Spark Summit 2016 Europe全部PPT下载[共75个]

　　Spark Summit 2016 Europe会议于2016年10月25日至10月27日在布鲁塞尔进行。本次会议有上百位Speaker，来自业界顶级的公司。官方日程：https://spark-summit.org/eu-2016/schedule/。

　　由于会议的全部资料存储在http://www.slideshare.net网站，此网站需要翻墙才能访问。基于此本站收集了本次会议的所有PPT资料供大家学习交流之用。本次会议PPT资料全部通过爬虫程序下载，可能会导致PPT出现问题请及时联系我修复。

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会议内容

Simplifying Big Data Applications with Apache Spark 2.0
The Next AMPLab: Real-Time, Intelligent, and Secure Computing
MmmooOgle: From Big Data to Decisions for Dairy Cows
Mentor and Mentee Relations Based on Authorship Graphs
Spark's Performance: The Past, Present, and Future
Automatic Checkpointing in Spark
High-Throughput Genomics at Your Fingertips with Apache Spark
How to Connect Spark to Your Own Datasource
Effective Spark with Alluxio
Dynamic On-the-Fly Modifications of Spark Applications
Making the Switch: Predictive Maintenance on Railway Switches
Dynamic Resource Allocation, Do More With Your Cluster
Lessons Learned Optimizing NoSQL for Apache Spark
Data-Aware Spark
Vegas, the Missing MatPlotLib for Spark
A Deep Dive into the Catalyst Optimizer
Lambda Architecture with Spark in the IoT
Scaling Factorization Machines on Spark Using Parameter Servers
OrderedRDD: A Distributed Time Series Analysis Framework for Spark
SparkLint: a Tool for Monitoring, Identifying and Tuning Inefficient Spark Jobs Across Your Cluster
Performance Characterization of Apache Spark on Scale-up Servers
Origin-Destination Matrix Using Mobile Network Data with Spark
How We Built an Event-Time Merge of Two Kafka-Streams with Spark Streaming
Sparkling Water 2.0: The Next Generation of Machine Learning on Apache Spark
Boosting Spark Performance on Many-Core Machines
From Single-Tenant Hadoop to 3000 Tenants in Apache Spark: Experiences from Watson Analytics
Spark and Object Stores —What You Need to Know
Better Together: Fast Data with Apache Spark and Apache Ignite
On-Premise Spark-as-a-Service for Swedish Researchers
Mastering Spark Unit Testing
Get Rid of Traditional ETL, Move to Spark!
SparkSheet—Transforming Spreadsheets into Spark DataFrames
Hive to Spark—Journey and Lessons Learned
Apache Spark 2.0 Performance Improvements Investigated With Flame Graphs
Glint: An Asynchronous Parameter Server for Spark
Accelerating Spark Machine Learning with Redis Modules
Democratizing AI with Apache Spark
Extreme-scale Ad-Tech using Spark and Databricks at MediaMath
The Spark (R)evolution in The Netherlands
From Machine Learning to Learning Machines: Creating an End-to-End Cognitive Process with Apache Spark™
How Apache Spark Is Helping Tame the Wild West of Wi-Fi
The Potential of GPU-driven High Performance Data Analytics in Spark
Time Series Analysis with Spark in the Automotive R&D Process
TensorFrames: Deep Learning with TensorFlow on Apache Spark
Using SparkR to Scale Data Science Applications in Production: Lessons From the Field
Talk Data to Me: Sparking Insights at Elsevier
Finding Outliers in Streaming Data: A Scalable Approach
MLeap and Combust.ML: Deploying Machine Learning Models to Production
Mobility Insights at Swisscom: Understanding Collective Mobility in Switzerland
Building Data Pipelines with Spark and StreamSets
Fusing Apache Spark and Lucene for Near-Realtime Predictive Model Building
Just Enough Scala for Spark
Apache Spark at Scale: A 60 TB+ Production Use Case
Paddling Up the Stream
Online Learning with Structured Streaming
Apache Kudu and Spark SQL for Fast Analytics on Fast Data
Spark Streaming at Bing Scale
Spark—Universal Computation Engine for Processing Oil Industry Data
Prediction as a Service with Ensemble Model Trained in SparkML on 1 billion Observed Flight Prices Daily
SparkOscope: Enabling Apache Spark Optimization Through Cross-Stack Monitoring and Visualization
Adopting Dataframes and Parquet in an Already Existing Warehouse
A Journey from Scikit-learn to Spark
Problem Solving Recipes Learned from Supporting Spark
Spark and Couchbase—Augmenting the Operational Database with Spark
Spark Cluster with Elasticsearch Inside
Build Your Next Apache Spark Job in .NET Using Mobius
Extending Spark with Java Agents
No One Puts Spark in the Container
Spark SQL 2.0 Experiences Using TPC-DS
Containerized Spark on Kubernetes
Productizing a Spark and Cassandra Based Solution in Telecom
Spark Streaming in a Multitenant World
Solving the App Market with Only Grit, Hustle, and a Spark Cluster
How Spark is Enabling the New Wave of Converged Applications
Distributed Computing with Spark for Actionable Business Insights