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oracle分片键,数据库SQL语句及性能优化

發布時間:2024/9/27 数据库 26 豆豆
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3、閱讀以下文章,回答一下問題:

3.1、什么是數據庫分片技術?

3.2、數據庫分片的好處有哪些?

3.3、Oracle 數據庫分片技術比NoSQL的分片有哪些優勢?

Overview of Oracle Sharding

Become familiar with the concepts related to managing a sharded database with Oracle Sharding.

Oracle Sharding terminology, concepts, and benefits are described in the following topics:

Benefits of Sharding

Sharding provides linear scalability and complete fault isolation for the most demanding OLTP applications.

Components of the Oracle Sharding Architecture

Oracle Sharding is a scalability and availability feature for suitable OLTP applications.

Application Suitability for Sharding

Oracle Sharding is for OLTP applications that are suitable for a sharded database.

About Sharding

Sharding is a data tier architecture in which data is horizontally partitioned across independent

databases.Each database is hosted on dedicated server with its own local resources - CPU, memory, flash,

or disk. Horizontal partitioning involves splitting a database table across shards so that each shard

contains the table with the same columns but a different subset of rows. A table split up in this manner

is also known as a sharded table.

Sharding is based on shared-nothing hardware infrastructure and it eliminates single points of failure

because shards do not share physical resources such as CPU, memory, or storage devices. Shards are also

loosely coupled in terms of software; they do not run clusterware.

Shards are typically hosted on dedicated servers. These servers can be commodity hardware or engineered

systems. The shards can run on single instance or Oracle RAC databases. They can be placed on-premises,

in a cloud, or in a hybrid on-premises and cloud configuration.

From the perspective of a database administrator, an SDB consists of multiple databases that can be

managed either collectively or individually. However, from the perspective of the application, an SDB

looks like a single database: the number of shards and distribution of data across those shards are

completely transparent to database applications.

Sharding is intended for custom OLTP applications that are suitable for a sharded database architecture.

Applications that use sharding must have a well-defined data model and data distribution strategy

(consistent hash, range, list, or composite) that primarily accesses data using a sharding key.

Examples of a sharding key include customer_id, account_no, or country_id.

Benefits of Sharding

Sharding provides linear scalability and complete fault isolation for the most demanding OLTP

applications.

Key benefits of sharding include:

Linear Scalability.

Sharding eliminates performance bottlenecks and makes it possible to linearly scale performance

and capacity by adding shards.

Fault Containment.

Sharding is a shared nothing hardware infrastructure that eliminates single points of failure,

such as shared disk, SAN, and clusterware, and provides strong fault isolation—the failure or

slow-down of one shard does not affect the performance or availability of other shards.

Geographical Distribution of Data.

Sharding makes it possible to store particular data close to its consumers and satisfy regulatory

requirements when data must be located in a particular jurisdiction.

Rolling Upgrades.

Applying configuration changes on one shard at a time does not affect other shards, and allows

administrators to first test the changes on a small subset of data.

Simplicity of Cloud Deployment.

Sharding is well suited to deployment in the cloud. Shards may be sized as required to accommodate

whatever cloud infrastructure is available and still achieve required service levels. Oracle Sharding

supports on-premises, cloud, and hybrid deployment models.

Unlike NoSQL data stores that implement sharding, Oracle Sharding provides the benefits of sharding

without sacrificing the capabilities of an enterprise RDBMS. For example, Oracle Sharding supports:

Relational schemas

Database partitioning

ACID properties and read consistency

SQL and other programmatic interfaces

Complex data types

Online schema changes

Multi-core scalability

Advanced security

Compression

High Availability features

Enterprise-scale backup and recovery

總結

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