Nosql emerging world of polygot persistence

LOGO

Emerging World of Polyglot
Persistence

By :
● Duc Nguyen
LOG ● Vu Truong
O

LOGO
Content
Part I : 1 Why NoSQL

2 Aggregate Data Models
Understand

3 Data Models

4 Distribution Models

5 Consistency

6 Stamps & Map-Reduce

LOGO
Content
Part II : 1 Key-Value Database

2 Document Database

3
Implement

Column-Family Stores

4 Graph Databases

5 Schema Migrations & Polygot Persistence

6 Choosing Your Database

LOGO
Why NoSQL

The Value of Relational Database

Persistent Data

Concurrency

Integration

Standard Model

LOGO
Why NoSQL

Impedance Mismatch

LOGO
Why NoSQL

Attack of the Clusters

LOGO
Why NoSQL

Common characteristics of NoSQL :

● Not using the relational model

● Running well on clusters

● Open-source

●
Built for the 21th century web estates

● Schemaless

LOGO
Aggregate Data Models
● A collection of data that we interact with as a unit.

● Aggregates form the boundaries for ACID operations
with the database.

● Key-Value , documents and column-family databases
can all be seen as forms of aggregate-oriented DB.

● Aggregates make it easier for the database to manage
data storage over clusters.

● Aggregate-oriented databases work best when most
data interaction is done.

LOGO
Data Models

Complex Schema :

LOGO
Data Models

Graph Databases :

LOGO
Data Models

Schemaless Databases :

Schemaless databases allow you to freely add fields to records.
But there is usually an implicit schema expected by users of the data

LOGO
Distribution Models

Single Server :

LOGO
Distribution Models

Sharding :

LOGO
Distribution Models

Master-Slave Replication :

LOGO
Distribution Models

Peer-to-peer Replication :

LOGO
Consistency

Update Consistency :

Write-write conflicts occur when two clients try
to write the same data at the same time.

Pessimistic approaches lock data records to
prevent conflicts. Optimistic approaches detect
conflicts and fix them.

LOGO
Consistency

Read Consistency :

LOGO
Consistency

CAP Theorem :

LOGO
Consistency

Some Consistency Model:

Strong consistency.

Weak consistency.

Eventually Consistent

LOGO
Consistency

Eventually consistent:

Causal Consistency.

Read-You-Writes Consistency.

Session Consistency.

Monotonic Read Consistency.

Monotonic Write Consistency.

LOGO
Stamps & Map-Reduce

Stamps :
Version stamps help you detect concurrency conflicts

Version stamps can be implemented using counters, GUIDs , content
hashes, timestamps, or a combination of these.

With distributed systems, a vector of version stamps allows you to detect
when different nodes have conflicting updates

LOGO
Stamps & Map-Reduce

Map-Reduce : Basic

LOGO
Stamps & Map-Reduce

Map-Reduce : Partitioning and Combining

LOGO
Content
Part II :
Implement

LOGO
Key-Value Databases

Comparison with Oracle :

LOGO
Key-Value Databases

What Is a Key – Value Store :

The simplest NoSQL data stores to use
From an API perspective.

Some of the popular key-value database :
Riak, Memcached DB , Berkeley DB,
Hamster DB , Amazon Dynamo DB ....

LOGO
Key-Value Databases

Key-Value Store Features :

Consistency : applicable only for operations on a single key , operations
are either a GET, PUT, or DELETE on a SINGLE KEY.

Transactions : Different products of the key-value store kind have different
specifications of transactions.

Query Features : Only support query by the key.

Structure of Data : Don't care what is stored in the value part of the
key-value. The value can be a blob, text, JSON, XML ...

Scaling : many key-value stores scale by using sharding.

LOGO
Key-Value Databases

Suitable Use Cases :

Storing Session Information : every web session is unique and is assigned
a unique session value.This single-request operation makes it very fast.
Solutions such as Memcached are used by many web applications.

User Profiles , Preferences : cause almost every user has a unique
userId , username , or some other attribute .

Shopping Cart Data : for E-commerce websites...

LOGO
Key-Value Databases

When Not to Use :

Relationships among Data :

Multioperation Transactions:

Query by Data:

Operations by Sets:

LOGO
Document Databases

Comparison with Oracle :

LOGO
Document Databases

What Is a Document Database :

LOGO
Document Databases

Features :
Consistency : using the replica sets and choosing to wait for the writes
to be replicated to all the slaves or a given number of slavers.

Transactions : Transactions at the single-document level are known as
atomic transactions. It's not possible with more than one operation.

