https://www.meetup.com/new-york-city-apache-pulsar-meetup/events/283837865/ Learn how to use Apache Pulsar and Apache NiFi to Stream to your Data Lake Discover how to stream data to and from your data lake or data mart using Apache Pulsar™ and Apache NiFi®. Learn how these cloud-native, scalable open-source projects built for streaming data pipelines work together to enable you to quickly build applications with minimal coding. |WHAT THE SESSION WILL COVER| Best Practices for using Pulsar and NiFi A deep dive on Apache NiFi's Pulsar connector and demos Building an End-to-End Application in the Hybrid Cloud Attend for a chance to win a We <3 Pulsar t-shirt! The first 50 registrants who register through here [https://hubs.ly/Q013LTpn0] will be entered in a drawing! —------------------------ |AGENDA| 6:00 - 7:00 PM EST: Presentation - Tim Spann, StreamNative Developer Advocate 7:00 - 8:00 PM EST: Presentation - John Kuchmek, Cloudera Principal Solutions Engineer 8:00 - 8:30 PM EST: Q&A + Networking —------------------------ |ABOUT THE SPEAKERS| John Kuchmek is a Principal Solutions Engineer for Cloudera. Before joining Cloudera, John transitioned to the Autonomous Intelligence team where he was in charge of integrating the platforms to allow data scientists to work with various types of data. Tim Spann is a Developer Advocate for StreamNative. He works with StreamNative Cloud, Apache Pulsar™, Apache Flink®, Flink® SQL, Big Data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, messaging, streaming technologies, and Java programming. Previously, he was a Principal DataFlow Field Engineer at Cloudera, a Senior Solutions Engineer at Hortonworks, a Senior Solutions Architect at AirisData, a Senior Field Engineer at Pivotal and a Team Leader at HPE. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on Big Data, Cloud, IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as ApacheCon, DeveloperWeek, Pulsar Summit and many more. He holds a BS and MS in computer science. He is currently working on a book about the FLiP Stack.

1. Welcome to
Apache Pulsar and Apache NiFi
for Cloud Data Lakes
In the meantime:
● (1) Use the chat to let us know
where you’re calling in from
● (2) Take part in our our poll, under
the booth “poll” tab in the right
panel of Hopin
We’ll start in 5min we’re just waiting for
People to sign in

3. Agenda
01
02
03
04
05
Intro to Apache Pulsar - Tim Spann
Intro to Apache NiFi - John Kuchmek
Demo
Key Takeaways + Resources
Additional Q&A

4. Tim Spann
Developer Advocate
● FLiP(N) Stack = Flink, Pulsar and NiFi Combined
● Streaming Systems & Data Architecture Expert
● Pulsar, Flink, Spark, NiFi, Big Data, Cloud, MXNet,
IoT, Java, Python, Sensors and more.
Tim Spann
Developer Advocate
StreamNative

5. Tim Spann
Developer Advocate
● Integration of OT & IT Data
● Cloudera Streaming SME
● NiFi, Spark, Flink, Kafka, Storm, Druid, Kudu,
Python, Sensors, PLCs, Private Cloud and Public
Cloud
John Kuchmek
Principal Solutions Engineer
Cloudera

6. Apache Pulsar is a Cloud-Native
Messaging and Event-Streaming Platform.

7. Why Apache Pulsar?
Unified
Messaging Platform
Guaranteed
Message Delivery Resiliency Infinite
Scalability

8. Component Description
Value / data payload The data carried by the message. All Pulsar messages contain raw bytes, although
message data can also conform to data schemas.
Key Messages are optionally tagged with keys, used in partitioning and also is useful for
things like topic compaction.
Properties An optional key/value map of user-defined properties.
Producer name The name of the producer who produces the message. If you do not specify a producer
name, the default name is used. Message De-Duplication.
Sequence ID Each Pulsar message belongs to an ordered sequence on its topic. The sequence ID of
the message is its order in that sequence. Message De-Duplication.
Messages - the basic unit of Pulsar

