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503 lines
15 KiB
503 lines
15 KiB
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<title>Flink Forward 2018</title> |
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<meta name="description" content="Colocando uma aplicação Flask em produção em 40 minutos (ou menos)"> |
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<meta name="author" content="Julio Biason"> |
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Flink Forward 2018 |
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<!-- Deployment and FLIP-6 --> |
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<!-- Metrics, Monitoring and Troubleshooting --> |
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<img src="_images/ff_monitoring2.png" alt=""/> |
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<thead> |
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<th>Keynotes</th> |
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What turns stream processing from a tool into a platform?<br/> |
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<small>Stephan Ewen, data Artisans</small> |
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Stream Processing Revolutionizing Big Data<br/> |
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<small> |
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Srikanth Satya, Dell EMC |
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</small> |
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Apache Flink + Apache Beam: Expanding the horizons of Big Data<br/> |
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<small> |
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Anand Iyer, Google Cloud |
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</small> |
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<thead> |
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<th>11:00</th> |
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</thead> |
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Powering Yelp’s Data Pipeline Infrastructure with Apache Flink</br><small>Enrico Canzonieri, Yelp Inc.</small> |
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</td> |
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<td class="seen"> |
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Scaling stream data pipelines <br/><small>Flavio Junqueira, Pravega by DellEMC</small> |
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</td> |
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<aside class="notes"> |
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- Pravega |
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- Kinda like Kafka |
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- Auto-partition |
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- When a partition is created or destroyed a Flink TaskManager is created/destroyed |
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- Pravega requires a key already |
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</aside> |
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</tr> |
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<td> |
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Building a scalable focused web crawler with Flink <br/><small>Ken Krugler, Scale Unlimited</small> |
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</td> |
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</tr> |
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</tbody> |
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</table> |
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</section> |
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<img src="_images/ff_pravega.png" alt=""/> |
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<thead> |
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<th>11:50</th> |
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</thead> |
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<td>Building Flink As a Service platform at Uber</br><small>Shuyi Chen, Uber</small></td> |
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<td class="seen">eBay monitoring platform preprocessing and alerting on Flink</br><small>Garret Li, ebay</small></td> |
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<aside class="notes"> |
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- Sherlock.IO |
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- "The Frink", nervous |
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- Policy changes go through the pipeline |
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- https://vimeo.com/265025956/c7d5576622 |
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</aside> |
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<td>Using Flink for balances and controls across platform boundaries<br/><small>Faraz Babar, American Express</small></td> |
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</tr> |
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</tbody> |
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<img src="_images/ff_sherlock.jpg" alt=""/> |
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<thead> |
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<tr><th>12:20</th></tr> |
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<tr><td>Scaling Flink in Cloud<br/><small>Steven Wu, Netflix</small></td></tr> |
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<tr><td>Flink real-time analysis in CloudStream Service of Huawei Cloud<br/><small>Jinkui Shi, Huawei</small></td></tr> |
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<td class="seen">Why and how to leverage the simplicity and power of SQL on Flink<br/><small>Fabian Hueske, data Artisans</small></td> |
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<aside class="notes"> |
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- Built-in in Flink 1.5 |
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- Can create pipelines on the fly |
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- Launches TaskManagers |
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</aside> |
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</tr> |
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</tbody> |
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</section> |
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<img src="_images/ff_sql.png" alt=""/> |
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<table> |
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<thead><tr><th>2:00</th></tr></thead> |
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<tbody> |
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<tr><td>Optimizations in Blink Runtime for Global Shopping Festival at Alibaba<br><small>Feng Wang, Alibaba </small></td></tr> |
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<tr> |
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<td class="seen">Bootstrapping State In Apache Flink<br/><small>Gregory Fee, Lyft </small></td> |
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<aside class="notes"> |
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- Lyft |
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- Grouping all information, including old ones |
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- Required for information of all rides of all users over all the time |
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- Old data on S3, new data on Kafka |
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- Multiple inputs |
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- Old input will hold new input |
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</aside> |
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<tr><td>Panta Rhei: designing distributed applications with streams<br/><small> Aris Koliopoulos, Drivetribe </small></td></tr> |
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</tbody> |
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<img src="_images/ff_lyft.png" alt=""/> |
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<table> |
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<thead><tr><th>2:50</th></tr></thead> |
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<tbody> |
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<tr><td> Powering Tensorflor with Big Data (Apache BEAM & Flink) <br/><small> Holden Karau, Google Cloud </small></td></tr> |
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<tr><td class="seen">Alibaba’s common algorithm platform on Flink<br/><small> Xu Yang, Alibaba </small></td></tr> |
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<tr><td> Cloud Native Flink <br/><small> Jowanza Joseph, One Click Retail </small></td></tr> |
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<thead><tr><th>3:20</th></tr></thead> |
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<tbody> |
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<tr><td> Embedding Flink Throughout an Operationalized Streaming ML Lifecycle <br/><small> Dave Torok, Comcast Corporation </small></td></tr> |
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<tr><td>Scaling Uber’s Realtime Optimization with Apache Flink <br/><small> Xingzhong Xu, Uber Technologies Inc. </small></td></tr> |
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<tr> |
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<td class="seen"> Operating Flink on Mesos at Scale <br/><small> Jörg Schad, Mesosphere </small></td> |
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<aside class="notes"> |
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- Basically, the same Kubernetes does |
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- Use of Kube or Mesos is a personal choice |
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</aside> |
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<thead><tr><th>4:30</th></tr></thead> |
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<tbody> |
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<td class="seen"> Finding Bad Acorns <br/><small> Andrew Gao, Capital One </small></td> |
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<aside class="notes"> |
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- Teller validation |
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- Python integration (because data scientists use Jupyter) |
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- Queryable state |
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- Broke the monolith |
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</aside> |
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</tr> |
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<tr><td> dA Platform – Production-ready stream processing with Apache Flink <br/><small> Robert Metzger, data Artisans </small></td></tr> |
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<tr><td> Real-time monitoring of Mobile Internet Quality of Experience using Flink <br/><small> David Reniz, Everis </small></td></tr> |
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</tbody> |
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</table> |
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</section> |
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<thead><tr><th>5:20</th></tr></thead> |
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<tbody> |
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<tr><td> How to build a modern stream processor: The science behind Apache Flink <br/><small> Stefan Richter, data Artisans </small></td></tr> |
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<tr> |
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<td class="seen"> Testing Stateful Streaming Applications <br/><small> Seth Wiesman, MediaMath </small></td> |
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<aside class="notes"> |
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- Math guy |
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- Test pipeline, break pipeline to test checkpoint |
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- WHYYYYY?!?!?! |
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</aside> |
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</tr> |
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<tr><td> Extending Flink metrics: Real-time BI atop existing Flink streaming pipelines <br/><small> Andrew Torson, Walmart Labs </small></td></tr> |
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</tbody> |
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</table> |
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</section> |
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</section> |
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