OSS EU: Deep Dive into Building Streaming Applications with Apache Pulsar

Timothy Spann
Timothy SpannDeveloper Advocate
Deep Dive into Building Streaming
Applications with Apache Pulsar
Tim Spann / Developer Advocate
#ossummit @PaaSDev
Deep Dive into Building
Streaming Applications with
Apache Pulsar
Tim Spann
Developer Advocate
● FLiP(N) Stack = Flink, Pulsar and NiFi Stack
● Streaming Systems/ Data Architect
● Experience:
○ 15+ years of experience with batch and streaming technologies
including Pulsar, Flink, Spark, NiFi, Spring, Java, Big Data, Cloud,
MXNet, Hadoop, Datalakes, IoT and more.
FLiP Stack Weekly
This week in Apache Flink, Apache Pulsar, Apache
NiFi, Apache Spark and open source friends.
https://bit.ly/32dAJft
#ossummit
Apache Pulsar is a Cloud-Native
Messaging and Event-Streaming Platform.
Why Apache Pulsar?
Unified
Messaging Platform
Guaranteed
Message Delivery Resiliency Infinite
Scalability
Building
Microservices
Asynchronous
Communication
Building Real Time
Applications
Highly Resilient
Tiered storage
7
Pulsar Benefits
● “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
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
Key Pulsar Concepts: Messaging vs Streaming
Message Queueing - Queueing
systems are ideal for work
queues that do not require
tasks to be performed in a
particular order.
Streaming - Streaming works
best in situations where the
order of messages is
important.
#ossummit
Connectivity
• 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
• Data Offloaders - Tiered Storage - (S3)
hub.streamnative.io
#ossummit
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
#ossummit
Kafka On Pulsar (KoP)
#ossummit
MQTT On Pulsar (MoP)
#ossummit
AMQP On Pulsar (AoP)
#ossummit
Presto/Trino workers can read
segments directly from bookies (or
offloaded storage) in parallel.
Pulsar SQL
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
Coordin
ator
SQL
Worker
SQL
Worker
SQL
Worker
SQL
Worker
Query
Topic
Metadata
OSS EU:  Deep Dive into Building Streaming Applications with Apache Pulsar
OSS EU:  Deep Dive into Building Streaming Applications with Apache Pulsar
● Buffer
● Batch
● Route
● Filter
● Aggregate
● Enrich
● Replicate
● Dedupe
● Decouple
● Distribute
#ossummit
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
#ossummit
● 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
#ossummit
Run a Local Standalone Bare Metal
wget
https://archive.apache.org/dist/pulsar/pulsar-2.10.1/apache-pulsar-2.10.1-
bin.tar.gz
tar xvfz apache-pulsar-2.10.1-bin.tar.gz
cd apache-pulsar-2.10.1
bin/pulsar standalone
(For Pulsar SQL Support)
bin/pulsar sql-worker start
https://pulsar.apache.org/docs/en/standalone/
#ossummit
<or> Run in Docker
docker run -it 
-p 6650:6650 
-p 8080:8080 
--mount source=pulsardata,target=/pulsar/data 
--mount source=pulsarconf,target=/pulsar/conf 
apachepulsar/pulsar:2.10.1 
bin/pulsar standalone
https://pulsar.apache.org/docs/en/standalone-docker/
#ossummit
Building Tenant, Namespace, Topics
bin/pulsar-admin tenants create conf
bin/pulsar-admin namespaces create conf/europe
bin/pulsar-admin tenants list
bin/pulsar-admin namespaces list conf
bin/pulsar-admin topics create persistent://conf/europe/first
bin/pulsar-admin topics list conf/europe
#ossummit
Install Python 3 Pulsar Client
pip3 install pulsar-client=='2.10.1[all]'
Includes AARCH64, ARM, M2, INTEL, …
For Python on Pulsar on Pi https://github.com/tspannhw/PulsarOnRaspberryPi
https://pulsar.apache.org/docs/en/client-libraries-python/
https://pypi.org/project/pulsar-client/2.10.0/#files
#ossummit
Building a Python 3 Producer
import pulsar
client = pulsar.Client('pulsar://localhost:6650')
producer
client.create_producer('persistent://conf/ete/first')
producer.send(('Simple Text Message').encode('utf-8'))
client.close()
#ossummit
Building a Python 3 Cloud Producer Oath
python3 prod.py -su pulsar+ssl://name1.name2.snio.cloud:6651 -t
persistent://public/default/pyth --auth-params
'{"issuer_url":"https://auth.streamnative.cloud", "private_key":"my.json",
"audience":"urn:sn:pulsar:name:myclustr"}'
from pulsar import Client, AuthenticationOauth2
parse = argparse.ArgumentParser(prog=prod.py')
parse.add_argument('-su', '--service-url', dest='service_url', type=str,
required=True)
args = parse.parse_args()
client = pulsar.Client(args.service_url,
authentication=AuthenticationOauth2(args.auth_params))
https://github.com/streamnative/examples/blob/master/cloud/python/OAuth2Producer.py
https://github.com/tspannhw/FLiP-Pi-BreakoutGarden
#ossummit
Example Avro Schema Usage
import pulsar
from pulsar.schema import *
from pulsar.schema import AvroSchema
class thermal(Record):
uuid = String()
client = pulsar.Client('pulsar://pulsar1:6650')
thermalschema = AvroSchema(thermal)
producer =
client.create_producer(topic='persistent://public/default/pi-thermal-avro',
schema=thermalschema,properties={"producer-name": "thrm" })
thermalRec = thermal()
thermalRec.uuid = "unique-name"
producer.send(thermalRec,partition_key=uniqueid)
https://github.com/tspannhw/FLiP-Pi-Thermal
#ossummit
Example Json Schema Usage
import pulsar
from pulsar.schema import *
from pulsar.schema import JsonSchema
class weather(Record):
uuid = String()
client = pulsar.Client('pulsar://pulsar1:6650')
wsc = JsonSchema(thermal)
producer =
client.create_producer(topic='persistent://public/default/wthr,schema=wsc,pro
perties={"producer-name": "wthr" })
weatherRec = weather()
weatherRec.uuid = "unique-name"
producer.send(weatherRec,partition_key=uniqueid)
https://github.com/tspannhw/FLiP-Pi-Weather
https://github.com/tspannhw/FLiP-PulsarDevPython101
#ossummit
Building a Python3 Consumer
import pulsar
client = pulsar.Client('pulsar://localhost:6650')
consumer =
client.subscribe('persistent://conf/ete/first',subscription_name='mine')
while True:
msg = consumer.receive()
print("Received message: '%s'" % msg.data())
consumer.acknowledge(msg)
client.close()
#ossummit
MQTT from Python
pip3 install paho-mqtt
import paho.mqtt.client as mqtt
client = mqtt.Client("rpi4iot")
row = { }
row['gasKO'] = str(readings)
json_string = json.dumps(row)
json_string = json_string.strip()
client.connect("pulsar-server.com", 1883, 180)
client.publish("persistent://public/default/mqtt-2",
payload=json_string,qos=0,retain=True)
https://www.slideshare.net/bunkertor/data-minutes-2-apache-pulsar-with-mqtt-for-edge-computing-lightning-2022
MQTT
#ossummit
Web Sockets from Python
pip3 install websocket-client
import websocket, base64, json
topic = 'ws://server:8080/ws/v2/producer/persistent/public/default/topic1'
ws = websocket.create_connection(topic)
message = "Hello Philly ETE Conference"
message_bytes = message.encode('ascii')
base64_bytes = base64.b64encode(message_bytes)
base64_message = base64_bytes.decode('ascii')
ws.send(json.dumps({'payload' : base64_message,'properties': {'device' :
'macbook'},'context' : 5}))
response = json.loads(ws.recv())
https://pulsar.apache.org/docs/en/client-libraries-websocket/
https://github.com/tspannhw/FLiP-IoT/blob/main/wspulsar.py
https://github.com/tspannhw/FLiP-IoT/blob/main/wsreader.py
Websockets
#ossummit
Kafka from Python
pip3 install kafka-python
from kafka import KafkaProducer
from kafka.errors import KafkaError
row = { }
row['gasKO'] = str(readings)
json_string = json.dumps(row)
json_string = json_string.strip()
producer = KafkaProducer(bootstrap_servers='pulsar1:9092',retries=3)
producer.send('topic-kafka-1', json.dumps(row).encode('utf-8'))
producer.flush()
