Download the javascript SDK and include it like any other javascript library by adding the following line in the appropriate HTML file:
<script src="path/to/asterix-sdk-stable.js"></script>
In this section, we explore how to form AQL queries using the javascript SDK. The queries from AsterixDB 101: An ADM and AQL Primer are used as examples here. For each AQL statement, the equivalent javascript expression is shown below it, followed by the results of executing the query.
use dataverse TinySocial; for $user in dataset FacebookUsers where $user.id = 8 return $user;
var expression0a = new FLWOGRExpression()
.ForClause("$user", new AExpression("dataset FacebookUsers"))
.WhereClause(new AExpression("$user.id = 8"))
.ReturnClause("$user");
{ "id": { int32: 8 } , "alias": "Nila", "name": "NilaMilliron", "user-since": { datetime: 1199182200000}, "friend-ids": { unorderedlist: [{ int32: 3 } ]}, "employment": { orderedlist: [{ "organization-name": "Plexlane", "start-date": { date: 1267315200000}, "end-date": null } ]} }
use dataverse TinySocial; for $user in dataset FacebookUsers where $user.id >= 2 and $user.id <= 4 return $user;
var expression0b = new FLWOGRExpression()
.ForClause("$user", new AExpression("dataset FacebookUsers"))
.WhereClause().and(new AExpression("$user.id >= 2"), new AExpression("$user.id <= 4"))
.ReturnClause("$user");
{ "id": { int32: 2 } , "alias": "Isbel", "name": "IsbelDull", "user-since": { datetime: 1295691000000}, "friend-ids": { unorderedlist: [{ int32: 1 } , { int32: 4 } ]}, "employment": { orderedlist: [{ "organization-name": "Hexviafind", "start-date": { date: 1272326400000}, "end-date": null } ]} }
{ "id": { int32: 3 } , "alias": "Emory", "name": "EmoryUnk", "user-since": { datetime: 1341915000000}, "friend-ids": { unorderedlist: [{ int32: 1 } , { int32: 5 } , { int32: 8 } , { int32: 9 } ]}, "employment": { orderedlist: [{ "organization-name": "geomedia", "start-date": { date: 1276732800000}, "end-date": { date: 1264464000000} } ]} }
{ "id": { int32: 4 } , "alias": "Nicholas", "name": "NicholasStroh", "user-since": { datetime: 1293444600000}, "friend-ids": { unorderedlist: [{ int32: 2 } ]}, "employment": { orderedlist: [{ "organization-name": "Zamcorporation", "start-date": { date: 1275955200000}, "end-date": null } ]} }
use dataverse TinySocial;
for $user in dataset FacebookUsers
where $user.user-since >= datetime('2010-07-22T00:00:00')
and $user.user-since <= datetime('2012-07-29T23:59:59')
return $user;
var expression1 = new FLWOGRExpression()
.ForClause("$user", new AExpression("dataset FacebookUsers"))
.WhereClause().and(
new AExpression("$user.user-since >= datetime('2010-07-22T00:00:00')"),
new AExpression("$user.user-since <= datetime('2012-07-29T23:59:59')")
).ReturnClause("$user");
{ "id": { int32: 2 } , "alias": "Isbel", "name": "IsbelDull", "user-since": { datetime: 1295691000000}, "friend-ids": { unorderedlist: [{ int32: 1 } , { int32: 4 } ]}, "employment": { orderedlist: [{ "organization-name": "Hexviafind", "start-date": { date: 1272326400000}, "end-date": null } ]} }
{ "id": { int32: 10 } , "alias": "Bram", "name": "BramHatch", "user-since": { datetime: 1287223800000}, "friend-ids": { unorderedlist: [{ int32: 1 } , { int32: 5 } , { int32: 9 } ]}, "employment": { orderedlist: [{ "organization-name": "physcane", "start-date": { date: 1181001600000}, "end-date": { date: 1320451200000} } ]} }
