Author: dmagda
Date: Fri Jan 31 20:53:39 2020
New Revision: 1873446
URL: http://svn.apache.org/viewvc?rev=1873446&view=rev
Log:
Updated in-memory caching and data grid pages
Added:
ignite/site/branches/ignite-redisign/use-cases/in-memory-cache.html
- copied, changed from r1873445,
ignite/site/branches/ignite-redisign/use-cases/caching/database-caching.html
ignite/site/branches/ignite-redisign/use-cases/spark-acceleration.html
- copied unchanged from r1873445,
ignite/site/branches/ignite-redisign/use-cases/spark/spark-acceleration.html
Removed:
ignite/site/branches/ignite-redisign/use-cases/caching/database-caching.html
ignite/site/branches/ignite-redisign/use-cases/database/distributed-database-2.html
ignite/site/branches/ignite-redisign/use-cases/database/sql-database-2.html
ignite/site/branches/ignite-redisign/use-cases/spark/
Modified:
ignite/site/branches/ignite-redisign/.htaccess
ignite/site/branches/ignite-redisign/features/datagrid.html
ignite/site/branches/ignite-redisign/includes/header.html
Modified: ignite/site/branches/ignite-redisign/.htaccess
URL:
http://svn.apache.org/viewvc/ignite/site/branches/ignite-redisign/.htaccess?rev=1873446&r1=1873445&r2=1873446&view=diff
==============================================================================
--- ignite/site/branches/ignite-redisign/.htaccess (original)
+++ ignite/site/branches/ignite-redisign/.htaccess Fri Jan 31 20:53:39 2020
@@ -12,7 +12,8 @@ Redirect 301 /memorycentric.html /arch/m
Redirect 301 /features/persistence.html /arch/persistence.html
Redirect 301 /features/deploy.html /arch/clustering.html
Redirect 301 /features/igniterdd.html /use-cases/spark/shared-memory-layer.html
-Redirect 301 /use-cases/spark/shared-memory-layer.html
/use-cases/spark/spark-acceleration.html
+Redirect 301 /use-cases/spark/shared-memory-layer.html
/use-cases/spark-acceleration.html
+Redirect 301 /use-cases/caching/database-caching.html
/use-cases/in-memory-cache.html
RewriteEngine On
Modified: ignite/site/branches/ignite-redisign/features/datagrid.html
URL:
http://svn.apache.org/viewvc/ignite/site/branches/ignite-redisign/features/datagrid.html?rev=1873446&r1=1873445&r2=1873446&view=diff
==============================================================================
--- ignite/site/branches/ignite-redisign/features/datagrid.html (original)
+++ ignite/site/branches/ignite-redisign/features/datagrid.html Fri Jan 31
20:53:39 2020
@@ -33,15 +33,16 @@ under the License.
<!DOCTYPE html>
<html lang="en">
<head>
- <link rel="canonical"
href="https://ignite.apache.org/features/datagrid.html"; />
+ <link rel="canonical"
href="https://ignite.apache.org/features/datagrid.html"/>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
- <meta http-equiv="Cache-Control" content="no-cache, no-store,
must-revalidate" />
- <meta http-equiv="Pragma" content="no-cache" />
- <meta http-equiv="Expires" content="0" />
- <meta name="description" content="Apache Ignite In-Memory Data Grid is a
distributed transactional key-value store that stores data
- in-memory and on-disk and supports key-value, SQL, and processing
APIs"/>
+
+ <meta name="description"
+ content="Apache Ignite as an In-Memory Data Grid accelerates and
scales your databases, services, and APIs
+ with support of ANSI SQL, ACID transactions, co-located compute, and
machine learning."/>
+
<title>In-Memory Data Grid - Apache Ignite</title>
+
<!--#include virtual="/includes/styles.html" -->
<!--#include virtual="/includes/sh.html" -->
@@ -55,30 +56,49 @@ under the License.
<h1 class="first">Key-Value In-Memory Data Grid</h1>
<div class="col-sm-12 col-md-12 col-xs-12" style="padding:0 0 20px
0;">
<p>
- Ignite provides extensive and rich key-value APIs and can
act as an in-memory data grid.
- You can think of Ignite as of a distributed partitioned
hash map with every
- cluster node owning a portion of the overall data set.
Unlike other in-memory data grids (IMDG),
- Ignite enables storing data both, in memory and on disk,
and
- therefore is able to store more data than can fit in the
physical memory.
+ Apache Ignite provides an extensive set of APIs to act as
an in-memory data grid that integrates into
+ your existing architecture and accelerates databases,
services, or custom APIs.
+ </p>
+ <p>
+ An in-memory data grid type of deployment is also known as
a read-through/write-through caching
+ strategy. With this strategy, Ignite plugs into your
existing architecture seamlessly, and the
+ application layer starts treating it as a primary store.
Your application layer writes to and reads
+ from Ignite, while the latter ensures that any underlying
external databases stay updated and
+ consistent with in-memory data.
