Beyond the Basics 2: Aggregation Framework
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The document discusses advanced MongoDB analytics, focusing on storage engines and the aggregation framework, which serves as an analytics engine for processing data within the database. It explains the distinction between Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP), and details the stages of data aggregation including operations like match, project, group, and sort. Additionally, it outlines practical examples of querying and creating visualizations from MongoDB data, emphasizing the importance of security in data handling.
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![11
Example Document
MongoDB Enterprise > db.members.find( { "batchID" : 138,
"member.member_name" : "Joe Drumgoole" },
{ "_id" : 0, "member.chapters" : 0 } ).pretty()
{
"member" : {
"city" : "Dublin",
"events_attended" : 19,
"last_access_time" : ISODate("2017-04-25T12:40:55Z"),
"country" : "Ireland",
"member_id" : 99473492,
"is_organizer" : true,
"photo_thumb_url" : "https://secure.meetupstatic.com/photos/member/e/5/0/1/thumb_255178625.jpeg",
"location" : {
"type" : "Point",
"coordinates" : [
-6.25,
53.33000183105469
]
},
"member_name" : "Joe Drumgoole",
"join_time" : ISODate("2013-10-30T17:05:31Z")
},
"timestamp" : ISODate("2017-04-26T10:13:54.079Z"),
"batchID" : 138
}](https://image.slidesharecdn.com/02btbanalytics-1-170427141842/85/Beyond-the-Basics-2-Aggregation-Framework-11-320.jpg)
![14
Let’s Query for Groups
JD10Gen:apps jdrumgoole$ ./mug_analytics_main.py --stats groups --url mongodb-belgium DublinMUG
Processing : ['mongodb-belgium', 'DublinMUG']
pro
db.groups.aggregate( [
{"$match": {"batchID": 138, "group.urlname": {"$in": ["mongodb-belgium", "DublinMUG"]}}},
{"$project": {"founded": "$group.founded_date", "urlname": "$group.urlname", "_id": 0, "members":
"$group.member_count"}},
])
{'founded': '11-Sep-2013 14:05', 'members': 399, 'urlname': u'mongodb-belgium'}
{'founded': '14-Mar-2012 17:40', 'members': 847, 'urlname': u'DublinMUG'}
Wrote 2 records
JD10Gen:apps jdrumgoole$](https://image.slidesharecdn.com/02btbanalytics-1-170427141842/85/Beyond-the-Basics-2-Aggregation-Framework-14-320.jpg)
![16
Search for New Members
JD10Gen:apps jdrumgoole$ ./mug_analytics_main.py --stats newmembers --url DublinMUG --sort join_date --format
csv --direction ascending --limit 10
Processing : ['DublinMUG']
Sorting on 'join_date' direction = 'ascending'
db.members.aggregate([
{"$match": {"batchID": 138}},
{"$unwind": "$member.chapters"},
{"$match": {"member.chapters.urlname": {"$in": ["DublinMUG"]}}},
{"$project": {"join_date": "$member.join_time", "_id": 0, "group": "$member.chapters.urlname", "name":
"$member.member_name"}},
{"$limit": 10}])
group,name,join_date
DublinMUG,Gosia,17-Apr-2017 12:51
DublinMUG,Luke Shiels,15-Apr-2017 14:00
DublinMUG,Silvia Sirbu,11-Apr-2017 12:00
DublinMUG,Steeve P.,04-Apr-2017 09:47
DublinMUG,Dafei W,30-Mar-2017 11:36
DublinMUG,Ross Norman,13-Mar-2017 11:30
DublinMUG,Grzegorz F.,08-Mar-2017 10:25