https://github.com/streamnative/kop
https://docs.streamnative.io/platform/v1.0.0/concepts/kop-concepts
Apache Kafka
#ossummit
Deploy Python Functions
bin/pulsar-admin functions create --auto-ack true --py py/src/sentiment.py
--classname "sentiment.Chat" --inputs "persistent://public/default/chat"
--log-topic "persistent://public/default/logs" --name Chat --output
"persistent://public/default/chatresult"
https://github.com/tspannhw/pulsar-pychat-function
#ossummit
Pulsar IO Function in Python3
from pulsar import Function
import json
class Chat(Function):
def __init__(self):
pass
def process(self, input, context):
logger = context.get_logger()
msg_id = context.get_message_id()
fields = json.loads(input)
https://github.com/tspannhw/pulsar-pychat-function
#ossummit
Building a Golang Pulsar App
http://pulsar.apache.org/docs/en/client-libraries-go/
go get -u "github.com/apache/pulsar-client-go/pulsar"
import (
"log"
"time"
"github.com/apache/pulsar-client-go/pulsar"
)
func main() {
client, err := pulsar.NewClient(pulsar.ClientOptions{
URL: "pulsar://localhost:6650",OperationTimeout: 30 * time.Second,
ConnectionTimeout: 30 * time.Second,
})
if err != nil {
log.Fatalf("Could not instantiate Pulsar client: %v", err)
}
defer client.Close()
}
#ossummit
Typed Java Client
Producer<User> producer =
client.newProducer(Schema.AVRO(User.class)).create();
producer.newMessage()
.value(User.builder()
.userName("pulsar-user")
.userId(1L)
.build())
.send();
Consumer<User> consumer =
client.newConsumer(Schema.AVRO(User.class)).create();
User user = consumer.receive();
#ossummit
Pulsar Producer
import java.util.UUID;
import java.net.URL;
import org.apache.pulsar.client.api.Producer;
import org.apache.pulsar.client.api.ProducerBuilder;
import org.apache.pulsar.client.api.PulsarClient;
import org.apache.pulsar.client.api.MessageId;
import org.apache.pulsar.client.impl.auth.oauth2.AuthenticationFactoryOAuth2;
PulsarClient client = PulsarClient.builder()
.serviceUrl(serviceUrl)
.authentication(
AuthenticationFactoryOAuth2.clientCredentials(
new URL(issuerUrl), new URL(credentialsUrl.), audience))
.build();
#ossummit
Spring RabbitMQ/AMQP Producer
rabbitTemplate.convertAndSend(topicName,
DataUtility.serializeToJSON(observation));
#ossummit
Spring MQTT Producer
MqttMessage mqttMessage = new MqttMessage();
mqttMessage.setPayload(DataUtility.serialize(payload));
mqttMessage.setQos(1);
mqttMessage.setRetained(true);
mqttClient.publish(topicName, mqttMessage);
#ossummit
Spring Kafka Producer
ProducerRecord<String, String> producerRecord = new
ProducerRecord<>(topicName, uuidKey.toString(),
DataUtility.serializeToJSON(message));
kafkaTemplate.send(producerRecord);
#ossummit
Pulsar Simple Producer
String pulsarKey = UUID.randomUUID().toString();
String OS = System.getProperty("os.name").toLowerCase();
ProducerBuilder<byte[]> producerBuilder = client.newProducer().topic(topic)
.producerName("demo");
Producer<byte[]> producer = producerBuilder.create();
MessageId msgID = producer.newMessage().key(pulsarKey).value("msg".getBytes())
.property("device",OS).send();
producer.close();
client.close();
#ossummit
import java.util.function.Function;
public class MyFunction implements Function<String, String> {
public String apply(String input) {
return doBusinessLogic(input);
}
}
Your Code Here
Pulsar Function Java
#ossummit
import org.apache.pulsar.client.impl.schema.JSONSchema;
import org.apache.pulsar.functions.api.*;
public class AirQualityFunction implements Function<byte[], Void> {
@Override
public Void process(byte[] input, Context context) {
context.getLogger().debug("File:” + new String(input));
context.newOutputMessage(“topicname”,
JSONSchema.of(Observation.class))
.key(UUID.randomUUID().toString())
.property(“prop1”, “value1”)
.value(observation)
.send();
}
}
Your Code Here
Pulsar Function SDK
#ossummit
Setting Subscription Type Java
Consumer<byte[]> consumer = pulsarClient.newConsumer()
.topic(topic)
.subscriptionName(“subscriptionName")
.subscriptionType(SubscriptionType.Shared)
.subscribe();
#ossummit
Subscribing to a Topic and Setting Subscription Name
Java
Consumer<byte[]> consumer = pulsarClient.newConsumer()
.topic(topic)
.subscriptionName(“subscriptionName")
.subscribe();
#ossummit
Producing Object Events From Java
ProducerBuilder<Observation> producerBuilder =
pulsarClient.newProducer(JSONSchema.of(Observation.class))
.topic(topicName)
.producerName(producerName).sendTimeout(60,
TimeUnit.SECONDS);
Producer<Observation> producer = producerBuilder.create();
msgID = producer.newMessage()
.key(someUniqueKey)
.value(observation)
.send();
#ossummit
Monitoring and Metrics Check
curl http://pulsar1:8080/admin/v2/persistent/conf/europe/first/stats |
python3 -m json.tool
bin/pulsar-admin topics stats-internal persistent://conf/europe/first
curl http://pulsar1:8080/metrics/
bin/pulsar-admin topics stats-internal persistent://conf/europe/first
bin/pulsar-admin topics peek-messages --count 5 --subscription
ete-reader persistent://conf/europe/first
bin/pulsar-admin topics subscriptions persistent://conf/europe/first
#ossummit
Metrics: Broker
Broker metrics are exposed under "/metrics" at port 8080.
You can change the port by updating webServicePort to a different port
in the broker.conf configuration file.
All the metrics exposed by a broker are labeled with
cluster=${pulsar_cluster}.
The name of Pulsar cluster is the value of ${pulsar_cluster},
configured in the broker.conf file.
For more information: https://pulsar.apache.org/docs/en/reference-metrics/#broker
#ossummit
Metrics: Broker
These metrics are available for brokers:
● Namespace metrics
○ Replication metrics
● Topic metrics
○ Replication metrics
● ManagedLedgerCache metrics
● ManagedLedger metrics
● LoadBalancing metrics
○ BundleUnloading metrics
○ BundleSplit metrics
● Subscription metrics
● Consumer metrics
● ManagedLedger bookie client metrics
#ossummit
Cleanup
bin/pulsar-admin topics delete persistent://conf/europe/first
bin/pulsar-admin namespaces delete conf/europe
bin/pulsar-admin tenants delete conf
#ossummit
• Unified Messaging Platform
• AdTech
• Fraud Detection
• Connected Car
• IoT Analytics
• Microservices Development
Use Cases
OSS EU:  Deep Dive into Building Streaming Applications with Apache Pulsar
#ossummit
Java for Pulsar
● https://github.com/tspannhw/airquality
● https://github.com/tspannhw/FLiPN-AirQuality-REST
● https://github.com/tspannhw/pulsar-airquality-function
● https://github.com/tspannhw/FLiPN-DEVNEXUS-2022
● https://github.com/tspannhw/FLiP-Py-ADS-B
● https://github.com/tspannhw/pulsar-adsb-function
● https://github.com/tspannhw/airquality-amqp-consumer
● https://github.com/tspannhw/airquality-mqtt-consumer
● https://github.com/tspannhw/airquality-consumer
● https://github.com/tspannhw/airquality-kafka-consumer
#ossummit
Python For Pulsar on Pi
● https://github.com/tspannhw/FLiP-Pi-BreakoutGarden
● https://github.com/tspannhw/FLiP-Pi-Thermal
● https://github.com/tspannhw/FLiP-Pi-Weather
● https://github.com/tspannhw/FLiP-RP400
● https://github.com/tspannhw/FLiP-Py-Pi-GasThermal
● https://github.com/tspannhw/FLiP-PY-FakeDataPulsar
● https://github.com/tspannhw/FLiP-Py-Pi-EnviroPlus
● https://github.com/tspannhw/PythonPulsarExamples
● https://github.com/tspannhw/pulsar-pychat-function
● https://github.com/tspannhw/FLiP-PulsarDevPython101
● https://github.com/tspannhw/airquality
OSS EU:  Deep Dive into Building Streaming Applications with Apache Pulsar
1 of 56

