Modern Data Processing - Big Data Analytical Streaming Data Pipelines

Timothy Spann
Timothy SpannDeveloper Advocate
Modern Data Processing / Big
Data Analytical Streaming Data
Pipelines
David Kjerrumgaard
Developer Advocate
● Apache Pulsar Committer | Author of Pulsar
In Action
● Former Principal Software Engineer on
Splunk’s messaging team responsible for
Splunk’s internal Pulsar-as-a-Service
platform
● Former Director of Solution Architecture at
Streamlio
2
Tim Spann
Developer Advocate
Tim Spann, Developer Advocate at StreamNative
● FLiP(N) Stack = Flink, Pulsar and NiFI Stack
● Streaming Systems & Data Architecture Expert
● Experience:
○ 15+ years of experience with streaming technologies including Pulsar,
Flink, Spark, NiFi, Big Data, Cloud, MXNet, IoT, Python and more.
○ Today, he helps to grow the Pulsar community sharing rich technical
knowledge and experience at both global conferences and through
individual conversations.
Hosted by
Save Your Spot Now
Use code MODERNDATA20
to get 20% off.
Pulsar Summit
San Francisco
Hotel Nikko
August 18 2022
5 Keynotes
12 Breakout Sessions
1 Amazing Happy Hour
Pulsar Summit
San Francisco
Sponsorship
Prospectus
Community Sponsorships Available
Help engage and connect the Apache Pulsar
community by becoming an official sponsor for
Pulsar Summit San Francisco 2022! Learn more
about the requirements and benefits of
becoming a community sponsor.
Hosted by
FLiP Stack Weekly
This week in Apache Flink, Apache Pulsar, Apache
NiFi, Apache Spark and open source friends.
https://bit.ly/32dAJft
streamnative.io
Agenda
• Streaming Data Pipelines The Easy Way.
• Code / Demonstration.
https://tinyurl.com/bddpwjuf
streamnative.io
Our Pipeline Example
Apache Pulsar is a Cloud-Native
Messaging and Event-Streaming Platform.
101
Unified
Messaging
Platform
Guaranteed
Message
Delivery
Resiliency Infinite
Scalability
What are the Benefits of Pulsar?
Data Durability
Scalability Geo-Replication
Multi-Tenancy
Unified Messaging
Model
The right API for async
12
Designed for teams, with
built in multi-tenancy
Power and flexibility,
w/ support for
simultaneous streaming
and messaging use cases
Ideal for high-scale,
mission critical
microservices
Easy to use, with a
simple pub/sub API
streamnative.io
The Right Architecture for Unified Data
Pulsar’s Architecture
Decoupled compute and storage
● Separate compute and storage
has become standard practice
in cloud-native architectures
● Supports easy scale up/down.
Architectural Advantages
Brokers
Stateless compute
Bookies
message &
subscription state
Pluggable
Metadata
Store
● “Bookies”
● Stores messages and cursors
● Messages are grouped in
segments/ledgers
● A group of bookies form an
“ensemble” to store a ledger
● “Brokers”
● Handles message routing and
connections
● Stateless, but with caches
● Automatic load-balancing
● Topics are composed of
multiple segments
●
● Stores metadata for both
Pulsar and BookKeeper
● Service discovery
Store
Messages
Metadata &
Service Discovery
Metadata &
Service Discovery
Key Pulsar Concepts: Architecture
MetaData
Storage
Streaming
Consumer
Consumer
Consumer
Subscription
Shared
Failover
Consumer
Consumer
Subscription
In case of failure in
Consumer B-0
Consumer
Consumer
Subscription
Exclusive
X
Consumer
Consumer
Key-Shared
Subscription
Pulsar
Topic/Partition
Messaging
Unified Messaging
Model
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.
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 Cluster
Pulsar Cluster
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
Pulsar Terminology
Producer is a process that
publishes messages to a topic.
Consumer is a process that
establishes a subscription to a
topic and processes messages
published to that topic.
Subscription: A subscription is a
named configuration rule that
determines how messages are
delivered to consumers.
