28March2024-Codeless-Generative-AI-Pipelines
https://www.meetup.com/futureofdata-princeton/events/299440871/
https://www.meetup.com/real-time-analytics-meetup-ny/events/299290822/
******Note*****
The event is seat-limited, therefore please complete your registration here. Only people completing the form will be able to attend.
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We're excited to invite you to join us in-person, for a Real-Time Analytics exploration!
Join us for an evening of insights, networking as we delve into the OSS technologies shaping the field!
Agenda:
05:30-06:00: Pizza and friends
06:00- 06:40: Codeless GenAI Pipelines with Flink, Kafka, NiFi
06:40- 07:20 Real-Time Analytics in the Corporate World: How Apache Pinot® Powers Industry Leaders
07:20-07:30 QNA
Codeless GenAI Pipelines with Flink, Kafka, NiFi | Tim Spann, Cloudera
Explore the power of real-time streaming with GenAI using Apache NiFi. Learn how NiFi simplifies data engineering workflows, allowing you to focus on creativity over technical complexities. I'll guide you through practical examples, showcasing NiFi's automation impact from ingestion to delivery. Whether you're a seasoned data engineer or new to GenAI, this talk offers valuable insights into optimizing workflows. Join us to unlock the potential of real-time streaming and witness how NiFi makes data engineering a breeze for GenAI applications!
Real-Time Analytics in the Corporate World: How Apache Pinot® Powers Industry Leaders | Viktor Gamov, StarTree
Explore how industry leaders like LinkedIn, Uber Eats, and Stripe are mastering real-time data with Viktor as your guide. Discover how Apache Pinot transforms data into actionable insights instantly. Viktor will showcase Pinot's features, including the Star-Tree Index, and explain why it's a game-changer in data strategy. This session is for everyone, from data geeks to business gurus, eager to uncover the future of tech. Join us and be wowed by the power of real-time analytics with Apache Pinot!
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Tim Spann is a Principal Developer Advocate in Data In Motion for Cloudera.
He works with Apache NiFi, Apache Kafka, Apache Pulsar, Apache Flink, Flink SQL, Apache Pinot, Trino, Apache Iceberg, DeltaLake, Apache Spark, Big Data, IoT, Cloud, AI/DL, machine learning, and deep learning. Tim has over ten years of experience with the IoT, big data, distributed computing, messaging, streaming technologies, and Java programming. Previously, he was a Developer Advocate at StreamNative, 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 & NYC 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.
14. 14
DataFlow Pipelines Can Help
External Context Ingest
Ingesting, routing, clean, enrich, transforming,
parsing, chunking and vectorizing structured,
unstructured, semistructured, binary data and
documents
Prompt engineering
Crafting and structuring queries to optimize
LLM responses
Context Retrieval
Enhancing LLM with external context such as
Retrieval Augmented Generation (RAG)
Roundtrip Interface
Act as a Discord, REST, Kafka, SQL, Slack bot to
roundtrip discussions
16. 16
Apache NiFi in a few numbers
A very active project with a dynamic community & comparison with ACEU 2019
2800+ members on the Slack channel (535+ - 4 years ago)
475+ contributors on Github across the repositories (260+ - 4 years ago)
65 committers in the Apache NiFi community (45 - 4 years ago)
Apache NiFi 1.25.0 is the latest release, NiFi 2.0.0-M2 is in alpha.
14M+ docker pulls of the Apache NiFi image (1M+ - 4 years ago)
18. 18
RECORD-ORIENTED DATA WITH NIFI
• Record Readers - Avro, CSV, Grok, IPFIX, JSAN1, JSON, Parquet,
Scripted, Syslog5424, Syslog, WindowsEvent, XML
• Record Writers - Avro, CSV, FreeFromText, Json, Parquet, Scripted,
XML
• Record Reader and Writer support referencing a schema registry
for retrieving schemas when necessary.
• Enable processors that accept any data format without having to
worry about the parsing and serialization logic.
• Allows us to keep FlowFiles larger, each consisting of multiple
records, which results in far better performance.
