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NoSQL em um mundo SQL
Airton Lastori
airton.lastori@oracle.com
Abril-2016
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
DBA Dev Gerencial
Quem?
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
Nunca usou
NoSQL
Usa NoSQL apenas
em apps não-
críticas
NoSQL em apps
críticas
Quem?
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
Agenda
1. NoSQL?
2. Uso do relacional como não-relacional
3. NewSQL
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
NoSQL?
uma breve introdução
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Oracle Confidential – Internal/Restricted/Highly Restricted 6
NoSQL = Não-relacional
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
Modelo Relacional
• Edgard F. Codd
–1970, IBM
–Turing Award 1981
• Forte base teórica matemática
–teoria dos conjuntos, lógica de predicados, etc.
• Implementada como SQL
Oracle Confidential – Internal/Restricted/Highly Restricted 7
The relational model for database management: version 2
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Oracle Confidential – Internal/Restricted/Highly Restricted 8
SQL = implementação do modelo
relacional
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
Sistemas Gerenciadores de Bancos de Dados Relacionais
• Software para gerenciar dados baseados no Modelo Relacional
• Estrutura lógica dos dados – visão do usuário
– Dados organizados em tabelas compostas de linhas e colunas e possuem regras de
relacionamento entre sí (constraints)
• Conhecidos como Dados Estruturados
– SQL permite criar, manter e consultar os dados nestas estruturas
– Normalização e Constraints evitam duplicidade da informação, aumentando
consistência e qualidade dos dados
– propriedades ACID (suporte a transações)
• Estrutura física dos dados – visão da máquina
– Árvores B*Tree = buscas muito rápidas O(log n)
Oracle Confidential – Internal/Restricted/Highly Restricted 9
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
Vários modelos de dados
• O modelo relacional não resolve bem todos os problemas
• 1960 - navigacional
– Hierárquico
– Network
• 1970 - SQL/relacional
• 1990 - Orientado a Objetos
– em parte, absorvido pelos SGBDRs
• 2000 – NoSQL
– será absorvido pelos SGBDRs? Apenas um Hype?
Oracle Confidential – Internal/Restricted/Highly Restricted 11
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
A Web
Oracle Confidential – Internal/Restricted/Highly Restricted 12
Dados massivos, problemas Big Data
Altíssima escala
Sempre online
Estratégia: hardwares commodity em nuvem + software livre
Modelo relacional: difícil escalar e implementar alta
disponibilidade em nuvem de hw commodity
www.leavcom.com/pdf/NoSQL.pdf
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
Standalone Clusterizado
Oracle Confidential – Internal/Restricted/Highly Restricted 13
Problemas diferentes
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
Problemas em ambientes clusterizados
• Quando os dados estão normalizados e distribuídos, é difícil manter a
performance
• Quando os dados estão distribuídos, é difícil manter a consistência e
implementar transações
• Quando o dado está distribuído em hw commodity, é preciso ter
duplicidade e sincronização para tolerância a falhas
• Etc.
Que tal abrir mão de algumas coisas do modelo relacional em prol de outras?
Oracle Confidential – Internal/Restricted/Highly Restricted 14
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Oracle Confidential – Internal/Restricted/Highly Restricted 15
Web = gatilho para o surgimento das
tecnologias NoSQL
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | 16
http://db-engines.com/en/ranking_categories
183NoSQL
12categorias
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
Características comuns
• Alta Performance
– Normalmente um banco NoSQL é muito rápido, pois possui uma arquitetura
simplificada
• Evita operações de JOINs
– armazenando dados duplicados e denormalizados
• Projetado para escalar Horizontalmente
– Lembra da Cloud Computing? Pois é...
• Normalmente abre-se mão de funcionalidades em prol da simplicidade de
uso, inclusive em escala
Oracle Confidential – Internal/Restricted/Highly Restricted 17
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
Schemaless
• key-value
• document
• wide column
• graph
• Etc
• Muda o modelo lógico, a visão do usuário
– Outras APIs de acesso = Not Only SQL
– Em muitos casos, simplifica a vida do desenvolvedor (do DBA, nem tanto...)