Brokers handle the connections
and routes messages.
Instance is a group of clusters
that act together as a single
unit.
Cluster is a set of Pulsar
brokers, ZooKeeper quorum, and
an ensemble of BookKeeper
bookies.
Tenants are the administrative
unit for allocating capacity and
enforcing an authentication/
authorization scheme.
Namespaces are a grouping
mechanism for related topics.
Topics are named channels for
transmitting messages from
producers to consumers.
Messages belong to a topic and
contain an arbitrary payload.
BookKeeper log storage system
that Pulsar uses for durable
storage of all messages.
Bookie Stores messages and
cursors. Messages are grouped in
segments/ledgers.
ZooKeeper Stores metadata for
both Pulsar and BookKeeper,
also performs service discovery.
Kafka
On Pulsar
(KoP)
MQTT
On Pulsar
(MoP)
AMQP
On Pulsar
(AoP)
Modern Data Processing - Big Data Analytical Streaming Data Pipelines
Modern Data Processing - Big Data Analytical Streaming Data Pipelines
Modern Data Processing - Big Data Analytical Streaming Data Pipelines
Demo
pyspark --packages io.delta:delta-core_2.12:1.2.1 --conf
"spark.sql.extensions=io.delta.sql.DeltaSparkSessionExtension" --conf
"spark.sql.catalog.spark_catalog=org.apache.spark.sql.delta.catalog.DeltaCatalog"
IoT Data
IoT Ingestion: High-volume
streaming sources, sensors,
multiple message formats,
diverse protocols and
multi-vendor devices
creates data ingestion
challenges.
Other Sources: Transit data,
news, twitter, status feeds,
REST data, stock data and
more.
StreamNative Hub
StreamNative Cloud
Unified Batch and Stream COMPUTING
Batch
(Batch + Stream)
Unified Batch and Stream STORAGE
Offload
(Queuing + Streaming)
Tiered Storage
Pulsar
---
Kafka
---
MQTT
---
Websocket
---
AMQP
Pulsar
Sink
Pulsar
Sink
Streaming
Edge Protocols
Modern Streaming Lakehouse Pipeline
Micro
Service
Modern Data Processing - Big Data Analytical Streaming Data Pipelines
Modern Data Processing - Big Data Analytical Streaming Data Pipelines
streamnative.io
Flink SQL
Q&A
[Webinar]
Building Microservices
Watch Now Learn More
[Blog post]
Event-Driven Microservices
Now Available
On-Demand Pulsar
Training
Academy.StreamNative.io
35
1 of 35

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Modern Data Processing - Big Data Analytical Streaming Data Pipelines

  • 1. Modern Data Processing / Big Data Analytical Streaming Data Pipelines
  • 2. David Kjerrumgaard Developer Advocate ● Apache Pulsar Committer | Author of Pulsar In Action ● Former Principal Software Engineer on Splunk’s messaging team responsible for Splunk’s internal Pulsar-as-a-Service platform ● Former Director of Solution Architecture at Streamlio 2
  • 3. Tim Spann Developer Advocate Tim Spann, Developer Advocate at StreamNative ● FLiP(N) Stack = Flink, Pulsar and NiFI Stack ● Streaming Systems & Data Architecture Expert ● Experience: ○ 15+ years of experience with streaming technologies including Pulsar, Flink, Spark, NiFi, Big Data, Cloud, MXNet, IoT, Python and more. ○ Today, he helps to grow the Pulsar community sharing rich technical knowledge and experience at both global conferences and through individual conversations.
  • 4. Hosted by Save Your Spot Now Use code MODERNDATA20 to get 20% off. Pulsar Summit San Francisco Hotel Nikko August 18 2022 5 Keynotes 12 Breakout Sessions 1 Amazing Happy Hour
  • 5. Pulsar Summit San Francisco Sponsorship Prospectus Community Sponsorships Available Help engage and connect the Apache Pulsar community by becoming an official sponsor for Pulsar Summit San Francisco 2022! Learn more about the requirements and benefits of becoming a community sponsor. Hosted by
  • 6. FLiP Stack Weekly This week in Apache Flink, Apache Pulsar, Apache NiFi, Apache Spark and open source friends. https://bit.ly/32dAJft
  • 7. streamnative.io Agenda • Streaming Data Pipelines The Easy Way. • Code / Demonstration. https://tinyurl.com/bddpwjuf
  • 9. Apache Pulsar is a Cloud-Native Messaging and Event-Streaming Platform.
