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Posted to notifications@ignite.apache.org by as...@apache.org on 2023/05/05 09:18:40 UTC
[ignite-website] branch master updated: IGNITE-19382: update Ignite Summit banners (#164)
This is an automated email from the ASF dual-hosted git repository.
ashapkin pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/ignite-website.git
The following commit(s) were added to refs/heads/master by this push:
new 63fb9b6c92 IGNITE-19382: update Ignite Summit banners (#164)
63fb9b6c92 is described below
commit 63fb9b6c928c153c2f4c1bb58a50fab0071ccc14
Author: Erlan Aytpaev <ay...@gmail.com>
AuthorDate: Fri May 5 12:18:34 2023 +0300
IGNITE-19382: update Ignite Summit banners (#164)
* IGNITE-19382: update banners
* IGNITE-19382: format blog pages
* IGNITE-19382: optimize the building process
---
_src/_blog/apache-ignite-2-12-0.pug | 4 +-
_src/index.pug | 17 +-
blog/1/index.html | 895 +++++++++++++++++----
blog/2/index.html | 677 ++++++++++++----
blog/apache-ignite-1-9-released.html | 712 ++++++++++++----
blog/apache-ignite-2-0-redesigned.html | 746 +++++++++++++----
blog/apache-ignite-2-1-a.html | 750 +++++++++++++----
blog/apache-ignite-2-10-thin.html | 757 ++++++++++++++----
blog/apache-ignite-2-11-1.html | 710 ++++++++++++----
blog/apache-ignite-2-11-stabilization.html | 769 ++++++++++++++----
blog/apache-ignite-2-12-0.html | 745 +++++++++++++----
blog/apache-ignite-2-13-0.html | 737 +++++++++++++----
blog/apache-ignite-2-3-more.html | 720 +++++++++++++----
blog/apache-ignite-2-4-brings.html | 726 +++++++++++++----
blog/apache-ignite-2-5-scaling.html | 769 ++++++++++++++----
blog/apache-ignite-2-7-deep.html | 699 ++++++++++++----
blog/apache-ignite-2-9-released.html | 700 ++++++++++++----
blog/apache-ignite-community-news-september.html | 847 ++++++++++++++++----
blog/apache-ignite-community-update-august.html | 764 ++++++++++++++----
blog/apache-ignite-essentials-series-for.html | 687 ++++++++++++----
blog/apache-ignite-momentum-highlights-from.html | 736 +++++++++++++----
blog/apache/1/index.html | 697 ++++++++++++----
blog/apache/index.html | 898 +++++++++++++++++----
blog/bigdata/index.html | 748 +++++++++++++----
blog/biodata/index.html | 674 ++++++++++++----
blog/computing/index.html | 678 ++++++++++++----
blog/data/index.html | 690 ++++++++++++----
blog/database/index.html | 892 +++++++++++++++++----
blog/fast/index.html | 673 ++++++++++++----
blog/grid/index.html | 667 +++++++++++----
blog/ignite-2-8-released-less.html | 738 +++++++++++++----
blog/ignite/1/index.html | 824 +++++++++++++++----
blog/ignite/index.html | 935 ++++++++++++++++++----
blog/imdb/index.html | 667 +++++++++++----
blog/in-memory/index.html | 792 ++++++++++++++----
blog/in/index.html | 680 ++++++++++++----
blog/index.html | 931 +++++++++++++++++----
blog/key-value/index.html | 672 ++++++++++++----
blog/learning/index.html | 718 +++++++++++++----
blog/log4j2/index.html | 680 ++++++++++++----
blog/machine/index.html | 718 +++++++++++++----
blog/meetup/index.html | 675 ++++++++++++----
blog/meltdown-and-spectre-patches-show.html | 705 ++++++++++++----
blog/meltdown/index.html | 700 ++++++++++++----
blog/memory/index.html | 680 ++++++++++++----
blog/nodal/index.html | 673 ++++++++++++----
blog/open-source/index.html | 736 +++++++++++++----
blog/open/index.html | 708 ++++++++++++----
blog/performance/index.html | 676 ++++++++++++----
blog/presenting-apache-ignite-sql-grid.html | 693 ++++++++++++----
blog/protecting-apache-ignite-from-meltdown.html | 742 +++++++++++++----
blog/rdbms/index.html | 691 ++++++++++++----
blog/release/index.html | 766 ++++++++++++++----
blog/security/index.html | 700 ++++++++++++----
blog/source/index.html | 708 ++++++++++++----
blog/spark/index.html | 675 ++++++++++++----
blog/spectre/index.html | 700 ++++++++++++----
blog/sql/index.html | 738 +++++++++++++----
blog/store/index.html | 672 ++++++++++++----
blog/two/index.html | 694 ++++++++++++----
css/frontpage.css | 7 +-
gulpfile.js | 21 +-
images/promos/Ignite-Summit-banner-square.jpg | Bin 142168 -> 200449 bytes
images/promos/ignite-Summit-call-for-speakers.jpg | Bin 988350 -> 819189 bytes
img/events/banner-bott-5.jpg | Bin 577327 -> 413604 bytes
index.html | 18 +-
66 files changed, 33858 insertions(+), 8659 deletions(-)
diff --git a/_src/_blog/apache-ignite-2-12-0.pug b/_src/_blog/apache-ignite-2-12-0.pug
index fac79aca8a..902b497606 100644
--- a/_src/_blog/apache-ignite-2-12-0.pug
+++ b/_src/_blog/apache-ignite-2-12-0.pug
@@ -86,8 +86,8 @@ p Example of query:
code.lang-java
pre // Find the persons who work in Organization 1 and have salary more than 1,000.
- pre QueryCursor<Cache.Entry<Integer, Person>> cursor = cache.query(
- pre new IndexQuery<Integer, Person>(Person.class, "ORG_SALARY_IDX")
+ pre QueryCursor<Cache.Entry<Integer, Person>> cursor = cache.query(
+ pre new IndexQuery<Integer, Person>(Person.class, "ORG_SALARY_IDX")
pre .setCriteria(eq("orgId", 1), gt("salary", 1000))
pre );
diff --git a/_src/index.pug b/_src/index.pug
index fac86a77c0..ee5889af2a 100644
--- a/_src/index.pug
+++ b/_src/index.pug
@@ -70,6 +70,14 @@ block main
// /.frontcard
// /.fronttopcards
+ .container.event-featured.fronteventsbanner
+ p.capstext Featured Event
+ a(href="https://ignite-summit.org/2023-june/", target="_blank").event-featured__banner.pt-5
+ picture
+ source(srcset="/images/promos/ignite-Summit-call-for-speakers.jpg" media="(max-width: 767px)")
+ img(src="/images/promos/ignite-Summit-call-for-speakers.jpg", alt="Ignite Summit call for speakers")
+ // /.event-featured
+
.container.forntcodes
@@ -529,15 +537,6 @@ block main
// /.frontconfs
- section.event-featured.container.fronteventsbanner
- p.capstext Featured Event
- a(href="https://ignite-summit.org/2023-june/", target="_blank").event-featured__banner.pt-5
- picture
- source(srcset="/images/promos/ignite-Summit-call-for-speakers.jpg" media="(max-width: 767px)")
- img(src="/images/promos/ignite-Summit-call-for-speakers.jpg", alt="Ignite Summit call for speakers")
- // /.event-featured
-
-
section.frontresourse.container
diff --git a/blog/1/index.html b/blog/1/index.html
index 6d424f4324..1ebde5f4aa 100644
--- a/blog/1/index.html
+++ b/blog/1/index.html
@@ -1,153 +1,754 @@
-<!DOCTYPE html><html lang="en"><head><meta charset="UTF-8"><meta name="viewport" content="width=device-width, initial-scale=1.0, maximum-scale=1"><title>Blogging in Action</title><link rel="canonical" href="https://ignite.apache.org/blog"><meta property="og:title" content="Blogging in Action"><meta property="og:type" content="article"><meta property="og:url" content="https://ignite.apache.org/blog"><meta property="og:image" content="/img/og-pic.png"><link rel="stylesheet" href="/js/vendo [...]
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- gtag('js', new Date());
- gtag('config', 'UA-61232409-1');
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+<!DOCTYPE html>
+<html lang="en">
+ <head>
+ <meta charset="UTF-8" />
+ <meta name="viewport" content="width=device-width, initial-scale=1.0, maximum-scale=1" />
+ <title>Blogging in Action</title>
+ <link rel="canonical" href="https://ignite.apache.org/blog" />
+ <meta property="og:title" content="Blogging in Action" />
+ <meta property="og:type" content="article" />
+ <meta property="og:url" content="https://ignite.apache.org/blog" />
+ <meta property="og:image" content="/img/og-pic.png" />
+ <link rel="stylesheet" href="/js/vendor/hystmodal/hystmodal.min.css?ver=0.9" />
+ <link rel="stylesheet" href="/css/utils.css?ver=0.9" />
+ <link rel="stylesheet" href="/css/site.css?ver=0.9" />
+ <link rel="stylesheet" href="/css/blog.css?ver=0.9" />
+ <link rel="stylesheet" href="/css/media.css?ver=0.9" media="only screen and (max-width:1199px)" />
+ <link rel="icon" type="image/png" href="/img/favicon.png" />
+ <!-- Global site tag (gtag.js) - Google Analytics -->
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<div class="hystmodal__window mobmenu" role="dialog" aria-modal="true">
- <button data-hystclose class="hystmodal__close">Close</button>
- <div class="mobmenu__wrap">
- <a href="/" class="mobmenu__logo"><img src="/img/logo.svg" alt="Logo"></a>
- <div class="mobmenu__menu">
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+ </li>
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+
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+ <span class="mobmenu__parent"> <a href="/features/">Features</a><button class="mobmenu__opener"></button> </span>
+ <ul>
+ <li>
+ <a href="/arch/multi-tier-storage.html">Multi-Tier Storage</a>
+ </li>
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+ <a href="/arch/native-persistence.html">Native Persistence</a>
+ </li>
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+ <a href="/features/sql.html">Distributed SQL</a>
+ </li>
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+ </li>
+ <li>
+ <a href="/features/acid-transactions.html">ACID Transactions</a>
+ </li>
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+ <a href="/features/compute-apis.html">Compute APIs</a>
+ </li>
+ <li>
+ <a href="/features/service-apis.html">Services</a>
+ </li>
+ <li>
+ <a href="/features/machinelearning.html">Machine Learning</a>
+ </li>
+ <li>
+ <a href="/features/streaming.html">Real-Time Streaming APIs</a>
+ </li>
+ <li>
+ <a href="/docs/latest/messaging">Messaging</a>
+ </li>
+ <li>
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+ </li>
+ <li>
+ <a href="/features/index.html">View All</a>
+ </li>
+ </ul>
+ </li>
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- </li><li>
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- </li>
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- <a href="/blog/">Blog</a>
- </li>
+ <li>
+ <a href="/community.html">Community</a>
+ <ul class="isdefault">
+ <li><a href="/community.html">Project Info</a></li>
+ <li><a href="/events.html">Events</a></li>
+ </ul>
+ </li>
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+ <a href="/use-cases/provenusecases.html">Powered by</a>
+ </li>
+ <li>
+ <a href="/resources.html">Resources</a>
+ </li>
+ <li>
+ <a href="/blog/">Blog</a>
+ </li>
- <li>
- <a href="/docs/latest/">Docs</a>
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- <a href="/download.cgi" class="button mobmenu__button">Download Ignite 2.11</a>
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+ <li>
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+ </li>
+ <li>
+ <a class="dropmenu__iconitem" href="/use-cases/digital-integration-hub.html"><img src="/img/menu/icon-folder.svg" alt="" /><span>Digital Integration Hub</span></a>
+ </li>
+ <li>
+ <a class="dropmenu__iconitem" href="/use-cases/spark-acceleration.html"><img src="/img/menu/icon-folder.svg" alt="" /><span>Spark Acceleration</span></a>
+ </li>
+ <li>
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+ <header class="hdrfloat hdr__white jsHdrFloatBase"></header>
+ <div class="container blog">
+ <section class="blog__header"><h1>Apache Ignite Blog</h1></section>
+ <div class="blog__content">
+ <main class="blog_main">
+ <section class="blog__posts">
+ <article class="post">
+ <div class="post__header">
+ <h2><a href="/blog/apache-ignite-2-4-brings.html">Apache Ignite 2.4 ings Advanced Machine Learning and Spark DataFrames Capabilities</a></h2>
+ <div>
+ March 15, 2018 by Denis Magda: <a href="http://www.facebook.com/sharer.php?u=https://ignite.apache.org/blog/apache-ignite-2-4-brings.html">Facebook</a><span>, </span
+ ><a href="http://twitter.com/home?status=Apache Ignite 2.4 ings Advanced Machine Learning and Spark DataFrames Capabilities%20https://ignite.apache.org/blog/apache-ignite-2-4-brings.html">Twitter</a>
+ </div>
+ </div>
+ <div class="post__content">
+ <p>
+ Usually, Ignite community rolls out a new version once in 3 months, but we had to make an exception for Apache Ignite 2.4 that consumed five months in total. We could easily blame Thanksgiving, Christmas and New Year
+ holidays for the delay and would be forgiven, but, in fact, we were forging the release you can't simply pass by.
+ </p>
+ <p>Let's dive in and search for a big fish.</p>
+ <h3>Machine Learning General Availability</h3>
+ <p>
+ Eight months ago, at the time of Apache Ignite 2.0, we put out the first APIs that formed the foundation of the Ignite's machine learning component of today. Since that time, Ignite machine learning experts and
+ enthusiasts have been moving the liary to the general availability condition meticulously. And Ignite 2.4 became a milestone that let us consider the
+ <a href="https://apacheignite.readme.io/docs/machine-learning" target="_blank">ML Grid</a> to be production ready.
