Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
To Stream or Not To Stream? The Landscape of Online Analytics
Search
Gianmarco De Francisci Morales
May 28, 2015
Research
1
260
To Stream or Not To Stream? The Landscape of Online Analytics
EVAM Solution Day 2015, Istanbul.
Gianmarco De Francisci Morales
May 28, 2015
Tweet
Share
More Decks by Gianmarco De Francisci Morales
See All by Gianmarco De Francisci Morales
Repurpose, Reuse, Recycle the building blocks of Machine Learning
gdfm
0
45
How I Learned to Stop Worrying and Love the Risk
gdfm
0
110
Controversy on Social Media: Collective Attention, Echo Chambers, and Price of Bipartisanship
gdfm
0
100
Controversy on Social Media: Collective Attention, Echo Chambers, and Price of Bipartisanship
gdfm
0
180
Quantifying and Reducing Controversy in Social Media
gdfm
0
120
Big Data Streams: The Next Frontier
gdfm
2
280
Mining Big Data Streams: Better Algorithms or Faster Systems?
gdfm
0
450
SAMOA @Strata Barcelona 2014
gdfm
2
590
Distributed Adaptive Model Rules for Mining Big Data Streams
gdfm
1
140
Other Decks in Research
See All in Research
The Theory behind Vector DB
matsui_528
0
1.6k
生成AIを用いたText to SQLの最前線
masatoto
1
2.3k
FMP L3 Year 1 Project Proposal
haiinya
0
150
リサーチに組織を巻き込むための「準備8割」の話
terasho
0
470
インタビューだけじゃない!ユーザーに共感しユーザーの目👀を手に入れるためのインプット
moco1013
0
230
方策の長期性能に対する効率的なオフライン評価・学習 (Long-term Off-Policy Evaluation and Learning)
usaito
PRO
2
180
株式会社リクルートホールディングス 企業分析
frandle256
0
130
「歴史的農業環境閲覧システム」と「迅速測図」について
wata909
1
600
音声処理ツールキットESPnetの現在と未来
kanbayashi1125
2
540
[ICLR'24] Towards Assessing and Benchmarking Risk-Return Tradeoff of OPE
harukakiyohara_
0
200
DeepCrysTet: A Deep Learning Approach Using Tetrahedral Mesh for Predicting Properties of Crystalline Materials
tsurubee
0
370
Accurate Method and Variable Tracking in Commit History
tsantalis
0
250
Featured
See All Featured
The Success of Rails: Ensuring Growth for the Next 100 Years
eileencodes
30
6k
Producing Creativity
orderedlist
PRO
337
39k
個人開発の失敗を避けるイケてる考え方 / tips for indie hackers
panda_program
60
14k
Docker and Python
trallard
34
2.7k
10 Git Anti Patterns You Should be Aware of
lemiorhan
648
58k
The Illustrated Children's Guide to Kubernetes
chrisshort
31
46k
Dealing with People You Can't Stand - Big Design 2015
cassininazir
357
22k
Product Roadmaps are Hard
iamctodd
44
9.7k
Sharpening the Axe: The Primacy of Toolmaking
bcantrill
17
1.4k
Designing for humans not robots
tammielis
248
25k
Fantastic passwords and where to find them - at NoRuKo
philnash
37
2.5k
What's in a price? How to price your products and services
michaelherold
237
11k
Transcript
To Stream or Not To Stream? The Landscape of Online
Analytics Gianmarco De Francisci Morales
[email protected]
@gdfm7
None
5 Questions What? Why? How? Where? When?
What? Data Stream
Text Big Data Too big to handle
Text Big Data Streams Drinking from a firehose
Stream Analytics Batch data = snapshot of streaming data Descriptive
Predictive Prescriptive
Value of Data
Online vs Real-Time
Why? Motivation and Goal
–Jay Kreps, Confluent founder (ex-LinkedIn) “Most of what happens inside
a company is some new information comes in and the company reacts to that asynchronously.” Asynchronous Processing
Nervous System vs Silos
Perishable Insights Great instantaneous value Ephemeral Opportunity cost
Hype Cycle
Hype Cycle
How? Stream Processing Architecture
Architecture Overview
Ingestion Plethora of solutions Still ad-hoc (read: messy) Schema evolution:
Avro Column-store: Parquet Log collection: Flume
Brokerage
Processing PE PE Input Stream PEI PEI PEI PEI PEI
Output Stream Event routing
Output Stream: Kafka Further processing View: Key-Value Store Applications Reactive
callbacks
Example: Reactive Web App
Lambda vs Kappa
Where? Applications
Application Domains Industrial applications Telecommunications and networks Web applications Internet
of Things
Predictive Maintenance
Text Search
Machine Learning SA SAMOA%
Anomaly Detection
When? Adoption Risks
– Gartner, 2015 “Despite considerable hype and reported successes for
early adopters, 54% of survey respondents report no plans to invest at this time, while only 18% have plans to invest in Hadoop over the next 2 years.” 5 Years Early
Cost Not an issue Cheap hardware Cloud-based solutions Amazon Kinesis,
MSFT Azure Stream Analytics Open source
Ease Inherently harder Ops best practices not ironed out (yet)
Lack of skills, training, and support Rethink applications from scratch
Actionable Insights? Define what you want Moving target Garbage in,
garbage out
Conclusions Who?
5 Answers What? Why? How? Where? When? Stream analytics Perishable
insights Asynchronous processing Everywhere In 5 years
Text Slow Fish or Fast Fish Which fish will you
be?
Thanks! 37 https://samoa.incubator.apache.org @ApacheSAMOA @gdfm7
[email protected]