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Dataflow	with	
Apache	NiFi
Aldrin	Piri	- @aldrinpiri
Apache	NiFi Crash	Course
DataWorks Summit	2017	– Munich
6	April	2017
2 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
Key:	'Apache	NiFi’
Value:	'PMC	Member'
Key:	'Work’
Value:	’Sr.	Member	of	Technical	Staff	@	Hortonworks'
Key:	'Working	with	NiFi Since’
Value:	'2010’
3 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
Agenda
What	is	dataflow	and	what	are	the	challenges?
Apache	NiFi
Architecture
Live	Demo
Community
4 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
Agenda
What	is	dataflow	and	what	are	the	challenges?
Apache	NiFi
Architecture
Live	Demo
Community
5 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
Let’s	Connect	A	to	B
Producers	A.K.A	Things
Anything
AND	
Everything
Internet!
Consumers
• User
• Storage
• System
• …More	Things
6 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
Moving	data	effectively	is	hard
Standards:		http://xkcd.com/927/
7 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
Why	is	moving	data	effectively	hard?	
à Standards
à Formats
à “Exactly	Once”	Delivery
à Protocols
à Veracity	of	Information
à Validity	of	Information
à Ensuring	Security
à Overcoming	Security
à Compliance
à Schemas
à Consumers	Change
à Credential	Management
à “That [person|team|group]”
à Network
à “Exactly	Once”	Delivery
8 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
Let’s	Connect	Lots	of	As	to	Bs to	As	to	Cs	to	Bs to	Δs to	Cs	to	ϕs
Let’s	consider	the	needs	of	a	courier	service
Physical	Store
Gateway	
Server
Mobile	Devices
Registers
Server	Cluster
Distribution	Center Core	Data	Center	at	HQ
Server	Cluster
On	Delivery	Routes
Trucks Deliverers
Delivery	Truck:	Creative	Stall,	https://thenounproject.com/creativestall/
Deliverer:	Rigo Peter,	https://thenounproject.com/rigo/
Cash	Register:	Sergey	Patutin,	https://thenounproject.com/bdesign.by/
Hand	Scanner:	Eric	Pearson,	https://thenounproject.com/epearson001/
9 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
Great!	I	am	collecting	all	this	data!		Let’s	use	it!
Finding	our	needles	in	the	haystack
Physical	Store
Gateway	
Server
Mobile	Devices
Registers
Server	Cluster
Distribution	Center
Kafka
Core	Data	Center	at	HQ
Server	Cluster
Others
Storm	/	Spark	/	
Flink /	Apex
Kafka
Storm	/	Spark	/	Flink /	Apex
On	Delivery	Routes
Trucks Deliverers
Delivery	Truck:	Creative	Stall,	https://thenounproject.com/creativestall/
Deliverer:	Rigo Peter,	https://thenounproject.com/rigo/
Cash	Register:	Sergey	Patutin,	https://thenounproject.com/bdesign.by/
Hand	Scanner:	Eric	Pearson,	https://thenounproject.com/epearson001/
10 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
Why	is	moving	data	effectively	hard	when	scoped	internally?	
à Standards
à Formats
à “Exactly	Once”	Delivery
à Protocols
à Veracity	of	Information
à Validity	of	Information
à Ensuring	Security
à Overcoming	Security
à Compliance
à Schemas
à Consumers	Change
à Credential	Management
à “That [person|team|group]”
à Network
à “Exactly	Once”	Delivery
11 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
Let’s	Connect	Lots	of	As	to	Bs to	As	to	Cs	to	Bs to	Δs to	Cs	to	ϕs
Oh,	that	courier	service	is	global
12 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
Why	is	moving	data	effectively	hard	when	scoped	globally?	
à Standards
à Formats
à “Exactly	Once”	Delivery
à Protocols
à Veracity	of	Information
à Validity	of	Information
à Ensuring	Security
à Overcoming	Security
à Compliance
à Schemas
à Consumers	Change
à Credential	Management
à “That [person|team|group]”
à Network
à “Exactly	Once”	Delivery
13 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
The	Unassuming	Line:		A	Case	Study
We’ve	seen	a	few	lines	show	up	in	the	wild	thus	far
Internet! Inter- &	Intra- connections	in
our	global	courier	enterprise
Spotlight:	Arthur	Lacôte,	https://thenounproject.com/turo/
14 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
Dataflow	Line	Anatomy	101
Let’s	dissect	what	this	line	typically	represents
Fig	1.		Lineus Worldwidewebus.	Common	Name:	Internet!