+ </p>
+ </div>
+ <div class="post__footer"><a class="more" href="/blog/apache-ignite-2-4-brings.html">↓ Read all</a></div>
+ </article>
+ <article class="post">
+ <div class="post__header">
+ <h2><a href="/blog/meltdown-and-spectre-patches-show.html">Meltdown and Spectre patches show negligible impact to Apache Ignite performance</a></h2>
+ <div>
+ January 30, 2018 by Denis Magda: <a href="http://www.facebook.com/sharer.php?u=https://ignite.apache.org/blog/meltdown-and-spectre-patches-show.html">Facebook</a><span>, </span
+ ><a href="http://twitter.com/home?status=Meltdown and Spectre patches show negligible impact to Apache Ignite performance%20https://ignite.apache.org/blog/meltdown-and-spectre-patches-show.html">Twitter</a>
+ </div>
+ </div>
+ <div class="post__content">
+ <p>
+ As promised in my <a href="https://blogs.apache.org/ignite/entry/protecting-apache-ignite-from-meltdown">initial blog post</a> on this matter, Apache Ignite community applied security patches against the
+ notorious Meltdown Spectre vulnerabilities and completed performance testing of general operations and workloads that are typical for Ignite deployments.
+ </p>
+ <p>
+ The security patches were applied only for <a href="https://nvd.nist.gov/vuln/detail/CVE-2017-5754" target="_blank">CVE-2017-5754</a> (Meltdown) and <a
+ href="https://nvd.nist.gov/vuln/detail/CVE-2017-5753"
+ target="_blank"
+ >CVE-2017-5753</a
+ > (Spectre Variant 1) vulnerabilities. The patches for <a href="https://nvd.nist.gov/vuln/detail/CVE-2017-5715" target="_blank">CVE-2017-5715</a> (Spectre Variant 2) for the hardware the community used for
+ testing are not stable yet an can
+ <a href="https://newsroom.intel.com/news/root-cause-of-reboot-issue-identified-updated-guidance-for-customers-and-partners/" target="_blank">cause system reboot issues or another unpredictable behavior</a>.
+ </p>
+ <p>The applied patches have shown that the performance implications are negligible - the performance drop is just in the 0 - 7% range as the figure shows:</p>
+ </div>
+ <div class="post__footer"><a class="more" href="/blog/meltdown-and-spectre-patches-show.html">↓ Read all</a></div>
+ </article>
+ <article class="post">
+ <div class="post__header">
+ <h2><a href="/blog/protecting-apache-ignite-from-meltdown.html">Protecting Apache Ignite from 'Meltdown' and 'Spectre' vulnerabilities</a></h2>
+ <div>
+ January 8, 2018 by Denis Magda: <a href="http://www.facebook.com/sharer.php?u=https://ignite.apache.org/blog/protecting-apache-ignite-from-meltdown.html">Facebook</a><span>, </span
+ ><a href="http://twitter.com/home?status=Protecting Apache Ignite from 'Meltdown' and 'Spectre' vulnerabilities%20https://ignite.apache.org/blog/protecting-apache-ignite-from-meltdown.html">Twitter</a>
+ </div>
+ </div>
+ <div class="post__content">
+ <p>
+ The world was rocked after the recent disclosure of the
+ <a href="https://www.vox.com/business-and-finance/2018/1/4/16850004/meltdown-spectre-intel-security-flaw-update" target="_blank">Meltdown and Spectre</a> vulnerabilities that literally affect almost all software ever
+ developed. Both issues are related to the way all modern CPUs are designed and this is why they have opened unprecedented security breaches -- making the software, including Apache Ignite, vulnerable to
+ hacker attacks.
+ </p>
+ <p>The vulnerabilities are registered in the National Vulnerability Database under the following CVEs:</p>
+ <ul>
+ <li><a href="https://nvd.nist.gov/vuln/detail/CVE-2017-5753" target="_blank">CVE-2017-5753</a> — Spectre variant 1</li>
+ <li><a href="https://nvd.nist.gov/vuln/detail/CVE-2017-5715" target="_blank">CVE-2017-5715</a> — Spectre variant 2</li>
+ <li><a href="https://nvd.nist.gov/vuln/detail/CVE-2017-5754" target="_blank">CVE-2017-5754</a> — Meltdown</li>
+ </ul>
+ </div>
+ <div class="post__footer"><a class="more" href="/blog/protecting-apache-ignite-from-meltdown.html">↓ Read all</a></div>
+ </article>
+ <article class="post">
+ <div class="post__header">
+ <h2><a href="/blog/apache-ignite-essentials-series-for.html">Apache Ignite Essentials: 2-part Webinar Series for Architects and Java Developers</a></h2>
+ <div>
+ November 17, 2017 by Denis Magda: <a href="http://www.facebook.com/sharer.php?u=https://ignite.apache.org/blog/apache-ignite-essentials-series-for.html">Facebook</a><span>, </span
+ ><a href="http://twitter.com/home?status=Apache Ignite Essentials: 2-part Webinar Series for Architects and Java Developers%20https://ignite.apache.org/blog/apache-ignite-essentials-series-for.html">Twitter</a>
+ </div>
+ </div>
+ <div class="post__content">
+ <p class="entryContent">
+ We finally made this happen! I’m happy to invite all of the software architects and engineers out there to a series of webinars that will introduce you to the fundamental capabilities of in-memory computing platforms
+ such as Apache Ignite.
+ </p>
+ <p>There will also be a mix of theory and practice. A lot of code examples are waiting to be shown so that you can apply the theory in practice right away.</p>
+ <p>The series consists of two parts.</p>
+ <h3><a href="https://ignite.apache.org/events.html#in-memory-computing-essentials-architects-and-developers-part-1" target="_blank">Part 1: Tuesday, November 21, 2017, 11:00am PT / 2:00pm ET</a></h3>
+ To be covered:
+ <ul>
+ <li>Cluster configuration and deployment.</li>
+ <li>Distributed database internals (partitioning, replication).</li>
+ <li>Data processing with key-value APIs.</li>
+ <li>Affinity Collocation.</li>
+ <li>Data processing with SQL.</li>
+ </ul>
+ </div>
+ <div class="post__footer"><a class="more" href="/blog/apache-ignite-essentials-series-for.html">↓ Read all</a></div>
+ </article>
+ <article class="post">
+ <div class="post__header">
+ <h2><a href="/blog/apache-ignite-2-3-more.html">Apache Ignite 2.3 - More SQL and Persistence Capabilities</a></h2>
+ <div>
+ November 1, 2017 by Denis Magda: <a href="http://www.facebook.com/sharer.php?u=https://ignite.apache.org/blog/apache-ignite-2-3-more.html">Facebook</a><span>, </span
+ ><a href="http://twitter.com/home?status=Apache Ignite 2.3 - More SQL and Persistence Capabilities%20https://ignite.apache.org/blog/apache-ignite-2-3-more.html">Twitter</a>
+ </div>
+ </div>
+ <div class="post__content">
+ <p>Putting aside the regular bug fixes and performance optimizations, the Apache Ignite 2.3 release brings new SQL capabilities and Ignite persistence improvements that are worth mentioning.</p>
+ <p></p>
+ <h3>SQL</h3>
+ <p></p>
+ <p>Let's start with SQL first.</p>
+ <p>Apache Ignite users have consistently told us that despite all of Ignite’s SQL capabilities, it’s been at times challenging trying to figure out how to start using Ignite as an SQL database.</p>
+ <p>
+ This was mostly caused by scattered documentation pages, lack of “getting started” guides and tutorials. We’ve remedied this oversight! All related SQL knowledge has been curated in a
+ <a href="https://apacheignite-sql.readme.io/docs" target="_blank">single documentation domain</a>.
+ </p>
+ </div>
+ <div class="post__footer"><a class="more" href="/blog/apache-ignite-2-3-more.html">↓ Read all</a></div>
+ </article>
+ <article class="post">
+ <div class="post__header">
+ <h2><a href="/blog/apache-ignite-community-news-september.html">Apache Ignite Community News (Issue 3)</a></h2>
+ <div>
+ September 15, 2017 by Denis Magda: <a href="http://www.facebook.com/sharer.php?u=https://ignite.apache.org/blog/apache-ignite-community-news-september.html">Facebook</a><span>, </span
+ ><a href="http://twitter.com/home?status=Apache Ignite Community News (Issue 3)%20https://ignite.apache.org/blog/apache-ignite-community-news-september.html">Twitter</a>
+ </div>
+ </div>
+ <div class="post__content">
+ <p><b>by Tom Diederich</b></p>
+ <p>This is our third community update – there’s a lot going on, so let's get started.</p>
+ <p>Apache Ignite experts have already spoken at two meetups this month, both in Silicon Valley, but there are several more scheduled this month around the world.</p>
+ <p></p>
+ <p style="margin-bottom: 15pt">
+ <span style="line-height: 19.5pt"
+ ><span style="font-family: Helvetica"
+ ><span style="color: #333333"
+ >On <b>Sept. 9</b> Apache Ignite PMC chair Denis Magda was the featured presenter at the<b> </b
+ ><a href="https://www.meetup.com/datariders/events/242523245/"
+ ><b><span style="color: #467d76">Big Data and Cloud Meetup</span></b></a
+ >
+ in Santa Clara, Calif. His talk, titled "Apache Spark and Apache Ignite: Where Fast Data Meets the IoT," was highly rated and we’re planning a hands-on workshop with meetup organizers for
+ November.</span
+ ></span
+ ></span
+ >
+ </p>
+ </div>
+ <div class="post__footer"><a class="more" href="/blog/apache-ignite-community-news-september.html">↓ Read all</a></div>
+ </article>
+ <article class="post">
+ <div class="post__header">
+ <h2><a href="/blog/apache-ignite-community-update-august.html">Apache Ignite Community Update (August 2017 Issue)</a></h2>
+ <div>
+ August 30, 2017 by Denis Magda: <a href="http://www.facebook.com/sharer.php?u=https://ignite.apache.org/blog/apache-ignite-community-update-august.html">Facebook</a><span>, </span
+ ><a href="http://twitter.com/home?status=Apache Ignite Community Update (August 2017 Issue)%20https://ignite.apache.org/blog/apache-ignite-community-update-august.html">Twitter</a>
+ </div>
+ </div>
+ <div class="post__content">
+ <p>
+ <b><i>by Tom Diederich</i></b>
+ </p>
+ <p>
+ Igniters, here are some community highlights from the last couple week. If I missed anything, please share it here. Meetups! Did you know that Apache Ignite experts are available to speak at your meetup? And we also have
+ spots open for YOU to speak at the following meetups that some of us co-organize:
+ </p>
+ <ul>
+ <li><a href="https://www.meetup.com/Apache-Ignite-London/" target="_blank">Apache Ignite London</a></li>
+ <li><a href="https://www.meetup.com/Bay-Area-In-Memory-Computing/" target="_blank">Bay Area In-Memory Computing Meetup</a></li>
+ <li><a href="https://www.meetup.com/NYC-In-Memory-Computing-Meetup/" target="_blank">NYC In-Memory Computing Meetup</a></li>
+ <li><a href="https://www.meetup.com/Moscow-Apache-Ignite-Meetup/" target="_blank">Moscow Apache Ignite Meetup</a></li>
+ </ul>
+ </div>
+ <div class="post__footer"><a class="more" href="/blog/apache-ignite-community-update-august.html">↓ Read all</a></div>
+ </article>
+ <article class="post">
+ <div class="post__header">
+ <h2><a href="/blog/apache-ignite-2-1-a.html">Apache Ignite 2.1 - A Leap from In-Memory to Memory-Centric Architecture</a></h2>
+ <div>
+ July 27, 2017 by Denis Magda: <a href="http://www.facebook.com/sharer.php?u=https://ignite.apache.org/blog/apache-ignite-2-1-a.html">Facebook</a><span>, </span
+ ><a href="http://twitter.com/home?status=Apache Ignite 2.1 - A Leap from In-Memory to Memory-Centric Architecture%20https://ignite.apache.org/blog/apache-ignite-2-1-a.html">Twitter</a>
+ </div>
+ </div>
+ <div class="post__content">
+ <p>
+ The power and beauty of in-memory computing projects are that they truly do what they state -- deliver outstanding performance improvements by moving data closer to the CPU, using RAM as a storage and spreading the data
+ sets out across a cluster of machines relying on horizontal scalability.
+ </p>
+ <p>
+ However, there is an unspoken side of the story. No matter how fast a platform is, we do not want to lose the data and encounter cluster restarts or other outages. To guarantee this we need to somehow make data persistent
+ on the disk.
+ </p>
+ <p>
+ Most in-memory computing projects address the persistence dilemma by giving a way to sync data back to a relational database (RDBMS). That sounds reasonable and undoubtedly works pretty well in practice, but if we dig
+ deeper, you’ll likely encounter the following limitations:
+ </p>
+ </div>
+ <div class="post__footer"><a class="more" href="/blog/apache-ignite-2-1-a.html">↓ Read all</a></div>
+ </article>
+ <article class="post">
+ <div class="post__header">
+ <h2><a href="/blog/apache-ignite-2-0-redesigned.html">Apache Ignite 2.0: Redesigned Off-heap Memory, DDL and Machine Learning</a></h2>
+ <div>
+ May 5, 2017 by Denis Magda: <a href="http://www.facebook.com/sharer.php?u=https://ignite.apache.org/blog/apache-ignite-2-0-redesigned.html">Facebook</a><span>, </span
+ ><a href="http://twitter.com/home?status=Apache Ignite 2.0: Redesigned Off-heap Memory, DDL and Machine Learning%20https://ignite.apache.org/blog/apache-ignite-2-0-redesigned.html">Twitter</a>
+ </div>
+ </div>
+ <div class="post__content">
+ <p>
+ We released the long-awaited Apache Ignite version 2.0 on May 5. The community spent almost a year incorporating tremendous changes to the legacy Apache Ignite 1.x architecture. And all of that effort paid off. Our
+ collective blood, sweat (and perhaps even a few tears) opened up new and exciting opportunities for the Apache Ignite project.