{ "id": { int32: 3 } , "alias": "Emory", "name": "EmoryUnk", "user-since": { datetime: 1341915000000}, "friend-ids": { unorderedlist: [{ int32: 1 } , { int32: 5 } , { int32: 8 } , { int32: 9 } ]}, "employment": { orderedlist: [{ "organization-name": "geomedia", "start-date": { date: 1276732800000}, "end-date": { date: 1264464000000} } ]} }
{ "id": { int32: 4 } , "alias": "Nicholas", "name": "NicholasStroh", "user-since": { datetime: 1293444600000}, "friend-ids": { unorderedlist: [{ int32: 2 } ]}, "employment": { orderedlist: [{ "organization-name": "Zamcorporation", "start-date": { date: 1275955200000}, "end-date": null } ]} }
use dataverse TinySocial;
for $user in dataset FacebookUsers
for $message in dataset FacebookMessages
where $message.author-id = $user.id
return {
"uname": $user.name,
"message": $message.message
};
var expression2a = new FLWOGRExpression()
.ForClause ("$user", new AExpression("dataset FacebookUsers"))
.ForClause ("$message", new AExpression("dataset FacebookMessages"))
.WhereClause(new AExpression("$message.author-id = $user.id"))
.ReturnClause({
"uname" : "$user.name",
"message" : "$message.message"
});
{ "uname": "MargaritaStoddard", "message": " dislike iphone its touch-screen is horrible" }
{ "uname": "MargaritaStoddard", "message": " like verizon the 3G is awesome:)" }
{ "uname": "MargaritaStoddard", "message": " can't stand motorola the touch-screen is terrible" }
{ "uname": "MargaritaStoddard", "message": " can't stand at&t the network is horrible:(" }
{ "uname": "MargaritaStoddard", "message": " can't stand at&t its plan is terrible" }
{ "uname": "IsbelDull", "message": " like samsung the plan is amazing" }
{ "uname": "IsbelDull", "message": " like t-mobile its platform is mind-blowing" }
{ "uname": "WoodrowNehling", "message": " love at&t its 3G is good:)" }
{ "uname": "BramHatch", "message": " dislike iphone the voice-command is bad:(" }
{ "uname": "BramHatch", "message": " can't stand t-mobile its voicemail-service is OMG:(" }
{ "uname": "EmoryUnk", "message": " love sprint its shortcut-menu is awesome:)" }
{ "uname": "EmoryUnk", "message": " love verizon its wireless is good" }
{ "uname": "WillisWynne", "message": " love sprint the customization is mind-blowing" }
{ "uname": "SuzannaTillson", "message": " like iphone the voicemail-service is awesome" }
{ "uname": "VonKemble", "message": " dislike sprint the speed is horrible" }
use dataverse TinySocial;
for $user in dataset FacebookUsers
for $message in dataset FacebookMessages
where $message.author-id /*+ indexnl */ = $user.id
return {
"uname": $user.name,
"message": $message.message
};
var expression2b = new FLWOGRExpression()
.ForClause ("$user", new AExpression("dataset FacebookUsers"))
.ForClause ("$message", new AExpression("dataset FacebookMessages"))
.WhereClause(new AExpression("$message.author-id /*+ indexnl */ = $user.id"))
.ReturnClause({
"uname" : "$user.name",
"message" : "$message.message"
});
{ "uname": "MargaritaStoddard", "message": " dislike iphone its touch-screen is horrible" }
{ "uname": "MargaritaStoddard", "message": " like verizon the 3G is awesome:)" }
{ "uname": "MargaritaStoddard", "message": " can't stand motorola the touch-screen is terrible" }
{ "uname": "MargaritaStoddard", "message": " can't stand at&t the network is horrible:(" }
{ "uname": "MargaritaStoddard", "message": " can't stand at&t its plan is terrible" }
{ "uname": "IsbelDull", "message": " like samsung the plan is amazing" }
{ "uname": "IsbelDull", "message": " like t-mobile its platform is mind-blowing" }
