neumino

r.table("t1").eqJoin(
    function(doc) { return doc("a")("b"); },
    r.table("t2")
).map( function(left, right) {
    return left.merge({
        a: {
            b: right
        }
    })
})

neumino

r.db('shred').table("teams").map(function(team) {
   return team.merge({
     members: r.db('shred').table("users").filter(function(user) {
       return team("members").contains(user("id"))
     }).coerceTo("ARRAY")
   })
 })


// More efficient query that uses the index id

neumino

conn = r.connect()

cursor = r.db('gbrl').table('race').get_all(14136, index='season_id') \
    .pluck({'results':['driver', 'position']}, 'time') \
    .order_by('time') \
        .map( lambda race:
            r.branch( # That's just a if
                # Check if Andrew is in the results
                race["results"]["driver"].contains("Andrew Vennaro"),
                race["results"].filter(lambda doc:

neumino

r.table("users").filter( function(user) {
    // map over all the keys of search
    return r.expr(search).keys().map( function(key) {
        // for each key, we return a boolean weather user(key) match search(key) (case insensitive)
        return user(key).match( r.expr("(?i)").add(r.expr(search)(key)) ).ne(null)
    }).reduce( function(left, right) { // Then for each boolean, we return left and right // so we perform a "and" operation here.
        return left.and(right)
    })
})

neumino

r.db('todomvc').table('posts').map( function(post) {
    return post.merge({
        comments: r.db('todomvc').table('comments').filter( function(comment) {
            comment("pid").eq( post("id") )
        }).coerceTo("ARRAY")
    })
})


// If you have an index on pid for the table comments, you can do

neumino

r.db("ScrobbleGraph").table("scrobbles").groupedMapReduce(
  function(doc) { return doc("date").date() },
  function(doc) { return [doc] },
  function(left, right) { return left.add(right)}
)


// It's better to use just an orderBy and group on the client because
// - The database won't have to keep everything in memory
// - It's faster because of the index

neumino

r.db('test').table('test').filter( function(doc) {
  return doc.keys().contains( function(key) { 
    return key.match("^(abc)")
  })
})

neumino

r.table('marvel').groupedMapReduce(
    function(hero) { return hero('weightClass'), // group function
    function(hero) { // map function
        return {
            strength: hero('strength'),
            height: hero('height'),
            count: 1
        }
    }, 
    function(left, right) { // reduce function

neumino

r.table("authors").filter( function(author) {
    return author("posts").contains( function(post) {
         post("tags").contains("tagSearched")
    })
}).map( function(author) {
    author.merge({
        posts: author("posts").filter( function(post) {
             post("tags").contains("tagSearched")
        })
    })

neumino

#!/bin/bash
if [ $# -eq 1 ]
NM=`uname -a && date`
NAME=`echo $NM | md5sum | cut -f1 -d" "`
then
	ppa_name=`echo "$1" | cut -d":" -f2 -s`
	if [ -z "$ppa_name" ]
	then
		echo "PPA name not found"
		echo "Utility to add PPA repositories in your debian machine"