Oracle Confidential – Internal/Restricted/Highly Restricted 18
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Oracle Confidential – Internal/Restricted/Highly Restricted 19
Computação acessível via clouds
públicas, software livre e simplicidade
no uso tornam o movimento NoSQL
muito relevante
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | 20
http://db-engines.com/en/ranking_trend (mar-2016)
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
Uso do relacional como não-relacional
casos de sucesso da web
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
Grandes usuários MySQL
23
Web, Cloud, Distribuído e Embarcado…
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Oracle Confidential – Internal/Restricted/Highly Restricted 24
Muitas foram start ups há poucos
anos, começaram e cresceram com
MySQL
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
Usa MySQL como NoSQL
eng.uber.com/schemaless-part-one
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
Usa MySQL como NoSQL
eng.uber.com/schemaless-part-one
• Our new solution needed to be able to linearly add capacity by adding more servers
• We needed write availability – substituir Redis como data pipeline em busca de
consistência de leitura sem abrir mão da performance de escrita
• We needed secondary indexes – saindo do Postgres, mas mantendo a mesma
funcionalidade
• We needed operation trust in the system, as it contains mission-critical trip data
• We needed a way of notifying downstream dependencies – múltiplos processos
(billing, analytics) inter-dependentes, mas que precisam ser isolados para escalar e
sem perdas
•
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
Usa MySQL como NoSQL
eng.uber.com/schemaless-part-one
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
Usa MySQL como NoSQL
eng.uber.com/schemaless-part-one
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
“We had an unexpected loss of data on
nearly every technology we used at
one time or another, except MySQL.”
– Pinterest Engineering
Oracle Confidential – Internal/Restricted/Highly Restricted 29
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
NewSQL
o mundo relacional abraça o NoSQL
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
Suporte ao modelo chave-valor
• Memcached plug-in
Oracle Confidential – Internal/Restricted/Highly Restricted 31
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
MySQL 5.7 Sysbench Benchmark: SQL Point Selects
3x Faster than MySQL 5.6
1,600,000 QPS
0
200,000
400,000
600,000
800,000
1,000,000
1,200,000
1,400,000
1,600,000
1,800,000
8 16 32 64 128 256 512 1,024
QueriesperSecond
Connections
MySQL 5.7: Sysbench OLTP Read Only (SQL Point Selects)
MySQL 5.7
MySQL 5.6
MySQL 5.5
Intel(R) Xeon(R) CPU E7-8890 v3
4 sockets x 18 cores-HT (144 CPU threads)
2.5 Ghz, 512GB RAM
Linux kernel 3.16
32
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
Suporte ao modelo orientado a documentos no MySQL 5.7
1. Native JSON datatype
2. JSON Functions
3. Generated Columns
33
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
Tipo nativo JSON
34
CREATE TABLE employees (data JSON);
INSERT INTO employees VALUES ('{"id": 1, "name": "Jane"}');
INSERT INTO employees VALUES ('{"id": 2, "name": "Joe"}');
SELECT * FROM employees;
+---------------------------+
| data |
+---------------------------+
| {"id": 1, "name": "Jane"} |
| {"id": 2, "name": "Joe"} |
+---------------------------+
2 rows in set (0,00 sec)
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
Vantagens sobre tipos TEXT/VARCHAR
1. Document Validation:
2. Eficiência no armazenamento físico
Allows quicker access to object members and array elements because its optimized
binary format
37
INSERT INTO employees VALUES ('some random text');
ERROR 3130 (22032): Invalid JSON text: "Expect a value here." at
position 0 in value (or column) 'some random text'.
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
JSON Functions
38
SET @document = '[10, 20, [30, 40]]';
SELECT JSON_EXTRACT(@document, '$[1]');
+---------------------------------+
| JSON_EXTRACT(@document, '$[1]') |
+---------------------------------+
| 20 |
+---------------------------------+
1 row in set (0.01 sec)
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
Testes com dados reais
• Via SF OpenData
• 206K JSON objects
representing subdivision
parcels.
• Imported from https://github.com/zemirco/sf-city-lots-json + small tweaks
39
CREATE TABLE features (
id INT NOT NULL auto_increment primary key,
feature JSON NOT NULL
);
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | 40
{
"type":"Feature",
"geometry":{
"type":"Polygon",
"coordinates":[
[
[-122.42200352825247,37.80848009696725,0],
[-122.42207601332528,37.808835019815085,0],
[-122.42110217434865,37.808803534992904,0],
[-122.42106256906727,37.80860105681814,0],
[-122.42200352825247,37.80848009696725,0]
]
]
},
"properties":{
"TO_ST":"0",
"BLKLOT":"0001001",
"STREET":"UNKNOWN",
"FROM_ST":"0",
"LOT_NUM":"001",
"ST_TYPE":null,
"ODD_EVEN":"E",
"BLOCK_NUM":"0001",
"MAPBLKLOT":"0001001"
}
}
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
Naive Performance Comparison
41
# as JSON type
SELECT DISTINCT
feature->"$.type" as json_extract
FROM features;
+--------------+
| json_extract |
+--------------+
| "Feature" |
+--------------+
1 row in set (1.25 sec)
Unindexed traversal of 206K documents
# as TEXT type
SELECT DISTINCT
feature->"$.type" as json_extract
FROM features;
+--------------+
| json_extract |
+--------------+
| "Feature" |
+--------------+
1 row in set (12.85 sec)
Explanation: Binary format of JSON type is very efficient at searching. Storing as TEXT
performs over 10x worse at traversal.