27. WatsonX SDK To Foundation
● Python 3.10+
● LLM
● WatsonX.AI Foundation Models
● Inference
● Secure
● Official SDK from IBM
https://github.com/tspannhw/FLaNK-python-watsonx-processor
28. CaptionImage
● Python 3.10+
● Hugging Face
● Salesforce/blip-image-captioning-large
● Generate Captions for Images
● Adds captions to FlowFile Attributes
● Does not require download or copies of
your images
https://github.com/tspannhw/FLaNK-python-processors
29. RESNetImageClassification
● Python 3.10+
● Hugging Face
● Transformers
● Pytorch
● Datasets
● microsoft/resnet-50
● Adds classification label to FlowFile
Attributes
● Does not require download or copies of
your images
https://github.com/tspannhw/FLaNK-python-processors
30. NSFWImageDetection
● Python 3.10+
● Hugging Face
● Transformers
● Falconsai/nsfw_image_detection
● Adds normal and nsfw to FlowFile
Attributes
● Gives score on safety of image
● Does not require download or copies of
your images
https://github.com/tspannhw/FLaNK-python-processors
31. FacialEmotionsImageDetection
● Python 3.10+
● Hugging Face
● Transformers
● facial_emotions_image_detection
● Image Classification
● Adds labels/scores to FlowFile Attributes
● Does not require download or copies of
your images
https://github.com/tspannhw/FLaNK-python-processors
40. Let’s do a metamorphosis on your data. Don’t fear changing data.
You don’t need to be a brilliant writer to stream
data.
Franz Kafka was a German-speaking
Bohemian novelist and short-story writer,
widely regarded as one of the major figures of
20th-century literature. His work fuses
elements of realism and the fantastic.
Wikipedia
YES, FRANZ, IT’S KAFKA
45. 45
Cloudera’s Open Data Lakehouse
❏ Multi-function analytics for Streaming, Data
Engineering, Data Warehouse and AI/ML with
integrated data services
❏ Common security and governance policies and data
lineage with SDX integration
❏ Common dataset with all CDP analytics engines
without data duplication and movement
❏ Deployment freedom with Multi-Hybrid Cloud
Iceberg Tables
DATA
WAREHOUSE
MACHINE
LEARNING
DATA
ENGINEERING
DATA
FLOW
STREAM
PROCESSING
Multi-Hybrid Cloud
Metadata | Security | Encryption | Control | Governance
46. 46
Compute Engine Interoperability & SDX
Integration
● Snapshot isolation ensures consistent data
access and processing with various
compute engines including Hive, Spark,
Impala and Nifi
● Security & Governance support (e.g. FGAC)
through Ranger integration
● Data lineage support through Atlas
integration
Apache Impala
Iceberg Tables
Ranger Atlas
47. FLINK & ICEBERG INTEGRATION
Robust Next Generation Architecture for Data Driven Business
Unified Processing Engine Massive Open table format
Iceberg Support for Flink APIs through SSB
• Maximally open
• Maximally flexible
• Ultra high performance for MASSIVE data
• Can be used as Source and Sink
• Supports batch and streaming modes
• Supports time travel
50. CSP Community Edition
● Docker compose file of CSP to run from command line w/o any
dependencies, including Flink, SQL Stream Builder, Kafka, Kafka
Connect, Streams Messaging Manager and Schema Registry.
○ $>docker compose up
● Licensed under the Cloudera Community License
● Unsupported Commercially (Community Help - Ask Tim)
● Community Group Hub for CSP
● Find it on docs.cloudera.com (see QR Code)
● Kafka, Kafka Connect, SMM, SR, Flink, Flink SQL, MV, Postgresql, SSB
● Develop apps locally
51. Open Source Edition
• Apache NiFi in Docker
• Try new features
quickly
• Develop applications
locally
● Docker NiFi
○ docker run --name nifi -p 8443:8443 -d -e
SINGLE_USER_CREDENTIALS_USERNAME=admin -e
SINGLE_USER_CREDENTIALS_PASSWORD=ctsBtRBKHRAx69EqUghv
vgEvjnaLjFEB apache/nifi:latest
● Licensed under the ASF License
● Unsupported
● NiFi 1.25 and NiFi 2.0.0-M2
https://hub.docker.com/r/apache/nifi