+ </p>
+ <p>Have I piqued your interest about this new release yet? Let's walk through some of the main new features that have appeared under the hood of Apache Ignite 2.0.</p>
+ </div>
+ <div class="post__footer"><a class="more" href="/blog/apache-ignite-2-0-redesigned.html">↓ Read all</a></div>
+ </article>
+ <article class="post">
+ <div class="post__header">
+ <h2><a href="/blog/presenting-apache-ignite-sql-grid.html">Presenting Apache Ignite SQL Grid at Big Data Bootcamp</a></h2>
+ <div>
+ March 13, 2017 by Denis Magda: <a href="http://www.facebook.com/sharer.php?u=https://ignite.apache.org/blog/presenting-apache-ignite-sql-grid.html">Facebook</a><span>, </span
+ ><a href="http://twitter.com/home?status=Presenting Apache Ignite SQL Grid at Big Data Bootcamp%20https://ignite.apache.org/blog/presenting-apache-ignite-sql-grid.html">Twitter</a>
+ </div>
+ </div>
+ <div class="post__content">
+ <p>
+ Apache Ignite community welcomes you to attend <a href="http://globalbigdataconference.com/santa-clara/big-data-bootcamp/event-79.html" target="_blank">Big Data Bootcamp</a> on March 27th, 28th and 29th 2017 in Santa
+ Clara, USA.
+ </p>
+ <p>
+ The conference gathers experts and vendors from Big Data realm in sunny California who will be covering a variety of Big Data products and technologies, including, but not limited to, Hadoop, Spark, NoSQL, Data Science,
+ Machine Learning, Artificial Intelligence & Deep Learning.
+ </p>
+ <p>Apache Ignite will be introduced at the conference by its PMC chair and committer - Denis Magda.</p>
+ </div>
+ <div class="post__footer"><a class="more" href="/blog/presenting-apache-ignite-sql-grid.html">↓ Read all</a></div>
+ </article>
+ </section>
+ <section class="blog__footer">
+ <ul class="pagination">
+ <li><a class="item" href="/blog/">1</a></li>
+ <li><a class="current" href="/blog/1/">2</a></li>
+ <li><a class="item" href="/blog/2/">3</a></li>
+ </ul>
+ </section>
+ </main>
+ <aside class="blog__sidebar">
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+ <h2><a href="/blog/apache-ignite-1-9-released.html">Apache Ignite 1.9 Released</a></h2>
+ <div>
+ March 7, 2017 by Denis Magda: <a href="http://www.facebook.com/sharer.php?u=https://ignite.apache.org/blog/apache-ignite-1-9-released.html">Facebook</a><span>, </span
+ ><a href="http://twitter.com/home?status=Apache Ignite 1.9 Released%20https://ignite.apache.org/blog/apache-ignite-1-9-released.html">Twitter</a>
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+ <p>
+ Apache Ignite community is pleased to announce Apache Ignite 1.9 - the next minor release of a well-known in-memory data fabric. The release, as usual, encompasses many bug fixes, performance improvements and fresh
+ features. Below you can see a description of the most significant updates.
+ </p>
+ <p><b>Kubernetes Support</b></p>
+ <p>
+ Apache Ignite was integrated with Kubernetes which is a modern open source container cluster manager. The integration helps to simplify a deployment of an Apache Ignite cluster in environments managed by Kubernetes and let
+ the latter care of resources management, cluster's scalability and lifecycle.
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diff --git a/blog/apache-ignite-1-9-released.html b/blog/apache-ignite-1-9-released.html
index 813717774f..7db02c42f7 100644
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+ <a href="/blog/">← Apache Ignite Blog</a>
+ <h1>Apache Ignite 1.9 Released</h1>
+ <p>
+ March 7, 2017 by <strong>Denis Magda: </strong><a href="http://www.facebook.com/sharer.php?u=https://ignite.apache.org/blog/undefined">Facebook</a><span>, </span
+ ><a href="http://twitter.com/home?status=Apache Ignite 1.9 Released%20https://ignite.apache.org/blog/undefined">Twitter</a>
+ </p>
+ </section>
+ <div class="blog__content">
+ <main class="blog_main">
+ <section class="blog__posts">
+ <article class="post">
+ <div>
+ <p>
+ Apache Ignite community is pleased to announce Apache Ignite 1.9 - the next minor release of a well-known in-memory data fabric. The release, as usual, encompasses many bug fixes, performance improvements and fresh
+ features. Below you can see a description of the most significant updates.
+ </p>
+ <p><b>Kubernetes Support</b></p>
+ <p>
+ Apache Ignite was integrated with Kubernetes which is a modern open source container cluster manager. The integration helps to simplify a deployment of an Apache Ignite cluster in environments managed by Kubernetes and let
+ the latter care of resources management, cluster's scalability and lifecycle.
+ </p>
+ <!-- end -->
+ <p>
+ For instance, you're no longer need to monitor a cluster state constantly to be sure that the number of cluster nodes doesn't go, let's say, below 4. If Kubernetes sees that one cluster node is disconnected
+ and only 3 are left then it will start one more automatically to meet the deployment requirements.
+ </p>
+ <p>Refer to <a href="https://apacheignite.readme.io/docs/kubernetes-deployment" target="_blank">Kubernetes Deployment Getting Started</a> if this is the feature of interest for you.</p>
+ <p><b>Performance Optimizations and Benchmarks Automation</b></p>
+ <p>
+ Apache Ignite 1.9 can boast of much better performance for core cache operations and SQL queries in compare to the previous Apache Ignite 1.8 release. In general, we observe up to 40% performance increase for particular
+ operations.
+ </p>
+ <p>
+ It's no longer a challenge to reproduce the performance numbers. Starting with Apache Ignite 1.9 release all the benchmarks are delivered in every Apache Ignite distribution and can be easily executed in your own
+ environment.
+ </p>
+ <p><b>Data Modification Language and Queries Parallelism</b></p>
+ <p>
+ The community keeps spending significant time improving <a href="https://apacheignite.readme.io/docs/sql-grid" target="_blank">SQL Grid</a> component that empowers Apache Ignite users with in-memory database capabilities.
+ </p>
+ <p>
+ In this release, DML (Data Modification Language) support was expanded to the level of <a href="https://apacheignite-net.readme.io/docs/distributed-dml" target="_blank">Ignite.NET</a> and
+ <a href="https://apacheignite-cpp.readme.io/docs/distributed-dml" target="_blank">Ignite.C++</a> APIs. Plus, a <a href="https://apacheignite.readme.io/docs/jdbc-driver#streaming-mode" target="_blank">streaming mode</a> was
+ introduced for DML allowing to execute DML operations even faster for specific scenarios like initial data preloading.
+ </p>
+ <p>
+ One more SQL Grid related optimization makes it possible to parallelize a query execution on every Ignite node where the query has been mapped. By default, a query is executed in a single thread on every participating
+ node. However, for a variety of OLAP use cases it might be a bottleneck and this is where the
+ <a href="https://apacheignite.readme.io/docs/sql-performance-and-debugging#section-query-parallelism" target="_blank">query parallelism</a> can help out.
+ </p>
+ <p><b>Ignite.NET</b></p>
+ <p>
+ Apache Ignite implemented .NET TransactionScope API allowing to work with distributed Apache Ignite transactions fully relaying on standard interfaces available in .NET Framework. Refer to
+ <a href="https://apacheignite-net.readme.io/docs/transactionscope-api" target="_blank">this documentation page</a> for more information.
+ </p>
+ <p><b>Ignite.C++</b></p>
+ <p>
+ Ignite.C++ introduced support for well-known <a href="https://apacheignite-cpp.readme.io/docs/continuous-queries" target="_blank">continuous queries API</a>. Now, you can listen to data modifications happened on Apache
+ Ignite's distributed caches side from your C++ applications.
+ </p>
+ <p><b>Spark</b></p>
+ <p>Ignite’s spark integration was upgraded to the latest Spark version. Presently, you can leverage from Ignite Shared RDDs in applications using latest Spark version.</p>
+ <p><b>Give a Try</b></p>
+ <p>Go and grab the latest 1.9 release from our <a href="https://ignite.apache.org/download.cgi" target="_blank">main site</a>. Looking forward to your feedback!</p>
+ </div>
+ </article>
+ <section class="blog__footer">
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index 2f6f7aa32b..c9ee4257b4 100644
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+ <section class="blog__header post_page__header">
+ <a href="/blog/">← Apache Ignite Blog</a>
+ <h1>Apache Ignite 2.0: Redesigned Off-heap Memory, DDL and Machine Learning</h1>
+ <p>
+ May 5, 2017 by <strong>Denis Magda: </strong><a href="http://www.facebook.com/sharer.php?u=https://ignite.apache.org/blog/undefined">Facebook</a><span>, </span
+ ><a href="http://twitter.com/home?status=Apache Ignite 2.0: Redesigned Off-heap Memory, DDL and Machine Learning%20https://ignite.apache.org/blog/undefined">Twitter</a>
+ </p>
+ </section>
+ <div class="blog__content">
+ <main class="blog_main">
+ <section class="blog__posts">
+ <article class="post">
+ <div>
+ <p>
+ We released the long-awaited Apache Ignite version 2.0 on May 5. The community spent almost a year incorporating tremendous changes to the legacy Apache Ignite 1.x architecture. And all of that effort paid off. Our
+ collective blood, sweat (and perhaps even a few tears) opened up new and exciting opportunities for the Apache Ignite project.
+ </p>
+ <p>Have I piqued your interest about this new release yet? Let's walk through some of the main new features that have appeared under the hood of Apache Ignite 2.0.</p>
+ <!-- end -->
+ <h3>Reengineered Off-Heap Memory Architecture.</h3>
+ <p>
+ The platform’s entire memory architecture was reengineered from scratch. In a nutshell, all of the data and indexes are now stored in a completely new manageable off-heap memory that has no issues with memory
+ fragmentation, accelerates SQL Grid significantly and helps your application easily tolerate Java GC pauses.
+ </p>
+ <p>
+ Take a peek at the illustration below and try to guess what’s changed. Afterward, please read <a href="https://apacheignite.readme.io/docs/page-memory" target="_blank">this documentation</a> to see if your
+ eye caught everything that’s new.
+ </p>
+ <p><img src="https://files.readme.io/0bf1bbf-Page-Memory-Diagram-v3.png" /></p>
+ <p>Here’s something extremely noteworthy: the architecture now integrates seamlessly with disk drives. Why do we care about this? Stay tuned!</p>
+ <p></p>
+ <h3>Data Definition Language.</h3>
+ <p></p>
+ <p>
+ This release introduces support for Data Definition Language (DDL) as a part of its SQL Grid functionality. Now you can define -- and, what’s more important, alter -- indexes in runtime without the need to restart
+ your cluster. Apache Ignite users have long awaited this feature! Even more exciting news: users can leverage this with standard SQL commands like CREATE or DROP index. This is only the beginning! Go to
+ <a href="https://apacheignite.readme.io/docs/distributed-ddl" target="_blank">this page</a> to learn more about current DDL support.
+ </p>
+ <p></p>
+ <h3>Machine Learning Grid Beta - Distributed Algebra.</h3>
+ <p></p>
+ <p>
+ Apache Ignite is about more than in-memory storage. And it’s not just one more product for distributed computations or real-time streaming. It's much, much more than that. It's a hot blend of
+ well-integrated distributed and highly concurrent modules that turned Apache Ignite into what is today: A robust data-fabric and framework with the goal of making your application thrive and outperform even the best of
+ expectations.
+ </p>
+ <p>But there was one thing missing until now. Drumroll, please: machine-learning support!</p>
+ <p>
+ With Apache Ignite 2.0 you can check project’s own <a href="https://apacheignite.readme.io/docs/machine-learning" target="_blank">distributed algebra implementation</a>. The distributed algebra is the foundation of
+ the entire component. And soon you can expect to get distributed versions of widely used regression algorithms, decision trees and more.
+ </p>
+ <p></p>
+ <h3>Spring Data Integration.</h3>
+ <p></p>
+ <p>
+ <a href="https://apacheignite-mix.readme.io/docs/spring-data" target="_blank">Spring Data integration</a> allows the interaction of an Apache Ignite cluster using the well-known and highly adopted Spring Data Framework.
+ You can connect to the cluster by means of Spring Data repositories and start executing distributed SQL queries as well as simple CRUD operations.
+ </p>
+ <p></p>
+ <h3>Rocket MQ</h3>
+ <p></p>
+ <p>Are you using Rocket MQ in your project and need to push data from the Rocket to Ignite? <a href="https://apacheignite-mix.readme.io/docs/rocketmq-streamer" target="_blank">Here is</a> an easy solution.</p>
+ <p></p>
+ <h3>Hibernate 5.</h3>
+ <p></p>
+ <p>
+ Hibernate L2 cache users have been anticipating support of Hibernate 5 on Apache Ignite for quite a long time. Apache Ignite 2.0 grants
+ <a href="https://apacheignite-mix.readme.io/docs/hibernate-l2-cache" target="_blank">this desire</a>. The integration now supports Hibernate 5 and contains a number of bug fixes and improvements.
+ </p>
+ <p></p>
+ <h3>Ignite.NET</h3>
+ <p></p>
+ <p>
+ Ignite.NET has been enhanced with an addition of a <a href="https://apacheignite-net.readme.io/docs/plugins" target="_blank">plugin system</a> that allows the writing and embedding 3rd party .NET components into
+ Ignite.NET.
+ </p>
+ <p></p>
+ <h3>Ignite.C++</h3>
+ <p></p>
+ <p>The Ignite.C++ part of the community finally came up with a way to execute arbitrary C++ code on remote cluster machines.</p>
+ <p>
+ This approach was initially tested for <a href="https://apacheignite-cpp.readme.io/docs/continuous-queries" target="_blank">continuous queries</a>. You can now register continuous queries' remote filters on any
+ cluster node you like. Going forward you can expect support for the Ignite.C++ compute grid and more.
+ </p>
+ <p>
+ Want to learn more? Please join me June 7 for a <a href="https://www.gridgain.com/resources/webinars/apacher-ignitetm-whats-new-version-20" target="_blank">webinar</a> titled, “Apache® Ignite™: What’s
+ New in Version 2.0.” I hope to see you there!
+ </p>
+ <p>
+ P.S. Just in case you can’t wait until June… <a href="https://ignite.apache.org/releases/2.0.0/release_notes.html" target="_blank">here's</a> a full list of the changes inside Apache Ignite 2.0.