Availability : Try to improve on available by replicating data using the
master-slave setup. Providing high availability using replica sets.

LOGO
Document Databases

Features :

Query Features : provide different query features. CouchDB allows you to
query via view.

One of good features of document databases, as compared to key-value
stores , is that we can query the data inside the document without having to
retrieve the whole document by its key and introspect the document.

LOGO
Document Databases

Features :
Scaling : When a new nod is added , it will sync up with the existing nodes,
join the replica set as secondary node , and start serving read request.

LOGO
Document Databases

Suitable Use Cases :
Event Logging : Application have different event logging needs; within
the enterprise, these are many different applications that want to log
events. Documents DB can store all these different types of events
and can act as a central data store for event storage.

Content Management Systems, Blogging Platforms: They work well in
content management systems or applications for publishing websites,
managing user comments , user registrations, profiles,
web-facing documents...

Web Analytics or Real-Time Analytics: store data for real-time analytics,
since parts of the document can be updated.It's very easy to store page
views or unique visitors.

E-Commerce Applications : often need to have flexible schema for
products and orders, as well as the ability to evolve their data models
without expensive database refactoring or data migration.

LOGO
Graph Databases

Common characteristics :

● What is a Graph Databases ?

● Features

● Suitable Use Cases

● When Not to Use

LOGO
Graph Databases

What is Graph Databases :

LOGO
Graph Databases

What is Graph Databases :
● Graph databases allow you to store entities and
relationships between these entities.
● We can query the graph in many ways.
● A query on the graph is also known as traversing the
graph.
● In graph databases, traversing the joins or relationships
is very fast.

LOGO
Graph Databases

Features :
● Consistency.

● Transactions.

● Availability.

● Query Features.

● Scaling.

LOGO
Graph Databases

Neo4J:
● We have to create relationship between the nodes in
both directions

● Relationships are first-class citizens in graph
databases

● Relationships don’t only have a type, a start node, and
an end node, but can have properties of their own.

LOGO
Graph Databases

Consistency:
● Graph databases ensure consistency through
transactions.
● When running Neo4J in a cluster, a write to the master
is eventually synchronized to the slaves.
● Slaves are always available for read.
● They do not allow dangling relationships.

LOGO
Graph Databases

Transactions:
● Neo4J is ACID-compliant.
● Before changing any nodes or adding any relationships
to existing nodes, we have to start a transaction.
● Read operations can be done without initiating a
transaction.

LOGO
Graph Databases

Availability:
● Neo4J achieves high availability by providing for
replicated slaves.
● These slaves can also handle writes.
● Neo4J uses the Apache ZooKeeper to keep track.

LOGO
Graph Databases

Query Features:
● Graph databases are supported by query languages
such as Gremlin.
● Gremlin is a domain-specific language for traversing
Graphs.
● Neo4J also has the Cypher query language for querying
the graph.
● Neo4J allows you to query the graph for properties of
the nodes, traverse the graph, or navigate the nodes
● Properties of a node can be indexed using the indexing
service.
● Neo4J uses Lucene as its indexing service.

LOGO
Graph Databases

Scaling:
● With graph databases, sharding is difficult.
● The working set of nodes and relationships is held
entirely in memory.
● Adding more slaves with read-only access to the data
● Sharding the data from the application side using
domain-specific knowledge.

LOGO
Graph Databases

Suitable use cases:
● Connected Data
● Routing, Dispatch, and Location-Based Services.
● Recommendation Engines.

LOGO
Graph Databases

When not to use:
● Problem when you want to update all or a subset of
entities.

LOGO
XU HƯỚNG PHÁT TRIỂN

Động lực phát triển:
•
Ngăn ngừa những sự phức tạp không cần thiết
•
Tính chịu tải cao ( High Throughput ).
•
Khả năng mở rộng theo chiều ngang và
•
chạy được trên các phần cứng thông thường.
•
Tính phức tạp và chi phí để thiết lập các cụm cơ sở
dữ liệu.
•
Thỏa hiệp giữ độ tin cậy và hiệu suất cao

LOGO

Động lực phát triển:
•
Xóa bỏ tư duy về một cơ sở dữ liệu có thể giải quyết
tất cả các vấn đề liên quan đến lưu trữ dữ liệu.
•
Ước mơ về một sự phân bố đơn giản và phân vùng
của các mô hình dữ liệu tập trung.
•
Sự phát triển của ngôn ngữ lập trình và các
frameworks.
•
Đáp ứng yêu cầu của điện toán đám mây.