{ "uname": "WoodrowNehling", "message": " love at&t its 3G is good:)" }
{ "uname": "BramHatch", "message": " dislike iphone the voice-command is bad:(" }
{ "uname": "BramHatch", "message": " can't stand t-mobile its voicemail-service is OMG:(" }
{ "uname": "EmoryUnk", "message": " love sprint its shortcut-menu is awesome:)" }
{ "uname": "EmoryUnk", "message": " love verizon its wireless is good" }
{ "uname": "WillisWynne", "message": " love sprint the customization is mind-blowing" }
{ "uname": "SuzannaTillson", "message": " like iphone the voicemail-service is awesome" }
{ "uname": "VonKemble", "message": " dislike sprint the speed is horrible" }
use dataverse TinySocial;
for $user in dataset FacebookUsers
return {
"uname": $user.name,
"messages": for $message in dataset FacebookMessages
where $message.author-id = $user.id
return $message.message
};
var expression3messages = new FLWOGRExpression()
.ForClause("$message", new AExpression("dataset FacebookMessages"))
.WhereClause(new AExpression("$message.author-id = $user.id"))
.ReturnClause("$message.message");
var expression3 = new FLWOGRExpression()
.ForClause ("$user", new AExpression("dataset FacebookUsers"))
.ReturnClause({
"uname": "$user.name",
"messages" : expression3messages
});
{ "uname": "MargaritaStoddard", "messages": { orderedlist: [" dislike iphone its touch-screen is horrible", " like verizon the 3G is awesome:)", " can't stand motorola the touch-screen is terrible", " can't stand at&t the network is horrible:(", " can't stand at&t its plan is terrible" ]} }
{ "uname": "IsbelDull", "messages": { orderedlist: [" like samsung the plan is amazing", " like t-mobile its platform is mind-blowing" ]} }
{ "uname": "NilaMilliron", "messages": { orderedlist: [ ]} }
{ "uname": "WoodrowNehling", "messages": { orderedlist: [" love at&t its 3G is good:)" ]} }
{ "uname": "BramHatch", "messages": { orderedlist: [" dislike iphone the voice-command is bad:(", " can't stand t-mobile its voicemail-service is OMG:(" ]} }
{ "uname": "EmoryUnk", "messages": { orderedlist: [" love sprint its shortcut-menu is awesome:)", " love verizon its wireless is good" ]} }
{ "uname": "WillisWynne", "messages": { orderedlist: [" love sprint the customization is mind-blowing" ]} }
{ "uname": "SuzannaTillson", "messages": { orderedlist: [" like iphone the voicemail-service is awesome" ]} }
{ "uname": "NicholasStroh", "messages": { orderedlist: [ ]} }
{ "uname": "VonKemble", "messages": { orderedlist: [" dislike sprint the speed is horrible" ]} }
use dataverse TinySocial;
for $t in dataset TweetMessages
return {
"message": $t.message-text,
"nearby-messages": for $t2 in dataset TweetMessages
where spatial-distance($t.sender-location, $t2.sender-location) <= 1
return { "msgtxt":$t2.message-text}
};
var expression4messages = new FLWOGRExpression()
.ForClause( "$t2", new AExpression("dataset TweetMessages"))
.WhereClause( new AExpression("spatial-distance($t.sender-location, $t2.sender-location) <= 1"))
.ReturnClause({ "msgtxt" : "$t2.message-text" });
var expression4 = new FLWOGRExpression()
.ForClause( "$t", new AExpression("dataset TweetMessages"))
.ReturnClause({
"message" : "$t.message-text",
"nearby-messages" : expression4messages
});
{ "message": " hate verizon its voice-clarity is OMG:(", "nearby-messages": { orderedlist: [{ "msgtxt": " hate verizon its voice-clarity is OMG:(" }, { "msgtxt": " like motorola the speed is good:)" } ]} }
