reading of 64-bit data is not atomic operations *, such as Long, Double). To ensure atomicity in a multi-threaded environment, it can be ensured by locks and synchronized. Volatile is no guarantee of the a

Multi-Thread final variable detailed

final type, it is also equivalent to telling the maintainer that these fields will not change.Just as "unless you need more visibility, you should declare all the hungry domains as private domains" [EJ Item 12] is a good habit to become, "unless a domain is mutable, it should be declared as a final field" is also a good habit.Example: Using Volatile types to publish immutable objectsAs we have said before, volatile can be used to guarantee the visibi

Some of the things about Java threading concurrency

thread has been canceled (cancelled), then calling its isalive when it returns false will vary depending on the implementation of each Java virtual machine. There is no way to know if an inactive thread has been started (the translator notes that the thread will return false before and after the start of the run and you will not know the specific state of the thread in false). Another point is that while a thread can know the identity of other threads of the same thread group, it does not know

Java Memory models and threads

the value of the variable. Assign (Assignment): A variable acting on a working memory that assigns a value to a working memory from the execution engine, and performs this operation whenever the virtual opportunity is assigned to a byte-code instruction that assigns a value to a variable. Store: A variable acting on a working memory that transfers the value of a variable in the working memory to the main memory for subsequent write operations. Write: A variable that acts on the main

Common data Structures in Java: List and map-how the bottom layer is implemented

chain list ensures that the elements are ordered. 29 The element is guaranteed to be unique by a hash table. TreeSet 31 The underlying data structure is a red-black tree. (is a self-balancing two-fork tree) 32 How to guarantee the uniqueness of elements? 33 based on whether the return value of the comparison is 34 how to guarantee the ordering of the elements? 352 Ways 36 Natural sort (elements are compara

Java concurrency mechanism and underlying implementation principles

using a method based on cache locking or bus locking. First the processor automatically guarantees the atomicity of basic memory operations. The processor guarantees that a byte is read or written from the system memory, meaning that when a processor reads one byte, the other processor cannot access the memory address of the byte. PENTIUM6 and the latest processors can automatically guarantee that the single-processor operation of 16/32/64 bits in a

Ethereum Source Analysis (52) Ethereum Fast Sync algorithm

trie downloaded successfully, the block defined by Pivot point is used as the current chunk header-it is fully processed like the original synchronization. Import all remaining blocks (1024)# # Analysis Analysisby downloading and verifying the entire header chain, we can guarantee with all the security of the Classica L Sync, that's the hashes (receipts, State tries, etc) contained within the www.yigouyule2.cn headers is valid. Based on those hashes,

Java Multithreading Knowledge points

prevent a thread from reading a shared variable when the value is incorrect, but volatile does not guarantee the atomicity of the variable, and if the shared variable is a simple data type, the modification of the variable is not based on its own value (e.g. x=10 can, X + + does not), can guarantee its atomicity. Because volatile does not guarantee atomicity, it

Thread Safety and lock optimization

are not absolutely thread-safe. Like the vector class, this is a thread-safe container whose add, get, and size methods are synchronized decorated, albeit inefficient. This does not mean that this is safe:Suppose a thread is constantly add, multiple threads are constantly remove,for (int i = 0; i This example shows that the size () and remove () operations must be locked at the same time, and the atomicity of a single operation does not guarantee tha

Sina Micro-Bo lottery What is the scheme of the purchase of a guaranteed?

The scheme is guaranteed to be the sponsor and site guarantee. The sponsor's guarantee means that after the deadline for the purchase, if the scheme is not full, the Promoter invests the guaranteed amount previously promised to make the scheme successful. The sponsor is guaranteed to be a voluntary guarantee, the minimum guaranteed amount is 5% of the total amou

"Fabric trading Process" Transaction flow non-direct translation

obtained a CA certificate for permission validation, along with the corresponding encrypted data (that is, a bunch of configuration files that do not have access to the network). The Chaincode (containing a set of key value pairs representing the initial state of the radish market) are installed on th E peers and instantiated on the channel. The Chaincode contains logic defining a set of transaction instructions and the agreed upon price for a radish. An endorsement policy have also been set fo

Hybridtime-accessible Global consistency with high Clock uncertainty

Amazon's Dynamo [9] and Facebook's Cassandra [], relax the consistency Model,and offer only eventual consistency. Others such as HBase [1] and BigTable [4] offer strong consistency only for operations touching a single partition, but no T across the database as a whole. The Dynamo and Cassandra are based on the vector clocks and gossip algorithms, emphasizing high availability and can reach eventual consistency HBase, however, can provide a single partition of strong consistency, but for cross-p

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