+ </p>
+ <p>
+ As an in-memory data grid, Ignite provides all the
essential developer APIs needed to simplify its
+ adoption. The APIs include distributed key-value and ANSI
SQL queries, ACID transactions,
+ co-located computations, and machine learning models.
While key-value and SQL calls let you request,
+ join, and group distributed data sets, the compute and
machine learning components help to eliminate
+ data shuffling over the network, thus, boosting compute
and data-intensive calculations.
</p>
<p>
- Ignite data grid is one of the fastest implementations of
ACID transactions or
- atomic data updates in distributed clusters today. We know
it because we constantly benchmark it ourselves.
+ Ignite is capable of storing data both in memory and on
disk with two options for data persistence
+ -- you can persist changes in an external database or let
Ignite keep data in its native persistence.
+ Let's review two of them.
</p>
+
<div class="col-sm-8 col-md-8 col-xs-12"
style="padding-left:0; padding-right:0">
- <div class="page-heading">3rd Party Databases</div>
+ <div class="page-heading">Ignite and External
Databases</div>
+ <p>
+ Ignite as an in-memory data grid can improve
performance and scalability of existing external
+ databases such as RDBMS, NoSQL or Hadoop, by sliding
in as an in-memory cache between the application
+ and database layers. Ignite will automatically
write-through or write-behind all the changes to
+ an external store. It also includes ACID transactions
- Ignite coordinates and commits a
+ transaction across its in-memory cluster as well as a
relational database.
+ </p>
<p>
- Ignite in-memory data grid can improve performance and
scalability of existing 3rd party databases - RDBMS,
- NoSQL, or Hadoop-based storages, by sliding in as a
distributed cache between the application and database layers.
- Ignite will automatically write-through or
read-through all the updates
- or reads to or from the underlying database. Ignite
will also merge with the underlying database
- transactions, providing transparent transactional
behavior to the users.
+ In addition to that, Ignite can be deployed as a
shared and unified in-memory layer that stores
+ data sets originating from disjointed databases. Your
applications can consume all the data from
+ Ignite as a single store while Ignite can keep the
original databases in sync whenever in-memory
+ data gets updated.
</p>
<p>
- However, this approach has its limitations. For
example, SQL or scan queries will only include the
- results stored in memory, and not in the external
database, since Ignite cannot index the external data.
- If you require that data on disk should be indexed and
accessible via SQL queries, we recommend that you look at
- <a href="/arch/persistence.html">Ignite native
persistence</a>.
+ However, there are some limitations if an external
database is used as a persistence layer for
+ Ignite deployments. For instance, if you run Ignite
SQL or scan queries, you need to ensure
+ that all the data has already been preloaded to the
in-memory cluster. Note that Ignite SQL or
+ scan queries can read data from disk only if it's
stored in Ignite native persistence.
</p>
</div>
@@ -86,435 +106,65 @@ under the License.
<img class="img-responsive" src="/images/IMDG.png"
width="300px" style="float:right;"/>
</div>
</div>
+
<div class="col-sm-12 col-md-12 col-xs-12" style="padding:0 0 20px
0;">
<div class="col-sm-8 col-md-8 col-xs-12"
style="padding-left:0; padding-right:0">
- <div class="page-heading">Native Persistence</div>
+ <div class="page-heading">Ignite Native Persistence</div>
<p>
- Ignite <a href="/arch/persistence.html">native
persistence</a> is a distributed ACID and SQL-compliant disk store that
transparently
- integrates with Ignite's durable memory. Ignite
persistence is optional and can be turned on and off.
- When turned off, Ignite becomes a pure in-memory
store. When native persistence is enabled, Ignite stores
- both data and indexes on disk. A subset of data and
the most frequently used indexes are stored in memory.
- Additionally, since Ignite persists indexes on disk,
they do not have to be rebuilt on cluster
- restart making the system faster than other in-memory
databases.
+ Ignite native persistence is a distributed ACID and
SQL-compliant disk store that transparently
+ integrates with Ignite in-memory layer. When native
persistence is enabled, Ignite stores
+ both data and indexes on disk.
+ The native persistence lets eliminate time-consuming
data reloading
+ phase from external databases as well as a cache
warm-up step. Furthermore, since the native
+ persistence always keeps a full copy of data on disk,
you are free to cache a subset of
+ records in memory. If Ignite finds that a record is
missing in memory, then it will read it from
+ disk automatically regardless of the API you use --
let it be SQL, key-value, or scan queries.
</p>
</div>
<div class="col-sm-4 col-md-4 col-xs-12"
style="padding-right:0">
- <img class="img-responsive"
src="/images/native_persistence_key_value.png" width="300px"
style="float:right;"/>
+ <img class="img-responsive"
src="/images/native_persistence_key_value.png" width="300px"
+ style="float:right;"/>
</div>
</div>
- <div class="page-heading">Key-Value APIs</div>
+ <div class="page-heading">Learn More</div>
<p>
- In addition to the standard <a
href="/use-cases/caching/jcache-provider.html">JCache (JSR 107)</a> API,
Ignites supports distributed ACID transactions,
- scan and continuous queries, collocated processing and more.