{ "message": " like iphone the voice-clarity is good:)", "nearby-messages": { orderedlist: [{ "msgtxt": " like iphone the voice-clarity is good:)" } ]} }
{ "message": " like samsung the platform is good", "nearby-messages": { orderedlist: [{ "msgtxt": " like samsung the platform is good" } ]} }
{ "message": " love t-mobile its customization is good:)", "nearby-messages": { orderedlist: [{ "msgtxt": " love t-mobile its customization is good:)" } ]} }
{ "message": " like samsung the voice-command is amazing:)", "nearby-messages": { orderedlist: [{ "msgtxt": " like samsung the voice-command is amazing:)" } ]} }
{ "message": " like motorola the speed is good:)", "nearby-messages": { orderedlist: [{ "msgtxt": " hate verizon its voice-clarity is OMG:(" }, { "msgtxt": " like motorola the speed is good:)" } ]} }
{ "message": " love verizon its voicemail-service is awesome", "nearby-messages": { orderedlist: [{ "msgtxt": " love verizon its voicemail-service is awesome" } ]} }
{ "message": " can't stand motorola its speed is terrible:(", "nearby-messages": { orderedlist: [{ "msgtxt": " can't stand motorola its speed is terrible:(" } ]} }
{ "message": " like t-mobile the shortcut-menu is awesome:)", "nearby-messages": { orderedlist: [{ "msgtxt": " like t-mobile the shortcut-menu is awesome:)" } ]} }
{ "message": " can't stand iphone its platform is terrible", "nearby-messages": { orderedlist: [{ "msgtxt": " can't stand iphone its platform is terrible" } ]} }
{ "message": " like verizon its shortcut-menu is awesome:)", "nearby-messages": { orderedlist: [{ "msgtxt": " like verizon its shortcut-menu is awesome:)" } ]} }
{ "message": " like sprint the voice-command is mind-blowing:)", "nearby-messages": { orderedlist: [{ "msgtxt": " like sprint the voice-command is mind-blowing:)" } ]} }
use dataverse TinySocial;
set simfunction "edit-distance";
set simthreshold "3";
for $fbu in dataset FacebookUsers
return {
"id": $fbu.id,
"name": $fbu.name,
"similar-users": for $t in dataset TweetMessages
let $tu := $t.user
where $tu.name ~= $fbu.name
return {
"twitter-screenname": $tu.screen-name,
"twitter-name": $tu.name
}
};
var similarUsersExpression = new FLWOGRExpression()
.ForClause("$t", new AExpression("dataset TweetMessages"))
.LetClause ("$tu", new AExpression("$t.user"))
.WhereClause(new AExpression("$tu.name ~= $fbu.name"))
.ReturnClause({
"twitter-screenname": "$tu.screen-name",
"twitter-name": "$tu.name"
});
var expression5 = new FLWOGRExpression()
.ForClause ("$fbu", new AExpression("dataset FacebookUsers"))
.ReturnClause(
{
"id" : "$fbu.id",
"name" : "$fbu.name",
"similar-users" : similarUsersExpression
}
);
{ "id": { int32: 1 } , "name": "MargaritaStoddard", "similar-users": { orderedlist: [ ]} }
{ "id": { int32: 2 } , "name": "IsbelDull", "similar-users": { orderedlist: [ ]} }
{ "id": { int32: 8 } , "name": "NilaMilliron", "similar-users": { orderedlist: [{ "twitter-screenname": "NilaMilliron_tw", "twitter-name": "Nila Milliron" } ]} }
{ "id": { int32: 9 } , "name": "WoodrowNehling", "similar-users": { orderedlist: [ ]} }
{ "id": { int32: 10 } , "name": "BramHatch", "similar-users": { orderedlist: [ ]} }
{ "id": { int32: 3 } , "name": "EmoryUnk", "similar-users": { orderedlist: [ ]} }
{ "id": { int32: 6 } , "name": "WillisWynne", "similar-users": { orderedlist: [ ]} }
{ "id": { int32: 7 } , "name": "SuzannaTillson", "similar-users": { orderedlist: [ ]} }
{ "id": { int32: 4 } , "name": "NicholasStroh", "similar-users": { orderedlist: [ ]} }
{ "id": { int32: 5 } , "name": "VonKemble", "similar-users": { orderedlist: [ ]} }