Using short cut for
JSON_EXTRACT. Coming
in 5.7.9.
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
Generated Columns
42
id my_integer my_integer_plus_one
1 10 11
2 20 21
3 30 31
4 40 41
CREATE TABLE t1 (
id INT NOT NULL PRIMARY KEY auto_increment,
my_integer INT,
my_integer_plus_one INT AS (my_integer+1)
);
UPDATE t1 SET my_integer_plus_one = 10 WHERE id = 1;
ERROR 3105 (HY000): The value specified for generated column
'my_integer_plus_one' in table 't1' is not allowed.
Column automatically maintained based
on your specification.
Read-only of course
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
Generated Columns Support Indexes!
43
ALTER TABLE features ADD feature_type VARCHAR(30) AS (feature->"$.type");
Query OK, 0 rows affected (0.01 sec)
Records: 0 Duplicates: 0 Warnings: 0
ALTER TABLE features ADD INDEX (feature_type);
Query OK, 0 rows affected (0.73 sec)
Records: 0 Duplicates: 0 Warnings: 0
SELECT DISTINCT feature_type FROM features;
+--------------+
| feature_type |
+--------------+
| "Feature" |
+--------------+
1 row in set (0.06 sec)
From table scan on 206K documents to index scan on 206K materialized values
Down from 1.25 sec to 0.06
sec
Creates index only.
Does not modify table
rows.
Meta data change only
(FAST). Does not need to
touch table.
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
Generated Columns (cont.)
• Used for “functional index”
• Available as either VIRTUAL (default) or STORED:
• Both types of computed columns permit for indexes to be added.
44
ALTER TABLE features ADD feature_type varchar(30) AS (feature-
>"$.type") STORED;
Query OK, 206560 rows affected (4.70 sec)
Records: 206560 Duplicates: 0 Warnings: 0
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
Indexing Options Available
45
STORED VIRTUAL
Primary and Secondary
BTREE, Fulltext, GIS
Mixed with fields
Requires table rebuild
Not Online
Secondary Only
BTREE Only
Mixed with fields
No table rebuild
INSTANT Alter
Faster Insert
Bottom Line: Unless you need a PRIMARY KEY, FULLTEXT or GIS index VIRTUAL is probably better.
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
Virtual vs. Stored Performance
• Approximate worst case scenario via a table scan:
46
SELECT DISTINCT feature_type FROM
features;
+--------------+
| feature_type |
+--------------+
| "Feature" |
+--------------+
VIRTUAL-TEXT (9.89 sec)
STORED-TEXT (0.22 sec)
VIRTUAL-JSON (0.85 sec)
STORED-JSON (0.24 sec)
Clarification: Since indexes are materialized (stored) themselves, the real-life case for STORED
is when generating the column is computationally expensive and you can not use indexes
effectively.