9. Connectivity
• Libraries - (Java, Python, Go, NodeJS, WebSockets,
C++, C#, Scala, Rust,...)
• Functions - Lightweight Stream Processing (Java,
Python, Go)
• Connectors - Sources & Sinks (Cassandra, Kafka, …)
• Protocol Handlers - AoP (AMQP), KoP (Kafka), MoP
(MQTT)
• Processing Engines - Flink, Spark, Presto/Trino via
Pulsar SQL, NiFi
• Data Offloaders - Tiered Storage - (S3)
hub.streamnative.io

10. Apache NiFi Pulsar Connector
https://github.com/streamnative/pulsar-nifi-bundle

11. Apache NiFi is a GUI based Data Flow
tool that runs anywhere.

12. Why NiFi
• Enable easy ingestion, routing, management and delivery of any data anywhere (Edge,
cloud, data center) to any downstream system with built in end-to-end security and
provenance
ACQUIRE PROCESS DELIVER
• Over 350 Prebuilt Processors
• Easy to build your own
• Parse, Enrich & Apply Schema
• Filter, Split, Merger & Route
• Throttle & Backpressure
• Guaranteed Delivery
• Full data provenance
• Eco-system integration
Advanced tooling to industrialize flow development
(Flow Development Life Cycle)
FTP
SFTP
HL7
UDP
XML
HTTP
EMAIL
HTML
IMAGE
SYSLOG
FTP
SFTP
HL7
UDP
XML
HTTP
EMAIL
HTML
IMAGE
SYSLOG
HASH
MERGE
EXTRACT
DUPLICATE
SPLIT
ROUTE TEXT
ROUTE CONTENT
ROUTE CONTEXT
CONTROL RATE
DISTRIBUTE LOAD
GEOENRICH
SCAN
REPLACE
TRANSLATE
CONVERT
ENCRYPT
TALL
EVALUATE
EXECUTE

13. Apache NiFi Capabilities
Data Ingest Data Transformation Data Enrichment
HTTP
Syslog
HL7
UDP
SFTP
MQTT
WS
Hash
Compress
Merge
Duplicate
Split
Encrypt
Syslog
REST
Mapcach
Enrich IP
GeoIP
XML

14. Flow Development Lifecycle

15. FLiP Stack Weekly
This week in Apache Flink, Apache Pulsar, Apache
NiFi, Apache Spark and open source friends.
https://bit.ly/32dAJft

16. Demo

17. Streaming NFTs
NFTs
NFT
Thermal
Aggregates
Status
APIs
CRYPTO
FEEDS
Weather
NFT++

18. Streaming NFTs
https://opensea.io/collection/tspannhw-collection

19. Key Takeaways
● Real-time ingest and data manipulation
● Easy to use/configure processors and
controller services
● Multiple ways to connect

20. Resources
Learn More about Nifi + Pulsar Integration
https://streamnative.io/apache-nifi-connector/
Github
https://github.com/tspannhw/awesome-nifi-pulsar
Blogpost on Apache Pulsar + Nifi Integration
https://hubs.ly/Q015PNMd0

21. ● StreamNative: Pulsar-as-a-Service
● AWS Certified Associate Solutions
Architect
● Reach me at doug@streamnative.io
Doug Cohen
Head of Sales, StreamNative
Additional
Resources

22. Let’s Keep
in Touch!
Tim Spann
Developer Advocate
@PaaSDev
linkedin.com/in/timo
thyspann
github.com/tspannhw
John Kuchmek
Principal
Solutions Engineer
@K_Physics
linkedin.com/in/jkuch
mek
github.com/johnkuch

23. Pulsar Subscription Modes
Different subscription modes
have different semantics:
Exclusive/Failover - guaranteed
order, single active consumer
Shared - multiple active
consumers, no order
Key_Shared - multiple active
consumers, order for given key
Producer 1
Producer 2
Pulsar Topic
Subscription D
Consumer D-1
Consumer D-2
Key-Shared
<
K
1,
V
10
>
<
K
1,
V
11
>
<
K
1,
V
12
>
<
K
2
,V
2
0
>
<
K
2
,V
2
1>
<
K
2
,V
2
2
>
Subscription C
Consumer C-1
Consumer C-2
Shared
<
K
1,
V
10
>
<
K
2,
V
21
>
<
K
1,
V
12
>
<
K
2
,V
2
0
>
<
K
1,
V
11
>
<
K
2
,V
2
2
>
Subscription A Consumer A
Exclusive
Subscription B
Consumer B-1
Consumer B-2
In case of failure in
Consumer B-1
Failover