use dataverse TinySocial; for $fbu in dataset FacebookUsers where (some $e in $fbu.employment satisfies is-null($e.end-date)) return $fbu;
var expression6 = new FLWOGRExpression()
.ForClause ("$fbu", new AQLClause().set("dataset FacebookUsers"))
.WhereClause(
new QuantifiedExpression (
"some" ,
{"$e" : new AExpression("$fbu.employment") },
new FunctionExpression("is-null", new AExpression("$e.end-date"))
)
)
.ReturnClause("$fbu");
{ "id": { int32: 1 } , "alias": "Margarita", "name": "MargaritaStoddard", "user-since": { datetime: 1345457400000}, "friend-ids": { unorderedlist: [{ int32: 2 } , { int32: 3 } , { int32: 6 } , { int32: 10 } ]}, "employment": { orderedlist: [{ "organization-name": "Codetechno", "start-date": { date: 1154822400000}, "end-date": null } ]} }
{ "id": { int32: 2 } , "alias": "Isbel", "name": "IsbelDull", "user-since": { datetime: 1295691000000}, "friend-ids": { unorderedlist: [{ int32: 1 } , { int32: 4 } ]}, "employment": { orderedlist: [{ "organization-name": "Hexviafind", "start-date": { date: 1272326400000}, "end-date": null } ]} }
{ "id": { int32: 8 } , "alias": "Nila", "name": "NilaMilliron", "user-since": { datetime: 1199182200000}, "friend-ids": { unorderedlist: [{ int32: 3 } ]}, "employment": { orderedlist: [{ "organization-name": "Plexlane", "start-date": { date: 1267315200000}, "end-date": null } ]} }
{ "id": { int32: 6 } , "alias": "Willis", "name": "WillisWynne", "user-since": { datetime: 1105956600000}, "friend-ids": { unorderedlist: [{ int32: 1 } , { int32: 3 } , { int32: 7 } ]}, "employment": { orderedlist: [{ "organization-name": "jaydax", "start-date": { date: 1242345600000}, "end-date": null } ]} }
{ "id": { int32: 7 } , "alias": "Suzanna", "name": "SuzannaTillson", "user-since": { datetime: 1344334200000}, "friend-ids": { unorderedlist: [{ int32: 6 } ]}, "employment": { orderedlist: [{ "organization-name": "Labzatron", "start-date": { date: 1303171200000}, "end-date": null } ]} }
{ "id": { int32: 4 } , "alias": "Nicholas", "name": "NicholasStroh", "user-since": { datetime: 1293444600000}, "friend-ids": { unorderedlist: [{ int32: 2 } ]}, "employment": { orderedlist: [{ "organization-name": "Zamcorporation", "start-date": { date: 1275955200000}, "end-date": null } ]} }
{ "id": { int32: 5 } , "alias": "Von", "name": "VonKemble", "user-since": { datetime: 1262686200000}, "friend-ids": { unorderedlist: [{ int32: 3 } , { int32: 6 } , { int32: 10 } ]}, "employment": { orderedlist: [{ "organization-name": "Kongreen", "start-date": { date: 1290816000000}, "end-date": null } ]} }
use dataverse TinySocial; for $fbu in dataset FacebookUsers where (every $e in $fbu.employment satisfies not(is-null($e.end-date))) return $fbu;
var expression7 = new FLWOGRExpression()
.ForClause("$fbu", new AExpression("dataset FacebookUsers"))
.WhereClause(
new QuantifiedExpression (
"every" ,
{"$e" : new AExpression("$fbu.employment") },
new FunctionExpression("not", new FunctionExpression("is-null", new AExpression("$e.end-date")))
)
)
.ReturnClause("$fbu");
{ "id": { int32: 9 } , "alias": "Woodrow", "name": "WoodrowNehling", "user-since": { datetime: 1127211000000}, "friend-ids": { unorderedlist: [{ int32: 3 } , { int32: 10 } ]}, "employment": { orderedlist: [{ "organization-name": "Zuncan", "start-date": { date: 1050969600000}, "end-date": { date: 1260662400000} } ]} }