Recommended

ApacheCon2022_Deep Dive into Building Streaming Applications with Apache Pulsar by
ApacheCon2022_Deep Dive into Building Streaming Applications with Apache PulsarApacheCon2022_Deep Dive into Building Streaming Applications with Apache Pulsar
ApacheCon2022_Deep Dive into Building Streaming Applications with Apache PulsarTimothy Spann
175 views54 slides
Deep Dive into Building Streaming Applications with Apache Pulsar by
Deep Dive into Building Streaming Applications with Apache Pulsar Deep Dive into Building Streaming Applications with Apache Pulsar
Deep Dive into Building Streaming Applications with Apache Pulsar Timothy Spann
298 views61 slides
CODEONTHEBEACH_Streaming Applications with Apache Pulsar by
CODEONTHEBEACH_Streaming Applications with Apache PulsarCODEONTHEBEACH_Streaming Applications with Apache Pulsar
CODEONTHEBEACH_Streaming Applications with Apache PulsarTimothy Spann
47 views66 slides
Building Modern Data Streaming Apps with Python by
Building Modern Data Streaming Apps with PythonBuilding Modern Data Streaming Apps with Python
Building Modern Data Streaming Apps with PythonTimothy Spann
532 views28 slides
Using FLiP with influxdb for edgeai iot at scale 2022 by
Using FLiP with influxdb for edgeai iot at scale 2022Using FLiP with influxdb for edgeai iot at scale 2022
Using FLiP with influxdb for edgeai iot at scale 2022Timothy Spann
465 views61 slides
Python Web Conference 2022 - Apache Pulsar Development 101 with Python (FLiP-Py) by
Python Web Conference 2022 - Apache Pulsar Development 101 with Python (FLiP-Py)Python Web Conference 2022 - Apache Pulsar Development 101 with Python (FLiP-Py)
Python Web Conference 2022 - Apache Pulsar Development 101 with Python (FLiP-Py)Timothy Spann
172 views49 slides

More Related Content

Similar to OSS EU: Deep Dive into Building Streaming Applications with Apache Pulsar

All Day DevOps - FLiP Stack for Cloud Data Lakes by
All Day DevOps - FLiP Stack for Cloud Data LakesAll Day DevOps - FLiP Stack for Cloud Data Lakes
All Day DevOps - FLiP Stack for Cloud Data LakesTimothy Spann
493 views31 slides
Big mountain data and dev conference apache pulsar with mqtt for edge compu... by
Big mountain data and dev conference   apache pulsar with mqtt for edge compu...Big mountain data and dev conference   apache pulsar with mqtt for edge compu...
Big mountain data and dev conference apache pulsar with mqtt for edge compu...Timothy Spann
440 views47 slides
Sink Your Teeth into Streaming at Any Scale by
Sink Your Teeth into Streaming at Any ScaleSink Your Teeth into Streaming at Any Scale
Sink Your Teeth into Streaming at Any ScaleTimothy Spann
12 views30 slides
Sink Your Teeth into Streaming at Any Scale by
Sink Your Teeth into Streaming at Any ScaleSink Your Teeth into Streaming at Any Scale
Sink Your Teeth into Streaming at Any ScaleScyllaDB
317 views30 slides
Conf42 Python_ ML Enhanced Event Streaming Apps with Python Microservices by
Conf42 Python_ ML Enhanced Event Streaming Apps with Python MicroservicesConf42 Python_ ML Enhanced Event Streaming Apps with Python Microservices
Conf42 Python_ ML Enhanced Event Streaming Apps with Python MicroservicesTimothy Spann
443 views29 slides
Using the FLiPN Stack for Edge AI (Flink, NiFi, Pulsar) by
Using the FLiPN Stack for Edge AI (Flink, NiFi, Pulsar) Using the FLiPN Stack for Edge AI (Flink, NiFi, Pulsar)
Using the FLiPN Stack for Edge AI (Flink, NiFi, Pulsar) Timothy Spann
305 views71 slides