+ </p>
+ </div>
+ </article>
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+ <section class="blog__header post_page__header">
+ <a href="/blog/">← Apache Ignite Blog</a>
+ <h1>Apache Ignite 2.1 - A Leap from In-Memory to Memory-Centric Architecture</h1>
+ <p>
+ July 27, 2017 by <strong>Denis Magda: </strong><a href="http://www.facebook.com/sharer.php?u=https://ignite.apache.org/blog/undefined">Facebook</a><span>, </span
+ ><a href="http://twitter.com/home?status=Apache Ignite 2.1 - A Leap from In-Memory to Memory-Centric Architecture%20https://ignite.apache.org/blog/undefined">Twitter</a>
+ </p>
+ </section>
+ <div class="blog__content">
+ <main class="blog_main">
+ <section class="blog__posts">
+ <article class="post">
+ <div>
+ <p>
+ The power and beauty of in-memory computing projects are that they truly do what they state -- deliver outstanding performance improvements by moving data closer to the CPU, using RAM as a storage and spreading the data
+ sets out across a cluster of machines relying on horizontal scalability.
+ </p>
+ <p>
+ However, there is an unspoken side of the story. No matter how fast a platform is, we do not want to lose the data and encounter cluster restarts or other outages. To guarantee this we need to somehow make data persistent
+ on the disk.
+ </p>
+ <p>
+ Most in-memory computing projects address the persistence dilemma by giving a way to sync data back to a relational database (RDBMS). That sounds reasonable and undoubtedly works pretty well in practice, but if we dig
+ deeper, you’ll likely encounter the following limitations:
+ </p>
+ <!-- end -->
+ <ul>
+ <li>
+ <b>RDBMS is a bottleneck.</b> No matter how fast your in-memory technology project, you can accelerate read operations only because every write has to be persisted to the disk -- which is usually a single machine running
+ an RDBMS instance.
+ </li>
+ <p></p>
+ <p></p>
+ <li>
+ <b>RDBMS is a single point of failure.</b> Your distributed in-memory cluster usually consists of dozens and even hundreds of nodes which means you can safely lose this node here or drop that node there without worrying
+ about data consistency and availability. However, if the RDBMS used by the cluster fails, then what? The answer is obvious -- the cluster can no longer be utilized because the RAM and disk parts go out of sync.
+ </li>
+ <p></p>
+ <p></p>
+ <li>
+ <b>SQL over RAM only</b>. Apache® Ignite™ provides SQL database capabilities, however, you can only leverage them if all of the data and indexes are located in RAM. If a single piece of data, represented by a
+ disk copy located in the RDBMS, then an Ignite-only SQL query will return an incomplete result set.
+ </li>
+ <p></p>
+ <p></p>
+ <li><b>Requried RAM warmup</b></li>
+ . When your cluster goes down, you have to restart it and preload all of the data from the RDBMS to RAM. That’s essential if you use SQL or similar advanced querying languages. This dramatically increases the overall
+ time of the downtime and can cost a lot of money.
+ </ul>
+ <br />
+ <p></p>
+ <p>If you use either Apache Ignite 1.x or 2.0 along with the RDBMS for disk storage, then you will hit these limitations. It’s just the way in-memory architectures are integrated with the disk.</p>
+ <p>
+ However, the limitations are <b>no longer relevant</b> for Apache Ignite 2.1! This version made a leap from in-memory to a
+ <b><a href="https://apacheignite.readme.io/docs/what-is-ignite" target="_blank">memory-centric</a></b> architecture that:
+ </p>
+ <p></p>
+ <div style="display: table-cell; vertical-align: middle; text-align: center"><br /><img src="https://files.readme.io/752653f-cluster_and_cylinders.png" align="middle" /><br /></div>
+ <p></p>
+ <p><br /></p>
+ <li>Keeps using RAM as a first memory tier for data and indexes -- giving all of the benefits you had before.</li>
+ <br />
+ <li>Supports durability criteria by treating disk as a secondary and larger tier that works in a distributed fashion and seamlessly integrates with the whole memory architecture.</li>
+ <br />
+ <li>
+ Supports the instantaneous cluster restarts -- once your cluster is up and running there is no reason to wait for RAM's warmup, go ahead and turn on back your applications that can safely execute all operations
+ including SQL. The data and indexes will be taken from disk.
+ </li>
+ <br />
+ <p></p>
+ <p>Curious about how Ignite achieved these huge advantages? Lifting the curtain….</p>
+ <p></p>
+ <h3>Durable Memory Architecture</h3>
+ <p></p>
+ <p>
+ The Apache Ignite memory-centric platform is based on the <a href="https://apacheignite.readme.io/docs/durable-memory" target="_blank">durable memory architecture</a> that allows storing and processing data and indexes
+ both in-memory and on disk when the <a href="https://apacheignite.readme.io/docs/distributed-persistent-store" target="_blank">Ignite Persistent Store</a> is enabled. The memory architecture helps to achieve in-memory
+ performance with the durability of the disk using all of the resources available in the cluster.
+ </p>
+ <p>
+ The durable memory is built and operates in a way similar to the virtual memory of operating systems such as Linux. However, the one significant difference between these two types of architectures is that the durable
+ memory one always keeps the whole data set and indexes on the disk -- if the Ignite Persistent Store is enabled -- while the virtual memory uses the disk for swapping purposes only.
+ </p>
+ <p></p>
+ <h3>Ignite Persistent Store</h3>
+ <p></p>
+ <p>
+ <a href="https://apacheignite.readme.io/docs/distributed-persistent-store" target="_blank">Persistent Store</a> is a distributed ACID and SQL-compliant disk store that transparently integrates with the durable memory as an
+ optional disk layer (SSD, Flash, 3D XPoint). Having the store enabled, you no longer need to keep all of the data in memory or warm-up the RAM after a whole cluster restart. The persistent store will keep the superset of
+ data and all the SQL indexes on the disk making Ignite fully operational from the disk.
+ </p>
+ <p></p>
+ <h3>The Upshot</h3>
+ <p></p>
+ <p>
+ Tired of hooking up Ignite with an RDBMS? Go ahead and download Apache Ignite 2.1, enable Ignite Persistent Store, and launch your first durable Ignite cluster that distributes data sets and workloads relying on the
+ performance of RAM and durability of the disk!
+ </p>
+ <p>Finally, Apache Ignite 2.1 can boast about another achievements in .NET, C++, SQL and Machine Learning. Go ahead and discover them!</p>
+ </div>
+ </article>
+ <section class="blog__footer">
+ <ul class="pagination post_page">
+ <li><a href="/blog/apache">apache</a></li>
+ <li><a href="/blog/biodata">biodata</a></li>
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+ </ul>
+ </section>
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+ </main>
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index d658c079f0..f87ed6370a 100644
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-<!-- MOBILE MENU END --><header class="hdr hdr__white jsHdrBase"><div class="hdr__wrap flexi jsHdrLine"><button class="hdr__burger" data-menumodal="#jsMenuModal"><img src="/img/menu.svg" alt=""></button><a class="hdr__logo" href="/"><img class="hdr__logoimg hdr__logo--white" src="/img/logo-white.svg" alt=""><img class="hdr__logoimg hdr__logo--black" src="/img/logo.svg" alt=""></a><a class="button hdr__button" href="/download.cgi">Download Ignite 2.15.0</a><nav class="hdrmenu"><ul class=" [...]
- check the full list of resolved <a href="https://s.apache.org/i3ny6">Important JIRA's</a> but here let’s briefly overview some valuable improvements.</p><h3 id="thin-clients">Thin Clients</h3>Thin clients now support several important features which, previously were available only on the thick clients.
- Thin clients are always backward and forward compatible with the server nodes of the cluster, so the cluster upgrade
- process will be more convenient if the lack of these features prevented you from doing that.<p>See the list of what is changed for thin clients below:</p><ul><li>Transactions</li><li>Service invocations</li><li>Continuous Queries</li><li>SQL API</li><li>Cluster API</li><li>Cache Async API</li><li>Kubernetes Discovery (<em>ThinClientKubernetesAddressFinder</em>)</li></ul>You may check the <a href="https://cwiki.apache.org/confluence/display/IGNITE/Thin+clients+features">List of Thin C [...]
- and command line scripts.<h4 id="new-_control-script_-commands">New <em>control-script</em> Commands</h4><p>Query any of the available system views.</p><code> <pre>control.sh --system-view views</pre><pre>Command [SYSTEM-VIEW] started</pre><pre>--------------------------------------------------------------------------------</pre><pre>name schema description</pre><pre>SQL_QUERIES_HISTORY SYS SQL queries history.</pre><pre>INDEXES [...]
-via
-Ignite system properties. Run the command below to see the list of all available system properties for
-configuration:</p><code> <pre>$./ ignite.sh -systemProps</pre><br/><pre>--------------------------------------------------------------------------------</pre><pre>IGNITE_AFFINITY_HISTORY_SIZE - [Integer] Maximum size for affinity assignment history. Default is 25.</pre><pre>IGNITE_ALLOW_ATOMIC_OPS_IN_TX - [Boolean] Allows atomic operations inside transactions. Default is true.</pre><pre>IGNITE_ALLOW_START_CACHES_IN_PARALLEL - [Boolean] Allows to start multiple caches [...]
- internal information about Queries, Compute Tasks, Cache operations, Checkpoint and WAL statistics, and so on for
- problem detection and cluster self-tuning purposes. Each cluster node collects performance statistics into a special
- binary file that is placed under the <code>[IGINTE_WORK_DIR]/perf_stat/</code> directory with the template filename
- as<code>node-[nodeId]-[index].prf</code>.
- All these files are consumed by offline-tool that builds the report in a human-readable format.<p><a href="https://ignite.apache.org/docs/latest/monitoring-metrics/performance-statistics">Read More</a></p><p><img src="/img/blog/d445a88f-98d1-4a6e-b4d8-037e819ca91f.png" alt="transactions statistics" style="display:block;margin:auto;width:50%;"/></p><h3 id="transparent-data-encryption-cache-key-rotation">Transparent Data Encryption - Cache Key Rotation</h3>Payment card industry data se [...]
- crypto period for each key in use and define a process for key changes at the end of the defined crypto period.
- An expired key should not be used to encrypt new data, but it can be used for archived data, such keys should be
- strongly protected (section 3.5 - 3.6 of PCI DSS Requirements and Security Assessment Procedures).<p>Apache Ignite now supports full PCI DSS requirements:</p><ul><li><em>Transparent Data Encryption</em> available since the 2.7 release.</li><li><em>Master Key Rotation</em> procedure available since the 2.9 release.</li><li><em>Cache Key Rotation</em> procedure available since the 2.10 release.</li></ul>You may use the CLI tools that provide the ability to change the re-encryption rate [...]
- resume background re-encryption at runtime.<p><a href="https://ignite.apache.org/docs/latest/security/cache-encryption-key-rotation">Read More</a></p></div></article><section class="blog__footer"><ul class="pagination post_page"><li><a href="/blog/ignite">ignite</a></li></ul></section></section></main><aside class="blog__sidebar"><ul><li><a href="/blog/database">database</a></li><li><a href="/blog/ignite">ignite</a></li><li><a href="/blog/in">in</a></li><li><a href="/blog/memory">mem [...]
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+ <a href="/blog/">← Apache Ignite Blog</a>
+ <h1>Apache Ignite 2.10: Thin Client Expansion</h1>
+ <p>
+ March 18, 2021 by <strong>Maxim Muzafarov: </strong><a href="http://www.facebook.com/sharer.php?u=https://ignite.apache.org/blog/undefined">Facebook</a><span>, </span
+ ><a href="http://twitter.com/home?status=Apache Ignite 2.10: Thin Client Expansion%20https://ignite.apache.org/blog/undefined">Twitter</a>
+ </p>
+ </section>
+ <div class="blog__content">
+ <main class="blog_main">
+ <section class="blog__posts">
+ <article class="post">
+ <div>
+ <p class="entryContent">
+ As of March 15, 2021, <a href="https://ignite.apache.org/">Apache Ignite</a> 2.10 has been released. You can directly check the full list of resolved <a href="https://s.apache.org/i3ny6">Important JIRA's</a> but here
+ let’s briefly overview some valuable improvements.
+ </p>
+ <h3 id="thin-clients">Thin Clients</h3>
+ Thin clients now support several important features which, previously were available only on the thick clients. Thin clients are always backward and forward compatible with the server nodes of the cluster, so the cluster
+ upgrade process will be more convenient if the lack of these features prevented you from doing that.
+ <p>See the list of what is changed for thin clients below:</p>
+ <ul>
+ <li>Transactions</li>
+ <li>Service invocations</li>
+ <li>Continuous Queries</li>
+ <li>SQL API</li>
+ <li>Cluster API</li>
+ <li>Cache Async API</li>
+ <li>Kubernetes Discovery (<em>ThinClientKubernetesAddressFinder</em>)</li>
+ </ul>
+ You may check the <a href="https://cwiki.apache.org/confluence/display/IGNITE/Thin+clients+features">List of Thin Client Features</a> that supported by platforms you are interested in or see the
+ <a href="https://ptupitsyn.github.io/Whats-New-In-Ignite-Net-2.10/">What's new in Apache Ignite.NET 2.10</a>.<!-- end -->
+ <h3 id="cluster-monitoring">Cluster Monitoring</h3>
+ Apache Ignite self-monitoring and cluster health check subsystems are also extended by additional SQL-views and command line scripts.
