Database NoSQL

1. BỘ GIÁO DỤC VÀ ĐÀO TẠO
TRƯỜNG ĐẠI HỌC KHOA HỌC TỰ NHIÊN TP.HCM
KHOA CÔNG NGHỆ THÔNG TIN
NoSQL
Column-Family Stores
GVHD: Ts. Nguyễn Trần Minh Thư
Nhóm 07:
1. 19C11015 - Đỗ Huy Gia Cát
2. 21C12003 - Đào Thanh Danh
3. 21C11026 - Nguyễn Thành Thái
Báo cáo môn Các hệ cơ sở dữ liệu nâng cao
1
NoSQL - Not Only SQL

2. CONTENTS
• Column-Family Stores NoSQL
o Overview
o Column-Family Databases
• Cassandra's Structure and Features
• Compare Colum-Family Data Store with others
• Query features
• Expand analyse
• Scaling
• Some compare Cassandra and HBase
• Apply suitable usecases
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3. Introduction
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4. Wide Column / Column Family Database
• Column-family stores are databases in which data is stored by key-
value mapping and values group into multiple column families, with
each being a map of data
• Keyword comparison between RDBMS and Cassandra
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RDBMS Cassandra
Database instance Cluster
Database Keyspace
Table Column Family
Row Row
Column (same for all rows) Column (can be different per row)

5. Column Family Database
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6. Column Family Unit Structure Storage
• Column: the basic storage unit,
consist of a name-value pair with
the name also acts as the key, and
stored with a timestamp value
• Super column: column
whose value is a map of columns
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7. Column Family Unit Structure Storage
• Standard column family: column
family where all columns are
simple columns
• Super column family: column
family where exists at least one
super column
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8. Cassandra's Features
• Consistency
• Transactions
• Availability
• Scaling
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9. Consistency
• Cassandra stores replicas on multiple nodes to ensure reliability
• Cassandra provides three consistency levels:
ONE: Only need one of the nodes to respond to the request, good for
high write performance requirements
QUOROM: Ensures that majority of the node respond to the request
ALL: All nodes will have to respond to the requests
• If a node is down, the data will be stored later when it comes back via
hints (hinted handoff) or repair command.
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10. Transactions
• In Cassandra, transactions are atomic and isolated
• Atomic: inserted or updating columns in a row is treated as a write
operation
• Isolation: writes to a row are isolated to client and not visible to other
uses until completion
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11. Availability
• Availability is governed by the formula
(R + W) > N
R, W: minimum number of nodes read/write request is successfully
responded; N: number of replicas of data
• Keyspaces should be set up depending on your need – higher
availability for read or write
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12. Scaling
• Cassandra handles scaling by adding additional nodes to the cluster
• Allows clusters to be scaled on the fly without operations => maxium
uptime
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13. 15
Database - Open-source NoSQL - Column Family
- Store data no relationship on column-family model
Scalability - Scalabilitiable by increasing nodes
Replication - Replica data on multi node

14. 16
Infrastructure Design independence, can integrate
with DBMS other and Storm, Hadoop
Base on Hadoop, can integrate with
Zookeeper
HBase master, HBase data node,
name node
Support Support ordered partitioning Not-support ordered partitioning
Node Multi seed node in clusster Node master monitoring/coordinator
nodes
Query language Cassandra Query Language – CQL
Cassandra Query Language Shell -
CQLSH
Only support HBase shell

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16. 18

17. Basic Queries CQL
• Cassandra Query Language
• Cassandra Query Language Shell -
CQLSH
• Only support HBase Shell
• Apache Phoenix -> Query Engine
https://data-
flair.training/blogs/hbase-shell-
commands/
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18. Cassandra Query Language
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• CREATE KEYSPACE <identifier> WITH <properties>
• CREATE KEYSPACE videodb WITH REPLICATION =
{ 'class' : 'SimpleStrategy', 'replication_factor' : 1 };
SimpleStrategy
NetworkTopologyStrategy

19. Cassandra Query Language
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USE videodb;
CREATE TABLE videos
(
videoid uuid,
videoname varchar,
username varchar,
description varchar,
location map<varchar,varchar>,
tags set<varchar>,
upload_date timestamp,
PRIMARY KEY (videoid)
);
CREATE TABLE video_rating
(
videoid uuid,
rating_counter counter,
rating_total counter,
PRIMARY KEY (videoid)
);
CREATE TABLE video_event
(
videoid uuid,
username varchar,
event varchar,
event_timestamp timeuuid,
video_timestamp bigint,
PRIMARY KEY ((videoid, username), event_timestamp, event)
) WITH CLUSTERING ORDER BY (event_timestamp DESC, event ASC);
CREATE (TABLE | COLUMNFAMILY)
<tablename>
('<column-definition>' , '<column-definition>')
(WITH <option> AND <option>)

20. Cassandra Query Language
• Built-In Data Type: boolean, int, bigint, variant, float, double, decimal,
ascii, varchar, text, timestamp, blob, inet, timeuuid, uuid,…
• Collection Data Type: LIST, SET, MAP
• User-Defined Data Type
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21. Cassandra Query Language
• User-Defined Data Type
CREATE TYPE <keyspace>.<data type>
(variable,variable)
CREATE TYPE records (
name text,
branch text,
phone int,
city text,
id set<int>
);
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22. Cassandra Query Language
SELECT Clause, WHERE Clause & ORDERBY
INSERT INTO <table name>
(<field name 1>,<field name 2>,<field name 3>.,...)
VALUES ('value 1','value 2','value 3',....)
USING <update parameter>;
UPDATE <table name> USING <update parameter>
SET <field name 1>=< value 1>,
< field name 2>=< value 2>,
< field name 3>=<value 3>, .....
WHERE <field>=<value>; 24

23. Cassandra Query Language
DELETE <table name>
USING <update parameter>
WHERE <identifier>
BEGIN BATCH
//different data manipulation command syntax -> INSERT, UPDATE
// DELETE
APPLY BATCH;
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24. Cassandra Query Language
• Advanced Queries and Indexing
• CREATE INDEX <field name> ON <table name>​
Indexes are implemented as bit-mapped indexes and perform well for
low-cardinality column values.
• USE, CREATE, ALTER, DROP, TRUNCATE,...
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25. Stores writing
• Memory space - memtable
• Disk store SSTable
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26. Retried reading
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27. Suitable Use Cases
• A great choice to store event information, such as application state or errors
encountered by the application
• Content Management Systems, Blogging Platforms
=> store blog entries with tags, categories, links, and trackbacks
• Count and categorize visitors of a page to calculate analytics
• Data for specific time -> as ad banners on a website
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28. When Not to Use
• Systems that require ACID transactions for writes and reads
• The database to aggregate the data using queries (such as SUM or
AVG)
• Sample product prototypes or initial tech spikes
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29. Conclusion
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