Databases

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Databases

Databases
• Basics
• Database types
• SQL
• Indexes
• Views
• Stored procedures
• MongoDB

Data
• The data itself doesn’t have any meaning
– 300
– A=25
– Yellow
– [32,12,43,21,55,76,54]

Information
• Data with meaning
– Ferenc is 39 years old
– My neighbor has four black dogs
– My grandfather was ten years older than my grandmother.
– A rose is a woody perennial flowering plant of the genus Rosa, in the
family Rosaceae, or the flower it bears.

Database
• A database is an organized collection of data

Database management system
The database management system (DBMS) is the software that interacts
with end users, applications, and the database itself to capture and analyze
the data.

Relational database system
• A relational database management system (RDBMS) is a database
management system (DBMS) based on the relational model of data.
• The relational model (RM) for database management is an approach to
managing data using a structure and language consistent with first-order
predicate logic, first described in 1969 by English computer scientist Edgar
F. Codd where all data is represented in terms of tuples, grouped into
relations.

RDBMS
Id Title Author Year ISBN10
1 Omerta Mario Puzo 2000 0-434-00870-2
2 The Godfather Mario Puzo 1969 0-399-10342-2
3 Birdy William
Wharton
1979 0-679-73412-0
4 Slaughterhouse-
five
Kurt
Vonnegut
1969 0-7910-9295-X
Id Name Year
1 Zoltan Kovacs 1998
2 Maria Vas 2000
3 Lajos Jo 2014
4 Klara Kis 1979

Relational Database Management Systems
• MySQL
• PostgreSQL
• SQLServer
• Oracle RDBMS
• DB2
• Amazon Aurora

RDBMS’s (Pro)
• SQL is a powerful query language
• There’s a lot’s of relational databases available, with good support
• It’s easy to find a developer with SQL experience
• They’re ACID complaint
– Atomicity
– Consistency
– Isolation
– Durabilty

RDBMS (Con)
• The data has to be stored in a structured way, planning needed
• It’s hard to convert between database tables and real objects
• It’s hard to optimize on scaling, they’re mostly vertically scalable

Non-relational databases (NoSQL)
Relational databases were never designed to cope with the scale and agility
challenges that face modern applications – and aren't built to take
advantage of cheap storage and processing power that's available today
through the cloud. NoSQL tries to solve these problems.

Key – Value store
• Memcached
• Redis
• Amazon DynamoDB

Wide column store
• Apache Cassandra
• Apache HBase

Document Store
• MongoDB
• Couchbase

Graphdb
• Neo4j

Searchengine
• Elasticsearch
• Splunk
• Apache solr

Time series data
• RRDTool
• Prometheus

NoSQL Pros
• Flexibile Scalability
• Stores Massive Amounts of data
• Database maintenance could be easier
• Cheaper to implement

(Cap Theorem)
• The CAP theorem states that it is impossible for a distributed data store to
simultaneously provide more than two out of the following three
guarantees:
– Consistency: Every read receives the most recent write or an error
– Availability: Every request receives a (non-error) response – without the guarantee
that it contains the most recent write
– Partition tolerance: The system continues to operate despite an arbitrary number of
messages being dropped (or delayed) by the network between nodes

NoSQL Cons
• They’re not mature
• Harder to get support
• Business Analytics and Business Intelligence could be harder to
implement

SQL
SELECT b.title
FROM friends f
JOIN books b
ON b.year =
f.year
WHERE f.name
= ‘Klara Kis’
Id Title Author Year ISBN1
0
1 Omerta Mario
Puzo
2000 0-434-
00870-
2
2 The
Godfat
her
Mario
Puzo
1969 0-399-
10342-
2
3 Birdy William
Wharto
n
1979 0-679-
73412-
0
4 Slaught
erhous
e-five
Kurt
Vonneg
ut
1969 0-
7910-
9295-x
Id Name Year
1 Zoltan
Kovacs
1998
2 Maria
Vas
2000
3 Lajos Jo 2014
4 Klara Kis 1979

DDL - Data definition language
• CREATE
• ALTER
• DROP
• TRUNCATE

DQL - Data query language
• SELECT
• FROM
• WHERE
• GROUP BY
• ORDER BY
• HAVING

DML - Data Manipulation Language
• INSERT
• UPDATE
• DELETE

JOIN
• A JOIN clause is used to combine rows from two or more tables, based on
a related column between them.