+ <h4 id="new-_control-script_-commands">New <em>control-script</em> Commands</h4>
+ <p>Query any of the available system views.</p>
+ <code>
+ <pre>control.sh --system-view views</pre>
+ <pre>Command [SYSTEM-VIEW] started</pre>
+ <pre>--------------------------------------------------------------------------------</pre>
+ <pre>name schema description</pre>
+ <pre>SQL_QUERIES_HISTORY SYS SQL queries history.</pre>
+ <pre>INDEXES SYS SQL indexes</pre>
+ <pre>BASELINE_NODES SYS Baseline topology nodes</pre>
+ <pre>STRIPED_THREADPOOL_QUEUE SYS Striped thread pool task queue</pre>
+ <pre>SCAN_QUERIES SYS Scan queries</pre>
+ <pre>PARTITION_STATES SYS Distribution of cache group partitions across cluster nodes</pre>
+ <br />
+ <pre>Command [SYSTEM-VIEW] finished with code: 0</pre>
+ <pre>--------------------------------------------------------------------------------</pre>
+ </code>
+ <p>Query any of the available system metrics.</p>
+ <code>
+ <pre>[source, text]</pre>
+ <pre>control.sh --metric sysCurrentThreadCpuTime</pre>
+ <pre>Command [METRIC] started</pre>
+ <pre>--------------------------------------------------------------------------------</pre>
+ <pre>metric value</pre>
+ <pre>sys.CurrentThreadCpuTime 17270000</pre>
+ <pre>Command [METRIC] finished with code: 0</pre>
+ <pre>--------------------------------------------------------------------------------</pre>
+ </code>
+ <p><a href="https://ignite.apache.org/docs/latest/tools/control-script">Read More</a></p>
+ <h4 id="managing-ignite-system-properties">Managing Ignite System Properties</h4>
+ <p>
+ In addition to basic cluster configuration settings, you can perform some low-level cluster configuration and tuning via Ignite system properties. Run the command below to see the list of all available system properties
+ for configuration:
+ </p>
+ <code>
+ <pre>$./ ignite.sh -systemProps</pre>
+ <br />
+ <pre>--------------------------------------------------------------------------------</pre>
+ <pre>IGNITE_AFFINITY_HISTORY_SIZE - [Integer] Maximum size for affinity assignment history. Default is 25.</pre>
+ <pre>IGNITE_ALLOW_ATOMIC_OPS_IN_TX - [Boolean] Allows atomic operations inside transactions. Default is true.</pre>
+ <pre>IGNITE_ALLOW_START_CACHES_IN_PARALLEL - [Boolean] Allows to start multiple caches in parallel. Default is true.</pre>
+ </code>
+ <p><a href="https://ignite.apache.org/docs/latest/setup#setting-ignite-system-properties">Read more</a></p>
+ <h3 id="cluster-profiling">Cluster Profiling</h3>
+ From now on, Apache Ignite is delivered with the cluster profiling tool. This tool collects and processes all cluster internal information about Queries, Compute Tasks, Cache operations, Checkpoint and WAL statistics, and so
+ on for problem detection and cluster self-tuning purposes. Each cluster node collects performance statistics into a special binary file that is placed under the <code>[IGINTE_WORK_DIR]/perf_stat/</code> directory with the
+ template filename as<code>node-[nodeId]-[index].prf</code>. All these files are consumed by offline-tool that builds the report in a human-readable format.
+ <p><a href="https://ignite.apache.org/docs/latest/monitoring-metrics/performance-statistics">Read More</a></p>
+ <p><img src="/img/blog/d445a88f-98d1-4a6e-b4d8-037e819ca91f.png" alt="transactions statistics" style="display: block; margin: auto; width: 50%" /></p>
+ <h3 id="transparent-data-encryption-cache-key-rotation">Transparent Data Encryption - Cache Key Rotation</h3>
+ Payment card industry data security standard (PCI DSS) requires that key-management procedures include a predefined crypto period for each key in use and define a process for key changes at the end of the defined crypto
+ period. An expired key should not be used to encrypt new data, but it can be used for archived data, such keys should be strongly protected (section 3.5 - 3.6 of PCI DSS Requirements and Security Assessment Procedures).
+ <p>Apache Ignite now supports full PCI DSS requirements:</p>
+ <ul>
+ <li><em>Transparent Data Encryption</em> available since the 2.7 release.</li>
+ <li><em>Master Key Rotation</em> procedure available since the 2.9 release.</li>
+ <li><em>Cache Key Rotation</em> procedure available since the 2.10 release.</li>
+ </ul>
+ You may use the CLI tools that provide the ability to change the re-encryption rate as well as suspend and resume background re-encryption at runtime.
+ <p><a href="https://ignite.apache.org/docs/latest/security/cache-encryption-key-rotation">Read More</a></p>
+ </div>
+ </article>
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diff --git a/blog/apache-ignite-2-11-1.html b/blog/apache-ignite-2-11-1.html
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-</div>
-<!-- MOBILE MENU END --><header class="hdr hdr__white jsHdrBase"><div class="hdr__wrap flexi jsHdrLine"><button class="hdr__burger" data-menumodal="#jsMenuModal"><img src="/img/menu.svg" alt=""></button><a class="hdr__logo" href="/"><img class="hdr__logoimg hdr__logo--white" src="/img/logo-white.svg" alt=""><img class="hdr__logoimg hdr__logo--black" src="/img/logo.svg" alt=""></a><a class="button hdr__button" href="/download.cgi">Download Ignite 2.15.0</a><nav class="hdrmenu"><ul class=" [...]
-set the JVM property <code>com.sun.jndi.ldap.object.trustURLCodebase</code> to <code>false</code> by default, which disables JNDI loading of classes
-from arbitrary URL code bases.</li></ul><p>NOTE: Relying only on the Java version as a protection against these vulnerabilities is very risky and has not been tested.</p><!-- end --><h3 id="risk-mitigation-without-upgrading">Risk Mitigation Without Upgrading</h3><p>Please note that all of these cases require a cluster downtime, but we still recommend to upgrade the Apache Ignite.</p><h4 id="method-1-removing-the-vulnerable-classes">Method 1: Removing the Vulnerable Classes</h4><p>When us [...]
-executing this command:</p><code>find $IGNITE_HOME/ -type f -name "*log4j-core-*.jar" -exec zip -q -d "{}" org/apache/logging/log4j/core/lookup/JndiLookup.class \;</code><p>This will recursively find all log4j-core JAR files, starting from the <code>IGNITE_HOME</code> directory, and remove the vulnerable
-JndiLookup class from them.</p><h4 id="method-2-disabling-message-lookups">Method 2: Disabling Message Lookups</h4><p>This method can be used as an additional protection layer in case you suspect not all log4j dependencies have been
-properly updated. If you are using the Apache Ignite of an older version, we recommend to disable message lookups globally
-by setting the environment variable <code>LOG4J_FORMAT_MSG_NO_LOOKUPS</code> to <code>true</code> or, alternatively, run the Apache Ignite with
-the <code>‐Dlog4j2.formatMsgNoLookups=true</code> command-line option.</p><h4 id="method-3-replace-log4j2-dependency-manually">Method 3: Replace log4j2 Dependency Manually</h4><p>It is still possible to manually replace the Log4j of 2.x version in the Apache Ignite binary distribution to the 2.17.0 Log4j
-version if your log configuration does not imply to use the RoutingAppender. In case the RoutingAppender is used it may produce
-some error messages in a log file at the startup or empty lines during the execution, which are considered as a minor flow,
-however, we do not recommend this mitigation method in this case.</p></div></article><section class="blog__footer"><ul class="pagination post_page"><li><a href="/blog/database">database</a></li><li><a href="/blog/ignite">ignite</a></li><li><a href="/blog/in-memory">in-memory</a></li><li><a href="/blog/log4j2">log4j2</a></li><li><a href="/blog/open-source">open-source</a></li><li><a href="/blog/release">release</a></li></ul></section></section></main><aside class="blog__sidebar"><ul><li>< [...]
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+ <a href="/blog/">← Apache Ignite Blog</a>
+ <h1>Apache Ignite 2.11.1: Emergency Log4j2 Update</h1>
+ <p>
+ December 21, 2021 by <strong>Maxim Muzafarov: </strong><a href="http://www.facebook.com/sharer.php?u=https://ignite.apache.org/blog/undefined">Facebook</a><span>, </span
+ ><a href="http://twitter.com/home?status=Apache Ignite 2.11.1: Emergency Log4j2 Update%20https://ignite.apache.org/blog/undefined">Twitter</a>
+ </p>
+ </section>
+ <div class="blog__content">
+ <main class="blog_main">
+ <section class="blog__posts">
+ <article class="post">
+ <div>
+ <p>
+ The new <a href="https://ignite.apache.org/">Apache Ignite</a> 2.11.1 is an emergency release that fixes <a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2021-44228">CVE-2021-44228</a>,
+ <a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2021-45046">CVE-2021-45046</a>,<a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2021-45105">CVE-2021-45105</a> related to the ignite-log4j2 module
+ usage.
+ </p>
+ <h3 id="apache-ignite-with-log4j-vulnerability">Apache Ignite with Log4j Vulnerability</h3>
+ <p>All the following conditions must be met:</p>
+ <ul>
+ <li>The Apache Ignite version lower than 2.11.0 is used (since these vulnerabilities are already fixed in 2.11.1, 2.12, and upper versions);</li>
+ <li>The <code>ignite-logj42</code> is used by Apache Ignite and located in the <code>libs</code> directory (by default it is located in the <code>libs/optional</code>directory, so these deployments are not affected);</li>
+ <li>
+ The Java version in use is older than the following versions: <code>8u191</code>, <code>11.0.1</code>. This is due to the fact that later versions set the JVM property
+ <code>com.sun.jndi.ldap.object.trustURLCodebase</code> to <code>false</code> by default, which disables JNDI loading of classes from arbitrary URL code bases.
+ </li>
+ </ul>
+ <p>NOTE: Relying only on the Java version as a protection against these vulnerabilities is very risky and has not been tested.</p>
+ <!-- end -->
+ <h3 id="risk-mitigation-without-upgrading">Risk Mitigation Without Upgrading</h3>
+ <p>Please note that all of these cases require a cluster downtime, but we still recommend to upgrade the Apache Ignite.</p>
+ <h4 id="method-1-removing-the-vulnerable-classes">Method 1: Removing the Vulnerable Classes</h4>
+ <p>When using an older Apache Ignite version, it is possible to remove the JndiLookup class from any Java application by executing this command:</p>
+ <code>find $IGNITE_HOME/ -type f -name "*log4j-core-*.jar" -exec zip -q -d "{}" org/apache/logging/log4j/core/lookup/JndiLookup.class \;</code>
+ <p>This will recursively find all log4j-core JAR files, starting from the <code>IGNITE_HOME</code> directory, and remove the vulnerable JndiLookup class from them.</p>
+ <h4 id="method-2-disabling-message-lookups">Method 2: Disabling Message Lookups</h4>
+ <p>
+ This method can be used as an additional protection layer in case you suspect not all log4j dependencies have been properly updated. If you are using the Apache Ignite of an older version, we recommend to disable message
+ lookups globally by setting the environment variable <code>LOG4J_FORMAT_MSG_NO_LOOKUPS</code> to <code>true</code> or, alternatively, run the Apache Ignite with the
+ <code>‐Dlog4j2.formatMsgNoLookups=true</code> command-line option.
+ </p>
+ <h4 id="method-3-replace-log4j2-dependency-manually">Method 3: Replace log4j2 Dependency Manually</h4>
+ <p>
+ It is still possible to manually replace the Log4j of 2.x version in the Apache Ignite binary distribution to the 2.17.0 Log4j version if your log configuration does not imply to use the RoutingAppender. In case the
+ RoutingAppender is used it may produce some error messages in a log file at the startup or empty lines during the execution, which are considered as a minor flow, however, we do not recommend this mitigation method in this
+ case.
+ </p>
+ </div>
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-extent as a stabilization release that closed a number of technical debts of the internal architecture and bugs. Out of more than
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-transactions on cells not affected by failing nodes. The time when transactions are parked also decreases on non-affected cells which
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-group nodes into virtual cells. Since the node baseline attributes are used as cell markers the corresponding <a href="https://ignite.apache.org/docs/latest/monitoring-metrics/system-views#baseline_node_attributes">BASELINE_NODE_ATTRIBUTES</a> system
-view was added.</p><p>See benchmarks below that represent the worst (max) latency, which happens in case of node left/failure/timeout events on broken
-and alive cells.</p><a href="/img/blog/ec8a7800-01e9-4910-aaa9-0e27ea2d4303.png"><img src="/img/blog/ec8a7800-01e9-4910-aaa9-0e27ea2d4303.png" alt="723rhosidfgu4787fh9sdhf.png" width="50%"/></a><h3 id="new-page-replacement-policies">New Page Replacement Policies</h3><p>When Native Persistence is on and the amount of data, which Ignite stores on the disk, is bigger than the off-heap memory amount
-allocated for the data region, another page should be evicted from the off-heap to the disk to preload a page from the disk to
-the completely full off-heap memory. This process is called page replacement. Previously, Apache Ignite used the Random-LRU page
-replacement algorithm which has a low maintenance cost, but it has many disadvantages and greatly affects the performance when
-the page replacement is started. On some deployments, administrators even force a cluster restart periodically to avoid page
-replacement. There are a few new algorithms available from now on:</p><ul><li>Segmented-LRU Algorithm</li><li>CLOCK Algorithm</li></ul><p>Page replacement algorithm can be configured by the <em>PageReplacementMode</em> property of <em>DataRegionConfiguration</em>. By default,
-the CLOCK algorithm is now used. You can check the <a href="https://ignite.apache.org/docs/latest/memory-configuration/replacement-policies">Replacement Policies</a> in the documentation
-for more details.</p><h3 id="snapshot-restore-and-check-commands">Snapshot Restore And Check Commands</h3><h4 id="check">Check</h4><p>All snapshots are fully consistent in terms of concurrent cluster-wide operations as well as ongoing changes with Ignite.
-However, in some cases and for your own peace of mind, it may be necessary to check the snapshot for completeness and
-for data consistency. The Apache Ignite is now delivered with a built-in snapshot consistency check commands that enable you to
-verify internal data consistency, calculate data partitions hashes and pages checksums, and print out the result if a problem
-is found. The check command also compares hashes calculated by containing keys of primary partitions with corresponding backup
-partitions and reports any differences.</p><code> <pre># This procedure does not require the cluster to be in the idle state.</pre><pre>control.(sh|bat) --snapshot check snapshot_name</pre></code><h4 id="restore">Restore</h4><p>Previously, only the manual snapshot restore procedure was available by fully copying persistence data files from the
-snapshot directory to the Apache Ignite <em>work</em> directory. The automatic restore procedure allows you to restore cache groups from
-a snapshot on an active cluster by using the Java API or command line script (using CLI is recommended). Currently, the restore
-procedure has several limitations, so please check the documentation pages for details.</p><code> <pre>Start restoring all user-created cache groups from the snapshot "snapshot_09062021".</pre><pre>control.(sh|bat) --snapshot restore snapshot_09062021 --start</pre><br/><pre># Start restoring only "cache-group1" and "cache-group2" from the snapshot "snapshot_09062021".</pre><pre>control.(sh|bat) --snapshot restore snapshot_09062021 --start cache-group1,cache-group2</pre><br/><pre># Get th [...]
