Modified: helix/site-content/1.0.2-docs/quota_scheduling.html
URL: 
http://svn.apache.org/viewvc/helix/site-content/1.0.2-docs/quota_scheduling.html?rev=1909461&r1=1909460&r2=1909461&view=diff
==============================================================================
--- helix/site-content/1.0.2-docs/quota_scheduling.html (original)
+++ helix/site-content/1.0.2-docs/quota_scheduling.html Thu Apr 27 23:08:36 2023
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                                <li>Quota-based Task Scheduling</li>
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+Licensed to the Apache Software Foundation (ASF) under one
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+"License"); you may not use this file except in compliance
+with the License.  You may obtain a copy of the License at
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+  http://www.apache.org/licenses/LICENSE-2.0
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+Unless required by applicable law or agreed to in writing,
+software distributed under the License is distributed on an
+"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+KIND, either express or implied.  See the License for the
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+<div class="page-header">
+ <h1>Quota-based Task Scheduling</h1>
+</div> 
+<section> 
+ <h2 id="Introduction">Introduction</h2> 
+ <p><img src="./images/quota_intro.png" alt="Intro"></p> 
+ <p>Quota-based task scheduling is a feature addition to Helix Task Framework 
that enables users of Task Framework to apply the notion of categories in 
distributed task management.</p> 
+</section> 
+<section> 
+ <h2 id="Purpose">Purpose</h2> 
+ <p>As Helix Task Framework gains usage in other open-source frameworks such 
as <a class="externalLink" href="https://gobblin.apache.org/";>Apache 
Gobblin</a> and <a class="externalLink" 
href="http://pinot.incubator.apache.org/";>Apache Pinot</a>, it has also seen an 
increase in the variety in the types of distributed tasks it was managing. 
There have also been explicit feature requests to Helix for differentiating 
different types of tasks by creating corresponding quotas.</p> 
+ <p>Quota-based task scheduling aims to fulfill these requests by allowing 
users to define a quota profile consisting of quota types and their 
corresponding quotas. The goal of this feature is threefold: 1) the user will 
have the ability to prioritize one type of workflows/jobs/tasks over another 
and 2) achieve isolation among the type of tasks and 3) make monitoring easier 
by tracking the status of distributed execution by type.</p> 
+</section> 
+<section> 
+ <h2 id="Glossary_and_Definitions">Glossary and Definitions</h2> 
+ <ul> 
+  <li>Task Framework: a component of Apache Helix. A framework on which users 
can define and run workflows, jobs, and tasks in a distributed way.</li> 
+  <li>Workflow: the largest unit of work in Task Framework. A workflow 
consists of one or more jobs. There are two types of workflows: 
+   <ul> 
+    <li>Generic workflow: a generic workflow is a workflow consisting of jobs 
(a job DAG) that are used for general purposes. <b>A generic workflow may be 
removed if expired or timed out.</b></li> 
+    <li>Job queue: a job queue is a special type of workflow consisting of 
jobs that tend to have a linear dependency (this dependency is configurable, 
however). <b>There is no expiration for job queues</b> - it lives on until it 
is deleted.</li> 
+   </ul> </li> 
+  <li>Job: the second largest unit of work in Task Framework. A job consists 
of one or more mutually independent tasks. There are two types of jobs: 
+   <ul> 
+    <li>Generic job: a generic job is a job consisting of one or more 
tasks.</li> 
+    <li>Targeted job: a targeted job differs from generic jobs in that these 
jobs must have a <i>target resource</i>, and the tasks belonging to such jobs 
will be scheduled alongside the partitions of the target resource. To 
illustrate, an Espresso user of Task Framework may wish to schedule a backup 
job on one of their DBs called <i>MemberDataDB</i>. This DB will be divided 
into multiple partitions (_MemberDataDB_1, _MemberDataDB_2, … 
<i>MemberDataDB_N)</i>__, and suppose that a targeted job is submitted such 
that its tasks will be paired up with each of those partitions. This 
“pairing-up” is necessary because this task is a backup task that needs to 
be on the same physical machine as those partitions the task is backing 
up.</li> 
+   </ul> </li> 
+  <li>Task: the <b>smallest unit of work</b> in Task Framework. A task is an 
independent unit of work.</li> 
+  <li>Quota resource type: denotes a particular type of resource. Examples 
would be JVM thread count, memory, CPU resources, etc.. Generally, each task 
that runs on a Helix Participant (= instance, worker, node) occupies a set 
amount of resources. <b>Note that only JVM thread count is the only quota 
resource type currently supported by Task Framework, with each task occupying 1 
thread out of 40 threads available per Helix Participant (instance).</b></li> 
+  <li>Quota type: denotes which category a given job and its underlying tasks 
should be classified as. For example, you may define a quota configuration with 
two quota types, type “Backup”, and type “Aggregation” and a default 
type “DEFAULT”. You may prioritize the backup type by giving it a higher 
quota ratio - such as 20:10:10, respectively. When there are streams of jobs 
being submitted, you can expect each Participant, assuming that it has a total 
of 40 JVM threads, will have 20 “Backup” tasks, 10 “Aggregation” tasks, 
and 10 “DEFAULT” tasks. <b>Quota types are defined and applied at the job 
level, meaning all tasks belonging to a particular job with a quota type will 
be of that quota type.</b> Note that if a quota type is set for a workflow, 
then all jobs belonging to that workflow will <i>inherit</i> the type from the 
workflow.</li> 
+  <li>Quota: a number referring to a <b>relative ratio</b> that determines 
what portion of given resources should be allotted to a particular quota type. 
