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Designing a TPS for clouds will meet these challenges: Diverse functionality. The concept of translytics as “a unified and integrated data platform that supports multi-workloads such as transactional, operational, and analytical simultaneously in realtime, … and ensures full transactional integrity and data consistency”. Scale Cloud-first data platforms are designed to scale well beyond the limits of a single application. Latency With the thrust into new interactive domains like social networks, messaging and algorithmic trading,latency becomes essential. Multi-tenancy Maintaining access rights is therefore an important design consideration for TPSs. 论文的工作集中于以下几点： ...

An entirely re-designed version of Omid1. Omid’s job is to manage the transaction control plane. The transaction metadata includes: A dedicated table(Commit Tabla, CT) holds a single record per committing transaction. Per-row metadata for items accessed by transactions. Feature: A middleware oriented. Snapshot isolate should provide: Visibility check rules. Write conflicts detection. Visibility Check Rules Intuitively, with SI, a transaction’s reads all appear to occur the time when it begins($ts_r$) while its writes appear to execute when it commits($ts_c$). ...

Background Database systems have evolved to be with a cloud-native architecture,i.e., disaggregation of compute and storage architecture, which decouples the storage from the compute nodes, then connects the compute nodes to shared storage through a high-speed network. The principle of cloud-native architecture is decoupling. (decoupled functions to make good use of disaggregated resources) Most existing cloud-native databases couple TP either with storage layer or with execution layer. Coupling TP with Storage Layer TiDB adopts a distributed transactional key-value store TiKV as the storage layer. ...

FAQ What is the difference between rolling backward and rolling forward in database transactions? “Rolling backward” and “rolling forward” in the context of database transactions refer to two distinct phases of the recovery process that helps maintain the integrity and consistency of the database after a system crash or failure. These concepts are tied to the idea of transaction logs that record the changes made to the database. Below are the key differences between rolling backward and rolling forward: ...

FAQ What is a deterministic database? A deterministic database is a system where the outcomes of any database operations are guaranteed to be the same every time they are executed, provided that the operations are started from the same database state. This concept implies a level of reliability and predictability in the behavior of the database system. Deterministic behavior is essential in many contexts, especially in distributed databases, where operations might need to be coordinated across multiple nodes, or in any system where replication, fault tolerance, and consistency are important. If a database operation is deterministic, it means the following: ...

The Three-Pass Approach Each pass accomplishes specific goals and builds upon the previous pass: The first pass gives you a general idea about the paper. The second pass lets you grasp the paper’s content, but not its details. The third pass helps you understand the paper in depth. The First Pass A quick scan to get a bird’s-eye view of the paper. This pass should take about five to ten minutes and consists of the following steps: ...

这篇文章讲道理不应该写这么长的，但讲的东西比较“好玩”，于是就多记录了一些。 FAQ What is an ad hoc transaction? It refers to database operations coordinated by application code. Specifically, developers might explicitly use locking primitives and validation procedures to implement concurrency control amid the application code to coordinate critical database operations. Why do not use database transactions instead? For flexibility or efficiency. 在一般的数据库使用场景下，伴随着数据库的隔离级别提升，性能下降十分严重，为此，应用层临时事务需要做到既利用低隔离级别的数据库防止性能下降，又要实现应用层的事务机制防止数据一致性错误等问题。 What is a false conflict in database systems? In database systems, a false conflict, also known as a phantom conflict, occurs when a transaction appears to conflict with other transactions, but in reality, it does not. This can happen in situations where transactions are using optimistic concurrency control or multi-version concurrency control mechanisms. ...

Analyze 这篇论文关注在如何使用黑盒的方式验证键值存储的的可串行化。 Background 如今许多客户选择使用云数据库提供的键值存储服务，客户程序的正确性受到云数据库的正确性的影响，云数据库的正确性常常通过可串行化来定义，即客户的事务仿佛以串行的方式执行，那么云数据库是否符合了可串行化的约束？这个问题有几个挑战，一方面数据库是黑盒的，我们无法得到数据库的代码，只能分析数据库的行为，即输入和输出，另一方面需要在数据库不断运行中，同步验证其是否符合可串行化的要求，这需要验证手段高效并具有可扩展性。 这篇论文的直觉来源于 SMT solver 以及计算能力的进步，认为其足以自动化的验证可串行化的问题，于是他们基于 SMT solver 提出 Cobra 框架，Cobra 包含一系列技术，做到了高效可扩展的验证可串行化，实验表明 Cobra 能验证实际场景下数据库的可串行化。 Structures Each client request is one of five operations: start, commit, abort (which refer to transactions), and read and write (which refer to keys). History collectors sit between clients and the database, capturing the requests that clients issue and the (possibly wrong) results delivered by the database. A verifier retrieves history fragments from collectors and attempts to verify whether the history is serializable. ...