  • 11. What are the Benefits of Pulsar? Data Durability Scalability Geo-Replication Multi-Tenancy Unified Messaging Model
  • 12. The right API for async 12 Designed for teams, with built in multi-tenancy Power and flexibility, w/ support for simultaneous streaming and messaging use cases Ideal for high-scale, mission critical microservices Easy to use, with a simple pub/sub API
  • 13. streamnative.io The Right Architecture for Unified Data Pulsar’s Architecture Decoupled compute and storage ● Separate compute and storage has become standard practice in cloud-native architectures ● Supports easy scale up/down. Architectural Advantages Brokers Stateless compute Bookies message & subscription state Pluggable Metadata Store
  • 14. ● “Bookies” ● Stores messages and cursors ● Messages are grouped in segments/ledgers ● A group of bookies form an “ensemble” to store a ledger ● “Brokers” ● Handles message routing and connections ● Stateless, but with caches ● Automatic load-balancing ● Topics are composed of multiple segments ● ● Stores metadata for both Pulsar and BookKeeper ● Service discovery Store Messages Metadata & Service Discovery Metadata & Service Discovery Key Pulsar Concepts: Architecture MetaData Storage
  • 15. Streaming Consumer Consumer Consumer Subscription Shared Failover Consumer Consumer Subscription In case of failure in Consumer B-0 Consumer Consumer Subscription Exclusive X Consumer Consumer Key-Shared Subscription Pulsar Topic/Partition Messaging Unified Messaging Model
  • 16. 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.
  • 17. 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 Cluster Pulsar Cluster
  • 18. 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
  • 19. Pulsar Terminology Producer is a process that publishes messages to a topic. Consumer is a process that establishes a subscription to a topic and processes messages published to that topic. Subscription: A subscription is a named configuration rule that determines how messages are delivered to consumers. Brokers handle the connections and routes messages. Instance is a group of clusters that act together as a single unit. Cluster is a set of Pulsar brokers, ZooKeeper quorum, and an ensemble of BookKeeper bookies. Tenants are the administrative unit for allocating capacity and enforcing an authentication/ authorization scheme. Namespaces are a grouping mechanism for related topics. Topics are named channels for transmitting messages from producers to consumers. Messages belong to a topic and contain an arbitrary payload. BookKeeper log storage system that Pulsar uses for durable storage of all messages. Bookie Stores messages and cursors. Messages are grouped in segments/ledgers. ZooKeeper Stores metadata for both Pulsar and BookKeeper, also performs service discovery.
  • 26. Demo pyspark --packages io.delta:delta-core_2.12:1.2.1 --conf "spark.sql.extensions=io.delta.sql.DeltaSparkSessionExtension" --conf "spark.sql.catalog.spark_catalog=org.apache.spark.sql.delta.catalog.DeltaCatalog"
  • 27. IoT Data IoT Ingestion: High-volume streaming sources, sensors, multiple message formats, diverse protocols and multi-vendor devices creates data ingestion challenges. Other Sources: Transit data, news, twitter, status feeds, REST data, stock data and more.
  • 28. StreamNative Hub StreamNative Cloud Unified Batch and Stream COMPUTING Batch (Batch + Stream) Unified Batch and Stream STORAGE Offload (Queuing + Streaming) Tiered Storage Pulsar --- Kafka --- MQTT --- Websocket --- AMQP Pulsar Sink Pulsar Sink Streaming Edge Protocols Modern Streaming Lakehouse Pipeline Micro Service
  • 33. Q&A
  • 34. [Webinar] Building Microservices Watch Now Learn More [Blog post] Event-Driven Microservices