Similar to OSS EU: Deep Dive into Building Streaming Applications with Apache Pulsar(20)

All Day DevOps - FLiP Stack for Cloud Data Lakes by Timothy Spann
All Day DevOps - FLiP Stack for Cloud Data LakesAll Day DevOps - FLiP Stack for Cloud Data Lakes
All Day DevOps - FLiP Stack for Cloud Data Lakes
Timothy Spann493 views
Big mountain data and dev conference apache pulsar with mqtt for edge compu... by Timothy Spann
Big mountain data and dev conference   apache pulsar with mqtt for edge compu...Big mountain data and dev conference   apache pulsar with mqtt for edge compu...
Big mountain data and dev conference apache pulsar with mqtt for edge compu...
Timothy Spann440 views
Sink Your Teeth into Streaming at Any Scale by Timothy Spann
Sink Your Teeth into Streaming at Any ScaleSink Your Teeth into Streaming at Any Scale
Sink Your Teeth into Streaming at Any Scale
Timothy Spann12 views
Sink Your Teeth into Streaming at Any Scale by ScyllaDB
Sink Your Teeth into Streaming at Any ScaleSink Your Teeth into Streaming at Any Scale
Sink Your Teeth into Streaming at Any Scale
ScyllaDB317 views
Conf42 Python_ ML Enhanced Event Streaming Apps with Python Microservices by Timothy Spann
Conf42 Python_ ML Enhanced Event Streaming Apps with Python MicroservicesConf42 Python_ ML Enhanced Event Streaming Apps with Python Microservices
Conf42 Python_ ML Enhanced Event Streaming Apps with Python Microservices
Timothy Spann443 views
Using the FLiPN Stack for Edge AI (Flink, NiFi, Pulsar) by Timothy Spann
Using the FLiPN Stack for Edge AI (Flink, NiFi, Pulsar) Using the FLiPN Stack for Edge AI (Flink, NiFi, Pulsar)
Using the FLiPN Stack for Edge AI (Flink, NiFi, Pulsar)
Timothy Spann305 views
Cloud lunch and learn real-time streaming in azure by Timothy Spann
Cloud lunch and learn real-time streaming in azureCloud lunch and learn real-time streaming in azure
Cloud lunch and learn real-time streaming in azure
Timothy Spann663 views
[March sn meetup] apache pulsar + apache nifi for cloud data lake by Timothy Spann
[March sn meetup] apache pulsar + apache nifi for cloud data lake[March sn meetup] apache pulsar + apache nifi for cloud data lake
[March sn meetup] apache pulsar + apache nifi for cloud data lake
Timothy Spann903 views
Apache Pulsar Development 101 with Python by Timothy Spann
Apache Pulsar Development 101 with PythonApache Pulsar Development 101 with Python
Apache Pulsar Development 101 with Python
Timothy Spann1.2K views
Living the Stream Dream with Pulsar and Spring Boot by Timothy Spann
Living the Stream Dream with Pulsar and Spring BootLiving the Stream Dream with Pulsar and Spring Boot
Living the Stream Dream with Pulsar and Spring Boot
Timothy Spann94 views
Machine Intelligence Guild_ Build ML Enhanced Event Streaming Applications wi... by Timothy Spann
Machine Intelligence Guild_ Build ML Enhanced Event Streaming Applications wi...Machine Intelligence Guild_ Build ML Enhanced Event Streaming Applications wi...
Machine Intelligence Guild_ Build ML Enhanced Event Streaming Applications wi...
Timothy Spann197 views
DBCC 2021 - FLiP Stack for Cloud Data Lakes by Timothy Spann
DBCC 2021 - FLiP Stack for Cloud Data LakesDBCC 2021 - FLiP Stack for Cloud Data Lakes
DBCC 2021 - FLiP Stack for Cloud Data Lakes
Timothy Spann717 views
Pulsar summit asia 2021 apache pulsar with mqtt for edge computing by Timothy Spann
Pulsar summit asia 2021   apache pulsar with mqtt for edge computingPulsar summit asia 2021   apache pulsar with mqtt for edge computing
Pulsar summit asia 2021 apache pulsar with mqtt for edge computing
Timothy Spann366 views
Python Streaming Pipelines on Flink - Beam Meetup at Lyft 2019 by Thomas Weise
Python Streaming Pipelines on Flink - Beam Meetup at Lyft 2019Python Streaming Pipelines on Flink - Beam Meetup at Lyft 2019
Python Streaming Pipelines on Flink - Beam Meetup at Lyft 2019
Thomas Weise1.4K views
Building an Event Streaming Architecture with Apache Pulsar by ScyllaDB
Building an Event Streaming Architecture with Apache PulsarBuilding an Event Streaming Architecture with Apache Pulsar
Building an Event Streaming Architecture with Apache Pulsar
ScyllaDB136 views
bigdata 2022_ FLiP Into Pulsar Apps by Timothy Spann
bigdata 2022_ FLiP Into Pulsar Appsbigdata 2022_ FLiP Into Pulsar Apps
bigdata 2022_ FLiP Into Pulsar Apps
Timothy Spann460 views
Real time cloud native open source streaming of any data to apache solr by Timothy Spann
Real time cloud native open source streaming of any data to apache solrReal time cloud native open source streaming of any data to apache solr
Real time cloud native open source streaming of any data to apache solr
Timothy Spann759 views
Timothy Spann: Apache Pulsar for ML by Edunomica
Timothy Spann: Apache Pulsar for MLTimothy Spann: Apache Pulsar for ML
Timothy Spann: Apache Pulsar for ML
Edunomica37 views
Introducing Kafka-on-Pulsar: bring native Kafka protocol support to Apache Pu... by StreamNative
Introducing Kafka-on-Pulsar: bring native Kafka protocol support to Apache Pu...Introducing Kafka-on-Pulsar: bring native Kafka protocol support to Apache Pu...
Introducing Kafka-on-Pulsar: bring native Kafka protocol support to Apache Pu...
StreamNative759 views
PhillyJug Getting Started With Real-time Cloud Native Streaming With Java by Timothy Spann
PhillyJug  Getting Started With Real-time Cloud Native Streaming With JavaPhillyJug  Getting Started With Real-time Cloud Native Streaming With Java
PhillyJug Getting Started With Real-time Cloud Native Streaming With Java
Timothy Spann625 views

