2012 09 GDG San Francisco Hackday at Parisoma

#neo4j

The Neo4j Election
Data @GDG SF

Andreas Kollegger Peter Neubauer Michael Hunger
@akollegger @peterneubauer @mesirii
1

Saturday, September 29, 12

#neo4j

1


#neo4j

Follow the Data
FEC Campaign Data
Andreas Kollegger Peter Neubauer Michael Hunger
@akollegger @peterneubauer @mesirii
2


#neo4j

2


Follow the Plan

4


Follow the Plan
1.Graph Database Primer

4


Follow the Plan

1.Why graphs?

4


Follow the Plan

1.Why graphs?

2.What's a graph database?

4


Follow the Plan

1.Why graphs?


2.FEC Campaign Data

4


Follow the Plan

1.Why graphs?


2.FEC Campaign Data

1.Data Model

4


Follow the Plan

1.Why graphs?


2.FEC Campaign Data

1.Data Model

2.Import Strategy

4


Follow the Plan

1.Why graphs?


2.FEC Campaign Data

1.Data Model

2.Import Strategy

3.Queries
4


Follow the Plan - Part 2

5


1. Intro to Google Apps Script by Alex

5



2. Register at Heroku and install the heroku gem

5




3. Create and install a Heroku app (heroku apps:create)

5





4. Add a Neo4j addon instance to it (heroku addons:add neo4j)

5






5. Upload existing data to the graph

5







6. Create a custom Ruby proxy app on Heroku

5








7. Connect to the app using a Google Spreadsheet

5








7. Connect to the app using a Google Spreadsheet

8. Build a small bar chart from a Cypher query

5


Graph Database
Primer

6


Why graphs, why now?

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A Graph?

8


A Graph?
Yes, a graph

8


A graph database...

9


A graph database...

๏ no: not for charts & diagrams, or vector artwork

9


A graph database...

๏ yes: for storing data that is structured as a graph

9


A graph database...

•remember linked lists, trees?

9


A graph database...

•graphs are the general-purpose data structure

9


A graph database...

•graphs are the general-purpose data structure
๏ “A relational database may tell you
the average age of everyone in the USA,
but a graph database will tell you
who is most likely to buy you a beer.”

9


A Graph Database

10


11


You know relational

11


You know relational

foo

11


You know relational

foo bar

11


You know relational

foo foo_bar bar

11


You know relational
now consider relationships...

11


12


We're talking about a
Property Graph

12


Property Graph

Nodes

12


Property Graph

Nodes

Relationships

12


Property Graph
Em Joh
il a n
knows knows
Alli Tob Lar

Nodes
son ias knows s
knows
And And knows
knows rea rés
s
knows knows knows
Pet Miic
Mc knows Ian
er knows a
a
knows knows
De Mic
lia h ael

Relationships

Properties (each a key+value)

+ Indexes (for easy look-ups)
12


13


And, but, so how do you
query this "graph" database?

13


14


Cypher - a graph query language
๏ a pattern-matching query language
๏ declarative grammar with clauses (like SQL)
๏ aggregation, ordering, limits
๏ create, read, update, delete

14


Cypher - a graph query language
๏ a pattern-matching query language
๏ declarative grammar with clauses (like SQL)
๏ aggregation, ordering, limits
๏ create, read, update, delete

// get node 1, traverse 2 steps away
start a=node(1) match (a)--()--(c) return c

// create a node with a 'name' property
CREATE (me {name: 'Andreas'}) return me

๏ more on this later...
14


Cypher - pattern matching

15


Cypher - pattern matching syntax

16



() --> ()

16



17



A B

17



A B

(A) --> (B)

17



18



A B

18



A B

(A) -- (B)

18



19



LOVES
A B

19



LOVES
A B

A -[:LOVES]-> B

19



20



A B C

20



A B C

A --> B --> C

20



21



A

B C

21



A

B C

A --> B --> C, A --> C

21



A

B C

A --> B --> C, A --> C
A --> B --> C <-- A
21


22


Cypher - common clauses

22


Cypher - common clauses
// get node 1, traverse 2 steps away
START a=node(1) MATCH (a)--()--(c) RETURN c