+   <ul> 
+    <li>E.g.) TYPE_0: 40, TYPE_1: 20, …, DEFAULT: 40</li> 
+   </ul> </li> 
+  <li>Quota config: a set of string-integer mappings that indicate the quota 
resource type, quota types, and corresponding quotas. <b>Task Framework stores 
the quota config in ClusterConfig.</b></li> 
+ </ul> 
+</section> 
+<section> 
+ <h2 id="Architecture">Architecture</h2> 
+ <section> 
+  <h3 id="AssignableInstance">AssignableInstance</h3> 
+  <p>AssignableInstance is an abstraction that represents each live 
Participant that is able to take on tasks from the Controller. Each 
AssignableInstance will cache what tasks it has running as well as remaining 
task counts from the quota-based capacity calculation.</p> 
+ </section> 
+ <section> 
+  <h3 id="AssignableInstanceManager">AssignableInstanceManager</h3> 
+  <p>AssignableInstanceManager manages all AssignableInstances. It also serves 
as a connecting layer between the Controller and each AssignableInstance. 
AssignableInstanceManager also provides a set of interfaces that allows the 
Controller to easily determine whether an AssignableInstance is able to take on 
more tasks.</p> 
+ </section> 
+ <section> 
+  <h3 id="TaskAssigner">TaskAssigner</h3> 
+  <p>The TaskAssigner interface provides basic API methods that involve 
assignments of tasks based on quota constraints. Currently, Task Framework only 
concerns the number of Participant-side JVM threads, each of which corresponds 
to an active task.</p> 
+ </section> 
+ <section> 
+  <h3 id="RuntimeJobDag_.28JobDagIterator.29">RuntimeJobDag 
(JobDagIterator)</h3> 
+  <p>This new component serves as an iterator for JobDAGs for the Controller. 
Previously, task assignment required the Controller to iterate through all jobs 
and their underlying tasks to determine whether there were any tasks that 
needed to be assigned and scheduled. This proved to be inefficient and did not 
scale with the increasing load we were putting on Task Framework. Each 
RuntimeJobDag records states, that is, it knows what task needs to be offered 
up to the Controller for scheduling. This saves the redundant computation for 
the Controller every time it goes through the TaskSchedulingStage of the Task 
pipeline.</p> 
+  <p><img src="./images/quota_InstanceCapacityManager.jpeg" 
alt="Architecture"></p> 
+ </section> 
+</section> 
+<section> 
+ <h2 id="User_Manual">User Manual</h2> 
+ <section> 
+  <h3 id="How_it_works">How it works</h3> 
+  <p>Quota-based task scheduling works as follows. If a quota type is set, 
Task Framework will calculate a ratio against the sum of all quota config 
numbers for each quota type. Then it will apply that ratio to find the actual 
resource amount allotted to each quota type. Here is an example to illustrate 
this: Suppose the quota config is as follows:</p> 
+  <div class="source"> 
+   <pre><code class="language-json">"QUOTA_TYPES":{
+  "A":"2"
+  ,"B":"1"
+  ,"DEFAULT":"1"
+}
+</code></pre> 
+  </div> 
+  <p>Based on these raw numbers, Task Framework will compute the ratios. With 
the ratios, Task Framework will apply them to find the actual resource amount 
per quota type. The following table summarizes these calculations with <b>the 
assumption of 40 JVM threads per instance</b>:</p> 
+  <table border="0" class="bodyTable table table-striped table-hover"> 
+   <thead> 
+    <tr class="a"> 
+     <th align="center">Quota Type</th> 
+     <th align="center">Quota Config</th> 
+     <th align="center">Ratio</th> 
+     <th align="center">Actual Resource Allotted (# of JVM Threads)</th> 
+    </tr> 
+   </thead> 
+   <tbody> 
+    <tr class="b"> 
+     <td align="left">A</td> 
+     <td align="center">2</td> 
+     <td align="center">50%</td> 
+     <td align="center">20</td> 
+    </tr> 
+    <tr class="a"> 
+     <td align="left">B</td> 
+     <td align="center">1</td> 
+     <td align="center">25%</td> 
+     <td align="center">10</td> 
+    </tr> 
+    <tr class="b"> 
+     <td align="left">DEFAULT</td> 
+     <td align="center">1</td> 
+     <td align="center">25%</td> 
+     <td align="center">10</td> 
+    </tr> 
+   </tbody> 
+  </table> 
+  <p>Every instance (node) will have a quota profile that looks like this. 