24. Schema Registry
Schema Registry
schema-1 (value=Avro/Protobuf/JSON) schema-2 (value=Avro/Protobuf/JSON) schema-3
(value=Avro/Protobuf/JSON)
Schema
Data
ID
Local Cache
for Schemas
+
Schema
Data
ID +
Local Cache
for Schemas
Send schema-1
(value=Avro/Protobuf/JSON) data
serialized per schema ID
Send (register)
schema (if not in
local cache)
Read schema-1
(value=Avro/Protobuf/JSON) data
deserialized per schema ID
Get schema by ID (if
not in local cache)
Producers Consumers

25. ● Buffer
● Batch
● Route
● Filter
● Aggregate
● Enrich
● Replicate
● Dedupe
● Decouple
● Distribute

26. Messaging
Ideal for work queues that do not
require tasks to be performed in a
particular order—for example, sending
one email message to many recipients.
RabbitMQ and Amazon SQS are
examples of popular queue-based
message systems.
Pulsar: Unified Messaging + Data Streaming

27. Messaging
Ideal for work queues that do not
require tasks to be performed in a
particular order—for example, sending
one email message to many recipients.
RabbitMQ and Amazon SQS are
examples of popular queue-based
message systems.
Pulsar: Unified Messaging + Data Streaming
.. and Streaming
Works best in situations where the order
of messages is important—for example,
data ingestion.
Kafka and Amazon Kinesis are examples
of messaging systems that use streaming
semantics for consuming messages.

28. Pulsar Instance
Pulsar Cluster
Pulsar Instance
Pulsar Cluster

29. A Unified Messaging Platform
Message Queuing
Data Streaming

30. Topics
Tenants
(Compliance)
Tenants
(Data Services)
Namespace
(Microservices)
Topic-1
(Cust Auth)
Topic-1
(Location Resolution)
Topic-2
(Demographics)
Topic-1
(Budgeted Spend)
Topic-1
(Acct History)
Topic-1
(Risk Detection)
Namespace
(ETL)
Namespace
(Campaigns)
Namespace
(ETL)
Tenants
(Marketing)
Namespace
(Risk Assessment)
Pulsar Instance
Pulsar Cluster

31. Pulsar’s Publish-Subscribe model
Broker
Subscription
Consumer 1
Consumer 2
Consumer 3
Topic
Producer 1
Producer 2
● Producers send messages.
● Topics are an ordered, named channel that producers
use to transmit messages to subscribed consumers.
● Messages belong to a topic and contain an arbitrary
payload.
● Brokers handle connections and routes
messages between producers / consumers.
● Subscriptions are named configuration rules
that determine how messages are delivered to
consumers.
● Consumers receive messages.

32. Producer-Consumer
Producer Consumer
Publisher sends data and
doesn't know about the
subscribers or their status.
All interactions go through
Pulsar and it handles all
communication.
Subscriber receives data
from publisher and never
directly interacts with it
Topic
Topic

33. Kafka
On Pulsar
(KoP)

34. streamnative.io
MQTT
On Pulsar
(MoP)

35. Pulsar Functions
● Lightweight
computation similar to
AWS Lambda.
● Specifically designed to
use Apache Pulsar as a
message bus.
● Function runtime can
be located within
Pulsar Broker.
A serverless event streaming
framework

36. streamnative.io
● Consume messages from one
or more Pulsar topics.
● Apply user-supplied
processing logic to each
message.
● Publish the results of the
computation to another topic.
● Support multiple
programming languages (Java,
Python, Go)
● Can leverage 3rd-party
libraries to support the
execution of ML models on
the edge.
Pulsar Functions