INNER JOIN
SELECT * FROM friends f JOIN books b
+------+---------------+------+------+------------------+-----------------+------+---------------+
| id | Name | Year | id | Title | Author | Year | ISBN10 |
+------+---------------+------+------+------------------+-----------------+------+---------------+
| 1 | Kovacs Zoltan | 1998 | 1 | Omerta | Mario Puzo | 2000 | 0-434-00870-2 |
| 2 | Vas Maria | 2000 | 1 | Omerta | Mario Puzo | 2000 | 0-434-00870-2 |
| 3 | Jo Lajos | 2014 | 1 | Omerta | Mario Puzo | 2000 | 0-434-00870-2 |
| 4 | Kis Klara | 1979 | 1 | Omerta | Mario Puzo | 2000 | 0-434-00870-2 |
| 1 | Kovacs Zoltan | 1998 | 2 | The Godfather | Mario Puzo | 1969 | 0-399-10342-2 |
| 2 | Vas Maria | 2000 | 2 | The Godfather | Mario Puzo | 1969 | 0-399-10342-2 |
| 3 | Jo Lajos | 2014 | 2 | The Godfather | Mario Puzo | 1969 | 0-399-10342-2 |
| 4 | Kis Klara | 1979 | 2 | The Godfather | Mario Puzo | 1969 | 0-399-10342-2 |
| 1 | Kovacs Zoltan | 1998 | 3 | Birdy | William Wharton | 1979 | 0-679-73412-0 |
| 2 | Vas Maria | 2000 | 3 | Birdy | William Wharton | 1979 | 0-679-73412-0 |
| 3 | Jo Lajos | 2014 | 3 | Birdy | William Wharton | 1979 | 0-679-73412-0 |
| 4 | Kis Klara | 1979 | 3 | Birdy | William Wharton | 1979 | 0-679-73412-0 |
| 1 | Kovacs Zoltan | 1998 | 4 | Slaughterhouse-5 | Kurt Vonnegut | 1969 | 0-7910-9295-x |
| 2 | Vas Maria | 2000 | 4 | Slaughterhouse-5 | Kurt Vonnegut | 1969 | 0-7910-9295-x |
| 3 | Jo Lajos | 2014 | 4 | Slaughterhouse-5 | Kurt Vonnegut | 1969 | 0-7910-9295-x |
| 4 | Kis Klara | 1979 | 4 | Slaughterhouse-5 | Kurt Vonnegut | 1969 | 0-7910-9295-x |
+------+---------------+------+------+------------------+-----------------+------+---------------+

SELF JOIN
mysql> SELECT * FROM friends a JOIN friends b;
+------+---------------+------+------+---------------+------+
| id | Name | Year | id | Name | Year |
+------+---------------+------+------+---------------+------+
| 1 | Kovacs Zoltan | 1998 | 1 | Kovacs Zoltan | 1998 |
| 2 | Vas Maria | 2000 | 1 | Kovacs Zoltan | 1998 |
| 3 | Jo Lajos | 2014 | 1 | Kovacs Zoltan | 1998 |
| 4 | Kis Klara | 1979 | 1 | Kovacs Zoltan | 1998 |
| 1 | Kovacs Zoltan | 1998 | 2 | Vas Maria. | 2000 |
| 2 | Vas Maria | 2000 | 2 | Vas Maria | 2000 |
| 3 | Jo Lajos | 2014 | 2 | Vas Maria | 2000 |
| 4 | Kis Klara | 1979 | 2 | Vas Maria | 2000 |
| 1 | Kovacs Zoltan | 1998 | 3 | Jo Lajos | 2014 |
| 2 | Vas Maria | 2000 | 3 | Jo Lajos | 2014 |
| 3 | Jo Lajos | 2014 | 3 | Jo Lajos | 2014 |
| 4 | Kis Klara | 1979 | 3 | Jo Lajos | 2014 |
| 1 | Kovacs Zoltan | 1998 | 4 | Kis Klara. | 1979 |
| 2 | Vas Maria | 2000 | 4 | Kis Klara | 1979 |
| 3 | Jo Lajos | 2014 | 4 | Kis Klara | 1979 |
| 4 | Kis Klara | 1979 | 4 | Kis Klara | 1979 |
+------+---------------+------+------+---------------+------+

Indexes
mysql> SHOW CREATE TABLE neos_largeG
*************************** 1. row ***************************
Table: neos_large
Create Table: CREATE TABLE `neos_large` (
ìd` int(11) DEFAULT NULL,
[...]
ìnk` double DEFAULT NULL,
òm` double DEFAULT NULL,
`w` double DEFAULT NULL,
KEY `tau` (`tau`)
) ENGINE=InnoDB DEFAULT CHARSET=latin1
1 row in set (0.00 sec)
mysql> SELECT COUNT(*) FROM neos_large;
+----------+
| COUNT(*) |
+----------+
| 18254688 |
+----------+

Indexes
mysql> SELECT MAX(ink) FROM neos_large;
+-------------------+
| MAX(ink) |
+-------------------+
| 154.3668580789491 |
+-------------------+
mysql> ALTER TABLE neos_large ADD INDEX(ink);
Query OK, 0 rows affected (44.76 sec)
Records: 0 Duplicates: 0 Warnings: 0
mysql> SELECT MAX(ink) FROM neos_large;
+-------------------+
| MAX(ink) |
+-------------------+
| 154.3668580789491 |
+-------------------+