// get node from an index, return it
START a=node:people(name='Andreas')
RETURN a

// get node from an index, match, filter
// with where, then return results
START a=node:people(name='Andreas')
MATCH (a)-[r]-(b) WHERE b.last='Sparrow'
RETURN r,b

22


FEC Campaign Data

23


FEC Campaign Data

yeah, this is the good stuff..
23


and now, it's time for

FEC Campaign Data

yeah, this is the good stuff..
23


FEC Campaign Data
๏In 1975, Congress created the Federal Election
Commission (FEC) to administer and enforce the
Federal Election Campaign Act (FECA) – The statute
that governs the ﬁnancing of federal elections.

๏The duties of the FEC, which is an independent
regulatory agency, are to disclose campaign ﬁnance
information

24


FEC Campaign Data
๏Detailed ﬁles about...
• Candidates Committee Candidate

• Committees
• Individual Contributions Individual Contributions

๏10 years of data
๏Updated every Sunday

25


FEC Campaign Data - Committees
๏Committees
• one record for each committee registered with the
Federal Election Commission.

Committee - cm12.txt
CMTE_ID: String
CMTE_NM: String
TRES_NM: String
CMTE_ST1: String
CMTE_ST2: String
CMTE_CITY: String
CMTE_ST: String
CMTE_ZIP: String
CMTE_DSGN: String
CMTE_TP: String
CMTE_PTY_AFFILIATION: String
CMTE_FILING_FREQ: String
ORG_TP: String
CONNECTED_ORG_NM: String
CAND_ID: String

26


FEC Campaign Data
๏Candidates
• one record for each candidateappeared on a ballot
registered with the FEC or
who has either

list prepared by a state elections ofﬁce.

Candidate - cn12.txt
CAND_ID: String
CAND_NAME: String
CAND_PTY_AFFILIATION: String
CAND_ELECTION_YR: String
CAND_OFFICE_ST: String
CAND_OFFICE: String
CAND_OFFICE_DISTRICT: String
CAND_ICI: String
CAND_STATUS: String
CAND_PCC: String
CAND_ST1: String
CAND_ST2: String
CAND_CITY: String
CAND_ST: String
CAND_ZIP: String

27


FEC Campaign Data
๏Individual Contributions
• each contribution from an individual to least $200.
committee if the contribution was at
a federal

Individual Contrib - itcont.txt
CMTE_ID: String
AMNDT_IND: String
RPT_TP: String
TRANSACTION_PGI: String
IMAGE_NUM: String
TRANSACTION_TP: String
ENTITY_TP: String
NAME: String
CITY: String
STATE: String
ZIP_CODE: String
EMPLOYER: String
OCCUPATION: String
TRANSACTION_DT: String
TRANSACTION_AMT: Double
OTHER_ID: String
TRAN_ID: String
FILE_NUM: Integer
MEMO_CD: String
MEMO_TEXT: String
SUB_ID: Integer

28


FEC Campaign Data - Extra Records
๏Candidate to Committee Linkage
• registered candidate to committee linkage

๏Transactions between Committees
• inter-committee contribution or independent
expenditure during the two-year election cycle

๏Contribution to Candidate
• contribution or independent expenditure from
committee to candidate during the two-year
election cycle 29


