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Zahid Mian Part of the Brown-bag Series
Schema-less Document DB (don't think Word Document) Document is a JSON object Supports Indexes Scalable Doesn't Support "traditional" Joins Doesn't Support Transactions (not ACID-compliant) Version 3.0.5 (in this doc) http://docs.mongodb.org/manual/ https://www.mongodb.org/downloads
Dictionaries and Arrays {} {"fruits": ["apple", "pear", "peach"]} {name: "Adam Smith"} {numbers: [7,2,3,8]} {name: "Adam Smith", hobbies: [hobby: "Econ",
hobby:"Tennis"]} Formal Representation: http://json.org/
RDBMS SQL MONGODB
database database
table collection
index index
row document
column field
joining N/A
mongod (launch server) mongo (launch client) mongorestore (load a db into mongo) use database (within client, use spceific db) db.collection.findOne();
Download/extract mongodb files Either update Path to include bin folder or navigate to bin folder …
Create folder for data …
> md \data -> md \data\db (remember where you created this folder)
> mongod --dbpath c:\data\db (default path on Windows) ▪ Now the mongodb server will be running (unless there is a problem)
From another command shell launch client: > mongo ▪ Now the mongodb shell will be running
▪ Try the following commands: ▪ show databases
▪ db
▪ show collections
Create - Insert Read - Find Update - Update Delete - Remove Everything is a method/API, not as SQL syntax Valid: db.names.find() Invalid: slect * from names
javascript interpreter > for (i=0;i<3;i++) print("hello"); > help > help keys auto complete with tab > z = {"a":1} > z.a > z["a"] > x={a:1}; y="a"; x[y]++; print(x.a); // output is 2
Binary Specification (bsonspec.org) Allows storage of extended datatypes
Date, Timestamp, Double, Integer, etc. > obj = {
a:1,
b: ISODate("2015-03-21T17:41:55.325Z", c:},
c: NumberLong(555389),
d: Boolean(true)
}
> doc = {name: "Brady", age: 38, team: "Patriots"} If players collection doesn’t exist, it will create one db.players.insert(doc) db.players.find() "_id" is a unique id created by the database; immutable > db.players.findOne() // random document > db.players.remove({}) // remove all objects in collection > db.players.delete() // remove the entire collection
> db.players.findOne() > db.players.findOne("name": "Brady") > db.players.findOne({"name":"Brady", {"_id": false}) > db.players.findOne({"name":"Brady", {"_id": false, "name": true}) > db.players.find().pretty() // well-formatted > db.players.count("name" : "Brady") // Count of records > db.players.find({"name":"Brady", "age": 38}).pretty() > db.players.find({"age": {$gt:30} }).pretty() // greater than 30 > db.players.find({"age": {$lt:40} }).pretty() // less than 40 > db.players.find({"age": {$gte:30, $lte:40}).pretty() // between 30
and 40
> db.players.find({"name": {$lt: "C"}}, {"_id":false, "name":true}) { "name" : "Brady" } { "name" : "B" } > db.players.find({"name": {$gt: "B"}}, {"_id":false, "name":true}) { "name" : "Brady" } { "name" : "brady" } { "name" : "Cano" } { "name" : "b" } { "name" : "brown" } > db.players.find({"name": {$gt: "b"}}, {"_id":false, "name":true}) { "name" : "brady" } { "name" : "brown" }
> db.players.find({}, {"_id":false, "name":true})
{ "name" : "Brady" }
{ "name" : "brady" }
{ "name" : "Cano" }
{ "name" : "B" }
{ "name" : "b" }
{ "name" : "brown" }
> db.players.find({"city": {$exists: true}}) > db.players.find({"city": {$exists: false}}) > db.players.find({"name": {$type: 2}}) // BSON Types Numbers