Views
mysql> CREATE VIEW neos_ink AS SELECT id, ink FROM neos_large;
Query OK, 0 rows affected (0.00 sec)
mysql> SELECT * FROM neos_ink LIMIT 5;
+----+---------------------+
| id | ink |
+----+---------------------+
| 1 | 10.82856921420592 |
| 2 | 11.56484503237207 |
| 3 | 9.384537356044309 |
| 4 | 26.68761210417409 |
| 5 | 11.87652956555689 |
+----+---------------------+
5 rows in set (0.00 sec)

Stored procedures
DELIMITER $$
DROP PROCEDURE IF EXISTS duplicate_rows$$
CREATE PROCEDURE duplicate_rows (
IN tablename VARCHAR(255),
IN times INT
)
BEGIN
SET @statement = CONCAT(CONCAT(CONCAT(CONCAT("INSERT INTO ",tablename),"
SELECT * FROM "),tablename),";");
PREPARE stmt FROM @statement;
WHILE times > 0 DO SELECT times as "Remaining";
EXECUTE stmt;
SET times = times - 1;
END WHILE;
DEALLOCATE PREPARE stmt;
END $$

Functions
CREATE FUNCTION circle_area (radius REAL)
RETURNS REAL DETERMINISTIC
RETURN POW(radius,2) * PI();
CREATE FUNCTION circle_circumference (radius REAL)
RETURNS REAL DETERMINISTIC
RETURN radius * 2 * PI();

Triggers
DELIMITER $$
CREATE TRIGGER remove_credit_card
BEFORE INSERT ON users FOR EACH ROW
BEGIN
IF new.credit_card_number = '' THEN
SET credit_card_number = NULL;
END IF;
END
$$

MongoDB
“MongoDB is a document database with the scalability and flexibility that you
want with the querying and indexing that you need”

INSERT
db.konyvek.insert(
[
{ Cim: "Omerta", Szerzo: "Mario Puzo", Ev: 2000, ISBN10:
"0-434-00870-2"},
{ Cim: "The Godfather", Szerzo: "Mario Puzo", Ev: 1969,
ISBN10: "0-399-10342-2"},
{ Cim: "Birdy", Szerzo: "William Wharton", Ev: 1979,
ISBN10: "0-679-73412-0"},
{ Cim: "Slaughterhouse-five", Szerzo: "Kurt Vonnegut ", Ev:
2000, ISBN10: "0-7910-9295-x"}
]
)

Find
> db.konyvek.find(
{Cim: "Slaughterhouse-five"}
)
{ "_id" : ObjectId("5c927003d9e410e1bb9fa583"), "Cim" :
"Slaughterhouse-five", "Szerzo" : "Kurt Vonnegut ", "Ev" :
2000, "ISBN10" : "0-7910-9295-x" }

Update
> db.konyvek.update(
{ISBN10: "0-7910-9295-x"},
{Cim: "Slaughterhouse-five", Szerzo: "Kurt Vonnegut ", Ev:
2000, ISBN10: "0-7910-9295-X"}
)
WriteResult({ "nMatched" : 1, "nUpserted" : 0, "nModified" :
1 })

“Schemaless”
> db.konyvek.update({"Cim" : "Slaughterhouse-five", "Szerzo" : "Kurt Vonnegut ",
"Ev" : 1969, "ISBN10" : "0-7910-9295-x"},{"Cim" : "Slaughterhouse-five", "Szerzo"
: "Kurt Vonnegut ", "Ev" : 2000, "ISBN10" : "0-7910-9295-X", ISBN13: "978-0-7910-
9295-8"})
WriteResult({ "nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })
> db.konyvek.find()
{ "_id" : ObjectId("5c929445345a87cb9fea0bc1"), "Cim" : "Omerta", "Szerzo" :
"Mario Puzo", "Ev" : 2000, "ISBN10" : "0-434-00870-2" }
{ "_id" : ObjectId("5c929445345a87cb9fea0bc2"), "Cim" : "The Godfather", "Szerzo"
: "Mario Puzo", "Ev" : 1969, "ISBN10" : "0-399-10342-2" }
{ "_id" : ObjectId("5c929445345a87cb9fea0bc3"), "Cim" : "Birdy", "Szerzo" :
"William Wharton", "Ev" : 1979, "ISBN10" : "0-679-73412-0" }
{ "_id" : ObjectId("5c929445345a87cb9fea0bc4"), "Cim" : "Slaughterhouse-five",
"Szerzo" : "Kurt Vonnegut ", "Ev" : 1969, "ISBN10" : "0-7910-9295-X", "ISBN13" :
"978-0-7910-9295-8" }

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