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commit60dd840ae3e06f0541b9ae9302b9c414b89a8fce[log] [tgz]
authorAndrey Zagrebin <azagrebin@apache.org>Tue Apr 21 12:08:00 2020 +0300
committerAndrey Zagrebin <azagrebin@apache.org>Tue Apr 21 12:09:29 2020 +0300
tree67d168ca1853288fd9b5ea8cdf2307d7c6bf3b3c
parent35bc782748b930e8593662fbff54f338cccc7f15 [diff]
Rebuild website

diff --git a/content/blog/feed.xml b/content/blog/feed.xml
index 126b62b..46654e8 100644
--- a/content/blog/feed.xml
+++ b/content/blog/feed.xml

@@ -7,6 +7,103 @@
 <atom:link href="https://flink.apache.org/blog/feed.xml" rel="self" type="application/rss+xml" />
 
 <item>
+<title>Memory Management Improvements with Apache Flink 1.10</title>
+<description>&lt;p&gt;Apache Flink 1.10 comes with significant changes to the memory model of the Task Managers and configuration options for your Flink applications. These recently-introduced changes make Flink more adaptable to all kinds of deployment environments (e.g. Kubernetes, Yarn, Mesos), providing strict control over its memory consumption. In this post, we describe Flink’s memory model, as it stands in Flink 1.10, how to set up and manage memory consumption of your Flink applications and the recent changes the community implemented in the latest Apache Flink release.&lt;/p&gt;
+
+&lt;h2 id=&quot;introduction-to-flinks-memory-model&quot;&gt;Introduction to Flink’s memory model&lt;/h2&gt;
+
+&lt;p&gt;Having a clear understanding of Apache Flink’s memory model allows you to manage resources for the various workloads more efficiently. The following diagram illustrates the main memory components in Flink:&lt;/p&gt;
+
+&lt;center&gt;
+&lt;img src=&quot;/img/blog/2020-04-21-memory-management-improvements-flink-1.10/total-process-memory.svg&quot; width=&quot;400px&quot; alt=&quot;Flink: Total Process Memory&quot; /&gt;
+&lt;br /&gt;
+&lt;i&gt;&lt;small&gt;Flink: Total Process Memory&lt;/small&gt;&lt;/i&gt;
+&lt;/center&gt;
+&lt;p&gt;&lt;br /&gt;&lt;/p&gt;
+
+&lt;p&gt;The Task Manager process is a JVM process. On a high level, its memory consists of the &lt;em&gt;JVM Heap&lt;/em&gt; and &lt;em&gt;Off-Heap&lt;/em&gt; memory. These types of memory are consumed by Flink directly or by JVM for its specific purposes (i.e. metaspace etc.). There are two major memory consumers within Flink: the user code of job operator tasks and the framework itself consuming memory for internal data structures, network buffers, etc.&lt;/p&gt;
+
+&lt;p&gt;&lt;strong&gt;Please note that&lt;/strong&gt; the user code has direct access to all memory types: &lt;em&gt;JVM Heap, Direct&lt;/em&gt; and &lt;em&gt;Native memory&lt;/em&gt;. Therefore, Flink cannot really control its allocation and usage. There are however two types of Off-Heap memory which are consumed by tasks and controlled explicitly by Flink:&lt;/p&gt;
+
+&lt;ul&gt;
+  &lt;li&gt;&lt;em&gt;Managed Memory&lt;/em&gt; (Off-Heap)&lt;/li&gt;
+  &lt;li&gt;&lt;em&gt;Network Buffers&lt;/em&gt;&lt;/li&gt;
+&lt;/ul&gt;
+
+&lt;p&gt;The latter is part of the &lt;em&gt;JVM Direct Memory&lt;/em&gt;, allocated for user record data exchange between operator tasks.&lt;/p&gt;
+
+&lt;h2 id=&quot;how-to-set-up-flink-memory&quot;&gt;How to set up Flink memory&lt;/h2&gt;
+
+&lt;p&gt;With the latest release of Flink 1.10 and in order to provide better user experience, the framework comes with both high-level and fine-grained tuning of memory components. There are essentially three alternatives to setting up memory in Task Managers.&lt;/p&gt;
+
+&lt;p&gt;The first two — and simplest — alternatives are configuring one of the two following options for total memory available for the JVM process of the Task Manager:&lt;/p&gt;
+
+&lt;ul&gt;
+  &lt;li&gt;&lt;em&gt;Total Process Memory&lt;/em&gt;: total memory consumed by the Flink Java application (including user code) and by the JVM to run the whole process.&lt;/li&gt;
+  &lt;li&gt;&lt;em&gt;Total Flink Memory&lt;/em&gt;: only memory consumed by the Flink Java application, including user code but excluding memory allocated by JVM to run it&lt;/li&gt;
+&lt;/ul&gt;
+
+&lt;p&gt;It is advisable to configure the &lt;em&gt;Total Flink Memory&lt;/em&gt; for standalone deployments where explicitly declaring how much memory is given to Flink is a common practice, while the outer &lt;em&gt;JVM overhead&lt;/em&gt; is of little interest. For the cases of deploying Flink in containerized environments (such as &lt;a href=&quot;https://ci.apache.org/projects/flink/flink-docs-release-1.10/ops/deployment/kubernetes.html&quot;&gt;Kubernetes&lt;/a&gt;, &lt;a href=&quot;https://ci.apache.org/projects/flink/flink-docs-release-1.10/ops/deployment/yarn_setup.html&quot;&gt;Yarn&lt;/a&gt; or &lt;a href=&quot;https://ci.apache.org/projects/flink/flink-docs-release-1.10/ops/deployment/mesos.html&quot;&gt;Mesos&lt;/a&gt;), the &lt;em&gt;Total Process Memory&lt;/em&gt; option is recommended instead, because it becomes the size for the total memory of the requested container. Containerized environments usually strictly enforce this memory limit.&lt;/p&gt;
+
+&lt;p&gt;If you want more fine-grained control over the size of &lt;em&gt;JVM Heap&lt;/em&gt; and &lt;em&gt;Managed Memory&lt;/em&gt; (Off-Heap), there is also a second alternative to configure both &lt;em&gt;&lt;a href=&quot;https://ci.apache.org/projects/flink/flink-docs-release-1.10/ops/memory/mem_setup.html#task-operator-heap-memory&quot;&gt;Task Heap&lt;/a&gt;&lt;/em&gt; and &lt;em&gt;&lt;a href=&quot;https://ci.apache.org/projects/flink/flink-docs-release-1.10/ops/memory/mem_setup.html#managed-memory&quot;&gt;Managed Memory&lt;/a&gt;&lt;/em&gt;. This alternative gives a clear separation between the heap memory and any other memory types.&lt;/p&gt;
+
+&lt;p&gt;In line with the community’s efforts to &lt;a href=&quot;https://flink.apache.org/news/2019/02/13/unified-batch-streaming-blink.html&quot;&gt;unify batch and stream processing&lt;/a&gt;, this model works universally for both scenarios. It allows sharing the &lt;em&gt;JVM Heap&lt;/em&gt; memory between the user code of operator tasks in any workload and the heap state backend in stream processing scenarios. In a similar way, the &lt;em&gt;Managed Memory&lt;/em&gt; can be used for batch spilling and for the RocksDB state backend in streaming.&lt;/p&gt;
+
+&lt;p&gt;The remaining memory components are automatically adjusted either based on their default values or additionally configured parameters. Flink also checks the overall consistency. You can find more information about the different memory components in the corresponding &lt;a href=&quot;https://ci.apache.org/projects/flink/flink-docs-release-1.10/ops/memory/mem_detail.html&quot;&gt;documentation&lt;/a&gt;. Additionally, you can try different configuration options with the &lt;a href=&quot;https://docs.google.com/spreadsheets/d/1mJaMkMPfDJJ-w6nMXALYmTc4XxiV30P5U7DzgwLkSoE/edit#gid=0&quot;&gt;configuration spreadsheet&lt;/a&gt; of &lt;a href=&quot;https://cwiki.apache.org/confluence/display/FLINK/FLIP-49%3A+Unified+Memory+Configuration+for+TaskExecutors&quot;&gt;FLIP-49&lt;/a&gt; and check the corresponding results for your individual case.&lt;/p&gt;
+
+&lt;p&gt;If you are migrating from a Flink version older than 1.10, we suggest following the steps in the &lt;a href=&quot;https://ci.apache.org/projects/flink/flink-docs-release-1.10/ops/memory/mem_migration.html&quot;&gt;migration guide&lt;/a&gt; of the Flink documentation.&lt;/p&gt;
+
+&lt;h2 id=&quot;other-components&quot;&gt;Other components&lt;/h2&gt;
+