docs.mongodb.org/manual/reference/bson-types/ // find all players with a "w" in the name key > db.players.find({name: {$regex: "w"}}, {"_id":false, "name":true}) // find all players with names ending in "n" > db.players.find({name: {$regex: "n$"}}, {"_id":false, "name":true}) // find all players with names that start with "b" > db.players.find({name: {$regex: "^b"}}, {"_id":false, "name":true})
// find players that have age of 38 OR have a city > db.players.find({$or: [{"age":38}, {"city": {$exists:true}}]}) // find players that have age 38 AND name equals "Brady" > db.players.find({$and [{age:38}, {name:"Brady"}]}) // same as … a bit more efficient > db.players.find({age:38, name:"Brady"}) // What about this? Think about javascript behavior!! > db.players.find({age:38, age:40})
> db.accounts.find() {"name" : "Adam", "favs" : [ "ice cream", "pretzels", "chips" ] } {"name" : "Mike", "favs" : [ "beer", "chips" ] } {"name" : "Sam", "favs" : "chips" } > db.accounts.find({favs:"chips"}) > db.accounts.find({favs:"chips", name: {$gte : "M"}}) > db.accounts.find({favs: {$all:["chips", "pretzels"]}}) > db.accounts.find({favs: {$any: ["beer", "pretzels"]}})
> db.users.find().pretty() { "_id" : ObjectId("55ca69a88b9e931abe0295db"), "name" : "Adam", "email" : { "work" : "[email protected]", "personal" : "[email protected]" } } { "_id" : ObjectId("55ca6a318b9e931abe0295dc"), "name" : "zahid", "email" : { "work" : "[email protected]", "personal" : "[email protected]" } }
> db.users.find({"email.work": {$regex:"dddd" }}).pretty() { "_id" : ObjectId("55ca69a88b9e931abe0295db"), "name" : "Adam", "email" : { "work" : "[email protected]", "personal" : "[email protected]" } }
> cur = db.players.find(); > cur.hasNext() > cur.next() > while (cur.hasNext()) printjson(cur.next()); > cur.limit(5); // nothing is executed until cursor is read > cur.sort( {name: -l} ); // negative lexicographical sort > cur.sort( {name: -l} ).limit(5); // chaining methods > cur.sort( {name: -l} ).limit(5).skip(1) // first sort, then limit,
then skip
> db.players.find({name:"brady"}) { "_id" : ObjectId("55ca58bf8b9e931abe0295d4"), "name" : "brady", "age" : 40, "team" : "Patriots" } // update all player documents where name equals "brady" (set age to 42, team to "Broncos") > db.players.update({name: "brady"}, {age: 42, team:"Broncos"} ) > db.players.find({team:"Broncos"}) { "_id" : ObjectId("55ca58bf8b9e931abe0295d4"), "age" : 42, "team" : "Broncos" } // name is gone! > db.players.update({team: "Broncos"}, {name: "brady", age: 42, team:"Patriots"} ) // put name back > db.players.find({name:"brady"}) { "_id" : ObjectId("55ca58bf8b9e931abe0295d4"), "name" : "brady", "age" : 42, "team" : "Patriots" } > db.players.update({name:"brady"},{$set: {age:50}}) > db.players.find({name:"brady"}) { "_id" : ObjectId("55ca58bf8b9e931abe0295d4"), "name" : "brady", "age" : 50, "team" : "Patriots" } > db.players.update({name:"brady"},{$unset: {age:1}} > db.players.find({name:"brady"}) { "_id" : ObjectId("55ca58bf8b9e931abe0295d4"), "name" : "brady", "team" : "Patriots" }
> db.arrays.insert( {_id: 0, a: [1,2,3,4]}) > db.arrays.find() { "_id" : 0, "a" : [ 1, 2, 3, 4 ] } > db.arrays.update({_id:0}, {$set: {"a.2": 5}}) > db.arrays.find() { "_id" : 0, "a" : [ 1, 2, 5, 4 ] } > db.arrays.update({_id:0}, {$push: {a: 6}}) > db.arrays.find() { "_id" : 0, "a" : [ 1, 2, 5, 4, 6 ] } > db.arrays.update({_id:0}, {$pop: {a: 1}}) > db.arrays.find() { "_id" : 0, "a" : [ 1, 2, 5, 4 ] } > db.arrays.update({_id:0}, {$pop: {a: -1}}) > db.arrays.find() { "_id" : 0, "a" : [ 2, 5, 4 ] }