\ No newline at end of file
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+ <section class="blog__header post_page__header">
+ <a href="/blog/">← Apache Ignite Blog</a>
+ <h1>Apache Ignite 2.11: Stabilization First</h1>
+ <p>
+ September 20, 2021 by <strong>Maxim Muzafarov: </strong><a href="http://www.facebook.com/sharer.php?u=https://ignite.apache.org/blog/undefined">Facebook</a><span>, </span
+ ><a href="http://twitter.com/home?status=Apache Ignite 2.11: Stabilization First%20https://ignite.apache.org/blog/undefined">Twitter</a>
+ </p>
+ </section>
+ <div class="blog__content">
+ <main class="blog_main">
+ <section class="blog__posts">
+ <article class="post">
+ <div>
+ <p>
+ The new <a href="https://ignite.apache.org/">Apache Ignite</a> 2.11 was released on September 17, 2021. It can be considered to be a greater extent as a stabilization release that closed a number of technical debts of the
+ internal architecture and bugs. Out of more than 200 completed tasks, 120 are bug fixes. However, some valuable improvements still exist, so let's take a quick look at them together.
+ </p>
+ <h3 id="thin-clients">Thin Clients</h3>
+ <p>
+ Partition awareness is enabled by default in the 2.11 release and allows thin clients to send query requests directly to the node that owns the queried data. Without partition awareness, an application executes all queries
+ and operations via a single server node that acts as a proxy for the incoming requests.
+ </p>
+ <p>
+ The support of <a href="https://ignite.apache.org/docs/latest/thin-clients/java-thin-client#cache-entry-listening">Continuous Queries</a>added to the java thin client. For the other supported features, you can check - the
+ <a href="https://cwiki.apache.org/confluence/display/IGNITE/Thin+clients+features">List of Thin Client Features</a>.
+ </p>
+ <!-- end -->
+ <h3 id="cellular-clusters-deployment">Cellular-clusters Deployment</h3>
+ <p>
+ The Apache Ignite internals has the so-called <em>switch</em> (a part of Partition Map Exchange) process that is used to perform atomic execution of cluster-wide operations and move a cluster from one consistent state to
+ another, for example, a cache creation/destroy, a node JOIN/LEFT/FAIL operations, snapshot creation, etc. During the switching process, all user transactions are parked for a small period of time which in turn increases
+ the average latency and decreases throughput of the overall cluster.
+ </p>
+ <p>
+ Splitting the cluster into virtual cells containing 4-8 nodes may increase the total cluster performance and minimize the influence of one cell on another in case of node fail events. Such a technique also significantly
+ increases the recovery speed of transactions on cells not affected by failing nodes. The time when transactions are parked also decreases on non-affected cells which in turn decreases the worst latency for the cluster
+ operations overall.
+ </p>
+ <p>
+ From now on, you can use the <em>RendezvousAffinityFunction</em> affinity function with <em>ClusterNodeAttributeColocatedBackupFilter</em> to group nodes into virtual cells. Since the node baseline attributes are used as
+ cell markers the corresponding <a href="https://ignite.apache.org/docs/latest/monitoring-metrics/system-views#baseline_node_attributes">BASELINE_NODE_ATTRIBUTES</a> system view was added.
+ </p>
+ <p>See benchmarks below that represent the worst (max) latency, which happens in case of node left/failure/timeout events on broken and alive cells.</p>
+ <a href="/img/blog/ec8a7800-01e9-4910-aaa9-0e27ea2d4303.png"><img src="/img/blog/ec8a7800-01e9-4910-aaa9-0e27ea2d4303.png" alt="723rhosidfgu4787fh9sdhf.png" width="50%" /></a>
+ <h3 id="new-page-replacement-policies">New Page Replacement Policies</h3>
+ <p>
+ When Native Persistence is on and the amount of data, which Ignite stores on the disk, is bigger than the off-heap memory amount allocated for the data region, another page should be evicted from the off-heap to the disk
+ to preload a page from the disk to the completely full off-heap memory. This process is called page replacement. Previously, Apache Ignite used the Random-LRU page replacement algorithm which has a low maintenance cost,
+ but it has many disadvantages and greatly affects the performance when the page replacement is started. On some deployments, administrators even force a cluster restart periodically to avoid page replacement. There are a
+ few new algorithms available from now on:
+ </p>
+ <ul>
+ <li>Segmented-LRU Algorithm</li>
+ <li>CLOCK Algorithm</li>
+ </ul>
+ <p>
+ Page replacement algorithm can be configured by the <em>PageReplacementMode</em> property of <em>DataRegionConfiguration</em>. By default, the CLOCK algorithm is now used. You can check the
+ <a href="https://ignite.apache.org/docs/latest/memory-configuration/replacement-policies">Replacement Policies</a> in the documentation for more details.
+ </p>
+ <h3 id="snapshot-restore-and-check-commands">Snapshot Restore And Check Commands</h3>
+ <h4 id="check">Check</h4>
+ <p>
+ All snapshots are fully consistent in terms of concurrent cluster-wide operations as well as ongoing changes with Ignite. However, in some cases and for your own peace of mind, it may be necessary to check the snapshot for
+ completeness and for data consistency. The Apache Ignite is now delivered with a built-in snapshot consistency check commands that enable you to verify internal data consistency, calculate data partitions hashes and pages
+ checksums, and print out the result if a problem is found. The check command also compares hashes calculated by containing keys of primary partitions with corresponding backup partitions and reports any differences.
+ </p>
+ <code>
+ <pre># This procedure does not require the cluster to be in the idle state.</pre>
+ <pre>control.(sh|bat) --snapshot check snapshot_name</pre>
+ </code>
+ <h4 id="restore">Restore</h4>
+ <p>
+ Previously, only the manual snapshot restore procedure was available by fully copying persistence data files from the snapshot directory to the Apache Ignite <em>work</em> directory. The automatic restore procedure allows
+ you to restore cache groups from a snapshot on an active cluster by using the Java API or command line script (using CLI is recommended). Currently, the restore procedure has several limitations, so please check the
+ documentation pages for details.
+ </p>
+ <code>
+ <pre>Start restoring all user-created cache groups from the snapshot "snapshot_09062021".</pre>
+ <pre>control.(sh|bat) --snapshot restore snapshot_09062021 --start</pre>
+ <br />
+ <pre># Start restoring only "cache-group1" and "cache-group2" from the snapshot "snapshot_09062021".</pre>
+ <pre>control.(sh|bat) --snapshot restore snapshot_09062021 --start cache-group1,cache-group2</pre>
+ <br />
+ <pre># Get the status of the restore operation for "snapshot_09062021".</pre>
+ <pre>control.(sh|bat) --snapshot restore snapshot_09062021 --status</pre>
+ <br />
+ <pre># Cancel the restore operation for "snapshot_09062021".</pre>
+ <pre>control.(sh|bat) --snapshot restore snapshot_09062021 --cancel</pre>
+ </code>
+ </div>
+ </article>
+ <section class="blog__footer">
+ <ul class="pagination post_page">
+ <li><a href="/blog/database">database</a></li>
+ <li><a href="/blog/ignite">ignite</a></li>
+ <li><a href="/blog/in-memory">in-memory</a></li>
+ <li><a href="/blog/open-source">open-source</a></li>
+ <li><a href="/blog/release">release</a></li>
+ </ul>
+ </section>
+ </section>
+ </main>
+ <aside class="blog__sidebar">
+ <ul>
+ <li><a href="/blog/database">database</a></li>
+ <li><a href="/blog/ignite">ignite</a></li>
+ <li><a href="/blog/in">in</a></li>
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+ <li><a href="/blog/bigdata">bigdata</a></li>
+ <li><a href="/blog/computing">computing</a></li>
+ <li><a href="/blog/two">two</a></li>
+ <li><a href="/blog/learning">learning</a></li>
+ <li><a href="/blog/machine">machine</a></li>
+ <li><a href="/blog/apache">apache</a></li>
+ <li><a href="/blog/spark">spark</a></li>
+ <li><a href="/blog/sql">sql</a></li>
+ <li><a href="/blog/data">data</a></li>
+ <li><a href="/blog/fast">fast</a></li>
+ <li><a href="/blog/nodal">nodal</a></li>
+ <li><a href="/blog/meltdown">meltdown</a></li>
+ <li><a href="/blog/performance">performance</a></li>
+ <li><a href="/blog/security">security</a></li>
+ <li><a href="/blog/spectre">spectre</a></li>
+ <li><a href="/blog/key-value">key-value</a></li>
+ <li><a href="/blog/store">store</a></li>
+ <li><a href="/blog/meetup">meetup</a></li>
+ <li><a href="/blog/biodata">biodata</a></li>
+ <li><a href="/blog/rdbms">rdbms</a></li>
+ <li><a href="/blog/grid">grid</a></li>
+ <li><a href="/blog/imdb">imdb</a></li>
+ </ul>
+ </aside>
+ </div>
+ </div>
+ <footer class="footer">
+ <div class="container footer__top">
+ <section class="footer1">
+ <a class="footer__title" href="/features/">Features</a>
+ <ul class="footer__menu">
+ <li><a href="/arch/multi-tier-storage.html">Multi-Tier Storage</a></li>
+ <li><a href="/arch/native-persistence.html">Native Persistence</a></li>
+ <li><a href="/features/sql.html">Distributed SQL</a></li>
+ <li><a href="/features/acid-transactions.html">ACID Transactions</a></li>
+ <li><a href="/features/key-value-apis.html">Key Value APIs</a></li>
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+ <a href="/blog/">← Apache Ignite Blog</a>
+ <h1>Apache Ignite 2.12.0: CDC, Index Query API, Vulnerabilities Fixes</h1>
+ <p>
+ January 14, 2022 by <strong>Nikita Amelchev: </strong><a href="http://www.facebook.com/sharer.php?u=https://ignite.apache.org/blog/undefined">Facebook</a><span>, </span
+ ><a href="http://twitter.com/home?status=Apache Ignite 2.12.0: CDC, Index Query API, Vulnerabilities Fixes%20https://ignite.apache.org/blog/undefined">Twitter</a>
+ </p>
+ </section>
+ <div class="blog__content">
+ <main class="blog_main">
+ <section class="blog__posts">
+ <article class="post">
+ <div>
+ <p>
+ As of January 14, 2022, <a href="https://ignite.apache.org/">Apache Ignite</a> 2.12 has been released. You can directly check the full list of resolved <a href="https://s.apache.org/0zyi2">Important JIRA tasks</a> but here
+ let’s briefly overview some valuable improvements.
+ </p>
+ <h3 id="vulnerability-updates">Vulnerability Updates</h3>
+ <p>
+ The Apache Ignite versions lower than 2.11.1 are vulnerable to <a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2021-44832">CVE-2021-44832</a> which is related to the <code>ignite-log4j2</code> module usage.
+ </p>
+ <p>The release also fixes 10+ CVE’s of various modules. See <a href="https://ignite.apache.org/releases/2.12.0/release_notes.html">release notes</a> for more details.</p>
+ <h3 id="change-data-capture">Change Data Capture</h3>
+ <p>
+ Change Data Capture (<a href="https://en.wikipedia.org/wiki/Change_data_capture">CDC</a>) is a data processing pattern used to asynchronously receive entries that have been changed on the local node so that action can be
+ taken using the changed entry.
+ </p>
+ <!-- end -->
+ <p>Below are some of the CDC use cases:</p>
+ <ul>
+ <li>Streaming changes in Warehouse;</li>
+ <li>Updating search index;</li>
+ <li>Calculating statistics (streaming queries);</li>
+ <li>Auditing logs;</li>
+ <li>Async interaction with external systems: Moderation, business process invocation, etc.</li>
+ </ul>
+ <p>Ignite implements CDC with the <code>ignite-cdc.sh</code> application and <a href="https://github.com/apache/ignite/blob/master/modules/core/src/main/java/org/apache/ignite/cdc/CdcConsumer.java#L56">Java API</a>.</p>
+ <p>Below are the CDC application and the Ignite node integrated via <a href="https://ignite.apache.org/docs/2.12.0/persistence/native-persistence#write-ahead-log">WAL archive segments</a>:</p>
+ <p><img src="/img/blog/c5574c7d-2a24-4def-b1c4-b2343ed98397.svg" alt="Apache Ignite CDC design" style="display: block; margin-left: auto; margin-right: auto; width: 30%" /></p>
+ <p>
+ When CDC is enabled, the Ignite server node creates a hard link to each WAL archive segment in the special <code>db/cdc/{consistency_id}</code> directory. The <code>ignite-cdc.sh</code> application can be runruns on a
+ different JVM and processes newly archived WAL segments. When the segment is fully processed by <code>ignite-cdc.sh</code>, it is removed. The actual disk space is free when both links (archive and CDC) are removed.
+ </p>
+ <p>State of consumption is a pointer to the last processed event. A consumer can tell <code>ignite-cdc.sh</code> to save the consumption state. On startup event processing will be continued from the last saved state.</p>
+ <p>See implementation details <a href="https://ignite.apache.org/docs/2.12.0/persistence/change-data-capture">here</a>.</p>
+ <h3 id="index-query-api">Index Query API</h3>
+ <p>The Apache Ignite now provides Index Query API for existing indexes. Index queries work over distributed indexes and retrieve cache entries that match the specified query.</p>
+ <p>It will help in some cases, where:</p>
+ <ul>
+ <li>SQL is not applicable by the design of user application;</li>
+ <li><code>IndexScan</code> is preferable to <code>ScanQuery</code> for performance reasons.</li>
+ </ul>
+ <p>Example of query:</p>
+ <code class="lang-java">
+ <pre>// Find the persons who work in Organization 1 and have salary more than 1,000.</pre>
+ <pre>QueryCursor<Cache.Entry<Integer, Person>> cursor = cache.query(</pre>
+ <pre> new IndexQuery<Integer, Person>(Person.class, "ORG_SALARY_IDX")</pre>
+ <pre> .setCriteria(eq("orgId", 1), gt("salary", 1000))</pre>
+ <pre>);</pre>
+ </code>
+ <p>See more details <a href="https://ignite.apache.org/docs/latest/key-value-api/using-cache-queries#executing-index-queries">here</a>.</p>
+ <h3 id="snapshots">Snapshots</h3>
+ <p>Previous versions can perform snapshot restore in the same cluster topology only. The new version provides the ability to restore snapshots on different cluster topologies. Moreover, added support of encrypted caches.</p>
+ <h3 id="distributed-environment-tests">Distributed Environment Tests</h3>
+ <p>
+ The <a href="https://cwiki.apache.org/confluence/display/IGNITE/IEP-56%3A+Distributed+environment+tests">new testing framework</a> was implemented. The main goal is to have a large enough set of integration tests that
+ cover most of the typical cluster usage scenarios.