+&lt;p&gt;While configuring Flink’s memory, the size of different memory components can either be fixed with the value of the respective option or tuned using multiple options. Below we provide some more insight about the memory setup.&lt;/p&gt;
+
+&lt;h3 id=&quot;fractions-of-the-total-flink-memory&quot;&gt;Fractions of the Total Flink Memory&lt;/h3&gt;
+
+&lt;p&gt;This method allows a proportional breakdown of the &lt;em&gt;Total Flink Memory&lt;/em&gt; where the &lt;a href=&quot;https://ci.apache.org/projects/flink/flink-docs-release-1.10/ops/memory/mem_setup.html#managed-memory&quot;&gt;Managed Memory&lt;/a&gt; (if not set explicitly) and &lt;a href=&quot;https://ci.apache.org/projects/flink/flink-docs-release-1.10/ops/memory/mem_detail.html#capped-fractionated-components&quot;&gt;Network Buffers&lt;/a&gt; can take certain fractions of it. The remaining memory is then assigned to the &lt;a href=&quot;https://ci.apache.org/projects/flink/flink-docs-release-1.10/ops/memory/mem_setup.html#task-operator-heap-memory&quot;&gt;Task Heap&lt;/a&gt; (if not set explicitly) and other fixed &lt;em&gt;JVM Heap&lt;/em&gt; and &lt;em&gt;Off-Heap components&lt;/em&gt;. The following picture represents an example of such a setup:&lt;/p&gt;
+
+&lt;center&gt;
+&lt;img src=&quot;/img/blog/2020-04-21-memory-management-improvements-flink-1.10/flink-memory-setup.svg&quot; width=&quot;800px&quot; alt=&quot;Flink: Example of Memory Setup&quot; /&gt;
+&lt;br /&gt;
+&lt;i&gt;&lt;small&gt;Flink: Example of Memory Setup&lt;/small&gt;&lt;/i&gt;
+&lt;/center&gt;
+&lt;p&gt;&lt;br /&gt;&lt;/p&gt;
+
+&lt;p&gt;&lt;strong&gt;Please note that&lt;/strong&gt;&lt;/p&gt;
+
+&lt;ul&gt;
+  &lt;li&gt;Flink will verify that the size of the derived &lt;em&gt;Network Memory&lt;/em&gt; is between its minimum and maximum value, otherwise Flink’s startup will fail. The maximum and minimum limits have default values which can be overwritten by the respective configuration options.&lt;/li&gt;
+  &lt;li&gt;In general, the configured fractions are treated by Flink as hints. Under certain scenarios, the derived value might not match the fraction. For example, if the &lt;em&gt;Total Flink Memory&lt;/em&gt; and the &lt;em&gt;Task Heap&lt;/em&gt; are configured to fixed values, the &lt;em&gt;Managed Memory&lt;/em&gt; will get a certain fraction and the &lt;em&gt;Network Memory&lt;/em&gt; will get the remaining memory which might not exactly match its fraction.&lt;/li&gt;
+&lt;/ul&gt;
+
+&lt;h3 id=&quot;more-hints-to-control-the-container-memory-limit&quot;&gt;More hints to control the container memory limit&lt;/h3&gt;
+
+&lt;p&gt;The heap and direct memory usage are managed by the JVM. There are also many other possible sources of native memory consumption in Apache Flink or its user applications which are not managed by Flink or the JVM. Controlling their limits is often difficult which complicates debugging of potential memory leaks. If Flink’s process allocates too much memory in an unmanaged way, it can often result in killing Task Manager containers in containerized environments. In this case, it may be hard to understand which type of memory consumption has exceeded its limit. Flink 1.10 introduces some specific tuning options to clearly represent such components. Although Flink cannot always enforce strict limits and borders among them, the idea here is to explicitly plan the memory usage. Below we provide some examples of how memory setup can prevent containers exceeding their memory limit:&lt;/p&gt;
+
+&lt;ul&gt;
+  &lt;li&gt;
+    &lt;p&gt;&lt;a href=&quot;https://ci.apache.org/projects/flink/flink-docs-release-1.10/ops/memory/mem_tuning.html#rocksdb-state-backend&quot;&gt;RocksDB state cannot grow too big&lt;/a&gt;. The memory consumption of RocksDB state backend is accounted for in the &lt;em&gt;Managed Memory&lt;/em&gt;. RocksDB respects its limit by default (only since Flink 1.10). You can increase the &lt;em&gt;Managed Memory&lt;/em&gt; size to improve RocksDB’s performance or decrease it to save resources.&lt;/p&gt;
+  &lt;/li&gt;
+  &lt;li&gt;
+    &lt;p&gt;&lt;a href=&quot;https://ci.apache.org/projects/flink/flink-docs-release-1.10/ops/memory/mem_setup.html#configure-off-heap-memory-direct-or-native&quot;&gt;User code or its dependencies consume significant off-heap memory&lt;/a&gt;. Tuning the &lt;em&gt;Task Off-Heap&lt;/em&gt; option can assign additional direct or native memory to the user code or any of its dependencies. Flink cannot control native allocations but it sets the limit for &lt;em&gt;JVM Direct&lt;/em&gt; memory allocations. The &lt;em&gt;Direct&lt;/em&gt; memory limit is enforced by the JVM.&lt;/p&gt;
+  &lt;/li&gt;
+  &lt;li&gt;
+    &lt;p&gt;&lt;a href=&quot;https://ci.apache.org/projects/flink/flink-docs-release-1.10/ops/memory/mem_detail.html#jvm-parameters&quot;&gt;JVM metaspace requires additional memory&lt;/a&gt;. If you encounter &lt;code&gt;OutOfMemoryError: Metaspace&lt;/code&gt;, Flink provides an option to increase its limit and the JVM will ensure that it is not exceeded.&lt;/p&gt;
+  &lt;/li&gt;
+  &lt;li&gt;
+    &lt;p&gt;&lt;a href=&quot;https://ci.apache.org/projects/flink/flink-docs-release-1.10/ops/memory/mem_detail.html#capped-fractionated-components&quot;&gt;JVM requires more internal memory&lt;/a&gt;. There is no direct control over certain types of JVM process allocations but Flink provides &lt;em&gt;JVM Overhead&lt;/em&gt; options. The options allow declaring an additional amount of memory, anticipated for those allocations and not covered by other options.&lt;/p&gt;
+  &lt;/li&gt;
+&lt;/ul&gt;
+
+&lt;h2 id=&quot;conclusion&quot;&gt;Conclusion&lt;/h2&gt;
+
+&lt;p&gt;The latest Flink release (Flink 1.10) introduces some significant changes to Flink’s memory configuration, making it possible to manage your application memory and debug Flink significantly better than before. Future developments in this area also include adopting a similar memory model for the job manager process in &lt;a href=&quot;https://cwiki.apache.org/confluence/display/FLINK/FLIP+116%3A+Unified+Memory+Configuration+for+Job+Managers&quot;&gt;FLIP-116&lt;/a&gt;, so stay tuned for more additions and features in upcoming releases. If you have any suggestions or questions for the community, we encourage you to sign up to the Apache Flink &lt;a href=&quot;https://flink.apache.org/community.html#mailing-lists&quot;&gt;mailing lists&lt;/a&gt; and become part of the discussion there.&lt;/p&gt;
+</description>
+<pubDate>Tue, 21 Apr 2020 14:00:00 +0200</pubDate>
+<link>https://flink.apache.org/news/2020/04/21/memory-management-improvements-flink-1.10.html</link>
+<guid isPermaLink="true">/news/2020/04/21/memory-management-improvements-flink-1.10.html</guid>
+</item>
+
+<item>
 <title>Flink Serialization Tuning Vol. 1: Choosing your Serializer — if you can</title>
 <description>&lt;p&gt;Almost every Flink job has to exchange data between its operators and since these records may not only be sent to another instance in the same JVM but instead to a separate process, records need to be serialized to bytes first. Similarly, Flink’s off-heap state-backend is based on a local embedded RocksDB instance which is implemented in native C++ code and thus also needs transformation into bytes on every state access. Wire and state serialization alone can easily cost a lot of your job’s performance if not executed correctly and thus, whenever you look into the profiler output of your Flink job, you will most likely see serialization in the top places for using CPU cycles.&lt;/p&gt;
 