This has a few implications. First, this allows for <b>prioritization of 
certain jobs by allotting a greater amount of resources to corresponding quota 
types</b>. In that sense, you may treat quota config numbers/ratios as 
user-defined priority values. More specifically, take the quota profile in the 
example above. In this case, when there are 100 jobs submitted for each quota 
type, jobs of type A will finish faster; in other words, quota type A will see 
twice as much throughput when there is a continuous stream of jobs due to its 
quota ratio being twice that of other quota types.</p> 
+  <p>Quota-based task scheduling also allows for 
<b>isolation/compartmentalization in scheduling jobs</b>. Suppose there are two 
categories of jobs, with the first category being <i>urgent</i> jobs that are 
short-lived but need to be run right away. On the other hand, suppose that the 
second category of jobs tend to take longer, but they aren't as urgent and can 
take their time running. Previously, these two types of jobs will get assigned, 
scheduled, and run in a mix, and it was indeed difficult to ensure that jobs in 
the first category be processed in an urgent manner. Quota-based scheduling 
solves this problem by allowing the user to create quota types that model 
“categories” with different characteristics and requirements.</p> 
+ </section> 
+ <section> 
+  <h3 id="How_to_use">How to use</h3> 
+  <ul> 
+   <li>Setting a Quota Config in ClusterConfig</li> 
+  </ul> 
+  <p>In order to use quota-based task scheduling, you must establish a quota 
config first. This is a one-time operation, and once you verified that your 
ClusterConfig has a quota config set, there is no need to set it again. See the 
following code snippet for example:</p> 
+  <div class="source"> 
+   <pre><code class="language-java">ClusterConfig clusterConfig = 
_manager.getConfigAccessor().getClusterConfig(CLUSTER_NAME); // Retrieve 
ClusterConfig
+clusterConfig.resetTaskQuotaRatioMap(); // Optional: you may want to reset the 
quota config before creating a new quota config
+clusterConfig.setTaskQuotaRatio(DEFAULT_QUOTA_TYPE, 10); // Define the default 
quota (DEFAULT_QUOTA_TYPE = "DEFAULT")
+clusterConfig.setTaskQuotaRatio("A", 20); // Define quota type A
+clusterConfig.setTaskQuotaRatio("B", 10); // Define quota type B
+_manager.getConfigAccessor().setClusterConfig(CLUSTER_NAME, clusterConfig); // 
Set the new ClusterConfig
+</code></pre> 
+  </div> 
+  <p>A word of caution - if you do set the quota config, you <b>must</b> 
<b>always define the default quota type (with the key “DEFAULT”)</b>. 
Otherwise, jobs with no type information will no longer be scheduled and run. 