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
Unquote JSON String
SELECT
DISTINCT JSON_UNQUOTE(feature->"$.type")
as feature_type
FROM features;
+-----------------+
| feature_type |
+-----------------+
| Feature |
+-----------------+
1 row in set (1.22 sec)
47
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
JSON Path Search
• Provides a novice way to know the path. To retrieve via:
[[database.]table.]column->"$<path spec>"
48
SELECT JSON_SEARCH(feature,
'one', 'MARKET') AS
extract_path
FROM features
WHERE id = 121254;
+-----------------------+
| extract_path |
+-----------------------+
| "$.properties.STREET" |
+-----------------------+
1 row in set (0.00 sec)
SELECT
feature->"$.properties.STREET"
AS property_street
FROM features
WHERE id = 121254;
+-----------------+
| property_street |
+-----------------+
| "MARKET" |
+-----------------+
1 row in set (0.00 sec)
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
JSON Array Creation
49
SELECT JSON_ARRAY(id,
feature->"$.properties.STREET",
feature->'$.type") AS json_array
FROM features ORDER BY RAND() LIMIT 3;
+-------------------------------+
| json_array |
+-------------------------------+
| [65298, "10TH", "Feature"] |
| [122985, "08TH", "Feature"] |
| [172884, "CURTIS", "Feature"] |
+-------------------------------+
3 rows in set (2.66 sec)
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
JSON Object Creation
50
SELECT JSON_OBJECT('id', id,
'street', feature->"$.properties.STREET",
'type', feature->"$.type"
) AS json_object
FROM features ORDER BY RAND() LIMIT 3;
+--------------------------------------------------------+
| json_object |
+--------------------------------------------------------+
| {"id": 122976, "type": "Feature", "street": "RAUSCH"} |
| {"id": 148698, "type": "Feature", "street": "WALLACE"} |
| {"id": 45214, "type": "Feature", "street": "HAIGHT"} |
+--------------------------------------------------------+
3 rows in set (3.11 sec)
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
JSON_REPLACE
51
SELECT JSON_REPLACE(feature, '$.type', JSON_ARRAY('feature', 'bug')) as
json_object FROM features LIMIT 1;
+--------------------------------------------------------+
| json_object |
+--------------------------------------------------------+
| {"type": ["feature", "bug"], "geometry": {"type": ..}} |
+--------------------------------------------------------+
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
• 5.7 supports functions to CREATE, SEARCH, MODIFY and RETURN JSON
values:
JSON Functions
52
JSON_ARRAY_APPEND()
JSON_ARRAY_INSERT()
JSON_ARRAY()
JSON_CONTAINS_PATH()
JSON_CONTAINS()
JSON_DEPTH()
JSON_EXTRACT()
JSON_INSERT()
JSON_KEYS()
JSON_LENGTH()
JSON_MERGE()
JSON_OBJECT()
JSON_QUOTE()
JSON_REMOVE()
JSON_REPLACE()
JSON_SEARCH()
JSON_SET()
JSON_TYPE()
JSON_UNQUOTE()
JSON_VALID()
https://dev.mysql.com/doc/refman/5.7/en/json-functions.html
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
JSON Comparator
53
SELECT CAST(1 AS JSON) = 1;
+---------------------+
| CAST(1 AS JSON) = 1 |
+---------------------+
| 1 |
+---------------------+
1 row in set (0.01 sec)
JSON value of 1 equals 1
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
JSON ou Coluna?
• Você escolhe
• Vantagens em ambas abordagens
54
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
Storing as a Column
• Easier to apply a schema to your application
• Schema may make applications easier to maintain over time, as change is
controlled;
• Do not have to expect as many permutations
• Allows some constraints over data
55
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
Storing as JSON
• More flexible way to represent data that is hard to model in schema;
• Imagine you are a SaaS application serving many customers
• Strong use-case to support custom-fields
• Historically this may have used Entity–attribute–value model (EAV). Does
not always perform well
56
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
JSON (cont.)
• Easier denormalization; an optimization that is important in some specific
situations
• No painful schema changes*
• Easier prototyping
• Fewer types to consider
• No enforced schema, start storing values immediately
57
* MySQL 5.6 has Online DDL. This is not as large of an issue as it
was historically.
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
Schema + Schemaless
58
SSDs have capacity_in_gb, CPUs have a core_count. These attributes are not consistent
across products.
CREATE TABLE pc_components (
id INT NOT NULL PRIMARY KEY,
description VARCHAR(60) NOT NULL,
vendor VARCHAR(30) NOT NULL,
serial_number VARCHAR(30) NOT NULL,
attributes JSON NOT NULL
);
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
Sumário
1. O movimento NoSQL é de grande relevância e têm os
gigantes da Web como protagonistas
2. NoSQL complementa Bancos Relacionais
3. NewSQL = combinando os dois mundos
4. MySQL continua muito relevante na Web
5. Memcached plugin e JSON são exemplos no MySQL de
como bancos relacionais podem abraçar o NoSQL
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
Obrigado!
Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
@MySQLBR meetup.com/MySQL-BRfacebook.com/MySQLBR
pt.planet.mysql.com
Copyright © 2015 Oracle and/or its affiliates. All rights reserved. |
Perguntas?