@@ -17254,54 +17351,5 @@
 <guid isPermaLink="true">/news/2015/02/09/streaming-example.html</guid>
 </item>
 
-<item>
-<title>January 2015 in the Flink community</title>
-<description>&lt;p&gt;Happy 2015! Here is a (hopefully digestible) summary of what happened last month in the Flink community.&lt;/p&gt;
-
-&lt;h3 id=&quot;release&quot;&gt;0.8.0 release&lt;/h3&gt;
-
-&lt;p&gt;Flink 0.8.0 was released. See &lt;a href=&quot;http://flink.apache.org/news/2015/01/21/release-0.8.html&quot;&gt;here&lt;/a&gt; for the release notes.&lt;/p&gt;
-
-&lt;h3 id=&quot;flink-roadmap&quot;&gt;Flink roadmap&lt;/h3&gt;
-
-&lt;p&gt;The community has published a &lt;a href=&quot;https://cwiki.apache.org/confluence/display/FLINK/Flink+Roadmap&quot;&gt;roadmap for 2015&lt;/a&gt; on the Flink wiki. Check it out to see what is coming up in Flink, and pick up an issue to contribute!&lt;/p&gt;
-
-&lt;h3 id=&quot;articles-in-the-press&quot;&gt;Articles in the press&lt;/h3&gt;
-
-&lt;p&gt;The Apache Software Foundation &lt;a href=&quot;https://blogs.apache.org/foundation/entry/the_apache_software_foundation_announces69&quot;&gt;announced&lt;/a&gt; Flink as a Top-Level Project. The announcement was picked up by the media, e.g., &lt;a href=&quot;http://sdtimes.com/inside-apache-software-foundations-newest-top-level-project-apache-flink/?utm_content=11232092&amp;amp;utm_medium=social&amp;amp;utm_source=twitter&quot;&gt;here&lt;/a&gt;, &lt;a href=&quot;http://www.datanami.com/2015/01/12/apache-flink-takes-route-distributed-data-processing/&quot;&gt;here&lt;/a&gt;, and &lt;a href=&quot;http://i-programmer.info/news/197-data-mining/8176-flink-reaches-top-level-status.html&quot;&gt;here&lt;/a&gt;.&lt;/p&gt;
-
-&lt;h3 id=&quot;hadoop-summit&quot;&gt;Hadoop Summit&lt;/h3&gt;
-
-&lt;p&gt;A submitted abstract on Flink Streaming won the community vote at “The Future of Hadoop” track.&lt;/p&gt;
-
-&lt;h3 id=&quot;meetups-and-talks&quot;&gt;Meetups and talks&lt;/h3&gt;
-
-&lt;p&gt;Flink was presented at the &lt;a href=&quot;http://www.meetup.com/Hadoop-User-Group-France/events/219778022/&quot;&gt;Paris Hadoop User Group&lt;/a&gt;, the &lt;a href=&quot;http://www.meetup.com/hadoop/events/167785202/&quot;&gt;Bay Area Hadoop User Group&lt;/a&gt;, the &lt;a href=&quot;http://www.meetup.com/Apache-Tez-User-Group/events/219302692/&quot;&gt;Apache Tez User Group&lt;/a&gt;, and &lt;a href=&quot;https://fosdem.org/2015/schedule/track/graph_processing/&quot;&gt;FOSDEM 2015&lt;/a&gt;. The January &lt;a href=&quot;http://www.meetup.com/Apache-Flink-Meetup/events/219639984/&quot;&gt;Flink meetup in Berlin&lt;/a&gt; had talks on recent community updates and new features.&lt;/p&gt;
-
-&lt;h2 id=&quot;notable-code-contributions&quot;&gt;Notable code contributions&lt;/h2&gt;
-
-&lt;p&gt;&lt;strong&gt;Note:&lt;/strong&gt; Code contributions listed here may not be part of a release or even the Flink master repository yet.&lt;/p&gt;
-
-&lt;h3 id=&quot;using-off-heap-memoryhttpsgithubcomapacheflinkpull290&quot;&gt;&lt;a href=&quot;https://github.com/apache/flink/pull/290&quot;&gt;Using off-heap memory&lt;/a&gt;&lt;/h3&gt;
-
-&lt;p&gt;This pull request enables Flink to use off-heap memory for its internal memory uses (sort, hash, caching of intermediate data sets).&lt;/p&gt;
-
-&lt;h3 id=&quot;gelly-flinks-graph-apihttpsgithubcomapacheflinkpull335&quot;&gt;&lt;a href=&quot;https://github.com/apache/flink/pull/335&quot;&gt;Gelly, Flink’s Graph API&lt;/a&gt;&lt;/h3&gt;
-
-&lt;p&gt;This pull request introduces Gelly, Flink’s brand new Graph API. Gelly offers a native graph programming abstraction with functionality for vertex-centric programming, as well as available graph algorithms. See &lt;a href=&quot;http://www.slideshare.net/vkalavri/largescale-graph-processing-with-apache-flink-graphdevroom-fosdem15&quot;&gt;this slide set&lt;/a&gt; for an overview of Gelly.&lt;/p&gt;
-
-&lt;h3 id=&quot;semantic-annotationshttpsgithubcomapacheflinkpull311&quot;&gt;&lt;a href=&quot;https://github.com/apache/flink/pull/311&quot;&gt;Semantic annotations&lt;/a&gt;&lt;/h3&gt;
-
-&lt;p&gt;Semantic annotations are a powerful mechanism to expose information about the behavior of Flink functions to Flink’s optimizer. The optimizer can leverage this information to generate more efficient execution plans. For example the output of a Reduce operator that groups on the second field of a tuple is still partitioned on that field if the Reduce function does not modify the value of the second field. By exposing this information to the optimizer, the optimizer can generate plans that avoid expensive data shuffling and reuse the partitioned output of Reduce. Semantic annotations can be defined for most data types, including (nested) tuples and POJOs. See the snapshot documentation for details (not online yet).&lt;/p&gt;
-
-&lt;h3 id=&quot;new-yarn-clienthttpsgithubcomapacheflinkpull292&quot;&gt;&lt;a href=&quot;https://github.com/apache/flink/pull/292&quot;&gt;New YARN client&lt;/a&gt;&lt;/h3&gt;
-
-&lt;p&gt;The improved YARN client of Flink now allows users to deploy Flink on YARN for executing a single job. Older versions only supported a long-running YARN session. The code of the YARN client has been refactored to provide an (internal) Java API for controlling YARN clusters more easily.&lt;/p&gt;
-</description>
-<pubDate>Wed, 04 Feb 2015 11:00:00 +0100</pubDate>
-<link>https://flink.apache.org/news/2015/02/04/january-in-flink.html</link>
-<guid isPermaLink="true">/news/2015/02/04/january-in-flink.html</guid>
-</item>
-
 </channel>
 </rss>

diff --git a/content/blog/index.html b/content/blog/index.html
index aa24919..780668e 100644
--- a/content/blog/index.html
+++ b/content/blog/index.html

