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How to Fast Load Large Datasets into Apache Ignite by Using a Key-Value API

Now, in-memory cache technology is becoming popular, motivating companies to experiment with distributed systems. The technology is advertised to be fast, and data-load speed is often critical for building a successful solution prototype. This blog post provides a technical tutorial on how to populate a distributed Apache Ignite cluster with values that originate from large relational tables. All the code in the tutorial is available from the FastDataLoad repository at the GitHub.
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Previous Entries

Two events in rather exotic locals are keeping GridGain experts busy this week – the Shanghai In-Memory Computing Meetup and the Open Data Science Meetup Saint Petersburg Meetup.   In Shanghai this evening (March 13), GridGain Asia-Pac solutions architect Stephen Leung is explaining how combining Apache® Ignite™ with a Relational DBMS gives companies a highly scalable, high-velocity grid-based…
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It’s a webinar trifecta next week with the focus on Apache® Ignite™ covering troubleshooting, Node.js and scalable full-text search.   As always, the webinars are free and will also be recorded. So if you miss one live, just register as usual to access to recording as well as the slides.   Tuesday, March 19: “Troubleshooting Apache Ignite.” Whether you are getting started with Apache Ignite…
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GridGain Systems will be hosting and/or participating in several industry events during March and April, where the company’s experts will share the latest information and developments related to in-memory computing technology and business trends. Let's take a closer look at these upcoming events (conferences, webinars and meetups). Conferences Big Data Paris 2019 – March 11-12, 2019 –…
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When the Ignite project emerged in the Apache Software Foundation, it was thought of as a pure in-memory-solution: a distributed cache that put data into memory to speed access time. But then in 2017 came Apache® Ignite™ 2.1, which saw the debut of Ignite’s Native Persistence module that allowed Ignite to be treated as a full-blown distributed database. Since then Ignite has not depended on an…
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GridGain today announced the availability of GridGain Community Edition (GCE) -- a hardened, high-performance, open source in-memory computing platform. Built on Apache® Ignite™, GCE includes additional functionality, tuning and patches developed by GridGain® to deliver optimal performance. It is available under the GridGain Community Edition License. (Download GCE.) GridGain Community Edition…
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Join technology evangelist Akmal Chaudhri for his free one-hour webinar on March 6 and learn what's new in Apache® Ignite™ version 2.7.  You'll learn how the new capabilities of Apache Ignite work and will also better understand more about some of the other changes made to Apache Ignite, and the reasoning behind them. Come with your questions, and learn from the questions of your peers. Topics…
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TensorFlow is the most popular deep learning framework.  Of course, all deep learning initiatives require data. The classical data-feeding approach is based on files in different formats: data is extracted from production system, written into files and then data scientists are able to train deep learning models using these files as a datasource. But if the amount of data is big -- or it's not…
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The third-annual In-Memory Computing Summit Europe 2019 is just three months away. A preview of breakout sessions was released today for the two-day conference, happening June 3-4 at the Park Plaza Victoria London. The breakout session speakers include representatives from Capital One, Cerner Corporation, Confluent, GigaSpaces, Hypi, Red Hat and Teradata. A Super Saver General Admission rate of…
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It’s Wednesday, but with four meetups across three countries along with one live webinar, the week is just getting started for some of our GridGain and Apache® Ignite™experts.   If you happen to be in Silicon Valley, Paris or Moscow, then you can join us in person for a meetup. For everyone else, there’s today’s webinar: “Troubleshooting Apache Ignite.” The great thing about our webinars is…
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Introduction In the first article in this series, we installed Node.js, the Node.js Thin Client package for Ignite and tested an example application. In this article, let's look at a particular scenario where Ignite can really help when working with existing data from another source, such as a Relational Database System. Often in industry, there are systems that have great business value. These…
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