+ <a href="/features/sql.html">
+ <b>Distributed SQL <i class="fa
fa-angle-double-right"></i></b>
+ </a>
</p>
-
<p>
- The data grid has been built from the ground up to linearly
scale to hundreds of nodes with strong
- semantics for data locality and affinity data routing to
reduce redundant data noise. It can be
- viewed as a distributed partitioned hash map with every
cluster node owning a portion of the
- overall data. This way the more cluster nodes we add, the more
data we can cache.
+ <a href="/features/collocatedprocessing.html">
+ <b>Co-located processing <i class="fa
fa-angle-double-right"></i></b>
+ </a>
</p>
-
- <div class="page-heading">Affinity Collocation</div>
<p>
- To improve performance and scalability of an application,
Ignite allows collocating data with data or compute with data.
- By collocating related cache keys together, you can make sure
that all keys will be cached on the same processing node,
- hence avoiding costly network trips to fetch data from remote
nodes.
- It is also possible to route computations to the nodes where
the data is cached.
+ <a href="/features/machinelearning.html">
+ <b>Machine Learning <i class="fa
fa-angle-double-right"></i></b>
+ </a>
+ </p>
+ <p>
+ <a href="/features/transactions.html">
+ <b>ACID Transactions <i class="fa
fa-angle-double-right"></i></b>
+ </a>
+ </p>
+ <p>
+ <a href="/arch/persistence.html">
+ <b>Native Persistence <i class="fa
fa-angle-double-right"></i></b>
+ </a>
+ </p>
+ <p>
+ <a href="/use-cases/database/in-memory-database.html">
+ <b>Ignite as an In-Memory Database <i class="fa
fa-angle-double-right"></i></b>
+ </a>
+ </p>
+ <p>
+ <a href="TODO">
+ <b>Ignite as a Digital Integration Hub <i class="fa
fa-angle-double-right"></i></b>
+ </a>
</p>
- <div class="videos">
- <div class="page-heading">Videos</div>
- <ul class="page-list">
- <li>
- <i class="fa fa-lg fa-play-circle-o"></i>
- <span class="video-title">
- <a target="youtube"
href="https://www.youtube.com/watch?v=pFbDWpOiMOU";>Getting Started with Data
Grid</a>
- </span>
- <span class="video-duration">03:49</span>
- </li>
- </ul>
- </div>
-
- <div class="code-examples">
- <div class="page-heading">Code Examples</div>
- <!-- Nav tabs -->
- <ul id="datagrid-examples" class="nav nav-tabs">
- <li class="active"><a href="#datagrid-example-basic"
role="tab" data-toggle="tab">Put and Get</a></li>
- <li><a href="#datagrid-example-transactions" role="tab"
data-toggle="tab">Transactions</a></li>
- <li><a href="#datagrid-example-locks" role="tab"
data-toggle="tab">Locks</a></li>
- <li><a href="#datagrid-example-sqlquery" role="tab"
data-toggle="tab">SQL Query</a></li>
- <li><a href="#datagrid-example-sqljoin" role="tab"
data-toggle="tab">SQL Join</a></li>
- <li><a href="#datagrid-example-sqlaggregation" role="tab"
data-toggle="tab">SQL Aggregation</a></li>
- </ul>
-
- <!-- Tab panes -->
- <div class="tab-content">
- <div role="tabpanel" class="tab-pane active"
id="datagrid-example-basic">
- <pre class="brush:java">
- Ignite ignite = Ignition.ignite();
-
- // Get an instance of named cache.
- final IgniteCache<Integer, String> cache =
ignite.cache("cacheName");
-
- // Store keys in cache.
- for (int i = 0; i < 10; i++)
- cache.put(i, Integer.toString(i));
-
- // Retrieve values from cache.
- for (int i = 0; i < 10; i++)
- System.out.println("Got [key=" + i + ", val="
+ cache.get(i) + ']');
-
- // Remove objects from cache.
- for (int i = 0; i < 10; i++)
- cache.remove(i);
-
- // Atomic put-if-absent.
- cache.putIfAbsent(1, "1");
-
- // Atomic replace.
- cache.replace(1, "1", "2");
- </pre>
- </div>
- <div role="tabpanel" class="tab-pane"
id="datagrid-example-transactions">
- <pre class="brush:java">
- Ignite ignite = Ignition.ignite();
-
- // Clone every object we get from cache, so we can
freely update it.
- IgniteCache<Integer, Account> cache =
ignite.cache("cacheName");
-
- try (IgniteTx tx =
Ignition.ignite().transactions().txStart()) {
- Account acct = cache.get(acctId);
-
- assert acct != null;
-
- // Deposit $20 into account.
- acct.setBalance(acct.getBalance() + 20);
-
- // Store updated account in cache.
- cache.put(acctId, acct);
-
- tx.commit();
- }
- </pre>
- </div>
- <div role="tabpanel" class="tab-pane"
id="datagrid-example-locks">
- <pre class="brush:java">
- Ignite ignite = Ignition.ignite();
-
- // Get an instance of named cache.
- final GridCache<String, Integer> cache =
ignite.cache("cacheName");
-
- // Lock cache key "Hello".