NoSQL em um mundo SQL
Contato:
airton.lastori@oracle.com
twitter.com/mysqlbr
facebook.com/mysqlbr
NoSQL no MySQL 5.7

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NoSQL no MySQL 5.7

  • 1. NoSQL em um mundo SQL Airton Lastori airton.lastori@oracle.com Abril-2016
  • 2. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | DBA Dev Gerencial Quem?
  • 3. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Nunca usou NoSQL Usa NoSQL apenas em apps não- críticas NoSQL em apps críticas Quem?
  • 4. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Agenda 1. NoSQL? 2. Uso do relacional como não-relacional 3. NewSQL
  • 5. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | NoSQL? uma breve introdução
  • 6. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Oracle Confidential – Internal/Restricted/Highly Restricted 6 NoSQL = Não-relacional
  • 7. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Modelo Relacional • Edgard F. Codd –1970, IBM –Turing Award 1981 • Forte base teórica matemática –teoria dos conjuntos, lógica de predicados, etc. • Implementada como SQL Oracle Confidential – Internal/Restricted/Highly Restricted 7 The relational model for database management: version 2
  • 8. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Oracle Confidential – Internal/Restricted/Highly Restricted 8 SQL = implementação do modelo relacional
  • 9. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Sistemas Gerenciadores de Bancos de Dados Relacionais • Software para gerenciar dados baseados no Modelo Relacional • Estrutura lógica dos dados – visão do usuário – Dados organizados em tabelas compostas de linhas e colunas e possuem regras de relacionamento entre sí (constraints) • Conhecidos como Dados Estruturados – SQL permite criar, manter e consultar os dados nestas estruturas – Normalização e Constraints evitam duplicidade da informação, aumentando consistência e qualidade dos dados – propriedades ACID (suporte a transações) • Estrutura física dos dados – visão da máquina – Árvores B*Tree = buscas muito rápidas O(log n) Oracle Confidential – Internal/Restricted/Highly Restricted 9
  • 10. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Vários modelos de dados • O modelo relacional não resolve bem todos os problemas • 1960 - navigacional – Hierárquico – Network • 1970 - SQL/relacional • 1990 - Orientado a Objetos – em parte, absorvido pelos SGBDRs • 2000 – NoSQL – será absorvido pelos SGBDRs? Apenas um Hype? Oracle Confidential – Internal/Restricted/Highly Restricted 11
  • 11. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | A Web Oracle Confidential – Internal/Restricted/Highly Restricted 12 Dados massivos, problemas Big Data Altíssima escala Sempre online Estratégia: hardwares commodity em nuvem + software livre Modelo relacional: difícil escalar e implementar alta disponibilidade em nuvem de hw commodity www.leavcom.com/pdf/NoSQL.pdf
  • 12. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Standalone Clusterizado Oracle Confidential – Internal/Restricted/Highly Restricted 13 Problemas diferentes
  • 13. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Problemas em ambientes clusterizados • Quando os dados estão normalizados e distribuídos, é difícil manter a performance • Quando os dados estão distribuídos, é difícil manter a consistência e implementar transações • Quando o dado está distribuído em hw commodity, é preciso ter duplicidade e sincronização para tolerância a falhas • Etc. Que tal abrir mão de algumas coisas do modelo relacional em prol de outras? Oracle Confidential – Internal/Restricted/Highly Restricted 14
  • 14. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Oracle Confidential – Internal/Restricted/Highly Restricted 15 Web = gatilho para o surgimento das tecnologias NoSQL
  • 15. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | 16 http://db-engines.com/en/ranking_categories 183NoSQL 12categorias
  • 16. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Características comuns • Alta Performance – Normalmente um banco NoSQL é muito rápido, pois possui uma arquitetura simplificada • Evita operações de JOINs – armazenando dados duplicados e denormalizados • Projetado para escalar Horizontalmente – Lembra da Cloud Computing? Pois é... • Normalmente abre-se mão de funcionalidades em prol da simplicidade de uso, inclusive em escala Oracle Confidential – Internal/Restricted/Highly Restricted 17
  • 17. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Schemaless • key-value • document • wide column • graph • Etc • Muda o modelo lógico, a visão do usuário – Outras APIs de acesso = Not Only SQL – Em muitos casos, simplifica a vida do desenvolvedor (do DBA, nem tanto...) Oracle Confidential – Internal/Restricted/Highly Restricted 18
  • 18. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Oracle Confidential – Internal/Restricted/Highly Restricted 19 Computação acessível via clouds públicas, software livre e simplicidade no uso tornam o movimento NoSQL muito relevante
  • 19. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | 20 http://db-engines.com/en/ranking_trend (mar-2016)
  • 20. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Uso do relacional como não-relacional casos de sucesso da web