+ </p>
+ <p>Features:</p>
+ <ul>
+ <li>Ignite nodes can be started/stopped on a Docker or a real cluster with any custom configuration;</li>
+ <li>Any Apache Ignite version is supported (released or compiled from sources);</li>
+ <li>Apache Ignite forks are also supported «out of the box»;</li>
+ <li>Any other application execution is also possible, e.g. we implemented starters for Spark and Zookeeper;</li>
+ <li>The cluster can be managed using the <code>control.sh</code>, we made this a part of the test API;</li>
+ <li>Custom Java applications can be executed remotely with/without a built-in Ignite node or a Thin client;</li>
+ <li>Any ssh command can be executed remotely, and the result will be available locally (at the python test);</li>
+ <li>A network can be broken by editing <code>iptables</code> to check communication issues;</li>
+ <li>Tests can be executed in parallel when the cluster size is bigger than tests requirements.</li>
+ </ul>
+ <p>Framework based on <a href="https://ducktape-docs.readthedocs.io/en/latest/index.html">Ducktape</a> library from Kafka team, that's why we called it Ducktests.</p>
+ <h3 id="migration-modules-to-the-apache-ignite-extensions">Migration modules to the Apache Ignite Extensions</h3>
+ <p>There is activity on the migration of frameworks to extensions:</p>
+ <ul>
+ <li>GCE, AWS, Azure modules were migrated to <code>gce</code>, <code>aws</code>, <code>azure</code> extensions.</li>
+ <li>CacheSpringStoreSessionListener was migrated to the <code>spring-tx</code> extension.</li>
+ <li>TcpDiscoveryZookeeperIpFinder was migrated to the <code>zookeeper-ip-finder</code> extension.</li>
+ </ul>
+ <p>The binaries archive now weighs 10 percent less.</p>
+ <h3 id="anything-else-">Anything else?</h3>
+ <p>See the <a href="https://ignite.apache.org/releases/2.12.0/release_notes.html">release notes</a> to learn about all of the new features and bug fixes.</p>
+ <p>Reach out to us on the community user list for more questions, details, and feedback.</p>
+ <p>Sincerely yours,</p>
+ <p>Ignite contributors and committers</p>
+ </div>
+ </article>
+ <section class="blog__footer">
+ <ul class="pagination post_page">
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+ <section class="blog__header post_page__header">
+ <a href="/blog/">← Apache Ignite Blog</a>
+ <h1>Apache Ignite 2.13.0: new Apache Calcite-based SQL engine</h1>
+ <p>
+ April 28, 2022 by <strong>Nikita Amelchev: </strong><a href="http://www.facebook.com/sharer.php?u=https://ignite.apache.org/blog/undefined">Facebook</a><span>, </span
+ ><a href="http://twitter.com/home?status=Apache Ignite 2.13.0: new Apache Calcite-based SQL engine%20https://ignite.apache.org/blog/undefined">Twitter</a>
+ </p>
+ </section>
+ <div class="blog__content">
+ <main class="blog_main">
+ <section class="blog__posts">
+ <article class="post">
+ <div>
+ <p>
+ As of April 26, 2022, <a href="https://ignite.apache.org/">Apache Ignite</a> 2.13 has been released. You can directly check the full list of resolved <a href="https://s.apache.org/x8u49">Important JIRA tasks</a> but here
+ let's briefly overview some valuable improvements.
+ </p>
+ <h4>This is a breaking change release: The legacy service grid implementation was removed.</h4>
+ <h3 id="new-apache-calcite-based-sql-engine">New Apache Calcite-based SQL engine</h3>
+ <p>We've implemented a new experimental SQL engine based on Apache Calcite. Now it's possible to:</p>
+ <ul>
+ <li>Get rid of some <a href="https://cwiki.apache.org/confluence/display/IGNITE/IEP-37%3A+New+query+execution+engine#IEP37:Newqueryexecutionengine-Motivation">H2 limitations</a>;</li>
+ <li><a href="https://cwiki.apache.org/confluence/display/IGNITE/IEP-37%3A+New+query+execution+engine#IEP37:Newqueryexecutionengine-Implementationdetails">Optimize</a> some query execution.</li>
+ </ul>
+ <p>The current H2-based engine has fundamental limitations. For example:</p>
+ <ul>
+ <li>some queries should be splitted into 2 phases (map subquery and reduce subquery), but some of them cannot be effectively executed in 2 phases.</li>
+ <li>H2 is a third-party database product with not-ASF license.</li>
+ <li>The optimizer and other internal things are not supposed to work in a distributed environment.</li>
+ <li>It's hard to make Ignite-specific changes to the H2 code, patches are often declined.</li>
+ </ul>
+ <!-- end -->
+ <p>The Apache Calcite is a SQL engine with customizable modules. Requests can be splitted into more than 2 phases.</p>
+ <p>A query engine can be set before query execution. Here is an example for SQL:</p>
+ <code class="lang-java">SELECT /*+ QUERY_ENGINE('h2') */ fld FROM table;</code>
+ <p>or</p>
+ <code class="lang-java">SELECT /*+ QUERY_ENGINE('calcite') */ fld FROM table;</code>
+ <p>See JDBC and ODBC examples <a href="https://github.com/apache/ignite/blob/master/modules/calcite/README.txt">here</a>.</p>
+ <p>The new engine requires the ignite-indexing module (which depends on H2) to be included to the classpath to support queries infrastructure.</p>
+ <p>See more technical details about the new engine in the <a href="https://cwiki.apache.org/confluence/pages/viewpage.action?pageId=130028084">IEP-37</a>.</p>
+ <h3 id="read-repair-strategies">Read Repair strategies</h3>
+ <p>
+ <a href="https://ignite.apache.org/docs/latest/read-repair">"Read Repair"</a> refers to a technique of repairing inconsistencies between primary and backup copies of data during normal read operations. When a
+ specific key (or keys) is read by a user operation, Ignite checks the values for the given key in all backup copies.
+ </p>
+ <p>We've implemented the new Read Repair strategies as follows:</p>
+ <ul>
+ <li>LWW (Last Write Wins) - Last write (the newest entry) wins.</li>
+ <li>PRIMARY - Value from the primary node wins.</li>
+ <li>RELATIVE_MAJORITY - The relative majority: a value found more often than any other wins.</li>
+ <li>REMOVE - Inconsistent entries will be removed.</li>
+ <li>CHECK_ONLY - Only check will be performed.</li>
+ </ul>
+ <h3 id="array-type-in-binary-object">Array type in Binary Object</h3>
+ <p>In previous versions Ignite did not save information about array type. Now it can be stored in a binary object:</p>
+ <code>
+ <pre>cache.put(1, new Person[] {new Person(1), new Person(2)});</pre>
+ <br />
+ <pre>Person[] obj = cache.get(1);</pre>
+ <br />
+ <pre>assertEquals(Person[].class, obj.getClass());</pre>
+ </code>
+ <p>The feature is disabled by default due to compatibility issues. Set the IGNITE_USE_BINARY_ARRAYS system property to true to enable it.</p>
+ <h3 id="cdc-for-in-memory-caches">CDC for in-memory caches</h3>
+ <p>
+ The <a href="https://ignite.apache.org/docs/latest/persistence/change-data-capture">Change Data Capture</a> now can be configured for in-memory caches. From now on, only CDC needed records for such caches will be logged to
+ WAL.
+ </p>
+ <h3 id="other-improvements-and-changes">Other improvements and changes</h3>
+ <ul>
+ <li>
+ The C++ thin client implemented continuous queries and asynchronous network events handling. See the updated thin clients features list
+ <a href="https://cwiki.apache.org/confluence/display/IGNITE/Thin+clients+features">here</a>;
+ </li>
+ <li>Implemented NUMA-aware <a href="https://github.com/apache/ignite/tree/master/modules/numa-allocator">allocator</a> for data regions;</li>
+ <li>Ignite maven BOM;</li>
+ <li>Removed the legacy service grid implementation;</li>
+ <li>100+ small improvements and bug fixes.</li>
+ </ul>
+ <h3 id="anything-else-">Anything else?</h3>
+ <p>See the <a href="https://ignite.apache.org/releases/2.13.0/release_notes.html">release notes</a> to learn about all of the new features and improvements.</p>
+ <p>Reach out to us on the community user list for more questions, details, and feedback.</p>
+ <p>Sincerely yours, Ignite contributors and committers</p>
+ </div>
+ </article>
+ <section class="blog__footer">
+ <ul class="pagination post_page">
+ <li><a href="/blog/database">database</a></li>
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+ <a href="/blog/">← Apache Ignite Blog</a>
+ <h1>Apache Ignite 2.3 - More SQL and Persistence Capabilities</h1>
+ <p>
+ November 1, 2017 by <strong>Denis Magda: </strong><a href="http://www.facebook.com/sharer.php?u=https://ignite.apache.org/blog/undefined">Facebook</a><span>, </span
+ ><a href="http://twitter.com/home?status=Apache Ignite 2.3 - More SQL and Persistence Capabilities%20https://ignite.apache.org/blog/undefined">Twitter</a>
+ </p>
+ </section>
+ <div class="blog__content">
+ <main class="blog_main">
+ <section class="blog__posts">
+ <article class="post">
+ <div>
+ <p>Putting aside the regular bug fixes and performance optimizations, the Apache Ignite 2.3 release brings new SQL capabilities and Ignite persistence improvements that are worth mentioning.</p>
+ <p></p>
+ <h3>SQL</h3>
+ <p></p>
+ <p>Let's start with SQL first.</p>
+ <p>Apache Ignite users have consistently told us that despite all of Ignite’s SQL capabilities, it’s been at times challenging trying to figure out how to start using Ignite as an SQL database.</p>
+ <p>
+ This was mostly caused by scattered documentation pages, lack of “getting started” guides and tutorials. We’ve remedied this oversight! All related SQL knowledge has been curated in a
+ <a href="https://apacheignite-sql.readme.io/docs" target="_blank">single documentation domain</a>.
+ </p>
+ <!-- end -->
+ <p>Are you curious about the SQL scope? Go to the new <a href="https://apacheignite-sql.readme.io/docs/sql-reference-overview" target="_blank">SQL Reference Overview</a> section!</p>
+ <p>
+ Cannot wait to learn how the Ignite SQL engine runs internally? We’ve prepared an <a href="https://apacheignite-sql.readme.io/docs/how-ignite-sql-works" target="_blank">Architectural Overview</a> section for you.
+ </p>
+ <p>Simply need to know how to connect to an Ignite cluster from an SQL tool? Here is a <a href="https://apacheignite-sql.readme.io/docs/how-ignite-sql-works" target="_blank">tooling</a> section for you.</p>
+ <p>Let’s take a look at some specific SQL features released in Ignite 2.3.</p>
+ <p>
+ First, we’re proud to deliver support of <a href="https://apacheignite-sql.readme.io/docs/alter-table" target="_blank">ALTER TABLE</a> command. Presently, the command allows adding new columns to an SQL schema in
+ runtime -- avoiding any cluster restarts. Once a new column is added, it can be turned into an index. Again, in runtime. No restarts!
+ </p>
+ <p>
+ Another significant addition seen in Ignite 2.3 is the integration with <a href="https://apacheignite-sql.readme.io/docs/sqlline" target="_blank">SQLLine tool</a> that is bundled with every Apache Ignite release and can be
+ used as a default command line tool for SQL based interactions.
+ </p>
+ <p>To prove that it's fairly simple to work with Ignite as with an SQL database using the tool, we recorded a short screencast for you:</p>
+ <p>
+ <a href="https://youtu.be/FKS8A86h-VY" target="_blank"><img src="/img/blog/89364a0d-3c7e-427c-8237-868318dcd6f1.png" alt="screencast.png" style="display: block; margin: auto; width: 50%" /></a>
+ </p>
+ <p></p>
+ <h3>Ignite Persistence</h3>
+ <p></p>
+ <p>
+ Ignite native persistence keeps getting more attention and installs -- which is why the community released a feature requested by at least a dozen users. The feature allows enabling the persistence for specific data sets.
+ Before Ignite version 2.3, the persistence could be enabled globally only.
+ </p>
+ <p>
+ Now, it's up to you to decide which data to persist and which to store in RAM only. The persistence can be configured via
+ <a href="https://apacheignite.readme.io/docs/memory-configuration#section-data-regions" target="_blank">data regions</a> as shown below:
+ </p>
+ <p>
+ <a href="https://apacheignite.readme.io/docs/memory-configuration#section-data-regions" target="_blank"
+ ><img src="/img/blog/0c7ce964-1218-49eb-bc9b-54a4725cabed.png" alt="persistence_cfg.png" style="display: block; margin: auto; width: 60%"
+ /></a>
+ </p>
+ <p>This data region will consume up to 500 MB of RAM and will store a superset of data on disk ensuring that no data loss happens in case of a crash or even if there is no more space left in RAM.</p>
+ <p></p>
+ <h3>Anything else?</h3>
+ <p></p>
+ <p>
+ Flip through <a href="https://ignite.apache.org/releases/2.3.0/release_notes.html">our release notes</a> to see all the changes and improvements available in Apache Ignite 2.3 -- and, for sure, download and use this
+ version in production.
+ </p>
+ <p>Questions, comments? Let us know!</p>
+ </div>
+ </article>
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index 96f8ff26e0..457981b621 100644
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+ <a href="/blog/">← Apache Ignite Blog</a>
+ <h1>Apache Ignite 2.4 ings Advanced Machine Learning and Spark DataFrames Capabilities</h1>
+ <p>
+ March 15, 2018 by <strong>Denis Magda: </strong><a href="http://www.facebook.com/sharer.php?u=https://ignite.apache.org/blog/undefined">Facebook</a><span>, </span
+ ><a href="http://twitter.com/home?status=Apache Ignite 2.4 ings Advanced Machine Learning and Spark DataFrames Capabilities%20https://ignite.apache.org/blog/undefined">Twitter</a>
+ </p>
+ </section>
+ <div class="blog__content">
+ <main class="blog_main">
+ <section class="blog__posts">
+ <article class="post">
+ <div>
+ <p>
+ Usually, Ignite community rolls out a new version once in 3 months, but we had to make an exception for Apache Ignite 2.4 that consumed five months in total. We could easily blame Thanksgiving, Christmas and New Year
+ holidays for the delay and would be forgiven, but, in fact, we were forging the release you can't simply pass by.