{ "id": { int32: 10 } , "alias": "Bram", "name": "BramHatch", "user-since": { datetime: 1287223800000}, "friend-ids": { unorderedlist: [{ int32: 1 } , { int32: 5 } , { int32: 9 } ]}, "employment": { orderedlist: [{ "organization-name": "physcane", "start-date": { date: 1181001600000}, "end-date": { date: 1320451200000} } ]} }
{ "id": { int32: 3 } , "alias": "Emory", "name": "EmoryUnk", "user-since": { datetime: 1341915000000}, "friend-ids": { unorderedlist: [{ int32: 1 } , { int32: 5 } , { int32: 8 } , { int32: 9 } ]}, "employment": { orderedlist: [{ "organization-name": "geomedia", "start-date": { date: 1276732800000}, "end-date": { date: 1264464000000} } ]} }
use dataverse TinySocial; count(for $fbu in dataset FacebookUsers return $fbu);
var expression8 = new FunctionExpression(
"count",
new FLWOGRExpression()
.ForClause("$fbu", new AExpression("dataset FacebookUsers"))
.ReturnClause("$fbu")
);
{ int64: 10 }
use dataverse TinySocial;
for $t in dataset TweetMessages
group by $uid := $t.user.screen-name with $t
return {
"user": $uid,
"count": count($t)
};
var expression9a = new FLWOGRExpression()
.ForClause("$t", new AExpression("dataset TweetMessages"))
.GroupClause("$uid", new AExpression("$t.user.screen-name"), "with", "$t")
.ReturnClause(
{
"user" : "$uid",
"count" : new FunctionExpression("count", new AExpression("$t"))
}
);
{ "user": "ColineGeyer@63", "count": { int64: 3 } }
{ "user": "OliJackson_512", "count": { int64: 1 } }
{ "user": "NilaMilliron_tw", "count": { int64: 1 } }
{ "user": "ChangEwing_573", "count": { int64: 1 } }
{ "user": "NathanGiesen@211", "count": { int64: 6 } }
use dataverse TinySocial;
for $t in dataset TweetMessages
/*+ hash*/
group by $uid := $t.user.screen-name with $t
return {
"user": $uid,
"count": count($t)
};
var expression9b = new FLWOGRExpression()
.ForClause("$t", new AExpression("dataset TweetMessages"))
.AQLClause("/*+ hash*/")
.GroupClause("$uid", new AExpression("$t.user.screen-name"), "with", "$t")
.ReturnClause(
{
"user" : "$uid",
"count" : new FunctionExpression("count", new AExpression("$t"))
}
);
{ "user": "ColineGeyer@63", "count": { int64: 3 } }
{ "user": "OliJackson_512", "count": { int64: 1 } }
{ "user": "NilaMilliron_tw", "count": { int64: 1 } }
{ "user": "ChangEwing_573", "count": { int64: 1 } }
{ "user": "NathanGiesen@211", "count": { int64: 6 } }
use dataverse TinySocial;
for $t in dataset TweetMessages
group by $uid := $t.user.screen-name with $t
let $c := count($t)
order by $c desc
limit 3
return {
"user": $uid,
"count": $c
};
var expression10 = new FLWOGRExpression()
.ForClause("$t", new AExpression("dataset TweetMessages"))
.GroupClause("$uid", new AExpression("$t.user.screen-name"), "with", "$t")
.LetClause("$c", new FunctionExpression("count", new AExpression("$t")))
.OrderbyClause( new AExpression("$c"), "desc" )
.LimitClause(new AExpression("3"))
.ReturnClause(
{
"user" : "$uid",
"count" : "$c"
}
);
{ "user": "NathanGiesen@211", "count": { int64: 6 } }
{ "user": "ColineGeyer@63", "count": { int64: 3 } }
{ "user": "NilaMilliron_tw", "count": { int64: 1 } }
use dataverse TinySocial;
set simfunction "jaccard";
set simthreshold "0.3";
for $t in dataset TweetMessages
return {
"tweet": $t,
"similar-tweets": for $t2 in dataset TweetMessages
where $t2.referred-topics ~= $t.referred-topics
and $t2.tweetid != $t.tweetid
return $t2.referred-topics
};
var expression11 = new FLWOGRExpression()
.ForClause( "$t", new AExpression("dataset TweetMessages"))
.ReturnClause({
"tweet" : new AExpression("$t"),
"similar-tweets": new FLWOGRExpression()