  • 21. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Grandes usuários MySQL 23 Web, Cloud, Distribuído e Embarcado…
  • 22. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Oracle Confidential – Internal/Restricted/Highly Restricted 24 Muitas foram start ups há poucos anos, começaram e cresceram com MySQL
  • 23. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Usa MySQL como NoSQL eng.uber.com/schemaless-part-one
  • 24. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Usa MySQL como NoSQL eng.uber.com/schemaless-part-one • Our new solution needed to be able to linearly add capacity by adding more servers • We needed write availability – substituir Redis como data pipeline em busca de consistência de leitura sem abrir mão da performance de escrita • We needed secondary indexes – saindo do Postgres, mas mantendo a mesma funcionalidade • We needed operation trust in the system, as it contains mission-critical trip data • We needed a way of notifying downstream dependencies – múltiplos processos (billing, analytics) inter-dependentes, mas que precisam ser isolados para escalar e sem perdas •
  • 25. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Usa MySQL como NoSQL eng.uber.com/schemaless-part-one
  • 26. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Usa MySQL como NoSQL eng.uber.com/schemaless-part-one
  • 27. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | “We had an unexpected loss of data on nearly every technology we used at one time or another, except MySQL.” – Pinterest Engineering Oracle Confidential – Internal/Restricted/Highly Restricted 29
  • 28. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | NewSQL o mundo relacional abraça o NoSQL
  • 29. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Suporte ao modelo chave-valor • Memcached plug-in Oracle Confidential – Internal/Restricted/Highly Restricted 31
  • 30. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | MySQL 5.7 Sysbench Benchmark: SQL Point Selects 3x Faster than MySQL 5.6 1,600,000 QPS 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 1,400,000 1,600,000 1,800,000 8 16 32 64 128 256 512 1,024 QueriesperSecond Connections MySQL 5.7: Sysbench OLTP Read Only (SQL Point Selects) MySQL 5.7 MySQL 5.6 MySQL 5.5 Intel(R) Xeon(R) CPU E7-8890 v3 4 sockets x 18 cores-HT (144 CPU threads) 2.5 Ghz, 512GB RAM Linux kernel 3.16 32
  • 31. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Suporte ao modelo orientado a documentos no MySQL 5.7 1. Native JSON datatype 2. JSON Functions 3. Generated Columns 33
  • 32. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Tipo nativo JSON 34 CREATE TABLE employees (data JSON); INSERT INTO employees VALUES ('{"id": 1, "name": "Jane"}'); INSERT INTO employees VALUES ('{"id": 2, "name": "Joe"}'); SELECT * FROM employees; +---------------------------+ | data | +---------------------------+ | {"id": 1, "name": "Jane"} | | {"id": 2, "name": "Joe"} | +---------------------------+ 2 rows in set (0,00 sec)
  • 33. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Vantagens sobre tipos TEXT/VARCHAR 1. Document Validation: 2. Eficiência no armazenamento físico Allows quicker access to object members and array elements because its optimized binary format 37 INSERT INTO employees VALUES ('some random text'); ERROR 3130 (22032): Invalid JSON text: "Expect a value here." at position 0 in value (or column) 'some random text'.
  • 34. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | JSON Functions 38 SET @document = '[10, 20, [30, 40]]'; SELECT JSON_EXTRACT(@document, '$[1]'); +---------------------------------+ | JSON_EXTRACT(@document, '$[1]') | +---------------------------------+ | 20 | +---------------------------------+ 1 row in set (0.01 sec)
  • 35. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Testes com dados reais • Via SF OpenData • 206K JSON objects representing subdivision parcels. • Imported from https://github.com/zemirco/sf-city-lots-json + small tweaks 39 CREATE TABLE features ( id INT NOT NULL auto_increment primary key, feature JSON NOT NULL );
  • 36. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | 40 { "type":"Feature", "geometry":{ "type":"Polygon", "coordinates":[ [ [-122.42200352825247,37.80848009696725,0], [-122.42207601332528,37.808835019815085,0], [-122.42110217434865,37.808803534992904,0], [-122.42106256906727,37.80860105681814,0], [-122.42200352825247,37.80848009696725,0] ] ] }, "properties":{ "TO_ST":"0", "BLKLOT":"0001001", "STREET":"UNKNOWN", "FROM_ST":"0", "LOT_NUM":"001", "ST_TYPE":null, "ODD_EVEN":"E", "BLOCK_NUM":"0001", "MAPBLKLOT":"0001001" } }
  • 37. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Naive Performance Comparison 41 # as JSON type SELECT DISTINCT feature->"$.type" as json_extract FROM features; +--------------+ | json_extract | +--------------+ | "Feature" | +--------------+ 1 row in set (1.25 sec) Unindexed traversal of 206K documents # as TEXT type SELECT DISTINCT feature->"$.type" as json_extract FROM features; +--------------+ | json_extract | +--------------+ | "Feature" | +--------------+ 1 row in set (12.85 sec) Explanation: Binary format of JSON type is very efficient at searching. Storing as TEXT performs over 10x worse at traversal. Using short cut for JSON_EXTRACT. Coming in 5.7.9.
