1+ // use FIT5137MASL collection
2+ show dbs
3+ use FIT5137MASL
4+ show collections
5+
6+ //C.1 MongoDB shell
7+ //(i) combine the date data (from the fields for year, month, day and hour) to proper MongoDB date data types.
8+ // Use dataFromParts to concat year,month,day,hour Reference: https://docs.mongodb.com/manual/reference/operator/aggregation/dateFromParts/
9+ db . ufo . aggregate ( [
10+ { $project :{ "dateTime" :{ $dateFromParts :{ "year" :"$year" , "month" :"$month" , "day" :"$day" , "hour" :"$hour" } } , _id :0 } }
11+ ] ) ;
12+
13+ //(ii) store the combined date data in a new field called dateTime.
14+ // use addFields to add a new field then store combined date. Reference:https://docs.mongodb.com/manual/reference/operator/aggregation/addFields/
15+ db . ufo . aggregate ( [
16+ { $addFields :{ "dateTime" :{ $dateFromParts :{ "year" :"$year" , "month" :"$month" , "day" :"$day" , "hour" :"$hour" } } } } ,
17+ { $merge :{ into :"ufo" } }
18+ ] ) ;
19+
20+ //(iii) remove the fields for year, month, day and hour.
21+ // use unset to delete specified fields
22+ db . ufo . updateMany ( { } , { $unset :{ "year" :1 , "month" :1 , "day" :1 , "hour" :1 } } ) ;
23+
24+ //(iv) add another field with your group name
25+ //(e.g. groupName: "Group FIT5137" if your group name is FIT5137)
26+ db . ufo . updateMany ( { } , { $set :{ "groupName" :"Group Suki&Albee" } } ) ;
27+
28+
29+ //(v) store the updated collection in a new collection called ufoDates.
30+ // $out to output a new collection that stores changed ufo data.
31+ db . ufo . aggregate ( [
32+ { $match :{ } } ,
33+ { $out :"ufoDates" }
34+ ] ) ;
35+
36+
37+ //C.1.4. Add data to the ufoDates collection
38+ // add new data into collection, dateTime use new Date(), sightingObs is a object contains other three string values.
39+ db . ufoDates . insertOne (
40+ { state :"MA" ,
41+ city :"BOSTON" ,
42+ countryName :"SUFFOLK" ,
43+ dateTime :new Date ( "1998-07-14T23:00:00.000+00:00" ) ,
44+ shape :"sphere" ,
45+ sightingObs :
46+ [ { duration :"40 min" ,
47+ text :"I was going to my work on my night shift at the St Albin’s hospital and saw an unearthly ray of shooting lights which could be none other than a UFO!" ,
48+ summary :"Unearthly ray of shooting lights" } ]
49+ } ) ;
50+
51+ //C.1.5.
52+ // use update to modify data, unsure rows so use updateMany
53+ // condition is duration time, delete sightingObs field after find matching data.
54+ db . ufoDates . updateMany ( { "sightingObs.duration" :"2 1/2 minutes" } , { $unset :{ "sightingObs" :"" } } ) ;
55+
56+ //C.1.6
57+ //(i)
58+ // conditions are state,city and time, group mathing data by state, then count numbers of data in state
59+ db . ufoDates . aggregate ( [
60+ { $match :{ "city" :"SAN FRANCISCO" , "state" :"CA" , "dateTime" :{ $gte :ISODate ( "1990-01-01" ) , $lt :ISODate ( "2001-01-01" ) } } } ,
61+ { $group :{ _id :"$state" , totalNumOfSObs :{ $sum :1 } } }
62+ ] ) ;
63+
64+
65+ //(ii)
66+ //condition is fireball shape, group temp,hum,pre,rain to calculate average value and use $round to keep 3 decimal places for results
67+ //Reference:https://docs.mongodb.com/manual/reference/operator/aggregation/round/
68+ db . ufoDates . aggregate ( [
69+ { $match :{ "shape" :"fireball" } } ,
70+ { $group :{ _id :"fireball" ,
71+ avgTemp :{ $avg :"$weatherObs.temp" } ,
72+ avgHumidity :{ $avg :"$weatherObs.hum" } ,
73+ avgPressure :{ $avg :"$weatherObs.pressure" } ,
74+ avgRainfallObs :{ $avg :"$weatherObs.rain" } } } ,
75+ { $project :{ _id :"fireball" ,
76+ avgTemp :{ $round :[ "$avgTemp" , 3 ] } ,
77+ avgHumidity :{ $round :[ "$avgHumidity" , 3 ] } ,
78+ avgPressure :{ $round :[ "$avgPressure" , 3 ] } ,
79+ avgRainfallObs :{ $round :[ "$avgRainfallObs" , 3 ] } } }
80+ ] ) ;
81+
82+
83+ //(iii)
84+ // use $switch to change month numbers to month names. group by month and calculate numbers of each month, sort result as descending order and limit 1 output.