@@ -195,6 +195,19 @@
     <!-- Blog posts -->
     
     <article>
+      <h2 class="blog-title"><a href="/news/2020/04/21/memory-management-improvements-flink-1.10.html">Memory Management Improvements with Apache Flink 1.10</a></h2>
+
+      <p>21 Apr 2020
+       Andrey Zagrebin </p>
+
+      <p>This post discusses the recent changes to the memory model of the Task Managers and configuration options for your Flink applications in Flink 1.10.</p>
+
+      <p><a href="/news/2020/04/21/memory-management-improvements-flink-1.10.html">Continue reading &raquo;</a></p>
+    </article>
+
+    <hr>
+    
+    <article>
       <h2 class="blog-title"><a href="/news/2020/04/15/flink-serialization-tuning-vol-1.html">Flink Serialization Tuning Vol. 1: Choosing your Serializer — if you can</a></h2>
 
       <p>15 Apr 2020
@@ -318,19 +331,6 @@
 
     <hr>
     
-    <article>
-      <h2 class="blog-title"><a href="/news/2020/02/07/a-guide-for-unit-testing-in-apache-flink.html">A Guide for Unit Testing in Apache Flink</a></h2>
-
-      <p>07 Feb 2020
-       Kartik Khare (<a href="https://twitter.com/khare_khote">@khare_khote</a>)</p>
-
-      <p>This post provides a detailed guide for unit testing of Apache Flink applications.</p>
-
-      <p><a href="/news/2020/02/07/a-guide-for-unit-testing-in-apache-flink.html">Continue reading &raquo;</a></p>
-    </article>
-
-    <hr>
-    
 
     <!-- Pagination links -->
     
@@ -363,6 +363,16 @@
 
     <ul id="markdown-toc">
       
+      <li><a href="/news/2020/04/21/memory-management-improvements-flink-1.10.html">Memory Management Improvements with Apache Flink 1.10</a></li>
+
+      
+        
+      
+    
+      
+      
+
+      
       <li><a href="/news/2020/04/15/flink-serialization-tuning-vol-1.html">Flink Serialization Tuning Vol. 1: Choosing your Serializer — if you can</a></li>
 
       

diff --git a/content/blog/page10/index.html b/content/blog/page10/index.html
index 21caa67..1c7f14b 100644
--- a/content/blog/page10/index.html
+++ b/content/blog/page10/index.html

@@ -195,6 +195,21 @@
     <!-- Blog posts -->
     
     <article>
+      <h2 class="blog-title"><a href="/news/2015/09/01/release-0.9.1.html">Apache Flink 0.9.1 available</a></h2>
+
+      <p>01 Sep 2015
+      </p>
+
+      <p><p>The Flink community is happy to announce that Flink 0.9.1 is now available.</p>
+
+</p>
+
+      <p><a href="/news/2015/09/01/release-0.9.1.html">Continue reading &raquo;</a></p>
+    </article>
+
+    <hr>
+    
+    <article>
       <h2 class="blog-title"><a href="/news/2015/08/24/introducing-flink-gelly.html">Introducing Gelly: Graph Processing with Apache Flink</a></h2>
 
       <p>24 Aug 2015
@@ -339,21 +354,6 @@
 
     <hr>
     
-    <article>
-      <h2 class="blog-title"><a href="/news/2015/02/04/january-in-flink.html">January 2015 in the Flink community</a></h2>
-
-      <p>04 Feb 2015
-      </p>
-
-      <p><p>Happy 2015! Here is a (hopefully digestible) summary of what happened last month in the Flink community.</p>
-
-</p>
-
-      <p><a href="/news/2015/02/04/january-in-flink.html">Continue reading &raquo;</a></p>
-    </article>
-
-    <hr>
-    
 
     <!-- Pagination links -->
     
@@ -386,6 +386,16 @@
 
     <ul id="markdown-toc">
       
+      <li><a href="/news/2020/04/21/memory-management-improvements-flink-1.10.html">Memory Management Improvements with Apache Flink 1.10</a></li>
+
+      
+        
+      
+    
+      
+      
+
+      
       <li><a href="/news/2020/04/15/flink-serialization-tuning-vol-1.html">Flink Serialization Tuning Vol. 1: Choosing your Serializer — if you can</a></li>
 
       

diff --git a/content/blog/page11/index.html b/content/blog/page11/index.html
index ed7f3aa..b9f63e2 100644
--- a/content/blog/page11/index.html
+++ b/content/blog/page11/index.html

@@ -195,6 +195,21 @@
     <!-- Blog posts -->
     
     <article>
+      <h2 class="blog-title"><a href="/news/2015/02/04/january-in-flink.html">January 2015 in the Flink community</a></h2>
+
+      <p>04 Feb 2015
+      </p>
+
+      <p><p>Happy 2015! Here is a (hopefully digestible) summary of what happened last month in the Flink community.</p>
+
+</p>
+
+      <p><a href="/news/2015/02/04/january-in-flink.html">Continue reading &raquo;</a></p>
+    </article>
+
+    <hr>
+    
+    <article>
       <h2 class="blog-title"><a href="/news/2015/01/21/release-0.8.html">Apache Flink 0.8.0 available</a></h2>
 
       <p>21 Jan 2015
@@ -334,6 +349,16 @@
 
     <ul id="markdown-toc">
       
+      <li><a href="/news/2020/04/21/memory-management-improvements-flink-1.10.html">Memory Management Improvements with Apache Flink 1.10</a></li>
+
+      
+        
+      
+    
+      
+      
+
+      
       <li><a href="/news/2020/04/15/flink-serialization-tuning-vol-1.html">Flink Serialization Tuning Vol. 1: Choosing your Serializer — if you can</a></li>
 
       

diff --git a/content/blog/page2/index.html b/content/blog/page2/index.html
index 42535b0..cb02f3b 100644
--- a/content/blog/page2/index.html
+++ b/content/blog/page2/index.html

@@ -195,6 +195,19 @@
     <!-- Blog posts -->
     
     <article>
+      <h2 class="blog-title"><a href="/news/2020/02/07/a-guide-for-unit-testing-in-apache-flink.html">A Guide for Unit Testing in Apache Flink</a></h2>
+
+      <p>07 Feb 2020
+       Kartik Khare (<a href="https://twitter.com/khare_khote">@khare_khote</a>)</p>
+
+      <p>This post provides a detailed guide for unit testing of Apache Flink applications.</p>
+
+      <p><a href="/news/2020/02/07/a-guide-for-unit-testing-in-apache-flink.html">Continue reading &raquo;</a></p>
+    </article>
+
+    <hr>
+    
+    <article>
       <h2 class="blog-title"><a href="/news/2020/01/30/release-1.9.2.html">Apache Flink 1.9.2 Released</a></h2>
 
       <p>30 Jan 2020
@@ -319,19 +332,6 @@
 
     <hr>
     
-    <article>
-      <h2 class="blog-title"><a href="/news/2019/09/10/community-update.html">Flink Community Update - September'19</a></h2>
-
-      <p>10 Sep 2019
-       Marta Paes (<a href="https://twitter.com/morsapaes">@morsapaes</a>)</p>
-
-      <p>This has been an exciting, fast-paced year for the Apache Flink community. But with over 10k messages across the mailing lists, 3k Jira tickets and 2k pull requests, it is not easy to keep up with the latest state of the project. Plus everything happening around it. With that in mind, we want to bring back regular community updates to the Flink blog.</p>
-
-      <p><a href="/news/2019/09/10/community-update.html">Continue reading &raquo;</a></p>
-    </article>
-
-    <hr>
-    
 
     <!-- Pagination links -->
     
@@ -364,6 +364,16 @@
 
     <ul id="markdown-toc">
       
+      <li><a href="/news/2020/04/21/memory-management-improvements-flink-1.10.html">Memory Management Improvements with Apache Flink 1.10</a></li>
+
+      
+        
+      
+    
+      
+      
+
+      
       <li><a href="/news/2020/04/15/flink-serialization-tuning-vol-1.html">Flink Serialization Tuning Vol. 1: Choosing your Serializer — if you can</a></li>
 