.ForClause( "$t2", new AExpression("dataset TweetMessages"))
.WhereClause().and(
new AExpression("$t2.referred-topics ~= $t.referred-topics"),
new AExpression("$t2.tweetid != $t.tweetid")
)
.ReturnClause("$t2.referred-topics")
});
{ "tweet": { "tweetid": "10", "user": { "screen-name": "ColineGeyer@63", "lang": "en", "friends_count": { int32: 121 } , "statuses_count": { int32: 362 } , "name": "Coline Geyer", "followers_count": { int32: 17159 } }, "sender-location": { point: [29.15, 76.53]}, "send-time": { datetime: 1201342200000}, "referred-topics": { unorderedlist: ["verizon", "voice-clarity" ]}, "message-text": " hate verizon its voice-clarity is OMG:(" }, "similar-tweets": { orderedlist: [{ unorderedlist: ["iphone", "voice-clarity" ]}, { unorderedlist: ["verizon", "shortcut-menu" ]}, { unorderedlist: ["verizon", "voicemail-service" ]} ]} }
{ "tweet": { "tweetid": "6", "user": { "screen-name": "ColineGeyer@63", "lang": "en", "friends_count": { int32: 121 } , "statuses_count": { int32: 362 } , "name": "Coline Geyer", "followers_count": { int32: 17159 } }, "sender-location": { point: [47.51, 83.99]}, "send-time": { datetime: 1273227000000}, "referred-topics": { unorderedlist: ["iphone", "voice-clarity" ]}, "message-text": " like iphone the voice-clarity is good:)" }, "similar-tweets": { orderedlist: [{ unorderedlist: ["verizon", "voice-clarity" ]}, { unorderedlist: ["iphone", "platform" ]} ]} }
{ "tweet": { "tweetid": "7", "user": { "screen-name": "ChangEwing_573", "lang": "en", "friends_count": { int32: 182 } , "statuses_count": { int32: 394 } , "name": "Chang Ewing", "followers_count": { int32: 32136 } }, "sender-location": { point: [36.21, 72.6]}, "send-time": { datetime: 1314267000000}, "referred-topics": { unorderedlist: ["samsung", "platform" ]}, "message-text": " like samsung the platform is good" }, "similar-tweets": { orderedlist: [{ unorderedlist: ["iphone", "platform" ]}, { unorderedlist: ["samsung", "voice-command" ]} ]} }
{ "tweet": { "tweetid": "1", "user": { "screen-name": "NathanGiesen@211", "lang": "en", "friends_count": { int32: 39339 } , "statuses_count": { int32: 473 } , "name": "Nathan Giesen", "followers_count": { int32: 49416 } }, "sender-location": { point: [47.44, 80.65]}, "send-time": { datetime: 1209204600000}, "referred-topics": { unorderedlist: ["t-mobile", "customization" ]}, "message-text": " love t-mobile its customization is good:)" }, "similar-tweets": { orderedlist: [{ unorderedlist: ["t-mobile", "shortcut-menu" ]} ]} }
{ "tweet": { "tweetid": "12", "user": { "screen-name": "OliJackson_512", "lang": "en", "friends_count": { int32: 445 } , "statuses_count": { int32: 164 } , "name": "Oli Jackson", "followers_count": { int32: 22649 } }, "sender-location": { point: [24.82, 94.63]}, "send-time": { datetime: 1266055800000}, "referred-topics": { unorderedlist: ["samsung", "voice-command" ]}, "message-text": " like samsung the voice-command is amazing:)" }, "similar-tweets": { orderedlist: [{ unorderedlist: ["samsung", "platform" ]}, { unorderedlist: ["sprint", "voice-command" ]} ]} }
{ "tweet": { "tweetid": "3", "user": { "screen-name": "NathanGiesen@211", "lang": "en", "friends_count": { int32: 39339 } , "statuses_count": { int32: 473 } , "name": "Nathan Giesen", "followers_count": { int32: 49416 } }, "sender-location": { point: [29.72, 75.8]}, "send-time": { datetime: 1162635000000}, "referred-topics": { unorderedlist: ["motorola", "speed" ]}, "message-text": " like motorola the speed is good:)" }, "similar-tweets": { orderedlist: [{ unorderedlist: ["motorola", "speed" ]} ]} }