- Lock lock = cache.lock("Hello");
-
- lock.lock();
-
- try {
- cache.put("Hello", 11);
- cache.put("World", 22);
- }
- finally {
- lock.unlock();
- }
- </pre>
- </div>
- <div role="tabpanel" class="tab-pane"
id="datagrid-example-sqlquery">
- <pre class="brush:java">
- IgniteCache<Long, Person> cache =
ignite.cache("mycache");
-
- SqlFieldsQuery sql = new SqlFieldsQuery(
- "select concat(firstName, ' ', lastName) from
Person");
-
- // Select concatinated first and last name for all
persons.
- try (QueryCursor<List<?>> cursor =
cache.query(sql)) {
- for (List<?> row : cursor)
- System.out.println("Full name: " + row.get(0));
- }
- </pre>
- </div>
- <div role="tabpanel" class="tab-pane"
id="datagrid-example-sqljoin">
- <pre class="brush:java">
- IgniteCache<Long, Person> personCache =
ignite.cache("personCache");
-
- // Select with join between Person and
Organization to
- // get the names of all the employees of a
specific organization.
- SqlFieldsQuery sql = new SqlFieldsQuery(
- "select p.name "
- + "from Person p,
\"orgCache\".Organization o where "
- + "p.orgId = o.id "
- + "and o.name = ?");
-
- // Execute the query and obtain the query result
cursor.
- try (QueryCursor<List<?>> cursor =
personCache.query(sql.setArgs("Ignite"))) {
- for (List<?> row : cursor)
- System.out.println("Person name=" + row);
- }
- </pre>
- </div>
- <div role="tabpanel" class="tab-pane"
id="datagrid-example-sqlaggregation">
- <pre class="brush:java">
- IgniteCache<Long, Person> personCache =
ignite.cache("personCache");
-
- // Select average age of people working within
different departments.
- SqlFieldsQuery sql = new SqlFieldsQuery(
- "select avg(p.age) as avg_age, d.name as
dpmt_name, o.name as org_name "
- + "from Person p, \"depCache\".Department
d, \"orgCache\".Organization o "
- + "where p.depid = d.id and d.orgid = o.id
"
- + "group by d.name, o.name "
- + "order by avg_age";
-
- // Execute the query and obtain the query result
cursor.
- try (QueryCursor<List<?>> cursor =
personCache.query(sql.setArgs("Ignite"))) {
- for (List<?> row : cursor)
- System.out.println("Average age by
department and organization: " + row);
- }
- </pre>
- </div>
- </div>
- </div>
- </section>
-
- <section id="key-features" class="page-section">
- <h2>More on Data Grid</h2>
- <table class="formatted" name="key-value-apis">
- <thead>
- <tr>
- <th width="35%" class="left">Feature</th>
- <th>Description</th>
- </tr>
- </thead>
- <tbody>
- <tr>
- <td class="left">Key-Value Store</td>
- <td>
- <p>
- Ignite data grid is a <code>key-value store</code>
which can store data both, in-memory
- and on-disk. It can be viewed as a distributed
partitioned hash map, with every cluster
- node owning a portion of the overall data. This
way the more cluster nodes we add,
- the more data we can store.
- </p>
-
- <div class="page-links">
- <a
href="/use-cases/database/key-value-store.html">Docs for this Feature <i
class="fa fa-angle-double-right"></i></a>
- </div>
- </td>
- </tr>
- <tr>
- <td class="left">Durable Memory</td>
- <td>
- <p>
- Ignite <code>Durable Memory</code> allows storing
and processing data and indexes
- both, in memory and on disk. The in-memory data,
including indexes, is always
- stored and managed <code>off-heap</code>,
completely removing any type of Garbage
- Collection overhead.
- </p>
- <div class="page-links">
- <a
href="https://apacheignite.readme.io/docs/durable-memory"; target="docs">Docs
for this Feature <i class="fa fa-angle-double-right"></i></a>
- </div>
- </td>
- </tr>
- <tr>
- <td class="left">JCache (JSR 107)</td>
- <td>
- <p>
- Ignite is a 100% compliant implementation of <span
style="white-space: nowrap">JCache (JSR 107)</span> specification.
- JCache provides a very simple to use, yet very
powerful API for data caching.
- </p>
- <div class="page-links">
- <a
href="/use-cases/caching/jcache-provider.html">Docs for this Feature <i
class="fa fa-angle-double-right"></i></a>
- </div>
- </td>
- </tr>
- <tr>
- <td class="left">Memory-Centric Storage</td>
- <td>
- <p>
- Apache Ignite is based on distributed
<i>memory-centric architecture</i> that combines the
- performance and scale of in-memory computing
together with the disk durability and strong
- consistency in one system.
- </p>
- <div class="page-links">
- <a href="/arch/memorycentric.html">Docs for this
Feature <i class="fa fa-angle-double-right"></i></a>
- </div>
- </td>
- </tr>
- <tr>
- <td class="left">Collocated Processing</td>
- <td>
- <p>
- Ignite allows executing any native Java, C++, and
.NET/C# code directly on the server-side,
- close to the data, in collocated fashion.