  • 38. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Generated Columns 42 id my_integer my_integer_plus_one 1 10 11 2 20 21 3 30 31 4 40 41 CREATE TABLE t1 ( id INT NOT NULL PRIMARY KEY auto_increment, my_integer INT, my_integer_plus_one INT AS (my_integer+1) ); UPDATE t1 SET my_integer_plus_one = 10 WHERE id = 1; ERROR 3105 (HY000): The value specified for generated column 'my_integer_plus_one' in table 't1' is not allowed. Column automatically maintained based on your specification. Read-only of course
  • 39. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Generated Columns Support Indexes! 43 ALTER TABLE features ADD feature_type VARCHAR(30) AS (feature->"$.type"); Query OK, 0 rows affected (0.01 sec) Records: 0 Duplicates: 0 Warnings: 0 ALTER TABLE features ADD INDEX (feature_type); Query OK, 0 rows affected (0.73 sec) Records: 0 Duplicates: 0 Warnings: 0 SELECT DISTINCT feature_type FROM features; +--------------+ | feature_type | +--------------+ | "Feature" | +--------------+ 1 row in set (0.06 sec) From table scan on 206K documents to index scan on 206K materialized values Down from 1.25 sec to 0.06 sec Creates index only. Does not modify table rows. Meta data change only (FAST). Does not need to touch table.
  • 40. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Generated Columns (cont.) • Used for “functional index” • Available as either VIRTUAL (default) or STORED: • Both types of computed columns permit for indexes to be added. 44 ALTER TABLE features ADD feature_type varchar(30) AS (feature- >"$.type") STORED; Query OK, 206560 rows affected (4.70 sec) Records: 206560 Duplicates: 0 Warnings: 0
  • 41. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Indexing Options Available 45 STORED VIRTUAL Primary and Secondary BTREE, Fulltext, GIS Mixed with fields Requires table rebuild Not Online Secondary Only BTREE Only Mixed with fields No table rebuild INSTANT Alter Faster Insert Bottom Line: Unless you need a PRIMARY KEY, FULLTEXT or GIS index VIRTUAL is probably better.
  • 42. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Virtual vs. Stored Performance • Approximate worst case scenario via a table scan: 46 SELECT DISTINCT feature_type FROM features; +--------------+ | feature_type | +--------------+ | "Feature" | +--------------+ VIRTUAL-TEXT (9.89 sec) STORED-TEXT (0.22 sec) VIRTUAL-JSON (0.85 sec) STORED-JSON (0.24 sec) Clarification: Since indexes are materialized (stored) themselves, the real-life case for STORED is when generating the column is computationally expensive and you can not use indexes effectively.