Script	or	
Application
Script	or	
Application
Data Data
Disparate	Transport
Mechanisms
15 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
Dataflow	Line	Anatomy	201
Sometimes	that	transport	is	just	more	lines
Fig	1.		Lineus Worldwidewebus.	Common	Name:	Internet!
Script	or	
Application
Script	or	
Application
Line	Inception
Data Data
16 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
Dataflow	Line	Anatomy	301
But	those	lines	could	also	have	components…
Fig	1.		Lineus Worldwidewebus.	Common	Name:	Internet!
17 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
Agenda
What	is	dataflow	and	what	are	the	challenges?
Apache	NiFi
Architecture
Live	Demo
Community
18 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
Apache	NiFi
Key	Features
• Guaranteed	delivery
• Data	buffering	
- Backpressure
- Pressure	release
• Prioritized	queuing
• Flow	specific	QoS
- Latency	vs.	throughput
- Loss	tolerance
• Data	provenance
• Supports	push	and	pull	
models
• Recovery/recording	
a	rolling	log	of	fine-
grained	history
• Visual	command	and	
control
• Flow	templates
• Pluggable/multi-role	
security
• Designed	for	extension
• Clustering
19 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
Apache	NiFi Subproject:	MiNiFi
à Let	me	get	the	key	parts	of	NiFi close	to	where	data	begins	and	provide	bidrectional
communication
à NiFi lives	in	the	data	center.		Give	it	an	enterprise	server	or	a	cluster	of	them.
à MiNiFi lives	as	close	to	where	data	is	born	and	is	a	guest	on	that	device	or	system
20 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
Let’s	revisit	our	courier	service	from	the	perspective	of	NiFi
Physical	Store
Gateway	
Server
Mobile	Devices
Registers
Server	Cluster
Distribution	Center
Kafka
Core	Data	Center	at	HQ
Server	Cluster
Others
Storm	/	Spark	/	
Flink /	Apex
Kafka
Storm	/	Spark	/	Flink /	Apex
On	Delivery	Routes
Trucks Deliverers
Delivery	Truck:	Creative	Stall,	https://thenounproject.com/creativestall/
Deliverer:	Rigo Peter,	https://thenounproject.com/rigo/
Cash	Register:	Sergey	Patutin,	https://thenounproject.com/bdesign.by/
Hand	Scanner:	Eric	Pearson,	https://thenounproject.com/epearson001/
Client	
Libraries
Client	
Libraries
MiNiFi
MiNiFi
NiFi NiFi NiFi NiFi NiFi NiFi
Client	
Libraries
21 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
Apache	NiFi Managed	Dataflow
SOURCES
REGIONAL	
INFRASTRUCTURE
CORE	
INFRASTRUCTURE
22 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
NiFi is	based	on	Flow	Based	Programming	(FBP)
FBP	Term NiFi Term Description
Information	
Packet
FlowFile Each object	moving	through	the	system.
Black Box FlowFile	
Processor
Performs	the	work, doing	some	combination	of	data	routing,	transformation,	
or	mediation	between	systems.
Bounded	
Buffer
Connection The	linkage between	processors, acting	as	queues	and	allowing	various	
processes	to	interact	at	differing	rates.
Scheduler Flow	
Controller
Maintains	the	knowledge	of	how	processes	are	connected, and	manages	the	
threads	and	allocations	thereof	which	all	processes	use.
Subnet Process	
Group
A	set	of	processes	and	their	connections,	which	can	receive	and	send	data	via	
ports.	A	process group	allows	creation	of	entirely	new	component	simply	by	
composition	of	its components.
23 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
FlowFiles &	Data	Agnosticism
à NiFi is	data	agnostic!
à But,	NiFi was	designed	understanding	that	users
can	care	about	specifics	and	provides	tooling	
to	interact	with	specific	formats,	protocols,	etc.
ISO	8601	- http://xkcd.com/1179/
Robustness	principle
Be	conservative	in	what	you	do,	
be	liberal	in	what	you	accept	from	others“
24 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
FlowFiles are	like	HTTP	data
HTTP	Data FlowFile
HTTP/1.1	200	OK
Date:	Sun,	10	Oct	2010	23:26:07	GMT
Server:	Apache/2.2.8	(CentOS)	OpenSSL/0.9.8g
Last-Modified:	Sun,	26	Sep	2010	22:04:35	GMT
ETag:	"45b6-834-49130cc1182c0"
Accept-Ranges:	bytes
Content-Length:	13
Connection:	close
Content-Type:	text/html
Hello	world!
