Beam exits incubation period and graduates to top-level Apache project, Google support and contribution to open source integration for various data processing backends and more.
Deep Learning is a rapidly evolving subfield of Machine Learning originating from Neural Networks. Recent algorithmic advances and utilization of GPU parallelization have resulted in Deep Learning based algorithms mastering the game of Go as well as several practical applications. The fashion industry is one of the target sectors for Deep Learning. Gilt is using Deep Learning for real world apps
Microsoft has developed and open sourced AirSim, a tool that can be used to simulate the flight of drones around the world. The simulator is built on the Unreal Engine and Microsoft will soon add support for robots and other types of vehicles.
Apache Flink 1.2 was announced and features dynamic rescaling, security, queryable state, and more. The release resolved 650 issues, maintains compatibility with all public APIs and ships with Apache Kafka 0.10 and Apache Mesos support. Flink’s dynamic rescaling allows one to change the parallelism of a streaming job or of an operator within the job.
MindMeld, a conversational AI company, has published The Conversational AI Playbook, a guide outlining the challenges and the steps to be made to create conversational applications.
Apache HBase 1.3.0 was released mid-January 2017 and ships with support for date-based tiered compaction and improvements in multiple areas, like write-ahead log (WAL), and a new RPC scheduler, among others. The release includes almost 1,700 resolved issues in total.
Apache Eagle, an open-source solution for identifying security and performance issues on big data platforms, graduates to Apache top level project on January 10, 2017. Firstly open-sourced by eBay on October 2015, Eagle was created to instantly detect access to sensitive data or malicious activities and, to take actions in a timely fashion.
In late 2016, Microsoft announced the general availability of Azure SQL Database In-Memory technologies. In-Memory processing is only available in Azure Premium database tiers and provides performance improvements for On-line Analytical Processing (OLTP), Clustered Columnstore Indexes and Non-clustered Columnstore Indexes for Hybrid Transactional and Analytical Processing (HTAP) scenarios.
Instacart is an online delivery service for groceries under one hour. Customers order the items on the website or using the mobile app, and a group of Instacart’s shoppers go to local stores, purchase the items and deliver them to the customer. InfoQ interviewed Mathieu Ripert, data scientist at Instacart, to find out how machine learning is leveraged to guarantee a better customer experience.
Stack Overflow recently announced making its dataset available through Google’s BigQuery. Using regular SQL statements, developers can query the full set of Stack Overflow data including posts, votes, tags, and badges. In this article we explore datasets that are available through Google's BigQuery platform.
Julien Nioche, director of DigitalPebble, PMC member and committer of the Apache Nutch web crawler project, talks about StormCrawler, a collection of reusable components to build distributed web crawlers based on the streaming framework Apache Storm. InfoQ interviewed Nioche, main contributor of the project, to find out more about StormCrawler and how it compares to other similar technologies.
A Facebook team has recently published a comparison of the performance of their existing Giraph-based graph processing system with the newer GraphX which is part of the popular Spark framework. Their conclusion is that GraphX is neither sufficiently scalable or performant to support their graph processing workloads.
Julien Le Dem, the PMC chair of the Apache Arrow project, presented on Data Eng Conf NY on the future of column-oriented data processing. Apache Arrow is an open-source standard for columnar in-memory execution. InfoQ interviewed Le Dem to find out the differences between Arrow and Parquet.
Couchbase 4.6 Developer Preview features full text search improvements, cross data center replication with globally-ordered conflict resolution and connectors for real-time analytics technologies: one for Spark 2.0 and the other for Kafka.
Apache Spark integration with deep learning library TensorFlow, online learning using Structured Streaming and GPU hardware acceleration were the highlights of Spark Summit EU 2016 held last week in Brussels.