- </p>
- <div class="page-links">
- <a href="/features/collocatedprocessing.html"
target="docs">Docs for this feature <i class="fa fa-angle-double-right"></i></a>
- </div>
- </td>
- </tr>
- <tr>
- <td class="left">Client-side Near Caches</td>
- <td>
- <p>
- Near cache is local client-side cache that stores
the most recently and most frequently accessed data.
- </p>
- <div class="page-links">
- <a
href="http://apacheignite.readme.io/docs/near-caches"; target="docs">Docs for
this Feature <i class="fa fa-angle-double-right"></i></a>
- </div>
- </td>
- </tr>
- <tr>
- <td class="left">ACID Transactions</td>
- <td>
- <p>
- Ignite supports distributed ACID transactions for
key-value as well as SQL operations.
- </p>
- <div class="page-links">
- <a href="/features/transactions.html">Docs for
this Feature <i class="fa fa-angle-double-right"></i></a>
- </div>
- </td>
- </tr>
- <tr>
- <td class="left" width="35%">Deadlock-Free
Transactions</td>
- <td>
- <p>
- Ignite supports deadlock-free, optimistic
transactions, which do not acquire any locks,
- and free users from worrying about the lock order.
- Such transactions also provide much better
performance.
- </p>
- <div class="page-links">
- <a
href="https://apacheignite.readme.io/docs/transactions"; target="docs">Docs for
this feature <i class="fa fa-angle-double-right"></i></a>
- </div>
- </td>
- </tr>
- <tr>
- <td class="left" width="35%">Transactional Entry
Processor</td>
- <td>
- <p>
- Ignite transactional entry processor allows
executing collocated user logic on the server
- side within a transaction.
- </p>
- <div class="page-links">
- <a
href="https://apacheignite.readme.io/docs/affinity-collocation#ignitecompute-vs-entryprocessor";
target="docs">Docs for this feature <i class="fa
fa-angle-double-right"></i></a>
- </div>
- </td>
- </tr>
- <tr>
- <td class="left" width="35%">Cross-Partition
Transactions</td>
- <td>
- <p>
- In Ignite, transactions can be performed on all
partitions of a cache across the whole cluster.
- </p>
- <div class="page-links">
- <a
href="https://apacheignite.readme.io/docs/transactions#ignitetransactions";
target="docs">Docs for this feature <i class="fa fa-angle-double-right"></i></a>
- </div>
- </td>
- </tr>
- <tr>
- <td class="left" width="35%">Locks</td>
- <td>
- <p>
- Ignite allows developers to define explicit locks
enforcing mutual exclusion on cached objects.
- </p>
- <div class="page-links">
- <a
href="https://apacheignite.readme.io/docs/distributed-locks"; target="docs">Docs
for this feature <i class="fa fa-angle-double-right"></i></a>
- </div>
- </td>
- </tr>
- <tr>
- <td class="left" width="35%">Continuous Queries</td>
- <td>
- <p>
- Continuous queries are useful for cases when you
want to execute a query and then
- continue to get notified about the data changes
that fall into your query filter.
- </p>
- <div class="page-links">
- <a
href="https://apacheignite.readme.io/docs/continuous-queries";
target="docs">Docs for this feature <i class="fa fa-angle-double-right"></i></a>
- </div>
- </td>
- </tr>
- <tr>
- <td class="left" width="35%">Write-Through</td>
- <td>
- <p>
- Write-Through mode allows updating the data in the
database.
- </p>
- <div class="page-links">
- <a
href="https://apacheignite.readme.io/docs/3rd-party-store#read-through-and-write-through";
target="docs">Docs for this feature <i class="fa
fa-angle-double-right"></i></a>
- </div>
- </td>
- </tr>
- <tr>
- <td class="left">Read-Through</td>
- <td>
- <p>
- Read-Through mode allows reading the data from the
database.
- </p>
- <div class="page-links">
- <a
href="https://apacheignite.readme.io/docs/3rd-party-store#read-through-and-write-through";
target="docs">Docs for this feature <i class="fa
fa-angle-double-right"></i></a>
- </div>
- </td>
- </tr>
- <tr>
- <td class="left">Write-Behind Caching</td>
- <td>
- <p>
- Ignite provides an option to asynchronously
perform updates to the database via Write-Behind Caching.
- </p>
- <div class="page-links">
- <a
href="https://apacheignite.readme.io/docs/3rd-party-store#section-write-behind-caching";
target="docs">Docs for this feature <i class="fa
fa-angle-double-right"></i></a>
- </div>
- </td>
- </tr>
- <tr>
- <td class="left">Hibernate L2 Caching</td>
- <td>
- <p>
- Ignite data grid can be used as <code>Hibernate
Second-Level Cache</code> (or L2 cache),
- which can significantly speed-up the persistence
layer of your application.