Standard	FlowFile Attributes
Key:	'entryDate’ Value:	'Fri	Jun	17	17:15:04	EDT	2016'
Key:	'lineageStartDate’			Value:	'Fri	Jun	17	17:15:04	EDT	2016'
Key:	'fileSize’ Value:	'23609'
FlowFile Attribute	Map	Content
Key:	'filename’ Value:	'15650246997242'
Key:	'path’ Value:	'./’
Binary	Content	*
Header
Content
25 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
Agenda
What	is	dataflow	and	what	are	the	challenges?
Apache	NiFi
Architecture
Live	Demo
Community
26 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
Extension	/	Integration	Points
NiFi Term Description
Flow File	
Processor
Push/Pull behavior.		Custom	UI
Reporting
Task
Used to	push	data	from	NiFi to	some	external	service	(metrics,	provenance,	
etc..)
Controller	
Service
Used	to	enable	reusable	components	/ shared	services	throughout	the	flow
REST	API Allows	clients	to	connect	to	pull	information,	change	behavior,	etc..
©	Hortonworks	Inc.	2011	–	2016.	All	Rights	ReservedX
Architecture
OS/Host
JVM
Flow	Controller
Web	Server
Processor	1 Extension	N
FlowFile

Repository
Content

Repository
Provenance

Repository
Local	Storage
Standalone
Cluster
27 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
NiFi	Architecture	– Repositories	- Pass	by	reference
FlowFile Content Provenance
F1à C1 C1 P1à F1
Excerpt	of	demo	flow… What’s	happening	inside	the	repositories…
BEFORE
AFTER
F2à C1 C1 P3à F2 – Clone	(F1)
F1à C1 P2à F1 – Route	
P1à F1 – Create
28 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
NiFi	Architecture	– Repositories	– Copy	on	Write
FlowFile Content Provenance
F1à C1 C1 P1à F1	- CREATE
Excerpt	of	demo	flow… What’s	happening	inside	the	repositories…
BEFORE
AFTER
F1à C1
F1.1à C2 C2	(encrypted)
C1	(plaintext)
P2à F1.1 - MODIFY
P1à F1	- CREATE
29 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
Agenda
What	is	dataflow	and	what	are	the	challenges?
Apache	NiFi
Architecture
Demo
Community
30 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
Learn,	Share	at	Birds	of	a	Feather
IOT,	STREAMING	&	DATA	FLOW
Thursday,	April	6
5:50	pm,	Room	5
31 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
Why	NiFi?
à Moving	data	is	multifaceted	in	its	challenges	and	these	are	present	in	different	contexts	
at	varying	scopes
– Think	of	our	courier	example	and	organizations	like	it:	inter	vs intra,	domestically,	internationally
à Provide	common	tooling	and	extensions	that	are	commonly	needed	but	be	flexible	for	
extension
– Leverage	existing	libraries	and	expansive	Java	ecosystem	for	functionality
– Allow	organizations	to	integrate	with	their	existing	infrastructure	
à Empower	folks	managing	your	infrastructure	to	make	changes	and	reason	about	issues	
that	are	occurring
– Data	Provenance	to	show	context	and	data’s	journey
– User	Interface/Experience	a	key	component
32 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
Learn	more	and	join	us!
Apache NiFi site
http://nifi.apache.org
Subproject MiNiFi site
http://nifi.apache.org/minifi/
Subscribe to and collaborate at
dev@nifi.apache.org
users@nifi.apache.org
Submit Ideas or Issues
https://issues.apache.org/jira/browse/NIFI
Follow us on Twitter
@apachenifi
33 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
Our	Lab	for	Today
à We	will	be	exploring	some	examples	to	work	through	creating	a	dataflow	with	Apache	
NiFi
à Use	Case:			An	urban	planning	board	is	evaluating	the	need	for	a	new	highway,	
dependent	on	current	traffic	patterns,	particularly	as	other	roadwork	initiatives	are	
under	way.	Integrating	live	data	poses	a	problem	because	traffic	analysis	has	
traditionally	been	done	using	historical,	aggregated	traffic	counts.	To	improve	traffic	
analysis,	the	city	planner	wants	to	leverage	real-time	data	to	get	a	deeper	understanding	
of	traffic	patterns.	NiFi was	selected	for	for	this	real-time	data	integration.
à Labs	are	available	at	http://tinyurl.com/nificrashcourse
34 ©	Hortonworks	Inc.	2011	– 2016.	All	Rights	Reserved
Thank	You

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