If you have been using Task Framework prior to the inception of quota-based 
scheduling, you might have recurrent workflows whose jobs do not have any type 
set. If you neglect to include the default quota type, these recurrent 
workflows will not execute properly.</p> 
+  <p>Upon setting the quota config in ClusterConfig, you will see the updated 
field in your ZooKeeper cluster config ZNode in the JSON format. See an example 
below:</p> 
+  <div class="source"> 
+   <pre><code class="language-json">{
+  "id":"Example_Cluster"
+  ,"simpleFields":{
+    "allowParticipantAutoJoin":"true"
+  }
+  ,"listFields":{
+  }
+  ,"mapFields":{
+    "QUOTA_TYPES":{
+      "A":"20"
+      ,"B":"10"
+      ,"DEFAULT":"10"
+    }
+  }
+}
+</code></pre> 
+  </div> 
+  <ul> 
+   <li>Setting a quota type for workflows and jobs The Builders for 
WorkflowConfig and JobConfig provides a method for setting the quota type for 
the job. See below:</li> 
+  </ul> 
+  <div class="source"> 
+   <pre><code class="language-java">JobConfig.Builder jobBuilderA =
+    new 
JobConfig.Builder().setCommand(JOB_COMMAND).setJobCommandConfigMap(_jobCommandMap)
+        
.addTaskConfigs(taskConfigsA).setNumConcurrentTasksPerInstance(50).setJobType("A");
 // Setting the job quota type as "A"
+workflowBuilder.addJob("JOB_A", jobBuilderA);
+</code></pre> 
+  </div> 
+ </section> 
+</section> 
+<section> 
+ <h2 id="FAQ">FAQ</h2> 
+ <ul> 
+  <li>What happens if I don't set a quota config in ClusterConfig? 
+   <ul> 
+    <li>When no quota config is found in ClusterConfig, Task Framework will 
treat all incoming jobs as DEFAULT and will give 100% of quota resources to the 
default type.</li> 
+   </ul> </li> 
+  <li>What happens if my job doesn't have a quota type set? 
+   <ul> 
+    <li>If Task Framework encounters a job without a quota type (that is, 
either the quotaType field is missing, is an empty String, or a literal 
“null”), then the job will be treated as a DEFAULT job.</li> 
+   </ul> </li> 
+  <li>What if there is a workflow/job whose quota type does not exist in the 
quota config I have in ClusterConfig? 
+   <ul> 
+    <li>Task Framework will <b>not</b> be able to locate the correct quota 
type, so it would <b>treat it as the DEFAULT type</b> and will assign and 
schedule accordingly using the quota for the DEFAULT type.</li> 
+   </ul> </li> 
+  <li>What about targeted jobs? 
+   <ul> 
+    <li>Quotas will also apply to targeted jobs, each task of the targeted job 
taking up a pre-set resource amount (currently each task occupies 1 JVM 
thread).</li> 
+   </ul> </li> 
+  <li>What about job queues? 
+   <ul> 
+    <li>Quota-based scheduling applies to all types of workflows - both 
generic workflows and job queues. A word of caution for the user is to be 
careful and always verify whether a job's quota type has been properly set. 
Task Framework will <b>not</b> automatically delete or inform the user of the 
jobs that are stuck due to an invalid quota type, so we caution all users to 
make sure the quota type exists by querying their settings in 
ClusterConfig.</li> 
+   </ul> </li> 
+ </ul> 
+</section> 
+<section> 
+ <h2 id="Future_Steps">Future Steps</h2> 
+ <p>Quota-based task scheduling has been tested internally at LinkedIn and has 
been integrated into <a class="externalLink" 
href="https://gobblin.apache.org/";>Apache Gobblin</a>, enabling users of Helix 
Task Framework and Gobblin's Job Launcher to define categories and 
corresponding quota values. There are a few immediate to-do's that will improve 
the usability of this feature:</p> 
+ <ul> 
+  <li>More fine-grained quota profile</li> 
+ </ul> 
+ <p>Currently, quota profiles apply across the entire cluster; that is, one 
quota profile defined in ClusterConfig will apply globally for all 
Participants. However, some use cases may require that each Participant have a 
different quota profile.</p> 
+ <ul> 
+  <li>Making Participants' maximum JVM thread capacity configurable</li> 
+ </ul> 
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Modified: helix/site-content/1.0.2-docs/recipes/lock_manager.html
URL: 
http://svn.apache.org/viewvc/helix/site-content/1.0.2-docs/recipes/lock_manager.html?rev=1909461&r1=1909460&r2=1909461&view=diff
==============================================================================
--- helix/site-content/1.0.2-docs/recipes/lock_manager.html (original)
+++ helix/site-content/1.0.2-docs/recipes/lock_manager.html Thu Apr 27 23:08:36 
2023
@@ -1,73 +1,101 @@
 
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-                                                                       <li 
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-                                                                       <li 