- </p>
- <div class="page-links">
- <a
href="https://apacheignite-mix.readme.io/docs/hibernate-l2-cache";
target="docs">Docs for this Feature <i class="fa fa-angle-double-right"></i></a>
- </div>
- </td>
- </tr>
- <tr>
- <td class="left">Spring Caching</td>
- <td>
- <p>
- Ignite provides Spring-annotation-based way to
enable caching for Java methods so that
- the result of a method execution is stored in the
Ignite cache. If later the same
- method is called with the same set of parameters,
the result will be retrieved from
- the cache instead of actually executing the method.
- </p>
- <div class="page-links">
- <a
href="http://apacheignite-mix.readme.io/docs/spring-caching"; target="docs">Docs
for this Feature <i class="fa fa-angle-double-right"></i></a>
- </div>
- </td>
- </tr>
- <tr>
- <td class="left">Spring Data</td>
- <td>
- <p>
- Apache Ignite implements Spring Data
<code>CrudRepository</code> interface that not only supports basic CRUD
operations but also provides access to the Apache Ignite SQL capabilities via
the unified Spring Data API.
- </p>
- <div class="page-links">
- <a
href="https://apacheignite-mix.readme.io/docs/spring-data"; target="docs">Docs
for this Feature <i class="fa fa-angle-double-right"></i></a>
- </div>
- </td>
- </tr>
- <tr>
- <td class="left">OSGI Support</td>
- <td>
- <p></p>
- <div class="page-links">
- <a
href="https://apacheignite-mix.readme.io/docs/starting-inside-an-osgi-container";
target="docs">Docs for this feature <i class="fa
fa-angle-double-right"></i></a>
- </div>
- </td>
- </tr>
- </tbody>
- </table>
</section>
</main>
Modified: ignite/site/branches/ignite-redisign/includes/header.html
URL:
http://svn.apache.org/viewvc/ignite/site/branches/ignite-redisign/includes/header.html?rev=1873446&r1=1873445&r2=1873446&view=diff
==============================================================================
--- ignite/site/branches/ignite-redisign/includes/header.html (original)
+++ ignite/site/branches/ignite-redisign/includes/header.html Fri Jan 31
20:53:39 2020
@@ -54,14 +54,14 @@
onclick="ga('send', 'event',
'apache_ignite_features', 'menu_click', 'distributed_sql');">
Distributed SQL</a>
</li>
- <li><a href="/features/datagrid.html"
aria-label="DataGrid"
+ <li><a href="#TODO"
aria-label="DataGrid"
onclick="ga('send', 'event',
'apache_ignite_features', 'menu_click', 'distributed_key_value');">
Distributed Key-Value</a>
</li>
- <!--<li><a
href="/arch/persistence.html"-->
- <!--onclick="ga('send', 'event',
'apache_ignite_features', 'menu_click', 'persistence');">-->
- <!--Distributed Persistence</a>-->
- <!--</li>-->
+ <li><a href="/arch/persistence.html"
+ onclick="ga('send', 'event',
'apache_ignite_features', 'menu_click', 'persistence');">
+ Native Persistence</a>
+ </li>
<li><a
href="/features/transactions.html" aria-label="Transactions"
onclick="ga('send', 'event',
'apache_ignite_features', 'menu_click', 'acid_transactions');">
ACID Transactions</a>
@@ -103,7 +103,8 @@
<a class="dropdown-toggle"
data-toggle="dropdown" aria-label="Use Cases">Use Cases<span
class="caret"></span></a>
<ul class="dropdown-menu" role="menu">
- <li><a
href="/use-cases/caching/database-caching.html"
+ <li role="presentation"
class="submenu-header">Caching & Database</li>
+ <li><a
href="/use-cases/in-memory-cache.html"
aria-label="In-Memory Cache"
onclick="ga('send', 'event',
'apache_ignite_usecases', 'menu_click', 'in_memory_cache');">
In-Memory Cache</a>
@@ -116,15 +117,26 @@
onclick="ga('send', 'event',
'apache_ignite_usecases', 'menu_click', 'distributed-database');">
In-Memory Database</a>
</li>
- <li><a href="#" aria-label="Digital
Integration Hub"
- onclick="ga('send', 'event',
'apache_ignite_usecases', 'menu_click', 'digital_integration_hub');">
- Digital Integration Hub</a>
- </li>
<li><a
href="/use-cases/database/key-value-store.html" aria-label="Key-Value Store"
onclick="ga('send', 'event',
'apache_ignite_usecases', 'menu_click', 'key_value_store');">
Key-Value Store</a>
</li>
- <li><a
href="/use-cases/spark/spark-acceleration.html"
+ <li class="divider">
+
+ <li role="presentation"
class="submenu-header">Data & Compute Hubs</li>
+ <li><a href="#TODO"
aria-label="Digital Integration Hub"
+ onclick="ga('send', 'event',
'apache_ignite_usecases', 'menu_click', 'digital_integration_hub');">
+ Digital Integration Hub</a>
+ </li>
+ <li><a href="#TODO"
aria-label="Compute Engine"
+ onclick="ga('send', 'event',
'apache_ignite_usecases', 'menu_click', 'massive_parallel_processing');">
+ Compute Engine</a>
+ </li>
+
+ <li class="divider">
+
+ <li role="presentation"
class="submenu-header">Faster Analytics</li>
+ <li><a
href="/use-cases/spark-acceleration.html"
aria-label="Apache Spark
Acceleration"
onclick="ga('send', 'event',
'apache_ignite_usecases', 'menu_click', 'apache_spark_acceleration');">
Apache Spark Acceleration</a>