Import Strategy

30


Raw Data Import

Committee Candidate

Candidate to Committee

Inter Committee Contributions

Candidate Contributions

Individual Contributions

31


Raw Data Import

Committee Candidate
CMTE_ID CAND_ID

Candidate to Committee
CMTE_ID CAND_ID

CMTE_ID

CAND_ID

CMTE_ID

31


Connected Data Import

32


Connected Data Import

Committee CAND_ID Candidate

CMTE_ID Candidate to Committee CAND_ID

OTHER_ID:CAND_ID
(from)
CMTE_ID

OTHER_ID:CMTE_ID
(from) CAND_ID

CMTE_ID

OTHER_ID:CAND_ID
CMTE_ID (from)
(to) Individual Contributions

OTHER_ID:CMTE_ID
(from)
32


Related Data Import

33


Related Data Import

Committee CAMPAIGNS_FOR Candidate

SUPPORTS

INTER_COMMITTEE_CONTRIBUTION


CANDIDATE_CONTRIBUTION

INDIVIDUAL_CONTRIBUTION
EARMARKED_BY


EARMARKED_BY

33


Related Data Import

Committee CAMPAIGNS_FOR Candidate

SUPPORTS

Committee INTER_COMMITTEE_CONTRIBUTION Candidate


CANDIDATE_CONTRIBUTION

INDIVIDUAL_CONTRIBUTION
EARMARKED_BY


EARMARKED_BY

33


Dave Fauth's Approach

34


Advanced Import - Dave Fauth
๏ includes SuperPAC data
๏ custom transform, then import
๏ model then looks like this...
Expenditures

Committee SUPPORTS Candidate

FUNDS
superPac
Contributions Contribution

GIVES

Individual
35


๏ Extract and Transform
• Stored ﬁles on S3
• Used MortarData to run Hadoop jobs to prepare data
(@MortarData)
๏ Load
• Used Neo4J BatchInserter to load
• Thanks to Michael Hunger (@mesirii)
• Loaded 2M+ nodes in <5 minutes

36



Java BatchInsert

Download Use S3
data Storage
Process with
Hadoop/Pig

Created Neo4J
DB

37


Wanna learn more?

๏Come hear Dave Fauth
present at...

38


Next...
Your Turn

39


From scratch
๏ git clone https://github.com/akollegger/FEC_GRAPH.git
๏ cd FEC_GRAPH
๏ ant initialize
• (need Apache ant? install from http://ant.apache.org)
๏ ant
• ant will build the importers and create a script
๏ ./bin/fec2graph --force --importer=RELATED
๏ ant neo4j-start
• will download and unpack neo4j, then start it
40


Investigate with Neo4j's Web UI

๏open http://localhost:7474
๏Dashboard - overview of data records
๏Data browser - examine data records, with
visualization options
๏Console - query the database using Cypher

41


Querying FEC with Cypher
๏ For Cypher documentation
• http://docs.neo4j.org/
๏ FEC Data Deﬁnitions
• http://www.fec.gov/ﬁnance/disclosure/ftpdet.shtml
๏ Ready for a challenge?

42


http://1.usa.gov/uIGzZ 43


Cypher Challenges



Cypher Challenges
// All presidential candidates for 2012

// Top 10 Presidential candidates according to number of
campaign committees

// find President Barack Obama

// lookup Obama by his candidate ID

// find Presidential Candidate Mitt Romney

// lookup Romney by his candidate ID

// find the shortest path of funding between Obama and Romney

// 10 top individual contributions to Obama

// 10 top individual contributions to Romney



44


Cypher Challenges

44


Cypher Challenges

// All presidential candidates for 2012
start candidate=node:candidates('CAND_ID:*')
where candidate.CAND_OFFICE='P' AND
candidate.CAND_ELECTION_YR='2012'
return candidate.CAND_NAME;

// Top 10 Presidential candidates according to
// number of campaign committees
start candidate=node:candidates('CAND_ID:*')
match candidate<-[r:SUPPORTS]-(campaign)
where candidate.CAND_OFFICE='P' AND
candidate.CAND_ELECTION_YR='2012'
return candidate.CAND_NAME, COUNT(campaign) as count
ORDER BY count desc LIMIT 10;

// find President Barack Obama
start obama=node:candidates('CAND_ID:*')
WHERE obama.CAND_NAME =~ '.*OBAMA.*'
return obama.CAND_NAME, obama.CAND_ID;

44


45


Cypher Challenges

45


Cypher Challenges
// lookup Obama by his candidate ID
start obama=node:candidates(CAND_ID='P80003338') return obama;

// find Presidential Candidate Mitt Romney
start romney=node:candidates('CAND_ID:*')
WHERE romney.CAND_NAME =~ '.*ROMNEY.*'
return romney.CAND_NAME, romney.CAND_ID;

// lookup Romney by his candidate ID
start romney=node:candidates(CAND_ID='P80003353')
return romney;