       

diff --git a/content/blog/page3/index.html b/content/blog/page3/index.html
index 9abb37e..ed7baab 100644
--- a/content/blog/page3/index.html
+++ b/content/blog/page3/index.html

@@ -195,6 +195,19 @@
     <!-- Blog posts -->
     
     <article>
+      <h2 class="blog-title"><a href="/news/2019/09/10/community-update.html">Flink Community Update - September'19</a></h2>
+
+      <p>10 Sep 2019
+       Marta Paes (<a href="https://twitter.com/morsapaes">@morsapaes</a>)</p>
+
+      <p>This has been an exciting, fast-paced year for the Apache Flink community. But with over 10k messages across the mailing lists, 3k Jira tickets and 2k pull requests, it is not easy to keep up with the latest state of the project. Plus everything happening around it. With that in mind, we want to bring back regular community updates to the Flink blog.</p>
+
+      <p><a href="/news/2019/09/10/community-update.html">Continue reading &raquo;</a></p>
+    </article>
+
+    <hr>
+    
+    <article>
       <h2 class="blog-title"><a href="/news/2019/08/22/release-1.9.0.html">Apache Flink 1.9.0 Release Announcement</a></h2>
 
       <p>22 Aug 2019
@@ -318,25 +331,6 @@
 
     <hr>
     
-    <article>
-      <h2 class="blog-title"><a href="/news/2019/04/09/release-1.8.0.html">Apache Flink 1.8.0 Release Announcement</a></h2>
-
-      <p>09 Apr 2019
-       Aljoscha Krettek (<a href="https://twitter.com/aljoscha">@aljoscha</a>)</p>
-
-      <p><p>The Apache Flink community is pleased to announce Apache Flink 1.8.0.  The
-latest release includes more than 420 resolved issues and some exciting
-additions to Flink that we describe in the following sections of this post.
-Please check the <a href="https://issues.apache.org/jira/secure/ReleaseNote.jspa?projectId=12315522&amp;version=12344274">complete changelog</a>
-for more details.</p>
-
-</p>
-
-      <p><a href="/news/2019/04/09/release-1.8.0.html">Continue reading &raquo;</a></p>
-    </article>
-
-    <hr>
-    
 
     <!-- Pagination links -->
     
@@ -369,6 +363,16 @@
 
     <ul id="markdown-toc">
       
+      <li><a href="/news/2020/04/21/memory-management-improvements-flink-1.10.html">Memory Management Improvements with Apache Flink 1.10</a></li>
+
+      
+        
+      
+    
+      
+      
+
+      
       <li><a href="/news/2020/04/15/flink-serialization-tuning-vol-1.html">Flink Serialization Tuning Vol. 1: Choosing your Serializer — if you can</a></li>
 
       

diff --git a/content/blog/page4/index.html b/content/blog/page4/index.html
index 4e0e20d..1700540 100644
--- a/content/blog/page4/index.html
+++ b/content/blog/page4/index.html

@@ -195,6 +195,25 @@
     <!-- Blog posts -->
     
     <article>
+      <h2 class="blog-title"><a href="/news/2019/04/09/release-1.8.0.html">Apache Flink 1.8.0 Release Announcement</a></h2>
+
+      <p>09 Apr 2019
+       Aljoscha Krettek (<a href="https://twitter.com/aljoscha">@aljoscha</a>)</p>
+
+      <p><p>The Apache Flink community is pleased to announce Apache Flink 1.8.0.  The
+latest release includes more than 420 resolved issues and some exciting
+additions to Flink that we describe in the following sections of this post.
+Please check the <a href="https://issues.apache.org/jira/secure/ReleaseNote.jspa?projectId=12315522&amp;version=12344274">complete changelog</a>
+for more details.</p>
+
+</p>
+
+      <p><a href="/news/2019/04/09/release-1.8.0.html">Continue reading &raquo;</a></p>
+    </article>
+
+    <hr>
+    
+    <article>
       <h2 class="blog-title"><a href="/features/2019/03/11/prometheus-monitoring.html">Flink and Prometheus: Cloud-native monitoring of streaming applications</a></h2>
 
       <p>11 Mar 2019
@@ -321,23 +340,6 @@
 
     <hr>
     
-    <article>
-      <h2 class="blog-title"><a href="/news/2018/11/30/release-1.7.0.html">Apache Flink 1.7.0 Release Announcement</a></h2>
-
-      <p>30 Nov 2018
-       Till Rohrmann (<a href="https://twitter.com/stsffap">@stsffap</a>)</p>
-
-      <p><p>The Apache Flink community is pleased to announce Apache Flink 1.7.0. 
-The latest release includes more than 420 resolved issues and some exciting additions to Flink that we describe in the following sections of this post. 
-Please check the <a href="https://issues.apache.org/jira/secure/ReleaseNote.jspa?projectId=12315522&amp;version=12343585">complete changelog</a> for more details.</p>
-
-</p>
-
-      <p><a href="/news/2018/11/30/release-1.7.0.html">Continue reading &raquo;</a></p>
-    </article>
-
-    <hr>
-    
 
     <!-- Pagination links -->
     
@@ -370,6 +372,16 @@
 
     <ul id="markdown-toc">
       
+      <li><a href="/news/2020/04/21/memory-management-improvements-flink-1.10.html">Memory Management Improvements with Apache Flink 1.10</a></li>
+
+      
+        
+      
+    
+      
+      
+
+      
       <li><a href="/news/2020/04/15/flink-serialization-tuning-vol-1.html">Flink Serialization Tuning Vol. 1: Choosing your Serializer — if you can</a></li>
 
       

diff --git a/content/blog/page5/index.html b/content/blog/page5/index.html
index fb48d96..535d7a8 100644
--- a/content/blog/page5/index.html
+++ b/content/blog/page5/index.html

@@ -195,6 +195,23 @@
     <!-- Blog posts -->
     
     <article>
+      <h2 class="blog-title"><a href="/news/2018/11/30/release-1.7.0.html">Apache Flink 1.7.0 Release Announcement</a></h2>
+
+      <p>30 Nov 2018
+       Till Rohrmann (<a href="https://twitter.com/stsffap">@stsffap</a>)</p>
+
+      <p><p>The Apache Flink community is pleased to announce Apache Flink 1.7.0. 
+The latest release includes more than 420 resolved issues and some exciting additions to Flink that we describe in the following sections of this post. 
+Please check the <a href="https://issues.apache.org/jira/secure/ReleaseNote.jspa?projectId=12315522&amp;version=12343585">complete changelog</a> for more details.</p>
+
+</p>
+
+      <p><a href="/news/2018/11/30/release-1.7.0.html">Continue reading &raquo;</a></p>
+    </article>
+
+    <hr>
+    
+    <article>
       <h2 class="blog-title"><a href="/news/2018/10/29/release-1.6.2.html">Apache Flink 1.6.2 Released</a></h2>
 
       <p>29 Oct 2018
@@ -329,21 +346,6 @@
 
     <hr>
     
-    <article>
-      <h2 class="blog-title"><a href="/news/2018/03/15/release-1.3.3.html">Apache Flink 1.3.3 Released</a></h2>
-
-      <p>15 Mar 2018
-      </p>
-
-      <p><p>The Apache Flink community released the third bugfix version of the Apache Flink 1.3 series.</p>
-
-</p>
-
-      <p><a href="/news/2018/03/15/release-1.3.3.html">Continue reading &raquo;</a></p>
-    </article>
-
-    <hr>
-    
 
     <!-- Pagination links -->
     
@@ -376,6 +378,16 @@
 
     <ul id="markdown-toc">
       
+      <li><a href="/news/2020/04/21/memory-management-improvements-flink-1.10.html">Memory Management Improvements with Apache Flink 1.10</a></li>
+
+      
+        
+      
+    
+      
+      
+
+      
       <li><a href="/news/2020/04/15/flink-serialization-tuning-vol-1.html">Flink Serialization Tuning Vol. 1: Choosing your Serializer — if you can</a></li>
 
