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TIMELESS STREAMSTIMELESS STREAMS
Decoupling events from time
by /Javier Salinas @MuSTa1nE
ABOUT MEABOUT ME
DEFINITION OF TIMEDEFINITION OF TIME
"The inde nite continued progress of
existence and events in the past, present
and future regarded as a whole"
Oxford Dictionary
"A continuous, measurable quantity in
which events occur in a sequence
proceeding from the past through the
present to the future"
Science Dictionary
EVENT SOURCINGEVENT SOURCING
With event sourcing, instead of storing the “current”
state of the entities that are used in our system, we
store a sequence of events that relate to these entities.
Events are immutable
LOGLOG
A Log is immutable, ordered, append-only and
persistent data structure. It’s a very simple structure,
but it is very powerful.
Logs have a speci c purpose: they record what
happened, when and where.
KAFKAKAFKA
Kafka is a distributed streaming platform
Order is guaranteed within a partition in a topic.
Each partition is a log.
REAL TIME PROCESSINGREAL TIME PROCESSING
DAILY PROCESSORDAILY PROCESSOR
PROBLEMSPROBLEMS
Time based systems are weak
Are hard to test
Dif cult to reproduce
Results might not be repeatable
DECOUPLE FROM TIMEDECOUPLE FROM TIME
Isolate time
Make your time de nition - as an event
React
DAILY PROCESSORDAILY PROCESSOR
USING MARKERSUSING MARKERS
Guarantees all events has been processed
Make an event as a result
React to events - not to time
WRAPPING UPWRAPPING UP
Time based systems are weak and hard to test
Isolate time
Be reactive to events - not to time
QUESTIONS?QUESTIONS?
THANK YOU!!THANK YOU!!
jsalinaspolo@gmail.com
@MuSTa1nE
blog: http://www.jspcore.com
Decoupling events from time with event sourcing and logs

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Decoupling events from time with event sourcing and logs