85+ //Reference:https://docs.mongodb.com/manual/reference/operator/aggregation/switch/
86+ db . ufoDates . aggregate ( [
87+ { $project :{ "monthName" :{ $switch :{ branches :[
88+ { case :{ $eq :[ { $month :"$dateTime" } , 1 ] } , then :"January" } ,
89+ { case :{ $eq :[ { $month :"$dateTime" } , 2 ] } , then :"February" } ,
90+ { case :{ $eq :[ { $month :"$dateTime" } , 3 ] } , then :"March" } ,
91+ { case :{ $eq :[ { $month :"$dateTime" } , 4 ] } , then :"April" } ,
92+ { case :{ $eq :[ { $month :"$dateTime" } , 5 ] } , then :"May" } ,
93+ { case :{ $eq :[ { $month :"$dateTime" } , 6 ] } , then :"June" } ,
94+ { case :{ $eq :[ { $month :"$dateTime" } , 7 ] } , then :"July" } ,
95+ { case :{ $eq :[ { $month :"$dateTime" } , 8 ] } , then :"August" } ,
96+ { case :{ $eq :[ { $month :"$dateTime" } , 9 ] } , then :"September" } ,
97+ { case :{ $eq :[ { $month :"$dateTime" } , 10 ] } , then :"October" } ,
98+ { case :{ $eq :[ { $month :"$dateTime" } , 11 ] } , then :"November" } ,
99+ { case :{ $eq :[ { $month :"$dateTime" } , 12 ] } , then :"December" } ] ,
100+ default :"..." } } } } ,
101+ { $group :{ _id :"$monthName" , "highest number of UFO sightings" :{ $sum :1 } } } ,
102+ { $sort :{ "highest number of UFO sightings" :- 1 } } ,
103+ { $limit :1 }
104+ ] ) ;
105+
106+ //(iv)
107+ // $max and $min function can pick maximum and minimum value from fields. filter null value colour and leave 3 decimal places.
108+ // Reference:https://docs.mongodb.com/manual/reference/operator/aggregation/toUpper/
109+ db . ufoDates . aggregate ( [
110+ { $group :{ _id :{ $toUpper :"$colour" } , maxTemp :{ $max :"$weatherObs.temp" } , minTemp :{ $min :"$weatherObs.temp" } } } ,
111+ { $match :{ _id :{ $ne :"" } } } ,
112+ { $project :{ _id :1 , maxTemp :{ $round :[ "$maxTemp" , 3 ] } , minTemp :{ $round :[ "$minTemp" , 3 ] } } }
113+ ] ) ;
114+
115+
116+ //(v)
117+ // condition is oval shape, group by direction and summarise number, sort by descending order and pick 1 row.
118+ db . ufoDates . aggregate ( [
119+ { $match :{ shape :"oval" } } ,
120+ { $group :{ _id :{ Direction :"$weatherObs.windCond.wdire" } , ObsRecord :{ $sum :1 } } } ,
121+ { $sort :{ ObsRecord :- 1 } } ,
122+ { $limit :1 }
123+ ] ) ;
124+
125+
126+ //(vi)
127+ // create text index for text and summary, search contents which contain light or LIGHT.