LOGO

Phân loại: (Theo lý thuyết CAP)

Nội dung LOGO

1 Giới thiệu

2 Xu hướng phát triển

3 Các nguyên lý hoạt động

4 Hệ cơ sở dữ liệu MongoDB

5 Tổng kết

6 Tài liệu tham khảo

LOGO
Các nguyên lý hoạt động

Lý thuyết CAP :

LOGO

Sự phân chia:

Memory Cached ( bộ nhớ Cache) .


Clustering ( Bó ) .


Separating Reads from Writes ( Tách biệt giữa việc đọc và ghi) .

LOGO

Các mô hình lưu trữ :

Lưu trữ theo hàng

LOGO


Lưu trữ theo cột

LOGO


Lưu trữ theo nhóm cột

LOGO

Các mô hình lưu trữ:

Lưu trữ sử dụng mô hình cấu trúc cây hợp nhất

LOGO

Mô hình truy vấn:

Truy vấn tương tự như các hệ CSDL quan hệ

LOGO


Truy vấn sử dụng phương thức tán xạ tập hợp

LOGO


Truy vấn sử dụng cây B++ tree

LOGO

Đánh giá hiệu xuất truy vấn :

LOGO
HỆ CƠ SỞ DỮ LiỆU MONGODB

Tạo cơ sở dữ liệu (Collection).
db.createCollection(<name> ,
{<configuration parameters >})

Định nghĩa một tài liệu : dùng JSON
{
title : " MongoDB " ,
last_editor : "172.5.123.91" ,
last_modified: new Date ( " 9/23/2010 " ) ,
body : " MongoDB is a ..." ,
categories : [" Database " , " NoSQL " , " Document Database ],
reviewed : false
}

LOGO

Thêm một tài liệu :
db.<collection>.insert({ title:"MongoDB",
last_editor: ... }) ;

Truy xuất một tài liệu :
db.< collection >. find ( { categories : [ "
NoSQL " , " Document Database" ] } ) ;

Cập nhật tài liệu :
db.< collection >.save ( { ... } ) ;

LOGO

Cập nhật dữ liệu :
db.<collection>.update (<criteria>,<new
document>,<upsert>,<multi >) ;

Xóa tài liệu:
db.< collection >.remove ( { < criteria > } ) ;

Tạo chỉ mục:
db.< collection >.ensureIndex ({ < field1 >:
< sorting >,< field2 >:< sorting > , ...}) ;

LOGO

So sánh với hiệu suất khi thực thi lệnh
INSERT với SQL Server:

LOGO

truy vấn đơn giản với SQL Server:

LOGO

truy vấn phức tạp với SQL Server:

LOGO

Chạy Demo so sánh INSERT với
MySQL:(mili giây)

LOGO
Tổng kết
Ưu điểm :


+ Đáp ứng được được hiệu suất cao , chịu tải lớn.
+ Khả năng mở rộng theo chiều ngang.
+ Chạy được trên nhiều phần cứng phổ thông.
+ Đáp ứng được nhu cầu của điện toán đám mây.

LOGO
Tổng kết
Nhược điểm:


+ Đại đa số đều đang trong quá trình phát triển .
+ Đa số đều là phần mềm nguồn mở . Khó có thể được
chấp nhận trong các môi trường kinh doanh lớn.
+ Không ràng buộc tức là không đảm bảo được tính toàn
vẹn của dữ liệu.
+ Không đáp ứng được nhu cầu của nhiều loại ứng
dụng.

LOGO
Tổng kết

NoSQL hay SQL:

Các chuyên gia khuyên rằng khi phát triển ứng dụng nhà sản xuất nên quan
tâm tới các NoSQL. Và ứng dụng của bạn nên chuyển qua NoSQL
khi thấy thực sự cần thiết.

LOGO
Tài liệu tham khảo
1. NoSQL resources: http://nosql-database.org/
2. NoSQL wiki - http://en.wikipedia.org/wiki/NoSQL
3. Scalability wiki -
http://en.wikipedia.org/wiki/Scalability#Scale_horizontally_.
28scale_out.29
4. A Brief History of NoSQL - http://
blog.knuthaugen.no/2010/03/a-brief-history-of-nosql.html
5. Nhất Quán Cuối Cùng - http://
www.sqlviet.com/blog/nhat-quan-cuoi-cung.
6. NoSQL Brief Guide to the Emerging World of Polygot Persistence.
Martin Fowler.

LOGO

www.themegallery.com

Thank You !
LOG
O

Nosql emerging world of polygot persistence

More Related Content

Featured (20)

Nosql emerging world of polygot persistence