> db.arrays.update({_id:0}, {$pushAll: {a: [7,8,9]}}) > db.arrays.find() { "_id" : 0, "a" : [ 2, 5, 4, 7, 8, 9 ] } > db.arrays.update({_id:0}, {$pull: {a: 5}}) > db.arrays.update({_id:0}, {$pull: {a: 5}}) > db.arrays.find() { "_id" : 0, "a" : [ 2, 4, 7, 8, 9 ] } > db.arrays.update({_id:0}, {$pullAll: {a: [8,9]}}) > db.arrays.find() { "_id" : 0, "a" : [ 2, 4, 7 ] } > db.arrays.update({_id:0}, {$addToSet: {a: 3}}) > db.arrays.find() { "_id" : 0, "a" : [ 2, 4, 7, 3 ] }
Combines Update/Insert Excellent use case when you don't know if a document already
exists > db.players.update({name:"Zahid"}, {$set: {age:30, team: "Patriots"}}, {upsert: true} ) > db.players.find({name:"Zahid"}).pretty() { "_id" : ObjectId("55ca7b04f971f0ee874cf2af"), "name" : "Zahid", "age" : 30, "team" : "Patriots" }
{} empty document matches every document in collection db.players.update({}, {$set : {newcol:10}}) Above statement will only update one document (the first
one) To add newcol to all documents, use the multi option db.players.update({}, {$set : {newcol:10}}, {multi: true}) Concurrency issues
Transactions are not isolated
If 10000 updates, possible that 2 different reads could get different results
db.players.remove( {name: "brady"}) db.players.remove({}) // no need for multi option db.players.drop() // drop the entire collection; more efficient
> db.players.ensureIndex({name:1}, {unique:true}) // ensure unique index on name
> db.players.ensureIndex({name:1, age:1}) // compound index on name and age
> db.players.getIndexes() // retrieves a list of all indexes on players collections
> db.players.getIndexSize() // number of bytes allocated to indexes
> db.players.reIndex()
count distinct group > db.records.group( { key: { a: 1 }, cond: { a: { $lt: 3 } }, reduce: function(cur, result) { result.count += cur.count }, initial: { count: 0 } } )
> db.grades.findOne() { "_id" : ObjectId("50906d7fa3c412bb040eb577"), "student_id" : 0, "type" : "exam", "score" : 54.6535436362647 } // sql: select Top 1 student_id _id, avg(score) average from grades group by student_id order by avg(score) desc > db.grades.aggregate( {'$group':{'_id':'$student_id', 'average':{$avg:'$score'}}}, {'$sort':{'average':-1}}, {'$limit':1}) // select student_id _id, min(score) min from grades where score >= 65 group by student_id order by min(score) > db.grades.aggregate([ { $match : { score : {$gte : 65 } } }, { '$group': {'_id':'$student_id', 'min': { $min:'$score'} } }, { '$sort': { 'min': 1 } } ] );
$bit - performs bitwise AND, OR, and XOR updates on integer values $mod - performs a modulo operation on the value of a field $not - returns documents that do not match query expression $nor - returns documents that fail to match both clauses (as in "neither/nor") Geospatial methods like $geoWithin, $geoIntersects, $near, $nearSphere $hint - forces the query optimizer to use specific index db.collection.find().explain() // retrieve query execution plan $maxTimeMS - specifies maximum time for execution of query $natural - sort documents by natural order (ordering of documents internally
within database) $project - reshapes each document in the stream (adding new fields or removing
fields) $cmp, $eq, $gt, $gte, $lt, $lte, $ne (equality operators)