DublinMUG,Lucas Sacramento,07-Mar-2017 11:05
DublinMUG,David Blount,06-Mar-2017 12:33
DublinMUG,Luca Ballerini,06-Mar-2017 10:41
Wrote 10 records
JD10Gen:apps jdrumgoole$](https://image.slidesharecdn.com/02btbanalytics-1-170427141842/85/Beyond-the-Basics-2-Aggregation-Framework-16-320.jpg)
![17
Search for New Members This Year
JD10Gen:apps jdrumgoole$ ./mug_analytics_main.py --stats newmembers --url DublinMUG --sort join_date --format csv --
direction ascending --limit 10 --start 1-Jan-2017
Processing : ['DublinMUG']
Sorting on 'join_date' direction = 'ascending'
db.members.aggregate([
{"$match": {"batchID": 138}},
{"$unwind": "$member.chapters"},
{"$match": {"member.chapters.urlname": {"$in": ["DublinMUG"]}}},
{"$match": {"member.join_time": {"$gte": "2017-01-01T00:00:00"}}},
{"$project": {"join_date": "$member.join_time", "_id": 0, "group": "$member.chapters.urlname", "name":
"$member.member_name"}},
{"$limit": 10}])
group,name,join_date
DublinMUG,Gosia,17-Apr-2017 12:51
DublinMUG,Luke Shiels,15-Apr-2017 14:00
DublinMUG,Silvia Sirbu,11-Apr-2017 12:00
DublinMUG,Steeve P.,04-Apr-2017 09:47
DublinMUG,Dafei W,30-Mar-2017 11:36
DublinMUG,Ross Norman,13-Mar-2017 11:30
DublinMUG,Grzegorz F.,08-Mar-2017 10:25
DublinMUG,Lucas Sacramento,07-Mar-2017 11:05
DublinMUG,David Blount,06-Mar-2017 12:33
DublinMUG,Luca Ballerini,06-Mar-2017 10:41
Wrote 10 records](https://image.slidesharecdn.com/02btbanalytics-1-170427141842/85/Beyond-the-Basics-2-Aggregation-Framework-17-320.jpg)
![18
Turn an Aggregation into a View
• Only supported on MongoDB 3.4
• Views are a non-materialised view on a collection
MongoDB Enterprise > db.createView( "batch138",
"members",
[ { "$match" : { "batchID" : 138 }} ] )
{ "ok" : 1 }
MongoDB Enterprise >
• A view persists and will return new results each time a find is run
• A view looks just like a collection
• Must turn 3.4 compatibility on
MongoDB Enterprise > db.adminCommand( { setFeatureCompatibilityVersion: "3.4"} )](https://image.slidesharecdn.com/02btbanalytics-1-170427141842/85/Beyond-the-Basics-2-Aggregation-Framework-18-320.jpg)
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Beyond the Basics 2: Aggregation Framework
- 2. Beyond The Basics : Part 2 Analytics and the Aggregation Framework Joe Drumgoole Director of Developer Advocacy, EMEA @jdrumgoole V1.1
- 3. 3 Beyond The Basics – Storage Engines • What storage engines are and how to pick them – Aggregation Framework • How to deploy advanced analytics processing right inside the database – The BI Connector • How to create visualisations and dashboards from your MongoDB data – Authentication and Authorisation • How to secure MongoDB, both on-premise and in the cloud
- 4. 4 The Aggregation Framework • An analytics engine for MongoDB • What is analytics? • Think of the two types of database, OLTP, OLAP • OLTP : Online Transaction Processing – Airline booking, – ATMs, – Taxi booking • OLAP : Online Analytical Processing – Which tickets make us most money? – When do we need to refill our ATMs? – How many cabs do we need to service the West End of London?
