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Concept

Database transaction

Résumé

A database transaction symbolizes a unit of work, performed within a database management system (or similar system) against a database, that is treated in a coherent and reliable way independent of other transactions. A transaction generally represents any change in a database. Transactions in a database environment have two main purposes:

To provide reliable units of work that allow correct recovery from failures and keep a database consistent even in cases of system failure. For example: when execution prematurely and unexpectedly stops (completely or partially) in which case many operations upon a database remain uncompleted, with unclear status.

To provide isolation between programs accessing a database concurrently. If this isolation is not provided, the programs' outcomes are possibly erroneous.

In a database management system, a transaction is a single unit of logic or work, sometimes made up of multiple operations. Any logical calculation done in a consistent mode in a

Source officielle

https://en.wikipedia.org/wiki/Database_transaction

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Publications associées (44)

The use of transactions in distributed systems dates back to the 70's. The last decade has also seen the proliferation of transactional systems. In the existing transactional systems, many protocols employ a centralized approach in executing a distributed transaction where one single process coordinates the participants of a transaction. The centralized approach is usually straightforward and efficient in the failure-free setting, yet the coordinator then turns to be a single point of failure, undermining reliability/security in the failure-prone setting, or even be a performance bottleneck in practice. In this dissertation, we explore the complexity of decentralized solutions for reliable and secure distributed transactions, which do not use a distinguished coordinator or use the coordinator as little as possible. We show that for some problems in reliable distributed transactions, there are decentralized solutions that perform as efficiently as the classical centralized one, while for some others, we determine the complexity limitations by proving lower and upper bounds to have a better understanding of the state-of-the-art solutions. We first study the complexity on two aspects of reliable transactions: atomicity and consistency. More specifically, we do a systematic study on the time and message complexity of non-blocking atomic commit of a distributed transaction, and investigate intrinsic limitations of causally consistent transactions. Our study of distributed transaction commit focuses on the complexity of the most frequent executions in practice, i.e., failure-free, and willing to commit. Through our systematic study, we close many open questions like the complexity of synchronous non-blocking atomic commit. We also present an effective protocol which solves what we call indulgent atomic commit that tolerates practical distributed database systems which are synchronous "most of the time", and can perform as efficiently as the two-phase commit protocol widely used in distributed database systems. Our investigation of causal transactions focuses on the limitations of read-only transactions, which are considered the most frequent in practice. We consider "fast" read-only transactions where operations are executed within one round-trip message exchange between a client seeking an object and the server storing it (in which no process can be a coordinator). We show two impossibility results regarding "fast" read-only transactions. By our impossibility results, when read-only transactions are "fast", they have to be "visible", i.e., they induce inherent updates on the servers. We also present a "fast" read-only transaction protocol that is "visible" as an upper bound on the complexity of inherent updates. We then study the complexity of secure transactions in the model of secure multiparty computation: even in the face of malicious parties, no party obtains the computation result unless all other parties obtain the same result. As it is impossible to achieve without any trusted party, we focus on optimism where if all parties are honest, they can obtain the computation result without resorting to a trusted third party, and the complexity of every optimistic execution where all parties are honest. We prove a tight lower bound on the message complexity by relating the number of messages to the length of the permutation sequence in combinatorics, a necessary pattern for messages in every optimistic execution.

EPFL2018

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Database Queries in Java

Christopher Ming-Yee Iu

In conventional programming languages like Java, the interface for accessing databases is often inelegant. Typically, an entire separate database query language must be embedded inside a conventional programming language for programmers to access the full power and speed of a database. Programmers, though, prefer working entirely from within their conventional programming languages, both for general-purpose computation and for database access. This thesis explores how database operations can be expressed using the existing syntax of conventional programming languages. Programmers are able to write all their code –both general purpose code and database access code– in a single language. To run these database operations efficiently though, algorithms are needed for finding these database operations and optimizing them. This thesis focuses on techniques that can be easily adopted because they do not require changes to existing compilers. Three systems have been developed: Queryll, JReq, and HadoopToSQL. Each system examines the problem from the context of functional-style code, imperative-style code, and MapReduce-style code respectively.

EPFL2010

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Efficient Protocols for Enforcing Causal Consistency in Geo-Replicated Key-Value Data Stores

Kristina Spirovska

Modern large-scale data platforms manage colossal amount of data, generated by the ever-increasing number of concurrent users. Geo-replicated and sharded key-value data stores play a central role when building such platforms. As the strongest consistency model proven not to compromise availability, causal consistency (CC) is perfectly positioned to address the needs of such large-scale systems, while preventing some ordering anomalies. Transactional Causal Consistency (TCC) augments CC by providing richer transactional semantics, simplifying the development of distributed applications. However, achieving CC/TCC in an efficient manner is very challenging. In this thesis we introduce several protocols and designs for high performance causally consistent geo-replicated key-value data stores in several different settings. First, we present a new approach to implementing CC in geo-replicated data stores, called Optimistic Causal Consistency (OCC). By introducing a technique that we call client-assisted lazy dependency resolution, OCC makes it possible for updates replicated to a remote data center to become visible immediately, without checking if their causal dependencies have been received. We further propose a recovery mechanism that allows an OCC system to fall back on a pessimistic protocol to continue operating during network partitions. We show that OCC improves data freshness, while offering performance that is comparable or better than its pessimistic counterpart. Next, we address the problem of providing low-latency TCC reads under full replication. We present Wren, the first TCC system that at the same time achieves low latency by implementing nonblocking read operations and efficiently scales out by sharding. Wren introduces new protocols for transaction execution, dependency tracking and stabilization. The transaction protocol supports nonblocking reads by providing a transaction snapshot as a union of a fresh causal snapshot installed by every partition in the local data center and a client-side cache for writes that are not yet included in the snapshot. The dependency tracking and stabilization protocols require only two scalar timestamps, resulting in efficient resource utilization and providing scalability in terms of shards and replication sites, under a full replication setting. In return for these benefits, Wren slightly increases the visibility latency of updates. Finally, we present PaRiS, the first TCC system that supports partial replication and provides low latency by implementing non-blocking parallel read operations. PaRiS relies on a novel protocol to track dependencies, called Universal Stable Time (UST). By means of a lightweight background gossip process, UST identifies a snapshot of the data that has been installed by every data center in the system. PaRiS equips clients with a private cache, in which they store their own updates that are not yet reflected in the snapshot. The combination of the UST-defined snapshot with client-side cache enables interactive transactions that can consistently read from any replication site without blocking. Moreover, PaRiS requires only one timestamp to track dependencies and define transactional snapshots, thereby achieving resource efficiency and scalability in terms of shards and replication sites, in a partial replication setting.

EPFL2020

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Efficient Protocols for Enforcing Causal Consistency in Geo-Replicated Key-Value Data Stores

Kristina Spirovska

EPFL2020

EPFL2018