5. Challenges with RDBMS
Assumes
WELL DEFINED data structure
data is DENSE and largely UNIFORM
PROPERTIES of data can be defined upfront
INTERRELATIONSHIP are well ESTABLISHED & SYSTEMATIC
INDEXES can be CONSISTENTLY DEFINED
May SNAP when data grows enormously
But ...
that may not be TRUE
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6. DATA is
Unstructured
Does not make sense
OW
DATA is GR IN G at high speed
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7. NoSQL?
No Rel / No SQL / Not Only SQL / NoSQL
Non RELATIONAL
DISTRIBUTED DATASTORES
May NOT provide ACID
Not a Single Product or Technology
Data Storage and Manipulation
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8. NoSQL Storage Types
DOCUMENT STORE
GRAPH
KEY-VALUE STORE
TABULAR
multivalue database
object database
rdf database
tuple store
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11. Best Features of KEY-VALUE stores,
DOCUMENT database & RELATIONAL
databases
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12. Why so POPULAR?
EASY to USE
SIMPLER concepts
EASY on ramp for NoSQL
Many DEV/OPERATIONAL things come inbuilt
More AGILE than RDBMS
Less UPFRONT DESIGN needed than RDBMS
SCALABLE schema and storage
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13. Built for SPEED
Built for SPEED (written in C++)
Data serialized to BSON
Extensive use of MEMORY MAPPED Files
PADS DISK SPACE around document
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15. Negatives of MONGODB
INDEXES are not flexible
REALTIME QUERIES may not be as fast as others
Good enough only if queries are SIMPLE
Not as MATURED as RDBMS
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22. MySQL to MongoDB
MySQL Term MongoDB Term
Database Database
Tables Collection
Rows BSON Document
Column BSON Fields
Index Index
Join Embedding and Linking
Primary Key _id field
Group by Aggregation
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23. SQL to MONGO
SQL Statements Mongo Statements
CREATE DATABASE sqltest use mongotest
USE sqltest implicit
CREATE TABLE table1 (a Number, b db.createCollection('coll1');
Number)
ALTER TABLE table1 add … implicit
INSERT INTO table1 values(100,22) db.coll1.insert({'a':'100,'b':22});
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24. SQL to MONGO
SQL Statements Mongo Statements
SELECT * from table1 db.coll1.find();
SELECT * from table1 where a=33 db.coll1.find({a:33});
SELECT a,b from table1 where a =44 db.coll1.find({a:44},{a:1,b:1});
SELECT * from table1 where b like '%abc%' db.coll1.find({b:/abc/});
SELECT * from table1 where b like 'abc%' db.coll1.find({b:/^abc/});
SELECT * from table1 where a>50 db.coll1.find({a:{$gt:50}});
SELECT * from table1 where a <40 db.coll1.find({a:{$lt:40}});
SELECT * from table1 where a<=40 db.coll1.find({a:{$lte:40}});
SELECT * from table1 where a =33 order by db.coll1.find({a:33}).sort({name:1})
name
SELECT * from table1 where a=33 order by db.coll1.find({a:33}).sort({name:-1})
name DESC
SELECT * from table1 LIMIT 1 db.coll1.findOne();
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25. SQL to MONGO
SQL Statements Mongo Statements
SELECT * from table1 where a=33 and b=100 db.coll1.find({a:33,b:100});
SELECT * from table1 LIMIT 100 db.coll1.find().limit(100);
SELECT * from table1 where a =33 or a=45 or db.coll1.find({$or:[{a:33},{a:45},{a:50}]})
a=50
SELECT DISTINCT a from table1 db.coll1.distinct('a');
SELECT count(*) from table1 db.coll1.count();
SELECT count(*) from table1 where a=33 db.coll1.find({a:33}).count();
CREATE INDEX myindexname ON table1(a) db.coll1.ensureIndex({a:1})
UPDATE table1 set a=44 where b=100 db.coll1.update({b:100},{$set:
{a:44}},false,true);
DELETE from table1 where a=44 db.coll1.remove({a:44});
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26. INSTALLATION
It is DEAD SIMPLE
Refer to the following link
http://www.mongodb.org/display/DOCS/Quickstart/
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32. Inserting DOCUMENT
db.collection.insert(<json formatted data>);
e.g.
db.articles.insert({title:'This is test article',slug:'this-is-test-article',text:'This is test article
and it does not contain anything',count:10});
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34. Updating DOCUMENTS
db.collection.update( criteria, objNew, upsert, multi )
Upsert = update data if exists, insert as new data if not
Multi = make multiple updates matching criteria
e.g.
db.articles.update({count:20},{$set:{title:'This is second article',slug:'this-is-second-
art'}},true,false)
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35. creating INDEX
db.collection.ensureIndex(index);
eg.
db.articles.ensureIndex({title:1})
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36. MONGODB-PHP EXTENSION
Available from PECL
shell> pecl install mongo
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37. Loading MONGO EXTENSION in PHP
Add extension=mongo.so to php.ini
Or any other file like mongo.ini but make sure it is loaded by php
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