       

diff --git a/content/blog/page6/index.html b/content/blog/page6/index.html
index 0a294fe..4be8077 100644
--- a/content/blog/page6/index.html
+++ b/content/blog/page6/index.html

@@ -195,6 +195,21 @@
     <!-- Blog posts -->
     
     <article>
+      <h2 class="blog-title"><a href="/news/2018/03/15/release-1.3.3.html">Apache Flink 1.3.3 Released</a></h2>
+
+      <p>15 Mar 2018
+      </p>
+
+      <p><p>The Apache Flink community released the third bugfix version of the Apache Flink 1.3 series.</p>
+
+</p>
+
+      <p><a href="/news/2018/03/15/release-1.3.3.html">Continue reading &raquo;</a></p>
+    </article>
+
+    <hr>
+    
+    <article>
       <h2 class="blog-title"><a href="/news/2018/03/08/release-1.4.2.html">Apache Flink 1.4.2 Released</a></h2>
 
       <p>08 Mar 2018
@@ -326,21 +341,6 @@
 
     <hr>
     
-    <article>
-      <h2 class="blog-title"><a href="/news/2017/06/23/release-1.3.1.html">Apache Flink 1.3.1 Released</a></h2>
-
-      <p>23 Jun 2017
-      </p>
-
-      <p><p>The Apache Flink community released the first bugfix version of the Apache Flink 1.3 series.</p>
-
-</p>
-
-      <p><a href="/news/2017/06/23/release-1.3.1.html">Continue reading &raquo;</a></p>
-    </article>
-
-    <hr>
-    
 
     <!-- Pagination links -->
     
@@ -373,6 +373,16 @@
 
     <ul id="markdown-toc">
       
+      <li><a href="/news/2020/04/21/memory-management-improvements-flink-1.10.html">Memory Management Improvements with Apache Flink 1.10</a></li>
+
+      
+        
+      
+    
+      
+      
+
+      
       <li><a href="/news/2020/04/15/flink-serialization-tuning-vol-1.html">Flink Serialization Tuning Vol. 1: Choosing your Serializer — if you can</a></li>
 
       

diff --git a/content/blog/page7/index.html b/content/blog/page7/index.html
index 8f00f06..b6f6c07 100644
--- a/content/blog/page7/index.html
+++ b/content/blog/page7/index.html

@@ -195,6 +195,21 @@
     <!-- Blog posts -->
     
     <article>
+      <h2 class="blog-title"><a href="/news/2017/06/23/release-1.3.1.html">Apache Flink 1.3.1 Released</a></h2>
+
+      <p>23 Jun 2017
+      </p>
+
+      <p><p>The Apache Flink community released the first bugfix version of the Apache Flink 1.3 series.</p>
+
+</p>
+
+      <p><a href="/news/2017/06/23/release-1.3.1.html">Continue reading &raquo;</a></p>
+    </article>
+
+    <hr>
+    
+    <article>
       <h2 class="blog-title"><a href="/news/2017/06/01/release-1.3.0.html">Apache Flink 1.3.0 Release Announcement</a></h2>
 
       <p>01 Jun 2017 by Robert Metzger (<a href="https://twitter.com/">@rmetzger_</a>)
@@ -322,21 +337,6 @@
 
     <hr>
     
-    <article>
-      <h2 class="blog-title"><a href="/news/2016/10/12/release-1.1.3.html">Apache Flink 1.1.3 Released</a></h2>
-
-      <p>12 Oct 2016
-      </p>
-
-      <p><p>The Apache Flink community released the next bugfix version of the Apache Flink 1.1. series.</p>
-
-</p>
-
-      <p><a href="/news/2016/10/12/release-1.1.3.html">Continue reading &raquo;</a></p>
-    </article>
-
-    <hr>
-    
 
     <!-- Pagination links -->
     
@@ -369,6 +369,16 @@
 
     <ul id="markdown-toc">
       
+      <li><a href="/news/2020/04/21/memory-management-improvements-flink-1.10.html">Memory Management Improvements with Apache Flink 1.10</a></li>
+
+      
+        
+      
+    
+      
+      
+
+      
       <li><a href="/news/2020/04/15/flink-serialization-tuning-vol-1.html">Flink Serialization Tuning Vol. 1: Choosing your Serializer — if you can</a></li>
 
       

diff --git a/content/blog/page8/index.html b/content/blog/page8/index.html
index 251627f..c854eb7 100644
--- a/content/blog/page8/index.html
+++ b/content/blog/page8/index.html

@@ -195,6 +195,21 @@
     <!-- Blog posts -->
     
     <article>
+      <h2 class="blog-title"><a href="/news/2016/10/12/release-1.1.3.html">Apache Flink 1.1.3 Released</a></h2>
+
+      <p>12 Oct 2016
+      </p>
+
+      <p><p>The Apache Flink community released the next bugfix version of the Apache Flink 1.1. series.</p>
+
+</p>
+
+      <p><a href="/news/2016/10/12/release-1.1.3.html">Continue reading &raquo;</a></p>
+    </article>
+
+    <hr>
+    
+    <article>
       <h2 class="blog-title"><a href="/news/2016/09/05/release-1.1.2.html">Apache Flink 1.1.2 Released</a></h2>
 
       <p>05 Sep 2016
@@ -326,21 +341,6 @@
 
     <hr>
     
-    <article>
-      <h2 class="blog-title"><a href="/news/2016/04/06/release-1.0.1.html">Flink 1.0.1 Released</a></h2>
-
-      <p>06 Apr 2016
-      </p>
-
-      <p><p>Today, the Flink community released Flink version <strong>1.0.1</strong>, the first bugfix release of the 1.0 series.</p>
-
-</p>
-
-      <p><a href="/news/2016/04/06/release-1.0.1.html">Continue reading &raquo;</a></p>
-    </article>
-
-    <hr>
-    
 
     <!-- Pagination links -->
     
@@ -373,6 +373,16 @@
 
     <ul id="markdown-toc">
       
+      <li><a href="/news/2020/04/21/memory-management-improvements-flink-1.10.html">Memory Management Improvements with Apache Flink 1.10</a></li>
+
+      
+        
+      
+    
+      
+      
+
+      
       <li><a href="/news/2020/04/15/flink-serialization-tuning-vol-1.html">Flink Serialization Tuning Vol. 1: Choosing your Serializer — if you can</a></li>
 
       

diff --git a/content/blog/page9/index.html b/content/blog/page9/index.html
index 7029cab..e88eb87 100644
--- a/content/blog/page9/index.html
+++ b/content/blog/page9/index.html

@@ -195,6 +195,21 @@
     <!-- Blog posts -->
     
     <article>
+      <h2 class="blog-title"><a href="/news/2016/04/06/release-1.0.1.html">Flink 1.0.1 Released</a></h2>
+
+      <p>06 Apr 2016
+      </p>
+
+      <p><p>Today, the Flink community released Flink version <strong>1.0.1</strong>, the first bugfix release of the 1.0 series.</p>
+
+</p>
+
+      <p><a href="/news/2016/04/06/release-1.0.1.html">Continue reading &raquo;</a></p>
+    </article>
+
+    <hr>
+    
+    <article>
       <h2 class="blog-title"><a href="/news/2016/03/08/release-1.0.0.html">Announcing Apache Flink 1.0.0</a></h2>
 
       <p>08 Mar 2016
@@ -327,21 +342,6 @@
 
     <hr>
     
-    <article>
-      <h2 class="blog-title"><a href="/news/2015/09/01/release-0.9.1.html">Apache Flink 0.9.1 available</a></h2>
-
-      <p>01 Sep 2015
-      </p>
-
-      <p><p>The Flink community is happy to announce that Flink 0.9.1 is now available.</p>
-
-</p>
-
-      <p><a href="/news/2015/09/01/release-0.9.1.html">Continue reading &raquo;</a></p>
-    </article>
-
-    <hr>
-    
 