@@ -134,7 +146,11 @@
onclick="ga('send', 'event',
'apache_ignite_usecases', 'menu_click', 'hadoop_acceleration');">
Apache Hadoop Acceleration</a>
</li>
- <li><a href="/provenusecases.html"
aria-label="Proven Use Cases"
+
+ <li class="divider">
+
+ <li role="presentation"
class="submenu-header">Ignite in Production</li>
+ <li><a href="/provenusecases.html"
aria-label="Powered by Ignite"
onclick="ga('send', 'event',
'apache_ignite_usecases', 'menu_click', 'proven_usecases');">
Powered by Ignite</a>
</li>
Copied: ignite/site/branches/ignite-redisign/use-cases/in-memory-cache.html
(from r1873445,
ignite/site/branches/ignite-redisign/use-cases/caching/database-caching.html)
URL:
http://svn.apache.org/viewvc/ignite/site/branches/ignite-redisign/use-cases/in-memory-cache.html?p2=ignite/site/branches/ignite-redisign/use-cases/in-memory-cache.html&p1=ignite/site/branches/ignite-redisign/use-cases/caching/database-caching.html&r1=1873445&r2=1873446&rev=1873446&view=diff
==============================================================================
---
ignite/site/branches/ignite-redisign/use-cases/caching/database-caching.html
(original)
+++ ignite/site/branches/ignite-redisign/use-cases/in-memory-cache.html Fri Jan
31 20:53:39 2020
@@ -36,7 +36,13 @@ under the License.
<link rel="canonical"
href="https://ignite.apache.org/use-cases/caching/database-caching.html"; />
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
- <title>Distributed In-Memory Cache With SQL and ACID Transactions - Apache
Ignite</title>
+
+ <meta name="description"
+ content="Apache Ignite as an In-Memory Cache accelerates and scales
your databases, services, and APIs
+ with support of ANSI SQL, ACID transactions, co-located compute, and
machine learning."/>
+
+ <title>In-Memory Cache - Apache Ignite</title>
+
<!--#include virtual="/includes/styles.html" -->
<!--#include virtual="/includes/sh.html" -->
@@ -47,16 +53,14 @@ under the License.
<main id="main" role="main" class="container">
<section id="database-caching" class="page-section">
- <h1 class="first">Distributed In-Memory Cache With SQL and ACID
Transactions</h1>
+ <h1 class="first">In-Memory Cache With ANSI SQL, ACID Transactions
and Compute APIs</h1>
<div class="col-sm-12 col-md-12 col-xs-12" style="padding:0 0 20px
0;">
<div class="col-sm-6 col-md-6 col-xs-12"
style="padding-left:0;">
<p>
- Distributed in-memory cache that supports ANSI SQL,
ACID transactions and co-located
- computations is one of the usage scenarios Apache
Ignite is selected for. From web sessions
- and financial instruments caching to external APIs and
existing databases acceleration, Ignite
- provides all essential components needed to speed up
enterprise applications as well as
- microservices-based architectures that require more
than standard key-value look-ups for data
- processing.
+ Distributed in-memory cache that supports ANSI SQL,
ACID transactions, and co-located
+ computations is one of the usage scenarios Apache
Ignite is selected for. From sessions and
+ APIs caching to databases and microservices
acceleration, Ignite provides all essential
+ components needed to speed things up.
</p>
</div>
<div class="col-sm-6 col-md-5 col-xs-12"
style="padding-right:0">
@@ -65,65 +69,63 @@ under the License.
</div>
<p>
- As a typical distributed cache, you would span Ignite cluster
across several interconnected
- physical or virtual machines letting it utilize all the
available memory and CPU resources.
- However, the difference comes in a way you can utilize the
cluster once it's up and running. In
- addition to classic key-value APIs you can run distributed SQL
queries joining and grouping
- various data sets. If strong consistency is required, you can
execute multi-records and
- cross-cache ACID transactions in both pessimistic and
optimistic modes. Next, if an
- application runs compute or data-intensive logic, you can
minimize data shuffling and network
- utilization by running co-located computations and distributed
machine learning APIs on the cluster
- nodes that store actual data.
+ As with classic distributed caches, you would span an Ignite
cluster across several interconnected
+ physical or virtual machines letting it utilize all the
available memory and CPU resources. However,
+ the difference comes in a way you can use the cluster once
it's up and running. In addition to
+ standard key-value APIs, you can run distributed SQL queries
joining and grouping various data sets.
+ If strong consistency is required, you can execute
multi-records and cross-cache ACID transactions in
+ both pessimistic and optimistic modes. Next, if an application
runs compute or data-intensive logic,
+ you can minimize data shuffling with network utilization by
running co-located computations and
+ distributed machine learning APIs right on the cluster nodes
that store your data.