// find the shortest path of funding between Obama and Romney
start romney=node:candidates(CAND_ID='P80003353'),
obama=node:candidates(CAND_ID='P80003338') MATCH
p=shortestPath(romney-[*..10]-obama) return p;

45


46


Cypher Challenges

46


Cypher Challenges
// 10 top individual contributions to Obama
start obama=node:candidates(CAND_ID='P80003338') match obama<-
[:SUPPORTS]-(campaign)<-[:INDIVIDUAL_CONTRIBUTION]-
(contribution) return contribution.NAME,
contribution.TRANSACTION_AMT order by
contribution.TRANSACTION_AMT desc limit 10;

// 10 top individual contributions to Romney
start romney=node:candidates(CAND_ID='P80003353') match
romney<-[:SUPPORTS]-(campaign)<-[:INDIVIDUAL_CONTRIBUTION]-
(contribution) return contribution.NAME,
contribution.TRANSACTION_AMT order by
contribution.TRANSACTION_AMT desc limit 10;

46


Customize the Data Importer
๏Java-savvy and feeling brave?
๏make a copy of
• CODE/fecGraph/src/importer/fec/RelatedFecImporter.java
๏add your class to
• CODE/fecGraph/src/importer/Tool.java
๏read docs about batch insertion
• http://docs.neo4j.org/chunked/milestone/batchinsert.html

๏Ideas:
• extract States and Zip Codes into "location index"
• extract individual contributors from contribution list 47


#neo4j

48


#neo4j

Let's have some Fun!
:)

48


#neo4j

Neo4j Google

REST Cypher

Ruby

Heroku

49


Follow the Plan - Part 2 #neo4j

Neo4j Google

REST Cypher

Ruby

Heroku

49


50




3. Add a Neo4j addon (http://addons.heroku.com/neo4j)
instance to it (heroku addons:add neo4j)

50





4. Create a custom Ruby app (code below, GitHub) https://
github.com/neo4j-examples/heroku-neo4j-proxy

50






5. Upload the data from example-data.neo4j.org

50







6. Connect to the app using a Google Spreadsheet , http://
bit.ly/GDG-GCALC

50







6. Connect to the app using a Google Spreadsheet , http://
bit.ly/GDG-GCALC

7. Build a small bar chart from a Cypher query

50


Heroku Challenges



Heroku Challenges
//Point the Database Instance to FEC http://bit.ly/SmkwUx/db/
data

// Build a Google Data table endpoint

// https://developers.google.com/chart/interactive/docs/
php_example



The Heroku Neo4j proxy App

52


The Heroku Neo4j proxy App

> gem install heroku
> git add github git@github.com:neo4j-examples/heroku-neo4j-
proxy.git
> heroku apps:create <app-name>
> heroku addons:add neo4j
> //add the project files
> git add *; git commit -m"neo4j demo"
> git push heroku master

52


The Google Spreadsheet Cypher driver

https://docs.google.com/spreadsheet/ccc?
key=0AsSBFHSo5OaPdGhzT1RTbDVaR0R3NW5iNUFpejVuSHc#gid=0 53


The Google Spreadsheet Cypher driver

function cypherUrlREST(payload, url, user, pwd) {
var auth = Utilities.base64Encode(user+":"+pwd);
var response = UrlFetchApp.fetch(
url,
{"method":"POST",
"payload": payload,
"contentType": "application/json",
"headers":{
"Authorization":"Basic "+auth,
"accept":"application/json",
}
});
return response.getContentText();
}

https://docs.google.com/spreadsheet/ccc?
key=0AsSBFHSo5OaPdGhzT1RTbDVaR0R3NW5iNUFpejVuSHc#gid=0 53


Google Challenges



Google Challenges
// Build a cypher parser in GoogleAppsScript

// Build a Cypher query Google Widget

// Visualize Cypher Results with Google Data Table

// Geographic data viz



The heatmap from Cypher to Google

55


Wanna learn more?

56


2012 09 GDG San Francisco Hackday at Parisoma

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2012 09 GDG San Francisco Hackday at Parisoma