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GridGain experts headed to next week's Spark+AI Summit 2019!
GridGain is a Silver Sponsor of next week's Spark+AI Summit 2019 in San Francisco and our own Alexey Zinovyev will deliver a session titled, "Distributed ML/DL with Ignite ML module using Apache Spark as database." The conference runs from April 23-25.
About his talk: The current implementation of Machine Learning (ML) algorithms in Spark has several disadvantages associated with the transition from standard Spark SQL types to ML-specific types, a low level of algorithms' adaptation to distributed computing, a relatively slow speed of adding new algorithms to the current library.
Previous Entries
In the previous blog post, I provided a quick summary of the first week of the Big Data Tour, where I am presenting on Apache® Ignite™. After returning home from the first week and able to rest over the weekend, I started the second week of the tour on Monday 10 September.
In this blog post, I will quickly summarise the second week of the tour. The second week required more travel as there were…
Join our free one-hour webinar on Sept. 19 at 11 a.m. Pacific Time for expert tips and tricks on managing your Apache® Ignite™ and/or GridGain deployment throughout its lifetime. Register here.
Once your cluster goes into production, you'll need to keep an eye on its state, too. These tasks might seem challenging, but managing and monitoring distributed systems is easy if you have a right…
With real-time streaming analytics there is no room (or time) for staging or disk.
Denis Magda, GridGain's director of product management and Apache Ignite PMC chair, delivered an excellent webinar Sept. 12 detailing the best practices used for real-time stream ingestion, processing and analytics using Apache® Ignite™, GridGain®, Apache Kafka™, Apache Spark™ and other technologies.
The webinar…
The full conference schedule was released today for the annual fourth annual In-Memory Computing Summit North America. Technical experts from American Airlines, ING Belgium, Salesforce.com, SberTech, Intel Corp., Oracle, Neeve Research, ScaleOut Software, Heimdall Data and more will lead the many conference breakout sessions.
The summit is happening October 2-3 at the conference center inside…
In my job at GridGain, I am privileged to work with some of the smartest and most talented people that I have ever met in my IT career. I am also fortunate in the variety of work that I get involved with. This includes presenting at meetups and conferences, building demos, writing blog posts, presenting webinars, occasionally writing and editing product documentation, and even contributing to the…
The fourth annual In-Memory Computing Summit North America is just around the corner -- happening Oct. 2-3 near San Francisco. I'm planning another community mixer so keep your evening free following the conference's first day. Details on that soon.
But first I need you to register! And here's a bonus for reading this post: I've loaded 5 FREE tickets to the conference when you use the promo code…
GridGain technology evangelist Akmal Chaudhri delivered the second webinar of his popular highly technical two-part series for software developers and architects on Aug. 28 titled, "In-Memory Computing Essentials for Architects and Developers: Part 2."
This free webinar was recorded and is available for playback (and the slides for download) here.
Akmal continued his introduction of more of the…
In this two-part series, we will look at how Apache® Ignite™ and Apache® Spark™ can be used together.
Let's briefly recap what we covered in the first article.
Ignite is a memory-centric distributed database, caching, and processing platform. It is designed for transactional, analytical, and streaming workloads, delivering in-memory performance at scale.
Spark is a streaming and compute engine…
Apache® Ignite™ is a very versatile product that supports a wide-range of integrated components. These components include a Machine Learning (ML) library that supports popular ML algorithms, such as Linear Regression, k-NN Classification and K-Means Clustering.
The ML capabilities of Ignite provide a wide-range of benefits, as shown in Figure 1. For example, Ignite can work on the data in-place…
In this two-part series, we will look at how Apache® Ignite™ and Apache® Spark™ can be used together.
Ignite is a memory-centric distributed database, caching, and processing platform. It is designed for transactional, analytical, and streaming workloads, delivering in-memory performance at scale.
Spark is a streaming and compute engine that typically ingests data from HDFS or other storage.…