     <!-- Pagination links -->
     
@@ -374,6 +374,16 @@
 
     <ul id="markdown-toc">
       
+      <li><a href="/news/2020/04/21/memory-management-improvements-flink-1.10.html">Memory Management Improvements with Apache Flink 1.10</a></li>
+
+      
+        
+      
+    
+      
+      
+
+      
       <li><a href="/news/2020/04/15/flink-serialization-tuning-vol-1.html">Flink Serialization Tuning Vol. 1: Choosing your Serializer — if you can</a></li>
 
       

diff --git a/content/img/blog/2020-04-21-memory-management-improvements-flink-1.10/flink-memory-setup.svg b/content/img/blog/2020-04-21-memory-management-improvements-flink-1.10/flink-memory-setup.svg
new file mode 100644
index 0000000..509b771
--- /dev/null
+++ b/content/img/blog/2020-04-21-memory-management-improvements-flink-1.10/flink-memory-setup.svg

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diff --git a/content/index.html b/content/index.html
index a374861..acf93c9 100644
--- a/content/index.html
+++ b/content/index.html

@@ -567,6 +567,9 @@
 
   <dl>
       
+        <dt> <a href="/news/2020/04/21/memory-management-improvements-flink-1.10.html">Memory Management Improvements with Apache Flink 1.10</a></dt>
+        <dd>This post discusses the recent changes to the memory model of the Task Managers and configuration options for your Flink applications in Flink 1.10.</dd>
+      
         <dt> <a href="/news/2020/04/15/flink-serialization-tuning-vol-1.html">Flink Serialization Tuning Vol. 1: Choosing your Serializer — if you can</a></dt>
         <dd>Serialization is a crucial element of your Flink job. This article is the first in a series of posts that will highlight Flink’s serialization stack, and looks at the different ways Flink can serialize your data types.</dd>
       
@@ -581,11 +584,6 @@
       
         <dt> <a href="/news/2020/04/01/community-update.html">Flink Community Update - April'20</a></dt>
         <dd>While things slow down around us, the Apache Flink community is privileged to remain as active as ever. This blogpost combs through the past few months to give you an update on the state of things in Flink — from core releases to Stateful Functions; from some good old community stats to a new development blog.</dd>
-      
-        <dt> <a href="/features/2020/03/27/flink-for-data-warehouse.html">Flink as Unified Engine for Modern Data Warehousing: Production-Ready Hive Integration</a></dt>
-        <dd><p>In this blog post, you will learn our motivation behind the Flink-Hive integration, and how Flink 1.10 can help modernize your data warehouse.</p>
-
-</dd>
     