More from Timothy Spann

Building Real-Time Travel Alerts by
Building Real-Time Travel AlertsBuilding Real-Time Travel Alerts
Building Real-Time Travel AlertsTimothy Spann
165 views48 slides
JConWorld_ Continuous SQL with Kafka and Flink by
JConWorld_ Continuous SQL with Kafka and FlinkJConWorld_ Continuous SQL with Kafka and Flink
JConWorld_ Continuous SQL with Kafka and FlinkTimothy Spann
156 views36 slides
[EN]DSS23_tspann_Integrating LLM with Streaming Data Pipelines by
[EN]DSS23_tspann_Integrating LLM with Streaming Data Pipelines[EN]DSS23_tspann_Integrating LLM with Streaming Data Pipelines
[EN]DSS23_tspann_Integrating LLM with Streaming Data PipelinesTimothy Spann
150 views25 slides
Evolve 2023 NYC - Integrating AI Into Realtime Data Pipelines Demo by
Evolve 2023 NYC - Integrating AI Into Realtime Data Pipelines DemoEvolve 2023 NYC - Integrating AI Into Realtime Data Pipelines Demo
Evolve 2023 NYC - Integrating AI Into Realtime Data Pipelines DemoTimothy Spann
162 views8 slides
CoC23_ Looking at the New Features of Apache NiFi by
CoC23_ Looking at the New Features of Apache NiFiCoC23_ Looking at the New Features of Apache NiFi
CoC23_ Looking at the New Features of Apache NiFiTimothy Spann
36 views24 slides
CoC23_ Let’s Monitor The Conditions at the Conference by
CoC23_ Let’s Monitor The Conditions at the ConferenceCoC23_ Let’s Monitor The Conditions at the Conference
CoC23_ Let’s Monitor The Conditions at the ConferenceTimothy Spann
17 views17 slides

More from Timothy Spann(20)

Building Real-Time Travel Alerts by Timothy Spann
Building Real-Time Travel AlertsBuilding Real-Time Travel Alerts
Building Real-Time Travel Alerts
Timothy Spann165 views
JConWorld_ Continuous SQL with Kafka and Flink by Timothy Spann
JConWorld_ Continuous SQL with Kafka and FlinkJConWorld_ Continuous SQL with Kafka and Flink
JConWorld_ Continuous SQL with Kafka and Flink
Timothy Spann156 views
[EN]DSS23_tspann_Integrating LLM with Streaming Data Pipelines by Timothy Spann
[EN]DSS23_tspann_Integrating LLM with Streaming Data Pipelines[EN]DSS23_tspann_Integrating LLM with Streaming Data Pipelines
[EN]DSS23_tspann_Integrating LLM with Streaming Data Pipelines
Timothy Spann150 views
Evolve 2023 NYC - Integrating AI Into Realtime Data Pipelines Demo by Timothy Spann
Evolve 2023 NYC - Integrating AI Into Realtime Data Pipelines DemoEvolve 2023 NYC - Integrating AI Into Realtime Data Pipelines Demo
Evolve 2023 NYC - Integrating AI Into Realtime Data Pipelines Demo
Timothy Spann162 views
CoC23_ Looking at the New Features of Apache NiFi by Timothy Spann
CoC23_ Looking at the New Features of Apache NiFiCoC23_ Looking at the New Features of Apache NiFi
CoC23_ Looking at the New Features of Apache NiFi
Timothy Spann36 views
CoC23_ Let’s Monitor The Conditions at the Conference by Timothy Spann
CoC23_ Let’s Monitor The Conditions at the ConferenceCoC23_ Let’s Monitor The Conditions at the Conference
CoC23_ Let’s Monitor The Conditions at the Conference
Timothy Spann17 views
OSSFinance_UnlockingFinancialDatawithReal-TimePipelines.pdf by Timothy Spann
OSSFinance_UnlockingFinancialDatawithReal-TimePipelines.pdfOSSFinance_UnlockingFinancialDatawithReal-TimePipelines.pdf
OSSFinance_UnlockingFinancialDatawithReal-TimePipelines.pdf
Timothy Spann23 views
CoC23_Utilizing Real-Time Transit Data for Travel Optimization by Timothy Spann
CoC23_Utilizing Real-Time Transit Data for Travel OptimizationCoC23_Utilizing Real-Time Transit Data for Travel Optimization
CoC23_Utilizing Real-Time Transit Data for Travel Optimization
Timothy Spann31 views
The Never Landing Stream with HTAP and Streaming by Timothy Spann
The Never Landing Stream with HTAP and StreamingThe Never Landing Stream with HTAP and Streaming
The Never Landing Stream with HTAP and Streaming
Timothy Spann254 views
Meetup - Brasil - Data In Motion - 2023 September 19 by Timothy Spann
Meetup - Brasil - Data In Motion - 2023 September 19Meetup - Brasil - Data In Motion - 2023 September 19
Meetup - Brasil - Data In Motion - 2023 September 19
Timothy Spann319 views
Implement a Universal Data Distribution Architecture to Manage All Streaming ... by Timothy Spann
Implement a Universal Data Distribution Architecture to Manage All Streaming ...Implement a Universal Data Distribution Architecture to Manage All Streaming ...
Implement a Universal Data Distribution Architecture to Manage All Streaming ...
Timothy Spann28 views
Building Real-time Pipelines with FLaNK_ A Case Study with Transit Data by Timothy Spann
Building Real-time Pipelines with FLaNK_ A Case Study with Transit DataBuilding Real-time Pipelines with FLaNK_ A Case Study with Transit Data
Building Real-time Pipelines with FLaNK_ A Case Study with Transit Data
Timothy Spann193 views
big data fest building modern data streaming apps by Timothy Spann
big data fest building modern data streaming appsbig data fest building modern data streaming apps
big data fest building modern data streaming apps
Timothy Spann317 views
Using Apache NiFi with Apache Pulsar for Fast Data On-Ramp by Timothy Spann
Using Apache NiFi with Apache Pulsar for Fast Data On-RampUsing Apache NiFi with Apache Pulsar for Fast Data On-Ramp
Using Apache NiFi with Apache Pulsar for Fast Data On-Ramp
Timothy Spann163 views
OSSNA Building Modern Data Streaming Apps by Timothy Spann
OSSNA Building Modern Data Streaming AppsOSSNA Building Modern Data Streaming Apps
OSSNA Building Modern Data Streaming Apps
Timothy Spann155 views
GSJUG: Mastering Data Streaming Pipelines 09May2023 by Timothy Spann
GSJUG: Mastering Data Streaming Pipelines 09May2023GSJUG: Mastering Data Streaming Pipelines 09May2023
GSJUG: Mastering Data Streaming Pipelines 09May2023
Timothy Spann255 views
BestInFlowCompetitionTutorials03May2023 by Timothy Spann
BestInFlowCompetitionTutorials03May2023BestInFlowCompetitionTutorials03May2023
BestInFlowCompetitionTutorials03May2023
Timothy Spann11 views
Cloudera Sandbox Event Guidelines For Workflow by Timothy Spann
Cloudera Sandbox Event Guidelines For WorkflowCloudera Sandbox Event Guidelines For Workflow
Cloudera Sandbox Event Guidelines For Workflow
Timothy Spann32 views
Meet the Committers Webinar_ Lab Preparation by Timothy Spann
Meet the Committers Webinar_ Lab PreparationMeet the Committers Webinar_ Lab Preparation
Meet the Committers Webinar_ Lab Preparation
Timothy Spann32 views