+ </p>
+ <p>Let's dive in and search for a big fish.</p>
+ <h3>Machine Learning General Availability</h3>
+ <p>
+ Eight months ago, at the time of Apache Ignite 2.0, we put out the first APIs that formed the foundation of the Ignite's machine learning component of today. Since that time, Ignite machine learning experts and
+ enthusiasts have been moving the liary to the general availability condition meticulously. And Ignite 2.4 became a milestone that let us consider the
+ <a href="https://apacheignite.readme.io/docs/machine-learning" target="_blank">ML Grid</a> to be production ready.
+ </p>
+ <!-- end -->
+ <p>
+ The component gained a variety of algorithms that can solve a myriad of regression and classification tasks, gave an ability to train models avoiding ETL from Ignite to other systems, paved a way to
+ <a href="https://apacheignite.readme.io/docs/multilayer-perceptron" target="_blank">deep learning</a> usage scenarios. All that now empowers Ignite users with the tools for dealing with fraud detection, predictive
+ analytics, and for building recommendation systems...if you want. Note, ETL is optional, and the whole memory-centric cluster is at your service!
+ </p>
+ <p>
+ Moreover, Machine Learning Grid welcomed a <a href="http://incubator.apache.org/ip-clearance/ga-grid-ignite.html" target="_blank">software donation</a> by NetMillennium, Inc. in the form of genetic algorithms that solve
+ optimization problems by simulating the process of biological evolution. The algorithms haven't got to Ignite 2.4 and waiting for their time for a release in the master anch. Once you get them, you can apply the
+ biological evolution simulation for real-world applications including automotive design, computer gaming, robotics, investments, traffic/shipment routing and more.
+ </p>
+ <p></p>
+ <p></p>
+ <h3>Spark DataFrames</h3>
+ <p></p>
+ <p>
+ It's not a joke or misprint. Spark users, the DataFrames are now officially supported for you! Many of you have been anticipating them for years and, thanks to Nikolay Izhikov, who was "promoted" to an
+ Ignite committer for the contribution, now you can leverage from them.
+ </p>
+ <p></p>
+ <p>No need to be wordy here. Just go ahead and start with <a href="https://apacheignite-fs.readme.io/docs/ignite-data-frame" target="_blank">DataFrames in Ignite</a>.</p>
+ <p></p>
+ <p></p>
+ <h3>Expanding Ignite ecosystem</h3>
+ <p></p>
+ <p>
+ It was unfair that only Java, C#, and C++ developers could utilize the eadth and depth of Ignite APIs in their applications. Ignite 2.4 solved the injustice with its new
+ <a href="https://apacheignite.readme.io/v2.4/docs/binary-client-protocol" target="_blank">low-level binary client protocol</a>. The protocol communicates with an existing Ignite cluster without starting a full-fledged
+ Ignite node. An application can connect to the cluster through a raw TCP socket from any programming language you like.
+ </p>
+ <p></p>
+ <p>
+ The beauty of the protocol is that you can develop a so-called Ignite thin client that is a lightweight client connected to the cluster and interacts with it using key-value, SQL, and other APIs.
+ <a href="https://apacheignite-net.readme.io/docs/thin-client" target="_blank">.NET thin client</a> is already at your service and Node.JS, Python, PHP, Java thin clients are in a forge and being developed for the next
+ releases.
+ </p>
+ <p></p>
+ <p></p>
+ <h3>RPM repository and much more</h3>
+ So, now Apache Ignite can also be installed from the <a href="https://www.apache.org/dist/ignite/rpm" target="blank_">official RPM repository</a>. Debian users, the packages for your operating systems to be assembled
+ <a href="https://cwiki.apache.org/confluence/display/IGNITE/IEP-11%3A+Introduce+Apache+Ignite+delivery+in+RPM+and+DEB+packages" target="_blank">soon</a>.
+ <p></p>
+ <p></p>
+ <p>
+ Overall, if to list all the features and benefits Ignite 2.4 ings, only 2 people will read the article till the end - me and my dear mom <img class="smiley" src="/img/smile.gif" alt=":)" title=":)" /> Thus, I'll let
+ you discover the rest from the <a href="https://ignite.apache.org/releases/2.4.0/release_notes.html" target="_blank">release notes</a>.
+ </p>
+ </div>
+ </article>
+ <section class="blog__footer">
+ <ul class="pagination post_page">
+ <li><a href="/blog/apache">apache</a></li>
+ <li><a href="/blog/bigdata">bigdata</a></li>
+ <li><a href="/blog/data">data</a></li>
+ <li><a href="/blog/database">database</a></li>
+ <li><a href="/blog/fast">fast</a></li>
+ <li><a href="/blog/ignite">ignite</a></li>
+ <li><a href="/blog/learning">learning</a></li>
+ <li><a href="/blog/machine">machine</a></li>
+ <li><a href="/blog/nodal">nodal</a></li>
+ </ul>
+ </section>
+ </section>
+ </main>
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+ <a href="/blog/">← Apache Ignite Blog</a>
+ <h1>Apache Ignite 2.5: Scaling to 1000s Nodes Clusters</h1>
+ <p>
+ May 31, 2018 by <strong>Denis Magda: </strong><a href="http://www.facebook.com/sharer.php?u=https://ignite.apache.org/blog/undefined">Facebook</a><span>, </span
+ ><a href="http://twitter.com/home?status=Apache Ignite 2.5: Scaling to 1000s Nodes Clusters%20https://ignite.apache.org/blog/undefined">Twitter</a>
+ </p>
+ </section>
+ <div class="blog__content">
+ <main class="blog_main">
+ <section class="blog__posts">
+ <article class="post">
+ <div>
+ <p>
+ Apache Ignite was always appreciated by its users for two primary things it delivers - scalability and performance. Throughout the lifetime many distributed systems tend to do performance optimizations from a release to
+ release while making scalability related improvements just a couple of times. It's not because the scalability is of no interest. Usually, scalability requirements are set and solved once by a distributed system and
+ don't require significant additional interventions by engineers.
+ </p>
+ <p>
+ However, Apache Ignite grew to the point when the community decided to revisit its discovery subsystem that influences how well and far Ignite scales out. The goal was pretty clear - Ignite has to scale to 1000s of nodes
+ as good as it scales to 100s now.
+ </p>
+ <p>
+ It took many months to get the task implemented. So, please join me in welcoming Apache Ignite 2.5 that now can be scaled easily to 1000s of nodes and goes with other exciting capabilities. Let's check out the most
+ prominent ones.
+ </p>
+ <!-- end -->
+ <h3>Massive Scalability</h3>
+ There are two components of Ignite that were modified in Ignite 2.5 to improve its scalability capabilities. The first one is related to 1000s nodes clusters while the other is related to the way we train machine learning
+ (ML) models in Ignite. Let's start with the first.
+ <h4>Marrying Apache Ignite and ZooKeeper</h4>
+ <p></p>
+ <p>Right, that 1000s nodes scalability goal was solved with the help of Apache ZooKeeper. Why did we turn to it?</p>
+ <p>
+ Apache Ignite default TCP/IP Discovery organizes cluster nodes into a ring-topology form that has its advantages and disadvantages. For instance, on topologies with hundreds of cluster nodes, it can take many seconds why a
+ system message traverse through all the nodes. As a result, necessary processing of events such as joining of new nodes or detecting of failed ones can take a while affecting overall cluster responsiveness and performance.
+ That is a big deal if you'd like to run 1000s nodes clusters.
+ </p>
+ <p>
+ The new ZooKeeper Discovery uses ZooKeeper as a single point of synchronization where Ignite nodes are exchanging discovery events through it. It solved the issue with long-to-be-processed discovery messages and, as a
+ result, allowed Ignite scaling to large cluster topologies.
+ </p>
+ <p><a href="https://apacheignite.readme.io/docs/zookeeper-discovery"></a></p>
+ <div style="text-align: center">
+ <a href="https://apacheignite.readme.io/docs/zookeeper-discovery"><img src="/img/blog/4b80632d-232d-4e4f-bd5e-9d91f0bc550f.png" width="450" /></a>
+ </div>
+ <p></p>
+ <p>
+ As a rule of thumb, keep using default <a href="https://apacheignite.readme.io/docs/tcpip-discovery" target="_blank">TCP/IP Discovery</a> if it's unlikely that your Ignite cluster scales beyond 300s nodes and switch
+ to <a href="https://apacheignite.readme.io/docs/zookeeper-discovery" target="_blank">ZooKeeper Discovery</a> if that's the case.
+ </p>
+ <p></p>
+ <h4>Machine Learning: Partition-Based Datasets</h4>
+ <p></p>
+ <p>
+ That's the second prominent feature of Ignite 2.5 that improves the way of how far you can scale your Ignite clusters to train ML models over terabytes or petabytes of data. The
+ <a href="https://apacheignite.readme.io/docs/ml-partition-based-dataset" target="_blank">partition-based datasets</a> moved us closer to the implementation of Zero-ETL concept which implies that Ignite can be used as a
+ single storage where ML models and algorithms are being improved iteratively and online without ETLing data back and forth between Ignite and another storage.
+ </p>
+ <p>Read more about the datasets from <a href="https://apacheignite.readme.io/docs/ml-partition-based-dataset" target="_blank">this</a> documentation page.</p>
+ <p></p>
+ <h3>Genetic Algorithms</h3>
+ Ignite's ML component is ramping up and in the version 2.5 it accepted a contribution of genetic algorithms (GAs) which help to solve optimization problems by simulating the process of biological evolution. GAs are
+ excellent for searching through large and complex data sets for an optimal solution. Real world applications of GAs include automotive design, computer gaming, robotics, investments, traffic/shipment routing and more.
+ <p></p>
+ <p>Refer to excessive articles of my community-mates Turik Campbell and Akmal B. Chaudhri which cover main benefits of GAs:</p>
+ <ul>
+ <li><a href="https://www.linkedin.com/pulse/travel-like-macgyver-solve-knapsack-problem-ga-grid-turik-campbell/" target="_blank">Travel Like MacGyver: Solve Knapsack Problem with GA Grid</a></li>
+ <li><a href="https://www.gridgain.com/resources/blog/genetic-algorithms-apacher-ignitetm" target="_blank">Genetic Algorithms with Apache® Ignite</a></li>
+ </ul>
+ <p></p>
+ <p></p>
+ <h3>Continuous Self-Healing and Consistency Checks</h3>
+ It's a known fact that many companies and businesses trusted Ignite its mission-critical deployments and solutions. As a result, sometimes Ignite doesn't even have a right to "misfire" and should be able
+ to handle critical or unpredictable situations automatically or provide facilities to do deal with them manually.
+ <p></p>
+ <p>
+ With Ignite 2.5, we've kicked off the realization of continuous self-healing concept that implies that no matter what happens with Ignite in production it should be able to tolerate unexpected failures and stay up and
+ running. The following was done in 2.5:
+ </p>
+ <ul>
+ <li><a href="https://apacheignite.readme.io/docs/critical-failures-handling" target="_blank">Critical Failures Handling</a></li>
+ <li><a href="https://apacheignite.readme.io/docs/transactions#section-long-running-transactions-termination" target="_blank">Long running transactions monitoring and termination</a></li>
+ <li><a href="https://apacheignite.readme.io/docs/consistency-check-facilities" target="_blank">Data Consistency Check Facilities</a></li>
+ </ul>
+ <p></p>
+ <p></p>
+ <h3>SQL: Security and Fast Data Loading</h3>
+ <p></p>
+ <p>
+ The community stays strong and determined in its goal of making Ignite SQL engine undistinguishable from SQL engines of famous and mature SQL database. What's the purpose? We want to make it easy for you to migrate
+ from a relational database to Ignite, so that you can reuse all your skills gained before. Overall, this is what our SQL engine got in 2.5:
+ </p>
+ <p></p>
+ <ul>
+ <li>
+ Fast data loading with <a href="https://apacheignite-sql.readme.io/docs/copy" target="_blank">COPY</a> command and
+ <a href="https://apacheignite-sql.readme.io/docs/jdbc-driver#section-streaming" target="_blank">streaming mode</a> using SQL APIs.
+ </li>
+ <li><a href="https://apacheignite.readme.io/docs/transactions#section-long-running-transactions-termination" target="_blank">Long running transactions monitoring and termination</a></li>
+ <li>Secured Ignite cluster. Use <a href="https://apacheignite-sql.readme.io/docs/ddl" target="_blank">CREATE USER, DROP USER and ALTER USER</a> commands to manage who is allowed to connect to your clusters.</li>
+ </ul>
+ <p></p>
+ <p></p>
+ <h3>In-place Execution of Spark DataFrame Queries</h3>
+ <p></p>
+ <p>
+ Apache Spark users can applaud because the <a href="https://issues.apache.org/jira/owse/IGNITE-7077" target="_blank">following ticket</a> got merged in 2.5. In short, it means that from now on Ignite will be able to
+ execute as many DataFrames SQL queries as it can in-place on Ignite servers side avoiding data movement from Ignite to Spark. The performance of your DataFrames queries should boost significantly. Enjoy!
+ </p>
+ <p></p>
+ <h3>DEB and RPM packages</h3>
+ <p></p>
+ <p>
+ Last but not least, if you're a Linux user, now you can install the latest Ignite versions directly from DEB and RPM repositories. Refer to
+ <a href="https://apacheignite.readme.io/docs/getting-started#section-rpm-deb-packages-installation" target="_blank">how-to</a> and share your feedback with us.
+ </p>
+ <p>Finally, I have no more paper left to cover other optimizations and improvements. So, go ahead and check out our <a href="https://ignite.apache.org/releases/2.5.0/release_notes.html" target="_blank">release notes</a>.</p>
+ </div>
+ </article>
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