</p>
<p>
There are two primary deployment strategies for Ignite as an
in-memory cache -- the cache-aside one and
- read-through/write-through caching. Let's review both
separately.
+ read-through/write-through caching. Let's review two of them.
</p>
<div class="page-heading">Cache-Aside Deployment</div>
<p>
- With the cache-aside deployment strategy, the cache is
deployed separately from a primary data store
- and might not even know about existence of the latter. An
application layer becomes in charge of
- synchronization between a cache and a primary data store. If a
record gets updated in the data store
- then either the application or some change-data-capture (CDC)
process needs to refresh a similar
- record in the cache.
- </p>
- <p>
- This strategy works well when the cached data is rather static
and not updated frequently or
- temporary data lag/inconsistency is allowed between the
primary store and the in-memory cache. It's
- assumed that the cache and the store will become consistent
eventually as soon as soon as changes are
- replicated in full.
- </p>
- <p>
- If Apache Ignite is deployed in this configuration, then its
native persistence can be used as a disk
- store. This lets eliminate time-consuming data reloading phase
from the primary store as well as
- a cache warm-up step. Furthermore, the native persistence
allows you to cache a subset of the data
- by keeping the full copy on disk. If any piece of data is not
cached in RAM then Ignite will take
- it from disk automatically regardless of the API you use let
it be SQL, key-value or scan queries.
+ With the cache-aside deployment strategy, a cache is deployed
separately from a primary data store and
+ might not even know that the latter exists. An application or
change-data-capture process (CDC) becomes
+ responsible for data synchronization between these two storage
locations. For instance, if any record
+ gets updated in the primary store, then its new value needs to
be replicated to the cache.
+ </p>
+ <p>
+ This strategy works well when the cached data is rather static
and not updated frequently, or
+ temporary data lag/inconsistency is allowed between the two
storage locations. It's usually assumed
+ that the cache and the primary store will become consistent
eventually as soon as changes are replicated
+ in full.
+ </p>
+ <p>
+ If Apache Ignite is deployed in a cache-aside configuration,
then its native persistence can be used as
+ a disk store for Ignite data sets. The native persistence lets
eliminate time-consuming data reloading
+ phase from the primary store as well as a cache warm-up step.
Furthermore, since the native persistence
+ always keeps a full copy of data on disk, you are free to
cache a subset of records in memory. If Ignite
+ finds that a record is missing in memory, then it will read it
from disk automatically regardless of the
+ API you use -- let it be SQL, key-value, or scan queries.
</p>
<div class="page-heading">Read-Through/Write-Through Caching</div>
<p>
- The read-through/write-through caching strategy can also be
classified as an in-memory data grid type
- of deployment. When Apache Ignite is deployed as a data grid,
the application layer starts
- treating an Ignite cluster as the primary store. The
applications write to and read from Ignite only
- and it becomes Ignite's responsobility to keep an underlying
external database updated and
- consistent with the in-memory data.
+ The read-through/write-through caching strategy can also be
classified as an in-memory data grid type of
+ deployment. When Apache Ignite is deployed as a data grid, the
application layer starts treating Ignite
+ as the primary store. The applications write to and read from
Ignite while the latter ensures that any
+ underlying external databases stay updated and consistent with
the in-memory data.
</p>
<p>
- This strategy is favorable for architectures that need to
accelerate performance or scale external
- disk-based databases such as RDBMS or NoSQL. Ignite integrates
with many databases out-of-the box and
- can write-through or write-behind all the changes to them.
This also includes ACID transactions -
- Ignite will coordinate and commit a transaction across its own
in-memory cluster as well as to a
- relational database.
+ This strategy is favorable for architectures that need to
accelerate existing disk-based databases or
+ create a shared caching layer across many disconnected data
sources. Ignite integrates with many
+ databases out-of-the box and can write-through or write-behind
all the changes to them. This also
+ includes ACID transactions - Ignite will coordinate and commit
a transaction across its own in-memory
+ cluster as well as to a relational database.
</p>
<p>
- The read-through capability assumes that a cache can read data
from the external database if a record
- is missing in memory. Ignite fully supports this capability
for key-value APIs. However, if Ignite
- SQL is at use then you have to preload an entire data set from
the underlying database first. (Note,
- that Ignite SQL can query disk if data is persisted in its own
native persistence).
+ The read-through capability implies that a cache can read data
from an external database if a record is
+ missing in memory. Ignite fully supports this capability for
key-value APIs. However, if Ignite SQL is
+ at use then you have to preload an entire data set in memory
first. (Note, that Ignite SQL can query
+ data on disk only if it's located in its native persistence).
</p>
<div class="page-heading">Learn More</div>
<p>
@@ -142,7 +144,7 @@ under the License.
</a>
</p>
<p>
- <a
href="https://apacheignite.readme.io/docs/distributed-persistent-store";
target="docs">
+ <a href="/arch/persistence.html">
<b>Native Persistence <i class="fa
fa-angle-double-right"></i></b>
</a>
</p>