Recently uploaded

Techstack Ltd at Slush 2023, Ukrainian delegation by
Techstack Ltd at Slush 2023, Ukrainian delegationTechstack Ltd at Slush 2023, Ukrainian delegation
Techstack Ltd at Slush 2023, Ukrainian delegationViktoriiaOpanasenko
7 views4 slides
FOSSLight Community Day 2023-11-30 by
FOSSLight Community Day 2023-11-30FOSSLight Community Day 2023-11-30
FOSSLight Community Day 2023-11-30Shane Coughlan
8 views18 slides
aATP - New Correlation Confirmation Feature.pptx by
aATP - New Correlation Confirmation Feature.pptxaATP - New Correlation Confirmation Feature.pptx
aATP - New Correlation Confirmation Feature.pptxEsatEsenek1
222 views6 slides
Page Object Model by
Page Object ModelPage Object Model
Page Object Modelartembondar5
7 views5 slides
JioEngage_Presentation.pptx by
JioEngage_Presentation.pptxJioEngage_Presentation.pptx
JioEngage_Presentation.pptxadmin125455
9 views4 slides
Automated Testing of Microsoft Power BI Reports by
Automated Testing of Microsoft Power BI ReportsAutomated Testing of Microsoft Power BI Reports
Automated Testing of Microsoft Power BI ReportsRTTS
11 views20 slides

Recently uploaded(20)

FOSSLight Community Day 2023-11-30 by Shane Coughlan
FOSSLight Community Day 2023-11-30FOSSLight Community Day 2023-11-30
FOSSLight Community Day 2023-11-30
Shane Coughlan8 views
aATP - New Correlation Confirmation Feature.pptx by EsatEsenek1
aATP - New Correlation Confirmation Feature.pptxaATP - New Correlation Confirmation Feature.pptx
aATP - New Correlation Confirmation Feature.pptx
EsatEsenek1222 views
JioEngage_Presentation.pptx by admin125455
JioEngage_Presentation.pptxJioEngage_Presentation.pptx
JioEngage_Presentation.pptx
admin1254559 views
Automated Testing of Microsoft Power BI Reports by RTTS
Automated Testing of Microsoft Power BI ReportsAutomated Testing of Microsoft Power BI Reports
Automated Testing of Microsoft Power BI Reports
RTTS11 views
tecnologia18.docx by nosi6702
tecnologia18.docxtecnologia18.docx
tecnologia18.docx
nosi67026 views
How To Make Your Plans Suck Less — Maarten Dalmijn at the 57th Hands-on Agile... by Stefan Wolpers
How To Make Your Plans Suck Less — Maarten Dalmijn at the 57th Hands-on Agile...How To Make Your Plans Suck Less — Maarten Dalmijn at the 57th Hands-on Agile...
How To Make Your Plans Suck Less — Maarten Dalmijn at the 57th Hands-on Agile...
Stefan Wolpers44 views
Top-5-production-devconMunich-2023.pptx by Tier1 app
Top-5-production-devconMunich-2023.pptxTop-5-production-devconMunich-2023.pptx
Top-5-production-devconMunich-2023.pptx
Tier1 app10 views
Unlocking the Power of AI in Product Management - A Comprehensive Guide for P... by NimaTorabi2
Unlocking the Power of AI in Product Management - A Comprehensive Guide for P...Unlocking the Power of AI in Product Management - A Comprehensive Guide for P...
Unlocking the Power of AI in Product Management - A Comprehensive Guide for P...
NimaTorabi217 views
Ports-and-Adapters Architecture for Embedded HMI by Burkhard Stubert
Ports-and-Adapters Architecture for Embedded HMIPorts-and-Adapters Architecture for Embedded HMI
Ports-and-Adapters Architecture for Embedded HMI
Burkhard Stubert35 views
Streamlining Your Business Operations with Enterprise Application Integration... by Flexsin
Streamlining Your Business Operations with Enterprise Application Integration...Streamlining Your Business Operations with Enterprise Application Integration...
Streamlining Your Business Operations with Enterprise Application Integration...
Flexsin 5 views
Supercharging your Python Development Environment with VS Code and Dev Contai... by Dawn Wages
Supercharging your Python Development Environment with VS Code and Dev Contai...Supercharging your Python Development Environment with VS Code and Dev Contai...
Supercharging your Python Development Environment with VS Code and Dev Contai...
Dawn Wages5 views
predicting-m3-devopsconMunich-2023-v2.pptx by Tier1 app
predicting-m3-devopsconMunich-2023-v2.pptxpredicting-m3-devopsconMunich-2023-v2.pptx
predicting-m3-devopsconMunich-2023-v2.pptx
Tier1 app14 views
Electronic AWB - Electronic Air Waybill by Freightoscope
Electronic AWB - Electronic Air Waybill Electronic AWB - Electronic Air Waybill
Electronic AWB - Electronic Air Waybill
Freightoscope 6 views