  • 43. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Unquote JSON String SELECT DISTINCT JSON_UNQUOTE(feature->"$.type") as feature_type FROM features; +-----------------+ | feature_type | +-----------------+ | Feature | +-----------------+ 1 row in set (1.22 sec) 47
  • 44. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | JSON Path Search • Provides a novice way to know the path. To retrieve via: [[database.]table.]column->"$<path spec>" 48 SELECT JSON_SEARCH(feature, 'one', 'MARKET') AS extract_path FROM features WHERE id = 121254; +-----------------------+ | extract_path | +-----------------------+ | "$.properties.STREET" | +-----------------------+ 1 row in set (0.00 sec) SELECT feature->"$.properties.STREET" AS property_street FROM features WHERE id = 121254; +-----------------+ | property_street | +-----------------+ | "MARKET" | +-----------------+ 1 row in set (0.00 sec)
  • 45. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | JSON Array Creation 49 SELECT JSON_ARRAY(id, feature->"$.properties.STREET", feature->'$.type") AS json_array FROM features ORDER BY RAND() LIMIT 3; +-------------------------------+ | json_array | +-------------------------------+ | [65298, "10TH", "Feature"] | | [122985, "08TH", "Feature"] | | [172884, "CURTIS", "Feature"] | +-------------------------------+ 3 rows in set (2.66 sec)
  • 46. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | JSON Object Creation 50 SELECT JSON_OBJECT('id', id, 'street', feature->"$.properties.STREET", 'type', feature->"$.type" ) AS json_object FROM features ORDER BY RAND() LIMIT 3; +--------------------------------------------------------+ | json_object | +--------------------------------------------------------+ | {"id": 122976, "type": "Feature", "street": "RAUSCH"} | | {"id": 148698, "type": "Feature", "street": "WALLACE"} | | {"id": 45214, "type": "Feature", "street": "HAIGHT"} | +--------------------------------------------------------+ 3 rows in set (3.11 sec)
  • 47. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | JSON_REPLACE 51 SELECT JSON_REPLACE(feature, '$.type', JSON_ARRAY('feature', 'bug')) as json_object FROM features LIMIT 1; +--------------------------------------------------------+ | json_object | +--------------------------------------------------------+ | {"type": ["feature", "bug"], "geometry": {"type": ..}} | +--------------------------------------------------------+
  • 48. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | • 5.7 supports functions to CREATE, SEARCH, MODIFY and RETURN JSON values: JSON Functions 52 JSON_ARRAY_APPEND() JSON_ARRAY_INSERT() JSON_ARRAY() JSON_CONTAINS_PATH() JSON_CONTAINS() JSON_DEPTH() JSON_EXTRACT() JSON_INSERT() JSON_KEYS() JSON_LENGTH() JSON_MERGE() JSON_OBJECT() JSON_QUOTE() JSON_REMOVE() JSON_REPLACE() JSON_SEARCH() JSON_SET() JSON_TYPE() JSON_UNQUOTE() JSON_VALID() https://dev.mysql.com/doc/refman/5.7/en/json-functions.html
  • 49. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | JSON Comparator 53 SELECT CAST(1 AS JSON) = 1; +---------------------+ | CAST(1 AS JSON) = 1 | +---------------------+ | 1 | +---------------------+ 1 row in set (0.01 sec) JSON value of 1 equals 1
  • 50. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | JSON ou Coluna? • Você escolhe • Vantagens em ambas abordagens 54
  • 51. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Storing as a Column • Easier to apply a schema to your application • Schema may make applications easier to maintain over time, as change is controlled; • Do not have to expect as many permutations • Allows some constraints over data 55
  • 52. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Storing as JSON • More flexible way to represent data that is hard to model in schema; • Imagine you are a SaaS application serving many customers • Strong use-case to support custom-fields • Historically this may have used Entity–attribute–value model (EAV). Does not always perform well 56
  • 53. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | JSON (cont.) • Easier denormalization; an optimization that is important in some specific situations • No painful schema changes* • Easier prototyping • Fewer types to consider • No enforced schema, start storing values immediately 57 * MySQL 5.6 has Online DDL. This is not as large of an issue as it was historically.
  • 54. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Schema + Schemaless 58 SSDs have capacity_in_gb, CPUs have a core_count. These attributes are not consistent across products. CREATE TABLE pc_components ( id INT NOT NULL PRIMARY KEY, description VARCHAR(60) NOT NULL, vendor VARCHAR(30) NOT NULL, serial_number VARCHAR(30) NOT NULL, attributes JSON NOT NULL );
  • 55. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Sumário 1. O movimento NoSQL é de grande relevância e têm os gigantes da Web como protagonistas 2. NoSQL complementa Bancos Relacionais 3. NewSQL = combinando os dois mundos 4. MySQL continua muito relevante na Web 5. Memcached plugin e JSON são exemplos no MySQL de como bancos relacionais podem abraçar o NoSQL
  • 56. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Obrigado! Copyright © 2014, Oracle and/or its affiliates. All rights reserved.
  • 57. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | @MySQLBR meetup.com/MySQL-BRfacebook.com/MySQLBR pt.planet.mysql.com
  • 58. Copyright © 2015 Oracle and/or its affiliates. All rights reserved. | Perguntas? NoSQL em um mundo SQL Contato: airton.lastori@oracle.com twitter.com/mysqlbr facebook.com/mysqlbr