class="active"><a href="" title="Rsync replicated file store">Rsync replicated 
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-                                                                       <li 
class="active"><a href="" title="Service discovery">Service discovery </a></li>
-                                                                       <li 
class="active"><a href="" title="Distributed task DAG execution">Distributed 
task DAG execution </a></li>
+                                                                       <li 
class="active"><a href="" title="Distributed lock manager">Distributed lock 
manager</a></li>
+                                                                       <li ><a 
href="rabbitmq_consumer_group.html" title="Rabbit MQ consumer group">Rabbit MQ 
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+                                                                       <li ><a 
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href="task_dag_execution.html" title="Distributed task DAG 
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@@ -75,30 +103,36 @@
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+                                       <a href="../../" id="bannerLeft"><img 
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id="bannerRight"><img src="" alt='"''"' /></a>
+                                       <a href="https://www.apache.org/"; 
id="bannerRight"><img src="../../images/feather_small.gif" alt='"''"' /></a>
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Helix">Apache Helix</a></li>
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-                               <li></li>
-                               <li class="publishDate version-date 
pull-right">Last Published: 2022-04-15</li>
+                               <li>Distributed Lock Manager</li>
+                               <li class="publishDate version-date 
pull-right">Last Published: 2022-10-19</li>
                        </ul>
                </div>
        </header>
@@ -107,94 +141,334 @@
        <div class="row">
                <div class="span12">
                        <div class="body-content">
-$bodyWithHeader
+<!--
+Licensed to the Apache Software Foundation (ASF) under one
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+"License"); you may not use this file except in compliance
+with the License.  You may obtain a copy of the License at
+
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+
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+software distributed under the License is distributed on an
+"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+KIND, either express or implied.  See the License for the
+specific language governing permissions and limitations
+under the License.
+--> 
+<section> 
+ <div class="page-header">
+  <h2 id="Distributed_Lock_Manager">Distributed Lock Manager</h2>
+ </div> 
+ <p>Distributed locks are used to synchronize accesses shared resources. Most 
applications today use ZooKeeper to model distributed locks.</p> 
+ <p>The simplest way to model a lock using ZooKeeper is (See ZooKeeper leader 
recipe for an exact and more advanced solution)</p> 
+ <ul> 
+  <li>Each process tries to create an emphemeral node</li> 
+  <li>If the node is successfully created, the process acquires the lock</li> 
+  <li>Otherwise, it will watch the ZNode and try to acquire the lock again if 
the current lock holder disappears</li> 
+ </ul> 
+ <p>This is good enough if there is only one lock. But in practice, an 
application will need many such locks. Distributing and managing the locks 
among difference process becomes challenging. Extending such a solution to many 
locks will result in:</p> 
+ <ul> 
+  <li>Uneven distribution of locks among nodes; the node that starts first 
will acquire all the locks. Nodes that start later will be idle.</li> 
+  <li>When a node fails, how the locks will be distributed among remaining 
nodes is not predicable.</li> 
+  <li>When new nodes are added the current nodes don't relinquish the locks so 
that new nodes can acquire some locks</li> 
+ </ul> 
+ <p>In other words we want a system to satisfy the following requirements.</p> 
+ <ul> 
+  <li>Distribute locks evenly among all nodes to get better hardware 
utilization</li> 
+  <li>If a node fails, the locks that were acquired by that node should be 
evenly distributed among other nodes</li> 
+  <li>If nodes are added, locks must be evenly re-distributed among 
nodes.</li> 
+ </ul> 
+ <p>Helix provides a simple and elegant solution to this problem. Simply 
specify the number of locks and Helix will ensure that above constraints are 
satisfied.</p> 