OSS EU: Deep Dive into Building Streaming Applications with Apache Pulsar

  • 1. Deep Dive into Building Streaming Applications with Apache Pulsar Tim Spann / Developer Advocate #ossummit @PaaSDev
  • 2. Deep Dive into Building Streaming Applications with Apache Pulsar
  • 3. Tim Spann Developer Advocate ● FLiP(N) Stack = Flink, Pulsar and NiFi Stack ● Streaming Systems/ Data Architect ● Experience: ○ 15+ years of experience with batch and streaming technologies including Pulsar, Flink, Spark, NiFi, Spring, Java, Big Data, Cloud, MXNet, Hadoop, Datalakes, IoT and more.
  • 4. FLiP Stack Weekly This week in Apache Flink, Apache Pulsar, Apache NiFi, Apache Spark and open source friends. https://bit.ly/32dAJft
  • 5. #ossummit Apache Pulsar is a Cloud-Native Messaging and Event-Streaming Platform.
  • 6. Why Apache Pulsar? Unified Messaging Platform Guaranteed Message Delivery Resiliency Infinite Scalability
  • 8. ● “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
  • 9. 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
  • 10. Key Pulsar Concepts: Messaging vs Streaming Message Queueing - Queueing systems are ideal for work queues that do not require tasks to be performed in a particular order. Streaming - Streaming works best in situations where the order of messages is important.
  • 11. #ossummit Connectivity • 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 • Data Offloaders - Tiered Storage - (S3) hub.streamnative.io
  • 12. #ossummit 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
  • 16. #ossummit Presto/Trino workers can read segments directly from bookies (or offloaded storage) in parallel. Pulsar SQL 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 Coordin ator SQL Worker SQL Worker SQL Worker SQL Worker Query Topic Metadata
  • 19. ● Buffer ● Batch ● Route ● Filter ● Aggregate ● Enrich ● Replicate ● Dedupe ● Decouple ● Distribute
  • 20. #ossummit 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
  • 21. #ossummit ● 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
  • 22. #ossummit Run a Local Standalone Bare Metal wget https://archive.apache.org/dist/pulsar/pulsar-2.10.1/apache-pulsar-2.10.1- bin.tar.gz tar xvfz apache-pulsar-2.10.1-bin.tar.gz cd apache-pulsar-2.10.1 bin/pulsar standalone (For Pulsar SQL Support) bin/pulsar sql-worker start https://pulsar.apache.org/docs/en/standalone/
  • 23. #ossummit <or> Run in Docker docker run -it -p 6650:6650 -p 8080:8080 --mount source=pulsardata,target=/pulsar/data --mount source=pulsarconf,target=/pulsar/conf apachepulsar/pulsar:2.10.1 bin/pulsar standalone https://pulsar.apache.org/docs/en/standalone-docker/
  • 24. #ossummit Building Tenant, Namespace, Topics bin/pulsar-admin tenants create conf bin/pulsar-admin namespaces create conf/europe bin/pulsar-admin tenants list bin/pulsar-admin namespaces list conf bin/pulsar-admin topics create persistent://conf/europe/first bin/pulsar-admin topics list conf/europe
  • 25. #ossummit Install Python 3 Pulsar Client pip3 install pulsar-client=='2.10.1[all]' Includes AARCH64, ARM, M2, INTEL, … For Python on Pulsar on Pi https://github.com/tspannhw/PulsarOnRaspberryPi https://pulsar.apache.org/docs/en/client-libraries-python/ https://pypi.org/project/pulsar-client/2.10.0/#files
  • 26. #ossummit Building a Python 3 Producer import pulsar client = pulsar.Client('pulsar://localhost:6650') producer client.create_producer('persistent://conf/ete/first') producer.send(('Simple Text Message').encode('utf-8')) client.close()
  • 27. #ossummit Building a Python 3 Cloud Producer Oath python3 prod.py -su pulsar+ssl://name1.name2.snio.cloud:6651 -t persistent://public/default/pyth --auth-params '{"issuer_url":"https://auth.streamnative.cloud", "private_key":"my.json", "audience":"urn:sn:pulsar:name:myclustr"}' from pulsar import Client, AuthenticationOauth2 parse = argparse.ArgumentParser(prog=prod.py') parse.add_argument('-su', '--service-url', dest='service_url', type=str, required=True) args = parse.parse_args() client = pulsar.Client(args.service_url, authentication=AuthenticationOauth2(args.auth_params)) https://github.com/streamnative/examples/blob/master/cloud/python/OAuth2Producer.py https://github.com/tspannhw/FLiP-Pi-BreakoutGarden
  • 28. #ossummit Example Avro Schema Usage import pulsar from pulsar.schema import * from pulsar.schema import AvroSchema class thermal(Record): uuid = String() client = pulsar.Client('pulsar://pulsar1:6650') thermalschema = AvroSchema(thermal) producer = client.create_producer(topic='persistent://public/default/pi-thermal-avro', schema=thermalschema,properties={"producer-name": "thrm" }) thermalRec = thermal() thermalRec.uuid = "unique-name" producer.send(thermalRec,partition_key=uniqueid) https://github.com/tspannhw/FLiP-Pi-Thermal
  • 29. #ossummit Example Json Schema Usage import pulsar from pulsar.schema import * from pulsar.schema import JsonSchema class weather(Record): uuid = String() client = pulsar.Client('pulsar://pulsar1:6650') wsc = JsonSchema(thermal) producer = client.create_producer(topic='persistent://public/default/wthr,schema=wsc,pro perties={"producer-name": "wthr" }) weatherRec = weather() weatherRec.uuid = "unique-name" producer.send(weatherRec,partition_key=uniqueid) https://github.com/tspannhw/FLiP-Pi-Weather https://github.com/tspannhw/FLiP-PulsarDevPython101
  • 30. #ossummit Building a Python3 Consumer import pulsar client = pulsar.Client('pulsar://localhost:6650') consumer = client.subscribe('persistent://conf/ete/first',subscription_name='mine') while True: msg = consumer.receive() print("Received message: '%s'" % msg.data()) consumer.acknowledge(msg) client.close()
  • 31. #ossummit MQTT from Python pip3 install paho-mqtt import paho.mqtt.client as mqtt client = mqtt.Client("rpi4iot") row = { } row['gasKO'] = str(readings) json_string = json.dumps(row) json_string = json_string.strip() client.connect("pulsar-server.com", 1883, 180) client.publish("persistent://public/default/mqtt-2", payload=json_string,qos=0,retain=True) https://www.slideshare.net/bunkertor/data-minutes-2-apache-pulsar-with-mqtt-for-edge-computing-lightning-2022 MQTT
  • 32. #ossummit Web Sockets from Python pip3 install websocket-client import websocket, base64, json topic = 'ws://server:8080/ws/v2/producer/persistent/public/default/topic1' ws = websocket.create_connection(topic) message = "Hello Philly ETE Conference" message_bytes = message.encode('ascii') base64_bytes = base64.b64encode(message_bytes) base64_message = base64_bytes.decode('ascii') ws.send(json.dumps({'payload' : base64_message,'properties': {'device' : 'macbook'},'context' : 5})) response = json.loads(ws.recv()) https://pulsar.apache.org/docs/en/client-libraries-websocket/ https://github.com/tspannhw/FLiP-IoT/blob/main/wspulsar.py https://github.com/tspannhw/FLiP-IoT/blob/main/wsreader.py Websockets
  • 33. #ossummit Kafka from Python pip3 install kafka-python from kafka import KafkaProducer from kafka.errors import KafkaError row = { } row['gasKO'] = str(readings) json_string = json.dumps(row) json_string = json_string.strip() producer = KafkaProducer(bootstrap_servers='pulsar1:9092',retries=3) producer.send('topic-kafka-1', json.dumps(row).encode('utf-8')) producer.flush() https://github.com/streamnative/kop https://docs.streamnative.io/platform/v1.0.0/concepts/kop-concepts Apache Kafka