   </dl>
 

diff --git a/content/news/2020/04/21/memory-management-improvements-flink-1.10.html b/content/news/2020/04/21/memory-management-improvements-flink-1.10.html
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+      <h1>Memory Management Improvements with Apache Flink 1.10</h1>
+      <p><i></i></p>
+
+      <article>
+        <p>21 Apr 2020 Andrey Zagrebin </p>
+
+<p>Apache Flink 1.10 comes with significant changes to the memory model of the Task Managers and configuration options for your Flink applications. These recently-introduced changes make Flink more adaptable to all kinds of deployment environments (e.g. Kubernetes, Yarn, Mesos), providing strict control over its memory consumption. In this post, we describe Flink’s memory model, as it stands in Flink 1.10, how to set up and manage memory consumption of your Flink applications and the recent changes the community implemented in the latest Apache Flink release.</p>
+
+<h2 id="introduction-to-flinks-memory-model">Introduction to Flink’s memory model</h2>
+
+<p>Having a clear understanding of Apache Flink’s memory model allows you to manage resources for the various workloads more efficiently. The following diagram illustrates the main memory components in Flink:</p>
+
+<center>
+<img src="/img/blog/2020-04-21-memory-management-improvements-flink-1.10/total-process-memory.svg" width="400px" alt="Flink: Total Process Memory" />
+<br />
+<i><small>Flink: Total Process Memory</small></i>
+</center>
+<p><br /></p>
+
+<p>The Task Manager process is a JVM process. On a high level, its memory consists of the <em>JVM Heap</em> and <em>Off-Heap</em> memory. These types of memory are consumed by Flink directly or by JVM for its specific purposes (i.e. metaspace etc.). There are two major memory consumers within Flink: the user code of job operator tasks and the framework itself consuming memory for internal data structures, network buffers, etc.</p>
+
+<p><strong>Please note that</strong> the user code has direct access to all memory types: <em>JVM Heap, Direct</em> and <em>Native memory</em>. Therefore, Flink cannot really control its allocation and usage. There are however two types of Off-Heap memory which are consumed by tasks and controlled explicitly by Flink:</p>
+
+<ul>
+  <li><em>Managed Memory</em> (Off-Heap)</li>
+  <li><em>Network Buffers</em></li>
+</ul>
+
+<p>The latter is part of the <em>JVM Direct Memory</em>, allocated for user record data exchange between operator tasks.</p>
+
+<h2 id="how-to-set-up-flink-memory">How to set up Flink memory</h2>
+
+<p>With the latest release of Flink 1.10 and in order to provide better user experience, the framework comes with both high-level and fine-grained tuning of memory components. There are essentially three alternatives to setting up memory in Task Managers.</p>
+
+<p>The first two — and simplest — alternatives are configuring one of the two following options for total memory available for the JVM process of the Task Manager:</p>
+
+<ul>
+  <li><em>Total Process Memory</em>: total memory consumed by the Flink Java application (including user code) and by the JVM to run the whole process.</li>
+  <li><em>Total Flink Memory</em>: only memory consumed by the Flink Java application, including user code but excluding memory allocated by JVM to run it</li>
+</ul>
+
+<p>It is advisable to configure the <em>Total Flink Memory</em> for standalone deployments where explicitly declaring how much memory is given to Flink is a common practice, while the outer <em>JVM overhead</em> is of little interest. For the cases of deploying Flink in containerized environments (such as <a href="https://ci.apache.org/projects/flink/flink-docs-release-1.10/ops/deployment/kubernetes.html">Kubernetes</a>, <a href="https://ci.apache.org/projects/flink/flink-docs-release-1.10/ops/deployment/yarn_setup.html">Yarn</a> or <a href="https://ci.apache.org/projects/flink/flink-docs-release-1.10/ops/deployment/mesos.html">Mesos</a>), the <em>Total Process Memory</em> option is recommended instead, because it becomes the size for the total memory of the requested container. Containerized environments usually strictly enforce this memory limit.</p>
+
+<p>If you want more fine-grained control over the size of <em>JVM Heap</em> and <em>Managed Memory</em> (Off-Heap), there is also a second alternative to configure both <em><a href="https://ci.apache.org/projects/flink/flink-docs-release-1.10/ops/memory/mem_setup.html#task-operator-heap-memory">Task Heap</a></em> and <em><a href="https://ci.apache.org/projects/flink/flink-docs-release-1.10/ops/memory/mem_setup.html#managed-memory">Managed Memory</a></em>. This alternative gives a clear separation between the heap memory and any other memory types.</p>
+
+<p>In line with the community’s efforts to <a href="https://flink.apache.org/news/2019/02/13/unified-batch-streaming-blink.html">unify batch and stream processing</a>, this model works universally for both scenarios. It allows sharing the <em>JVM Heap</em> memory between the user code of operator tasks in any workload and the heap state backend in stream processing scenarios. In a similar way, the <em>Managed Memory</em> can be used for batch spilling and for the RocksDB state backend in streaming.</p>
+
+<p>The remaining memory components are automatically adjusted either based on their default values or additionally configured parameters. Flink also checks the overall consistency. You can find more information about the different memory components in the corresponding <a href="https://ci.apache.org/projects/flink/flink-docs-release-1.10/ops/memory/mem_detail.html">documentation</a>. Additionally, you can try different configuration options with the <a href="https://docs.google.com/spreadsheets/d/1mJaMkMPfDJJ-w6nMXALYmTc4XxiV30P5U7DzgwLkSoE/edit#gid=0">configuration spreadsheet</a> of <a href="https://cwiki.apache.org/confluence/display/FLINK/FLIP-49%3A+Unified+Memory+Configuration+for+TaskExecutors">FLIP-49</a> and check the corresponding results for your individual case.</p>
+
+<p>If you are migrating from a Flink version older than 1.10, we suggest following the steps in the <a href="https://ci.apache.org/projects/flink/flink-docs-release-1.10/ops/memory/mem_migration.html">migration guide</a> of the Flink documentation.</p>
+
+<h2 id="other-components">Other components</h2>
+
+<p>While configuring Flink’s memory, the size of different memory components can either be fixed with the value of the respective option or tuned using multiple options. Below we provide some more insight about the memory setup.</p>
+
+<h3 id="fractions-of-the-total-flink-memory">Fractions of the Total Flink Memory</h3>
+
+<p>This method allows a proportional breakdown of the <em>Total Flink Memory</em> where the <a href="https://ci.apache.org/projects/flink/flink-docs-release-1.10/ops/memory/mem_setup.html#managed-memory">Managed Memory</a> (if not set explicitly) and <a href="https://ci.apache.org/projects/flink/flink-docs-release-1.10/ops/memory/mem_detail.html#capped-fractionated-components">Network Buffers</a> can take certain fractions of it. The remaining memory is then assigned to the <a href="https://ci.apache.org/projects/flink/flink-docs-release-1.10/ops/memory/mem_setup.html#task-operator-heap-memory">Task Heap</a> (if not set explicitly) and other fixed <em>JVM Heap</em> and <em>Off-Heap components</em>. The following picture represents an example of such a setup:</p>
+
+<center>
+<img src="/img/blog/2020-04-21-memory-management-improvements-flink-1.10/flink-memory-setup.svg" width="800px" alt="Flink: Example of Memory Setup" />
+<br />
+<i><small>Flink: Example of Memory Setup</small></i>
+</center>
+<p><br /></p>
+
+<p><strong>Please note that</strong></p>
+
+<ul>
+  <li>Flink will verify that the size of the derived <em>Network Memory</em> is between its minimum and maximum value, otherwise Flink’s startup will fail. The maximum and minimum limits have default values which can be overwritten by the respective configuration options.</li>
+  <li>In general, the configured fractions are treated by Flink as hints. Under certain scenarios, the derived value might not match the fraction. For example, if the <em>Total Flink Memory</em> and the <em>Task Heap</em> are configured to fixed values, the <em>Managed Memory</em> will get a certain fraction and the <em>Network Memory</em> will get the remaining memory which might not exactly match its fraction.</li>
+</ul>
+
+<h3 id="more-hints-to-control-the-container-memory-limit">More hints to control the container memory limit</h3>
+
+<p>The heap and direct memory usage are managed by the JVM. There are also many other possible sources of native memory consumption in Apache Flink or its user applications which are not managed by Flink or the JVM. Controlling their limits is often difficult which complicates debugging of potential memory leaks. If Flink’s process allocates too much memory in an unmanaged way, it can often result in killing Task Manager containers in containerized environments. In this case, it may be hard to understand which type of memory consumption has exceeded its limit. Flink 1.10 introduces some specific tuning options to clearly represent such components. Although Flink cannot always enforce strict limits and borders among them, the idea here is to explicitly plan the memory usage. Below we provide some examples of how memory setup can prevent containers exceeding their memory limit:</p>
+
+<ul>
+  <li>
+    <p><a href="https://ci.apache.org/projects/flink/flink-docs-release-1.10/ops/memory/mem_tuning.html#rocksdb-state-backend">RocksDB state cannot grow too big</a>. The memory consumption of RocksDB state backend is accounted for in the <em>Managed Memory</em>. RocksDB respects its limit by default (only since Flink 1.10). You can increase the <em>Managed Memory</em> size to improve RocksDB’s performance or decrease it to save resources.</p>
+  </li>
+  <li>
+    <p><a href="https://ci.apache.org/projects/flink/flink-docs-release-1.10/ops/memory/mem_setup.html#configure-off-heap-memory-direct-or-native">User code or its dependencies consume significant off-heap memory</a>. Tuning the <em>Task Off-Heap</em> option can assign additional direct or native memory to the user code or any of its dependencies. Flink cannot control native allocations but it sets the limit for <em>JVM Direct</em> memory allocations. The <em>Direct</em> memory limit is enforced by the JVM.</p>
+  </li>
+  <li>
+    <p><a href="https://ci.apache.org/projects/flink/flink-docs-release-1.10/ops/memory/mem_detail.html#jvm-parameters">JVM metaspace requires additional memory</a>. If you encounter <code>OutOfMemoryError: Metaspace</code>, Flink provides an option to increase its limit and the JVM will ensure that it is not exceeded.</p>
+  </li>
+  <li>
+    <p><a href="https://ci.apache.org/projects/flink/flink-docs-release-1.10/ops/memory/mem_detail.html#capped-fractionated-components">JVM requires more internal memory</a>. There is no direct control over certain types of JVM process allocations but Flink provides <em>JVM Overhead</em> options. The options allow declaring an additional amount of memory, anticipated for those allocations and not covered by other options.</p>
+  </li>
+</ul>
+
+<h2 id="conclusion">Conclusion</h2>
+
+<p>The latest Flink release (Flink 1.10) introduces some significant changes to Flink’s memory configuration, making it possible to manage your application memory and debug Flink significantly better than before. Future developments in this area also include adopting a similar memory model for the job manager process in <a href="https://cwiki.apache.org/confluence/display/FLINK/FLIP+116%3A+Unified+Memory+Configuration+for+Job+Managers">FLIP-116</a>, so stay tuned for more additions and features in upcoming releases. If you have any suggestions or questions for the community, we encourage you to sign up to the Apache Flink <a href="https://flink.apache.org/community.html#mailing-lists">mailing lists</a> and become part of the discussion there.</p>
+
+      </article>
+    </div>
+
+    <div class="row">
+      <div id="disqus_thread"></div>
+      <script type="text/javascript">
+        /* * * CONFIGURATION VARIABLES: EDIT BEFORE PASTING INTO YOUR WEBPAGE * * */
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diff --git a/content/zh/index.html b/content/zh/index.html
index c67dadd..fb9d47e 100644
--- a/content/zh/index.html
+++ b/content/zh/index.html

@@ -564,6 +564,9 @@
 
   <dl>
       
+        <dt> <a href="/news/2020/04/21/memory-management-improvements-flink-1.10.html">Memory Management Improvements with Apache Flink 1.10</a></dt>
+        <dd>This post discusses the recent changes to the memory model of the Task Managers and configuration options for your Flink applications in Flink 1.10.</dd>
+      
         <dt> <a href="/news/2020/04/15/flink-serialization-tuning-vol-1.html">Flink Serialization Tuning Vol. 1: Choosing your Serializer — if you can</a></dt>
         <dd>Serialization is a crucial element of your Flink job. This article is the first in a series of posts that will highlight Flink’s serialization stack, and looks at the different ways Flink can serialize your data types.</dd>
       
@@ -578,11 +581,6 @@
       
         <dt> <a href="/news/2020/04/01/community-update.html">Flink Community Update - April'20</a></dt>
         <dd>While things slow down around us, the Apache Flink community is privileged to remain as active as ever. This blogpost combs through the past few months to give you an update on the state of things in Flink — from core releases to Stateful Functions; from some good old community stats to a new development blog.</dd>
-      
-        <dt> <a href="/features/2020/03/27/flink-for-data-warehouse.html">Flink as Unified Engine for Modern Data Warehousing: Production-Ready Hive Integration</a></dt>
-        <dd><p>In this blog post, you will learn our motivation behind the Flink-Hive integration, and how Flink 1.10 can help modernize your data warehouse.</p>
-
-</dd>
     
   </dl>