Skip to main content

Posts

Showing posts with the label Apache Ignite

Apache Ignite - Internals

We have learnt about What is Apache Ignite? , Setting up Apache Ignite and few quick examples in last few posts. In this post, we will deep dive into Apache Ignite core Ignite classes and discuss about following internals. Core classes Lifecycle events Client and Server mode Thread pools configurations Asynchronous support in Ignite Resource injection Core classes Whenever you will be interacting with Apache Ignite in application, you will always encounter Ignite interface and Ignition class. Ignition is the main entry point to create a Ignite node. This class provides various methods to start a grid node in the network topology. // Starting with default configuration Ignite igniteWithDefaultConfig = Ignition.start(); // Ignite with Spring configuration xml file Ignite igniteWithSpringCfgXMLFile = Ignition.start("/path_to_spring_configuration_xml.xml"); // ignite with java based configuration IgniteConfiguration icfg = ...; Ignite igniteWithJavaConfigurat

Apache Ignite - Examples on Data grid, compute grid, service grid and executing SQL queries

In this article, we will show few examples on using Apache Ignite as Compute Grid, Data Grid, Service Grid and executing SQL queries on Apache Ignite. These are basic examples and use the basic api available. There will be few posts in near future which explains the available API in Compute Grid, Service Grid and Data Grid. Ignite SQL Example Apache Ignite comes with JDBC Thin driver support to execute SQL queries on the In memory data grid. In the example below, we will create tables, insert data into tables and get data from tables. I will assume that you are running Apache Ignite on your local environment otherwise please read setup guide for running Apache Ignite server. Creating Tables try (Connection conn = DriverManager.getConnection("jdbc:ignite:thin://127.0.0.1/"); Statement stmt = conn.createStatement();) { //line 1 stmt.executeUpdate("CREATE TABLE City (id LONG PRIMARY KEY, name VARCHAR) WITH \"template=replicated\"");

Apache Ignite - Setup guide

In this post, we will discuss about setting up Apache Ignite. Installation You can download the Apache Ignite from its official site . You can download the binary , sources , Docker or Cloud images and maven . There is also a third party support from GridGain. Steps for binary installation This is pretty straightforward installation. Download the binary from website. You can optionally setup installation path as IGNITE_HOME . To run Ignite as server, you need to run below command on terminal. /bin/ignite.bat // If it is Windows /bin/ignite.sh //if it is Linux The above command will run the Ignite with default configuration file under $IGNITE_HOME/config/default-config.xml , you can pass your own configuration file with following command /bin/ignite.sh config/ignite-config.xml Steps for building from sources If you are likely to build everything from sources, than follow the steps listed below. # Unpack the source package $ unzip -q apache-ignite-{version}-src.zip $ cd ap

Introduction to Apache Ignite

This is an introduction series to Apache Ignite. We will discuss about Apache Ignite, its features, usage as in-memory data grid, compute grid, distributed caching, near real-time caching and persistence distributed database. What is Ignite? It is in-memory compute platform . It is in-memory data grid . Durable , strongly consistent and highly available. Providing option to run SQL like queries on cache (Providing JDBC API to support this). Durable memory Apache Ignite is memory-centric platform based on durable memory architecture. It allows you to store and processing data on in-memory(RAM) and on disk (If Ignite Native persistence is enabled). When the Ignite native persistence is enabled, it will treat disk as superset of data, which is cable of surviving crash and restarts. In-memory features RAM is always treated as first memory tier, all the processing happens there. It has following characteristics. Off-heap based: All the data and indexes are stored outs