128+ //Reference:https://docs.mongodb.com/manual/reference/operator/query/text/
129+ db . ufoDates . createIndex ( { "sightingObs.text" :"text" , "sightingObs.summary" :"text" } ) ;
130+ db . ufoDates . aggregate ( [
131+ { $match :{ $text :{ $search :"light" , $caseSensitive : false } } } ,
132+ { $count :"sumOfLight" }
133+ ] ) ;
134+
135+ //C.1.7. lat,long:doubles
136+ // city,state,countyname
137+ // join two collections using $lookup. different state might have same city names,so use $let to generate new fields,
138+ // use pipeline to aggregate multiple conditions. match state,city and county, then save location as one list
139+ // $unwind to split new list field, save latitude and longitude as seperate field.
140+ // output new collection
141+ //Reference:https://docs.mongodb.com/manual/reference/operator/aggregation/lookup/
142+ db . ufoDates . aggregate ( [
143+ { $lookup :{ from : "states" ,
144+ let :{ "post_city" :"$city" , "post_countyName" :"$countyName" , "post_state" :"$state" } ,
145+ pipeline :[
146+ { $match :
147+ { $expr :{ $and :[
148+ { $eq :[ "$$post_city" , "$city" ] } ,
149+ { $eq :[ "$$post_countyName" , "$countyName" ] } ,
150+ { $eq :[ "$$post_state" , "$state" ] } ] } ,
151+ } } ,
152+ { $project :{ _id :0 , countyName :0 , city :0 , state :0 } } ] ,
153+ as :"geoDocs" } } ,
154+ { $unwind :"$geoDocs" } ,
155+ { $addFields :{ "geoLat" :"$geoDocs.lat" , "geoLng" :"$geoDocs.lng" } } ,
156+ { $project :{ "geoDocs" :0 } } ,
157+ { $out :"ufoStates" }
158+ ] ) ;
159+
160+ //C.1.8 convert the latitude and longitude [coordinate:[long,lat]
161+ // https://docs.mongodb.com/manual/reference/operator/aggregation/let/
162+ // use let to defined new attribute
163+ // https://docs.mongodb.com/manual/geospatial-queries/
164+ // geo location
165+ db . ufoStates . aggregate ( [
166+ { $addFields :{ location :{ type :"Point" , coordinates :[ "$geoLng" , "$geoLat" ] } } } ,
167+ { $project :{ "geoLat" :0 , "geoLng" :0 } } ,
168+ { $out :"ufoStatesGeojson" }
169+ ] ) ;
170+
171+ //1.9
172+ // find which city has most records, use location info of this city
173+ // create index on coordinates[lng,lat]
174+ // $geoNear to search points near my setting range[10000,100000]
175+ // avoid same city names, so group by city and state
176+ //https://blog.mlab.com/2014/08/a-primer-on-geospatial-data-and-mongodb/
177+ //https://stackoverflow.com/questions/22374312/meteor-js-mongodb-near-geometry-geojson-point-coordinates-longitude-limit?rq=1
178+ db . ufoStatesGeojson . aggregate ( [
179+ { $group :{ _id :"$city" , sumOfCities :{ $sum :1 } } } ,
180+ { $sort :{ "sumOfCities" :- 1 } } ,
181+ { $limit :1 }
182+ ] ) ;
183+ db . ufoStatesGeojson . find ( { city :{ $eq :"PHOENIX" } } , { "location.coordinates" :1 , "_id" :0 } ) ;
184+ db . ufoStatesGeojson . createIndex ( { "location.coordinates" :"2dsphere" } ) ;
185+ db . ufoStatesGeojson . aggregate ( [
186+ { $geoNear :{ near : { type : "Point" , coordinates : [ - 112.0891 , 33.5722 ] } ,
187+ spherical :true ,
188+ key :"location.coordinates" ,
189+ distanceField :"distance" ,
190+ minDistance :10000 ,
191+ maxDistance :100000 } } ,
192+ { $group :{ _id :{ "city" :"$city" , "countyName" :"$countyName" , "state" :"$state" } } } ] ) ;
193+
194+ //1.10 output ufo.csv file
195+ // compass action
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