+ <p>To quickly see this working run the <code>lock-manager-demo</code> script 
where 12 locks are evenly distributed among three nodes, and when a node fails, 
the locks get re-distributed among remaining two nodes. Note that Helix does 
not re-shuffle the locks completely, instead it simply distributes the locks 
relinquished by dead node among 2 remaining nodes evenly.</p> 
+ <hr> 
+ <section> 
+  <h3 id="Short_Version">Short Version</h3> 
+  <p>This version starts multiple threads within the same process to simulate 
a multi node deployment. Try the long version to get a better idea of how it 
works.</p> 
+  <div class="source"> 
+   <pre><code>git clone https://git-wip-us.apache.org/repos/asf/helix.git
+cd helix
+git checkout tags/helix-1.0.2
+mvn clean install package -DskipTests
+cd recipes/distributed-lock-manager/target/distributed-lock-manager-pkg/bin
+chmod +x *
+./lock-manager-demo
+</code></pre> 
+  </div> 
+  <section> 
+   <h4 id="Output">Output</h4> 
+   <div class="source"> 
+    <pre><code>./lock-manager-demo
+STARTING localhost_12000
+STARTING localhost_12002
+STARTING localhost_12001
+STARTED localhost_12000
+STARTED localhost_12002
+STARTED localhost_12001
+localhost_12001 acquired lock:lock-group_3
+localhost_12000 acquired lock:lock-group_8
+localhost_12001 acquired lock:lock-group_2
+localhost_12001 acquired lock:lock-group_4
+localhost_12002 acquired lock:lock-group_1
+localhost_12002 acquired lock:lock-group_10
+localhost_12000 acquired lock:lock-group_7
+localhost_12001 acquired lock:lock-group_5
+localhost_12002 acquired lock:lock-group_11
+localhost_12000 acquired lock:lock-group_6
+localhost_12002 acquired lock:lock-group_0
+localhost_12000 acquired lock:lock-group_9
+lockName    acquired By
+======================================
+lock-group_0    localhost_12002
+lock-group_1    localhost_12002
+lock-group_10    localhost_12002
+lock-group_11    localhost_12002
+lock-group_2    localhost_12001
+lock-group_3    localhost_12001
+lock-group_4    localhost_12001
+lock-group_5    localhost_12001
+lock-group_6    localhost_12000
+lock-group_7    localhost_12000
+lock-group_8    localhost_12000
+lock-group_9    localhost_12000
+Stopping localhost_12000
+localhost_12000 Interrupted
+localhost_12001 acquired lock:lock-group_9
+localhost_12001 acquired lock:lock-group_8
+localhost_12002 acquired lock:lock-group_6
+localhost_12002 acquired lock:lock-group_7
+lockName    acquired By
+======================================
+lock-group_0    localhost_12002
+lock-group_1    localhost_12002
+lock-group_10    localhost_12002
+lock-group_11    localhost_12002
+lock-group_2    localhost_12001
+lock-group_3    localhost_12001
+lock-group_4    localhost_12001
+lock-group_5    localhost_12001
+lock-group_6    localhost_12002
+lock-group_7    localhost_12002
+lock-group_8    localhost_12001
+lock-group_9    localhost_12001
+
+</code></pre> 
+   </div> 
+   <hr> 
+  </section> 
+ </section> 
+ <section> 
+  <h3 id="Long_version">Long version</h3> 
+  <p>This provides more details on how to setup the cluster and where to 
plugin application code.</p> 
+  <section> 
+   <h4 id="Start_ZooKeeper">Start ZooKeeper</h4> 
+   <div class="source"> 
+    <pre><code>./start-standalone-zookeeper 2199
+</code></pre> 
+   </div> 
+  </section> 
+  <section> 
+   <h4 id="Create_a_Cluster">Create a Cluster</h4> 
+   <div class="source"> 
+    <pre><code>./helix-admin --zkSvr localhost:2199 --addCluster 
lock-manager-demo
+</code></pre> 
+   </div> 
+  </section> 
+  <section> 
+   <h4 id="Create_a_Lock_Group">Create a Lock Group</h4> 
+   <p>Create a lock group and specify the number of locks in the lock 
group.</p> 
+   <div class="source"> 
+    <pre><code>./helix-admin --zkSvr localhost:2199  --addResource 
lock-manager-demo lock-group 6 OnlineOffline --mode AUTO_REBALANCE
+</code></pre> 
+   </div> 
+  </section> 
+  <section> 
+   <h4 id="Start_the_Nodes">Start the Nodes</h4> 
+   <p>Create a Lock class that handles the callbacks.</p> 
+   <div class="source"> 
+    <pre><code>public class Lock extends StateModel {
+  private String lockName;
+
+  public Lock(String lockName) {
+    this.lockName = lockName;
+  }
+
+  public void lock(Message m, NotificationContext context) {
+    System.out.println(" acquired lock:"+ lockName );
+  }
+
+  public void release(Message m, NotificationContext context) {
+    System.out.println(" releasing lock:"+ lockName );
+  }
+
+}
+</code></pre> 
+   </div> 
+   <p>and a LockFactory that creates Locks</p> 
+   <div class="source"> 
+    <pre><code>public class LockFactory extends StateModelFactory&lt;Lock&gt; {
+    /* Instantiates the lock handler, one per lockName */
+    public Lock create(String lockName) {
+        return new Lock(lockName);
+    }
+}
