2016年是深度学习之年，而且目前越来越多的人在加入这个，深度学习 + 大数据是目前一个很热门的趋势，所以spark中支持深度学习并且提供一个友好的API势在必行。
ppt下载：https://github.com/397090770/spark-summit-2017-Europe
高清视频下载：https://share.weiyun.com/4a186135b3213f1af2cd4cf6da1e3f9e
本次会议由很多比较值得关注的PPT，比如：Accelerating Shuffle A Tailor-Made RDMA Solution for Apache Spark、Deep Dive into Stateful Stream Processing in Structured Streaming、Deep Learning and Streaming in Apache Spark 2.x、Easy, Scalable, Fault-tolerant Stream Processing with Structured Streaming、An Adaptive Execution Engine for apache Spark SQL、Lessons From the Field Applying Best Practices to Your Apache Spark™ Applications等等。
下面的PPT是本次会议可下载的，已经全部上传到 GitHub 供大家下载：（GitHub）：进入GitHub下载本次会议全部PPT
A Tale of Three Apache Spark APIs RDDs, DataFrames & Datasets Accelerating Shuffle A Tailor-Made RDMA Solution for Apache Spark An Adaptive Execution Engine for apache Spark SQL Apache Spark Streaming + Kafka 0.10 An Integration Story Apache Spark Streaming Programming Techniques You Should Know Apache Spark-Bench Simulate, Test, Compare, Exercise, and Yes, Benchmark Apache Spark-and-Tensorflow-as-a-Service Apache Sparkpache HBase Connector Feature Rich and Efficient Access to HBase through Spark SQL Apache-Spark-Performance-Troubleshooting-at-Scale,-Challenges,-Tools,-and-Methodologies-with-Luca-Canali Approximate Computing for Stream Analytics in Apache Spark Art of Feature Engineering For Data Science Best Practices for Using Alluxio with Spark Beyond unit tests Testing for SparkHadoop workflows Build, Scale, and Deploy Deep Learning Pipelines Using Apache Spark Building Custom ML PipelineStages for Feature Selection Building a Business Logic Translation Engine with Spark Streaming for Communicating Between Legacy Code and Microservices Building machine learning algorithms on Apache Spark Deduplication and Author-Disambiguation of Streaming Records via Supervised Models based on Content Encoders Deep Dive into Stateful Stream Processing in Structured Streaming Deep Learning and Streaming in Apache Spark 2.x Digitalising the Core How Analytics is Shaping the Energy Industry Dr. Elephant Achieving Quicker, Easier, and Cost-Effective Big Data Analytics Easy, Scalable, Fault-tolerant Stream Processing with Structured Streaming Experimental Design for Distributed Machine Learning Extending Spark SQL Data Sources APIs with Join Push Down Extending Spark's Ingestion Build Your Own Java Data Source Fast Data with Apache Ignite & Apache Spark Feature Hashing for Scalable Machine Learning Fire in the Sky An Introduction to Monitoring Apache Spark in the Cloud From pipelines to refineries scaling big data applications High Performance Enterprise Data Processing with Apache Spark Hotels.com's Journey to Becoming an Algorithmic Business How to share state across multiple Spark jobs using Apache Ignite Indicium Interactive Querying at Scale Lessons From the Field Applying Best Practices to Your Apache Spark Applications Lessons Learned Developing and Managing Massive (300TB+) Apache Spark Pipelines in Production Lessons Learned while Implementing a Sparse Logistic Regression Algorithm in Spark Low touch machine learning Lucid Genetic Programming Library for Apache Spark MatFast In-Memory Distributed Matrix Computation Processing and Optimization Based on Spark SQL Natural Language Understanding at Scale with Spark-Native NLP, Spark ML, and TensorFlow Near Data Computing Architectures Opportunities and Challenges for Apache Spark Next CERN Accelerator Logging Service A road to Big Data One-Pass Data Science In Apache Spark With Generative T-Digests Optimal Strategies for Large-Scale Batch ETL Jobs Parallelizing Large Simulations with Apache SparkR Preventing Revenue Leakage and Monitoring Distributed Systems with Machine Learning Productionizing Behavioural Features for Machine Learning with Apache Spark Streaming Real-Time Image Recognition with Apache Spark Real-time Detection Of Anomalies In The Database Infrastructure Using Apache Spark Real-time Machine Learning with Redis-ML and Apache Spark Running Spark Inside Docker Containers Saving energy with Apache Spark and Toon Scaling Your Skillset with Your Data Smack Stack and Beyond Building Fast Data Pipelines Spark Pipelines in the Cloud with Alluxio Spatial Processing of Global Heat Maps with Apache Spark Speedup Spark Applications using FPGA Accelerators on the cloud Storage Engine Considerations for your Apache Spark Applications Story Deduplication and Mutation Supporting Highly Multitenant Spark Notebook Workloads Tagging Text in Money Transfers A Use-Case of Spark in Banking The state of spark in the cloud Using Pluggable Apache Spark SQL Filters to Help GridPocket Users Keep Up with the Jones' (and save the planet) Using Spark in the Cloud A Devops perspective VEGAS The Missing Matplotlib for ScalaApache Spark VariantSpark Apache Spark for Bioinformatics Web-Scale Graph Analytics with Apache Spark Working with Skewed Data The Iterative Broadcast
本地址只下载了本次会议的部分视频（共42个），如果需要全部的视频，请自行到 https://spark-summit.org/eu-2017/schedule/ 里面选择观看。
本博客文章除特别声明，全部都是原创！