- 5. 5 OLTP – Online Transaction processing
- 6. 6 OLTP – Online Transaction processing sum() avg()
- 7. 7 The Aggregation Framework – A Processing Pipeline Match Project Group SortLimit • Think unix pipeline • The output of one stage is passed to the input of the next stage • Each stage performs one job • Stages can be repeated • Output is a cursor, a new collection or a view
- 8. 8 Typical Goals of Aggregation Framework • Columnar Analytics • Reshaping data • Unwinding arrays into individual documents • Linking collections together • Generating new data from old (collections and views)
- 9. 9 Pipeline Operators • $match Filter documents • $project Reshape documents • $group Summarize documents • $out Create new collections • $sort Order documents • $limit/$skip Paginate documents • $lookup Join two collections together • $unwind Expand an array
- 10. 10 Example Pipeline Match Project Group Sort Out • Find content • Standard query • Uses indexes • Reduce doc count • Use first • Select content • Remove fields • Add fields • Reduce doc size • Looks at every doc • Collect content • Sum, Avg etc. • Rewrite _id • Reduce doc count • Looks at every doc • Sort on fields • Several sorts allowed • Ascending or descending • 100mb limit • Allow Disk Use • New collection • $out overwrites • Only one per aggregate • Last member
- 11. 11 Example Document MongoDB Enterprise > db.members.find( { "batchID" : 138, "member.member_name" : "Joe Drumgoole" }, { "_id" : 0, "member.chapters" : 0 } ).pretty() { "member" : { "city" : "Dublin", "events_attended" : 19, "last_access_time" : ISODate("2017-04-25T12:40:55Z"), "country" : "Ireland", "member_id" : 99473492, "is_organizer" : true, "photo_thumb_url" : "https://secure.meetupstatic.com/photos/member/e/5/0/1/thumb_255178625.jpeg", "location" : { "type" : "Point", "coordinates" : [ -6.25, 53.33000183105469 ] }, "member_name" : "Joe Drumgoole", "join_time" : ISODate("2013-10-30T17:05:31Z") }, "timestamp" : ISODate("2017-04-26T10:13:54.079Z"), "batchID" : 138 }
- 12. 12 Meetup Data
- 13. 13 Group Document MongoDB Enterprise > db.groups.findOne({ "batchID": 138 }, { "group.photos" : 0, "group.topics" : 0, "group.location" : 0, "group.description" : 0, "group.organizers" : 0, "group.category" : 0, "_id" : 0 } ) { "batchID" : 138, "timestamp" : ISODate("2017-04-26T10:12:06.388Z"), "group" : { "rsvps_per_event" : 39.285701751708984, "repeat_rsvpers" : 62, "upcoming_events" : 0, "gender_female" : 0.039500001817941666, "pro_join_date" : ISODate("2017-04-10T18:11:49Z"), "id" : 10209022, "city" : "Gent", "member_count" : 399, "average_age" : 35.15570068359375, "status" : "Active", "founded_date" : ISODate("2013-09-11T14:05:30Z"), "urlname" : "mongodb-belgium", "gender_male" : 0.9473999738693237, "name" : "MongoDB Belgium", "last_event" : ISODate("2015-06-16T18:00:00Z"), "country" : "Belgium", "gender_unknown" : 0.013199999928474426, "past_events" : 7, "gender_other" : 0, "past_rsvps" : 275 } }
- 14. 14 Let’s Query for Groups JD10Gen:apps jdrumgoole$ ./mug_analytics_main.py --stats groups --url mongodb-belgium DublinMUG Processing : ['mongodb-belgium', 'DublinMUG'] pro db.groups.aggregate( [ {"$match": {"batchID": 138, "group.urlname": {"$in": ["mongodb-belgium", "DublinMUG"]}}}, {"$project": {"founded": "$group.founded_date", "urlname": "$group.urlname", "_id": 0, "members": "$group.member_count"}}, ]) {'founded': '11-Sep-2013 14:05', 'members': 399, 'urlname': u'mongodb-belgium'} {'founded': '14-Mar-2012 17:40', 'members': 847, 'urlname': u'DublinMUG'} Wrote 2 records JD10Gen:apps jdrumgoole$