  • 34. #ossummit Deploy Python Functions bin/pulsar-admin functions create --auto-ack true --py py/src/sentiment.py --classname "sentiment.Chat" --inputs "persistent://public/default/chat" --log-topic "persistent://public/default/logs" --name Chat --output "persistent://public/default/chatresult" https://github.com/tspannhw/pulsar-pychat-function
  • 35. #ossummit Pulsar IO Function in Python3 from pulsar import Function import json class Chat(Function): def __init__(self): pass def process(self, input, context): logger = context.get_logger() msg_id = context.get_message_id() fields = json.loads(input) https://github.com/tspannhw/pulsar-pychat-function
  • 36. #ossummit Building a Golang Pulsar App http://pulsar.apache.org/docs/en/client-libraries-go/ go get -u "github.com/apache/pulsar-client-go/pulsar" import ( "log" "time" "github.com/apache/pulsar-client-go/pulsar" ) func main() { client, err := pulsar.NewClient(pulsar.ClientOptions{ URL: "pulsar://localhost:6650",OperationTimeout: 30 * time.Second, ConnectionTimeout: 30 * time.Second, }) if err != nil { log.Fatalf("Could not instantiate Pulsar client: %v", err) } defer client.Close() }
  • 37. #ossummit Typed Java Client Producer<User> producer = client.newProducer(Schema.AVRO(User.class)).create(); producer.newMessage() .value(User.builder() .userName("pulsar-user") .userId(1L) .build()) .send(); Consumer<User> consumer = client.newConsumer(Schema.AVRO(User.class)).create(); User user = consumer.receive();
  • 38. #ossummit Pulsar Producer import java.util.UUID; import java.net.URL; import org.apache.pulsar.client.api.Producer; import org.apache.pulsar.client.api.ProducerBuilder; import org.apache.pulsar.client.api.PulsarClient; import org.apache.pulsar.client.api.MessageId; import org.apache.pulsar.client.impl.auth.oauth2.AuthenticationFactoryOAuth2; PulsarClient client = PulsarClient.builder() .serviceUrl(serviceUrl) .authentication( AuthenticationFactoryOAuth2.clientCredentials( new URL(issuerUrl), new URL(credentialsUrl.), audience)) .build();
  • 40. #ossummit Spring MQTT Producer MqttMessage mqttMessage = new MqttMessage(); mqttMessage.setPayload(DataUtility.serialize(payload)); mqttMessage.setQos(1); mqttMessage.setRetained(true); mqttClient.publish(topicName, mqttMessage);
  • 41. #ossummit Spring Kafka Producer ProducerRecord<String, String> producerRecord = new ProducerRecord<>(topicName, uuidKey.toString(), DataUtility.serializeToJSON(message)); kafkaTemplate.send(producerRecord);
  • 42. #ossummit Pulsar Simple Producer String pulsarKey = UUID.randomUUID().toString(); String OS = System.getProperty("os.name").toLowerCase(); ProducerBuilder<byte[]> producerBuilder = client.newProducer().topic(topic) .producerName("demo"); Producer<byte[]> producer = producerBuilder.create(); MessageId msgID = producer.newMessage().key(pulsarKey).value("msg".getBytes()) .property("device",OS).send(); producer.close(); client.close();
  • 43. #ossummit import java.util.function.Function; public class MyFunction implements Function<String, String> { public String apply(String input) { return doBusinessLogic(input); } } Your Code Here Pulsar Function Java
  • 44. #ossummit import org.apache.pulsar.client.impl.schema.JSONSchema; import org.apache.pulsar.functions.api.*; public class AirQualityFunction implements Function<byte[], Void> { @Override public Void process(byte[] input, Context context) { context.getLogger().debug("File:” + new String(input)); context.newOutputMessage(“topicname”, JSONSchema.of(Observation.class)) .key(UUID.randomUUID().toString()) .property(“prop1”, “value1”) .value(observation) .send(); } } Your Code Here Pulsar Function SDK
  • 45. #ossummit Setting Subscription Type Java Consumer<byte[]> consumer = pulsarClient.newConsumer() .topic(topic) .subscriptionName(“subscriptionName") .subscriptionType(SubscriptionType.Shared) .subscribe();
  • 46. #ossummit Subscribing to a Topic and Setting Subscription Name Java Consumer<byte[]> consumer = pulsarClient.newConsumer() .topic(topic) .subscriptionName(“subscriptionName") .subscribe();
  • 47. #ossummit Producing Object Events From Java ProducerBuilder<Observation> producerBuilder = pulsarClient.newProducer(JSONSchema.of(Observation.class)) .topic(topicName) .producerName(producerName).sendTimeout(60, TimeUnit.SECONDS); Producer<Observation> producer = producerBuilder.create(); msgID = producer.newMessage() .key(someUniqueKey) .value(observation) .send();
  • 48. #ossummit Monitoring and Metrics Check curl http://pulsar1:8080/admin/v2/persistent/conf/europe/first/stats | python3 -m json.tool bin/pulsar-admin topics stats-internal persistent://conf/europe/first curl http://pulsar1:8080/metrics/ bin/pulsar-admin topics stats-internal persistent://conf/europe/first bin/pulsar-admin topics peek-messages --count 5 --subscription ete-reader persistent://conf/europe/first bin/pulsar-admin topics subscriptions persistent://conf/europe/first
  • 49. #ossummit Metrics: Broker Broker metrics are exposed under "/metrics" at port 8080. You can change the port by updating webServicePort to a different port in the broker.conf configuration file. All the metrics exposed by a broker are labeled with cluster=${pulsar_cluster}. The name of Pulsar cluster is the value of ${pulsar_cluster}, configured in the broker.conf file. For more information: https://pulsar.apache.org/docs/en/reference-metrics/#broker
  • 50. #ossummit Metrics: Broker These metrics are available for brokers: ● Namespace metrics ○ Replication metrics ● Topic metrics ○ Replication metrics ● ManagedLedgerCache metrics ● ManagedLedger metrics ● LoadBalancing metrics ○ BundleUnloading metrics ○ BundleSplit metrics ● Subscription metrics ● Consumer metrics ● ManagedLedger bookie client metrics
  • 51. #ossummit Cleanup bin/pulsar-admin topics delete persistent://conf/europe/first bin/pulsar-admin namespaces delete conf/europe bin/pulsar-admin tenants delete conf
  • 52. #ossummit • Unified Messaging Platform • AdTech • Fraud Detection • Connected Car • IoT Analytics • Microservices Development Use Cases
  • 54. #ossummit Java for Pulsar ● https://github.com/tspannhw/airquality ● https://github.com/tspannhw/FLiPN-AirQuality-REST ● https://github.com/tspannhw/pulsar-airquality-function ● https://github.com/tspannhw/FLiPN-DEVNEXUS-2022 ● https://github.com/tspannhw/FLiP-Py-ADS-B ● https://github.com/tspannhw/pulsar-adsb-function ● https://github.com/tspannhw/airquality-amqp-consumer ● https://github.com/tspannhw/airquality-mqtt-consumer ● https://github.com/tspannhw/airquality-consumer ● https://github.com/tspannhw/airquality-kafka-consumer
  • 55. #ossummit Python For Pulsar on Pi ● https://github.com/tspannhw/FLiP-Pi-BreakoutGarden ● https://github.com/tspannhw/FLiP-Pi-Thermal ● https://github.com/tspannhw/FLiP-Pi-Weather ● https://github.com/tspannhw/FLiP-RP400 ● https://github.com/tspannhw/FLiP-Py-Pi-GasThermal ● https://github.com/tspannhw/FLiP-PY-FakeDataPulsar ● https://github.com/tspannhw/FLiP-Py-Pi-EnviroPlus ● https://github.com/tspannhw/PythonPulsarExamples ● https://github.com/tspannhw/pulsar-pychat-function ● https://github.com/tspannhw/FLiP-PulsarDevPython101 ● https://github.com/tspannhw/airquality