{ "tweet": { "tweetid": "9", "user": { "screen-name": "NathanGiesen@211", "lang": "en", "friends_count": { int32: 39339 } , "statuses_count": { int32: 473 } , "name": "Nathan Giesen", "followers_count": { int32: 49416 } }, "sender-location": { point: [36.86, 74.62]}, "send-time": { datetime: 1342865400000}, "referred-topics": { unorderedlist: ["verizon", "voicemail-service" ]}, "message-text": " love verizon its voicemail-service is awesome" }, "similar-tweets": { orderedlist: [{ unorderedlist: ["verizon", "voice-clarity" ]}, { unorderedlist: ["verizon", "shortcut-menu" ]} ]} }
{ "tweet": { "tweetid": "5", "user": { "screen-name": "NathanGiesen@211", "lang": "en", "friends_count": { int32: 39339 } , "statuses_count": { int32: 473 } , "name": "Nathan Giesen", "followers_count": { int32: 49416 } }, "sender-location": { point: [40.09, 92.69]}, "send-time": { datetime: 1154686200000}, "referred-topics": { unorderedlist: ["motorola", "speed" ]}, "message-text": " can't stand motorola its speed is terrible:(" }, "similar-tweets": { orderedlist: [{ unorderedlist: ["motorola", "speed" ]} ]} }
{ "tweet": { "tweetid": "8", "user": { "screen-name": "NathanGiesen@211", "lang": "en", "friends_count": { int32: 39339 } , "statuses_count": { int32: 473 } , "name": "Nathan Giesen", "followers_count": { int32: 49416 } }, "sender-location": { point: [46.05, 93.34]}, "send-time": { datetime: 1129284600000}, "referred-topics": { unorderedlist: ["t-mobile", "shortcut-menu" ]}, "message-text": " like t-mobile the shortcut-menu is awesome:)" }, "similar-tweets": { orderedlist: [{ unorderedlist: ["verizon", "shortcut-menu" ]}, { unorderedlist: ["t-mobile", "customization" ]} ]} }
{ "tweet": { "tweetid": "11", "user": { "screen-name": "NilaMilliron_tw", "lang": "en", "friends_count": { int32: 445 } , "statuses_count": { int32: 164 } , "name": "Nila Milliron", "followers_count": { int32: 22649 } }, "sender-location": { point: [37.59, 68.42]}, "send-time": { datetime: 1205057400000}, "referred-topics": { unorderedlist: ["iphone", "platform" ]}, "message-text": " can't stand iphone its platform is terrible" }, "similar-tweets": { orderedlist: [{ unorderedlist: ["iphone", "voice-clarity" ]}, { unorderedlist: ["samsung", "platform" ]} ]} }
{ "tweet": { "tweetid": "2", "user": { "screen-name": "ColineGeyer@63", "lang": "en", "friends_count": { int32: 121 } , "statuses_count": { int32: 362 } , "name": "Coline Geyer", "followers_count": { int32: 17159 } }, "sender-location": { point: [32.84, 67.14]}, "send-time": { datetime: 1273745400000}, "referred-topics": { unorderedlist: ["verizon", "shortcut-menu" ]}, "message-text": " like verizon its shortcut-menu is awesome:)" }, "similar-tweets": { orderedlist: [{ unorderedlist: ["t-mobile", "shortcut-menu" ]}, { unorderedlist: ["verizon", "voice-clarity" ]}, { unorderedlist: ["verizon", "voicemail-service" ]} ]} }
{ "tweet": { "tweetid": "4", "user": { "screen-name": "NathanGiesen@211", "lang": "en", "friends_count": { int32: 39339 } , "statuses_count": { int32: 473 } , "name": "Nathan Giesen", "followers_count": { int32: 49416 } }, "sender-location": { point: [39.28, 70.48]}, "send-time": { datetime: 1324894200000}, "referred-topics": { unorderedlist: ["sprint", "voice-command" ]}, "message-text": " like sprint the voice-command is mind-blowing:)" }, "similar-tweets": { orderedlist: [{ unorderedlist: ["samsung", "voice-command" ]} ]} }