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SIMPLIFYING STREAMING ANALYTICS

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Cassandra Summit 2015

Brenden Matthews @brndnmtthws

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AGENDA

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• Introduction • Streaming analytics:

• What is it? • Why do it? • When do I need it? • How? - Demo! • What are the limitations?

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ABOUT ME - BRENDEN MATTHEWS

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• ASF member, Mesos committer • Have contributed to a number of related OSS projects,

including Spark, Storm, Kafka, Presto, and a number of Mesos schedulers

• SA @Mesosphere, formerly on the DI team @Airbnb

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STREAMING ANALYTICS: WHAT IS IT?

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Indeed.

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STREAMING ANALYTICS: WHAT IS IT?

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• Perform joins, aggregations, mutations on data as it happens

• Components typically include: • Producer • Message broker • [E] Consumer • [T] Processing engine • [L] Storage

© 2015 Mesosphere, Inc. All Rights Reserved.

STREAMING ANALYTICS: WHAT IS IT?

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• Perform joins, aggregations, mutations on data as it happens

• Components typically include: • Producer • Message broker • [Extract] Consumer • [Transform] Processing engine • [Load] Storage

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STREAMING ANALYTICS: WHY DO IT?

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• Data is constantly being generated • HTTP traffic, clickstream, IoT, metrics

• Most data is correlated (requires joins) • Data can be pre-denormalized (i.e.,

flattened) • Immutability • Build “real time” services—what’s

happening right now? • Compute once

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STREAMING ANALYTICS: WHEN DO I NEED IT?

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• Messaging platform • Compliance • Fraud detection • Firehose consumption • Recommendation engine

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STREAMING ANALYTICS: HOW?

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Producer

Broker

Consumer/ML

Storage

Pipeline

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STREAMING ANALYTICS: HOW?

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Pipeline

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STREAMING ANALYTICS: HOW?

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Demo time!

github.com/mesosphere/iot-demo

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STREAMING ANALYTICS: WHAT ARE THE LIMITATIONS?

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• Not a replacement for all batch workloads

• Backfilling is tricky • Unless you retain a log of all data

mutations, backfilling my be impossible

• Maintaining a completely immutable system may explode storage costs

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QUESTIONS?

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