Stratosphere. Next Generation Big Data Analytics Platform from Europe

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1 Stratosphere Next Generation Big Data Analytics Platform from Europe Márton Balassi Data Mining and Search Group 1 Big Data Business Intelligence Group 1 1 Computer and Automation Research Institute of the Hungarian Academy of Sciences May 11, 2014

2 Table of Contents Motivation Project info

3 Motivation Table of contents Motivation Project info

4 Motivation The Big Data scene The Big Data scene What s all the hype for? Data acquisition is cheap Eva Andreasson (Cloudera), 2014 Data storage is cheap Data Science is the Sexiest Job of the 21st century It s a piece of cake...

5 Motivation The Big Data scene The Big Data scene What s all the hype for? Data acquisition is cheap Data storage is cheap Matthew Komorowski, 2014 Data Science is the Sexiest Job of the 21st century It s a piece of cake...

6 Motivation The Big Data scene The Big Data scene What s all the hype for? Data acquisition is cheap Data storage is cheap Data Science is the Sexiest Job of the 21st century Harvard Business Review, 2012 It s a piece of cake...

7 Motivation The Big Data scene The Big Data scene What s all the hype for? Data acquisition is cheap Data storage is cheap Data Science is the Sexiest Job of the 21st century It s a piece of cake...

8 Motivation The Big Data scene The Big Data scene What s all the hype for? Data acquisition is cheap Data storage is cheap Data Science is the Sexiest Job of the 21st century It s a piece of cake... Or is it?

9 Motivation The Big Data scene The Big Data scene Image courtesy of Matt Turck and Shivon Zilis

10 Table of contents Motivation Project info

11 A European project just accepted to the Apache Incubator Declarative programming (native language bindings) Schema-on-read (HDFS, databases,... ) Rich programming model (beyond MapReduce) User-defined functions as first-class citizens Automated parallelization and optimization Efficient and scalable execution engine Intensive development

12 A European project just accepted to the Apache Incubator Declarative programming (native language bindings) Schema-on-read (HDFS, databases,... ) Rich programming model (beyond MapReduce) User-defined functions as first-class citizens Automated parallelization and optimization Efficient and scalable execution engine Intensive development

13 A European project just accepted to the Apache Incubator Declarative programming (native language bindings) Schema-on-read (HDFS, databases,... ) Rich programming model (beyond MapReduce) User-defined functions as first-class citizens Automated parallelization and optimization Efficient and scalable execution engine Intensive development

14 A European project just accepted to the Apache Incubator Declarative programming (native language bindings) Schema-on-read (HDFS, databases,... ) Rich programming model (beyond MapReduce) User-defined functions as first-class citizens Automated parallelization and optimization Efficient and scalable execution engine Intensive development

15 A European project just accepted to the Apache Incubator Declarative programming (native language bindings) Schema-on-read (HDFS, databases,... ) Rich programming model (beyond MapReduce) User-defined functions as first-class citizens Automated parallelization and optimization Efficient and scalable execution engine Intensive development

16 A European project just accepted to the Apache Incubator Declarative programming (native language bindings) Schema-on-read (HDFS, databases,... ) Rich programming model (beyond MapReduce) User-defined functions as first-class citizens Automated parallelization and optimization Efficient and scalable execution engine Intensive development

17 A European project just accepted to the Apache Incubator Declarative programming (native language bindings) Schema-on-read (HDFS, databases,... ) Rich programming model (beyond MapReduce) User-defined functions as first-class citizens Automated parallelization and optimization Efficient and scalable execution engine Intensive development

18 Contributors

19 1. Thou shalt use declarative programming 1. Thou shalt use declarative programming K-Means Clustering in Stratosphere s Scala front-end

20 2. Thou shalt accept external (dynamic) sources 2. Thou shalt accept external (dynamic) sources In situ data no load

21 3. Thou shalt use rich primitives 3. Thou shalt use rich primitives Beyond MapReduce

22 3. Thou shalt use rich primitives 3. Thou shalt use rich primitives Beyond MapReduce

23 4. Thou shalt deeply embed UDFs 4. Thou shalt deeply embed UDFs Flexible and transparent

24 5. Thou shalt optimize 5. Thou shalt optimize Auto-parallelization and optimization as in relational databases

25 6. Thou shalt iterate 6. Thou shalt iterate Needed for most interesting analysis cases

26 7. Thou shalt use a scalable and efficient execution engine 7. Thou shalt use a scalable and efficient execution engine Reliable and robust infrastructure

27 8. Thou shalt tackle streaming 8. Thou shalt tackle streaming Integration of low latency jobs

28 9. Thou shalt provide a common API through the whole framework 9. Thou shalt provide a common API through the whole framework Batch? BSP? Streaming? You just write the same code...

29 10. Thou shalt support the lambda architecture 10. Thou shalt support the lambda architecture Combine the reliability of batch and the speed of streaming to enable real-time queries on large datasets Batch 1... Batch n 1 First hour of input... 1 to 2 hours old input Less than an hour old input Output Streaming 1... Streaming n 1 Streaming n

30 Project info Table of contents Motivation Project info

31 Project info Where to look for us Where to look for us Project homepage The project can be found at stratosphere.eu. The homepage served as a source for the code and most of the pictures presented on these slides. Data Mining and Search & Big Data BI Groups The webpage of Budapest team members research groups can be found at dms.sztaki.hu and at bigdatabi.sztaki.hu. Márton Balassi

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