- 15. 15 Attendee Doc MongoDB Enterprise > db.attendees.findOne( { "batchID" : 138 }, { "info.event.description" : 0, "_id" : 0, "info.event.group" : 0, "info.event.venue" : 0, "info.event.rating" : 0 } ) { "info" : { "attendee" : { "status" : "attended", "member" : { "name" : "Former member" }, "rsvp" : { "response" : "yes", } }, "event" : { "status" : "past", "event_url" : "https://www.meetup.com/mongodb-belgium/events/162104572/", "created" : ISODate("2014-01-23T09:10:20Z"), "rsvp_limit" : 75, "updated" : ISODate("2014-03-20T11:49:00Z"), "visibility" : "public", "yes_rsvp_count" : 75, "time" : ISODate("2014-03-18T18:00:00Z"), "headcount" : 0, "id" : "162104572", "name" : "MongoDB Belgium #1: the kickoff" } }, "timestamp" : ISODate("2017-04-26T10:14:30.129Z"), "batchID" : 138 }
- 16. 16 Search for New Members JD10Gen:apps jdrumgoole$ ./mug_analytics_main.py --stats newmembers --url DublinMUG --sort join_date --format csv --direction ascending --limit 10 Processing : ['DublinMUG'] Sorting on 'join_date' direction = 'ascending' db.members.aggregate([ {"$match": {"batchID": 138}}, {"$unwind": "$member.chapters"}, {"$match": {"member.chapters.urlname": {"$in": ["DublinMUG"]}}}, {"$project": {"join_date": "$member.join_time", "_id": 0, "group": "$member.chapters.urlname", "name": "$member.member_name"}}, {"$limit": 10}]) group,name,join_date DublinMUG,Gosia,17-Apr-2017 12:51 DublinMUG,Luke Shiels,15-Apr-2017 14:00 DublinMUG,Silvia Sirbu,11-Apr-2017 12:00 DublinMUG,Steeve P.,04-Apr-2017 09:47 DublinMUG,Dafei W,30-Mar-2017 11:36 DublinMUG,Ross Norman,13-Mar-2017 11:30 DublinMUG,Grzegorz F.,08-Mar-2017 10:25 DublinMUG,Lucas Sacramento,07-Mar-2017 11:05 DublinMUG,David Blount,06-Mar-2017 12:33 DublinMUG,Luca Ballerini,06-Mar-2017 10:41 Wrote 10 records JD10Gen:apps jdrumgoole$
- 17. 17 Search for New Members This Year JD10Gen:apps jdrumgoole$ ./mug_analytics_main.py --stats newmembers --url DublinMUG --sort join_date --format csv -- direction ascending --limit 10 --start 1-Jan-2017 Processing : ['DublinMUG'] Sorting on 'join_date' direction = 'ascending' db.members.aggregate([ {"$match": {"batchID": 138}}, {"$unwind": "$member.chapters"}, {"$match": {"member.chapters.urlname": {"$in": ["DublinMUG"]}}}, {"$match": {"member.join_time": {"$gte": "2017-01-01T00:00:00"}}}, {"$project": {"join_date": "$member.join_time", "_id": 0, "group": "$member.chapters.urlname", "name": "$member.member_name"}}, {"$limit": 10}]) group,name,join_date DublinMUG,Gosia,17-Apr-2017 12:51 DublinMUG,Luke Shiels,15-Apr-2017 14:00 DublinMUG,Silvia Sirbu,11-Apr-2017 12:00 DublinMUG,Steeve P.,04-Apr-2017 09:47 DublinMUG,Dafei W,30-Mar-2017 11:36 DublinMUG,Ross Norman,13-Mar-2017 11:30 DublinMUG,Grzegorz F.,08-Mar-2017 10:25 DublinMUG,Lucas Sacramento,07-Mar-2017 11:05 DublinMUG,David Blount,06-Mar-2017 12:33 DublinMUG,Luca Ballerini,06-Mar-2017 10:41 Wrote 10 records
- 18. 18 Turn an Aggregation into a View • Only supported on MongoDB 3.4 • Views are a non-materialised view on a collection MongoDB Enterprise > db.createView( "batch138", "members", [ { "$match" : { "batchID" : 138 }} ] ) { "ok" : 1 } MongoDB Enterprise > • A view persists and will return new results each time a find is run • A view looks just like a collection • Must turn 3.4 compatibility on MongoDB Enterprise > db.adminCommand( { setFeatureCompatibilityVersion: "3.4"} )
- 19. 19 Useful Links • The Aggregation Python class https://github.com/jdrumgoole/mongodb_utils/blob/master/mongodb_utils/agg.py • Aggregation docs https://docs.mongodb.com/manual/aggregation/ • MongoDB Views in 3.4 https://docs.mongodb.com/manual/core/views/
- 20. 20 Q&A