37. Pulsar SQL
Presto/Trino workers can read
segments directly from
bookies (or offloaded storage)
in parallel.
Bookie
1
Segment 1
Producer Consumer
Broker 1
Topic1-Part1
Broker 2
Topic1-Part2
Broker 3
Topic1-Part3
Segment 2 Segment 3 Segment 4 Segment X
Segment 1
Segment 1 Segment 1
Segment 3 Segment 3
Segment 3
Segment 2
Segment 2
Segment 2
Segment 4
Segment 4
Segment 4
Segment X
Segment X
Segment X
Bookie
2
Bookie
3
Query
Coordinator
...
...
SQL Worker SQL Worker SQL Worker
SQL Worker
Query
Topic
Metadata

38. Use Cases
Multi-Tenant Data
Infrastructure
AdTech
Fraud Detection
Connected Car
IoT Analytics
Data Lake Hydration

39. Apache NiFi

40. Apache NiFi Pulsar Connector
https://github.com/streamnative/pulsar-nifi-bundle

41. Apache NiFi Pulsar Connector
https://github.com/david-streamlio/pulsar-nifi-bundle

42. Apache NiFi Pulsar Connector

43. Apache NiFi Pulsar Connector

44. Apache NiFi Pulsar Connector

45. StreamNative
Cloud

46. streamnative.io
Passionate and dedicated team.
Founded by the original developers of
Apache Pulsar.
StreamNative helps teams to capture,
manage, and leverage data using Pulsar’s
unified messaging and streaming
platform.

47. Founded By The
Creators Of Apache Pulsar
Sijie Guo
ASF Member
Pulsar/BookKeeper PMC
Founder and CEO
Jia Zhai
Pulsar/BookKeeper PMC
Co-Founder
Matteo Merli
ASF Member
Pulsar/BookKeeper PMC
CTO
Data veterans with extensive industry experience

49. REST Feed Non-Fungible Token
{"date":"Thu, 24 Feb 2022 22:26:41
GMT","short_description":"","featured":"false","image_thumbnail_url":"htt","asset_contract_created_date":"2022-02-17T15:4
8:44.822206","asset_contract_owner":"50299352","image_preview_url":"https://lh3.googleus","asset_contract_symbol":"TD
","twitter_username":"","description":"10,000metaverse-readyAvatars","asset_contract_address":"0xc7df86762ba83f2a619
7e1ff9bb40ae0f696b9e6","external_url":"https://www.sandbox.game/en/snoopdogg/","token_id":"492","asset_contract_na
me":"Theoggies","asset_contract_nft_version":"3.0","asset_contract_description":"metaverse.","asset_contract_external_lin
k":"https://www.sandbox.game/en/snoopdogg/","id":"307922619","featured_image_url":"https","slug":"snoop-dogg-doggie
s","token_metadata":"https://contracts.sandbox.game/unrevealed.json?tokenId=492","asset_contract_schema_name":"ER
C721","animation_url":"https","num_sales":"1","image_url":"https://lh","asset_contract_default_to_fiat":"false","external_link":
"","image_original_url":"https://contracts.sandbox.game/preview.png","asset_contract_payout_address":"0x4489590a1166
18b506f0efe885432f6a8ed998e9","animation_original_url":"https://con","background_color":"","asset_contract_asset_cont
ract_type":"non-fungible","name":"The Doggies","asset_contract_image_url":"https","asset_contract_total_supply":"0"}
https://docs.opensea.io/reference/retrieving-bundles

50. StreamNative Hub
StreamNative Cloud
Unified Batch and Stream STORAGE
Offload
(Queuing + Streaming)
Apache Pulsar - Apache NiFi <-> Events <-> Cloud Data Stores
Tiered Storage
Pulsar
---
KoP
---
MoP
---
Websocket
---
HTTP
Pulsar
Sink
Pulsar
Sink
Data Gateway
Protocols
Data to Cloud Data Lake
Micro
Service
(Queuing + Streaming)

51. StreamNative Cloud
Tiered Storage

52. (Queuing + Streaming)

53. (Queuing + Streaming)
Tiered Storage
(Queuing + Streaming)