+</code></pre> 
+   </div> 
+   <p>At node start up, simply join the cluster and Helix will invoke the 
appropriate callbacks on the appropriate Lock instance. One can start any 
number of nodes and Helix detects that a new node has joined the cluster and 
re-distributes the locks automatically.</p> 
+   <div class="source"> 
+    <pre><code>public class LockProcess {
+  public static void main(String args) {
+    String zkAddress= "localhost:2199";
+    String clusterName = "lock-manager-demo";
+    //Give a unique id to each process, most commonly used format hostname_port
+    String instanceName ="localhost_12000";
+    ZKHelixAdmin helixAdmin = new ZKHelixAdmin(zkAddress);
+    //configure the instance and provide some metadata
+    InstanceConfig config = new InstanceConfig(instanceName);
+    config.setHostName("localhost");
+    config.setPort("12000");
+    admin.addInstance(clusterName, config);
+    //join the cluster
+    HelixManager manager;
+    manager = HelixManagerFactory.getHelixManager(clusterName,
+                                                  instanceName,
+                                                  InstanceType.PARTICIPANT,
+                                                  zkAddress);
+    manager.getStateMachineEngine().registerStateModelFactory("OnlineOffline", 
modelFactory);
+    manager.connect();
+    Thread.currentThread.join();
+  }
+}
+</code></pre> 
+   </div> 
+  </section> 
+  <section> 
+   <h4 id="Start_the_Controller">Start the Controller</h4> 
+   <p>The controller can be started either as a separate process or can be 
embedded within each node process</p> 
+   <section> 
+    <h5 id="Separate_Process">Separate Process</h5> 
+    <p>This is recommended when number of nodes in the cluster &gt; 100. For 
fault tolerance, you can run multiple controllers on different boxes.</p> 
+    <div class="source"> 
+     <pre><code>./run-helix-controller --zkSvr localhost:2199 --cluster 
lock-manager-demo 2&gt;&amp;1 &gt; /tmp/controller.log &amp;
+</code></pre> 
+    </div> 
+   </section> 
+   <section> 
+    <h5 id="Embedded_Within_the_Node_Process">Embedded Within the Node 
Process</h5> 
+    <p>This is recommended when the number of nodes in the cluster is less 
than 100. To start a controller from each process, simply add the following 
lines to MyClass</p> 
+    <div class="source"> 
+     <pre><code>public class LockProcess {
+  public static void main(String args) {
+    String zkAddress= "localhost:2199";
+    String clusterName = "lock-manager-demo";
+    // .
+    // .
+    manager.connect();
+    HelixManager controller;
+    controller = HelixControllerMain.startHelixController(zkAddress,
+                                                          clusterName,
+                                                          "controller",
+                                                          
HelixControllerMain.STANDALONE);
+    Thread.currentThread.join();
+  }
+}
+</code></pre> 
+    </div> 
+   </section> 
+  </section> 
+ </section> 
+</section>
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+                                                       <a href="#" 
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+                                               <li >
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+                                               <li >
+                                                       <a 
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\ No newline at end of file

Modified: helix/site-content/1.0.2-docs/recipes/rabbitmq_consumer_group.html
URL: 
http://svn.apache.org/viewvc/helix/site-content/1.0.2-docs/recipes/rabbitmq_consumer_group.html?rev=1909461&r1=1909460&r2=1909461&view=diff
==============================================================================
--- helix/site-content/1.0.2-docs/recipes/rabbitmq_consumer_group.html 
(original)
+++ helix/site-content/1.0.2-docs/recipes/rabbitmq_consumer_group.html Thu Apr 
27 23:08:36 2023
@@ -1,8 +1,13 @@
 
 <!DOCTYPE html>
+
+
+
+
+
+
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- Generated by Apache Maven Doxia at 2022-04-15
- Rendered using Maven Reflow Skin 1.0.0 
(http://andriusvelykis.github.com/reflow-maven-skin)
+ Generated by Apache Maven Doxia at 2022-10-19  Rendered using Reflow Maven 
Skin 2.0.0 (https://olamy.github.io/reflow-maven-skin)
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@@ -13,61 +18,84 @@
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-                                                                       <li 
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group </a></li>
-                                                                       <li 
class="active"><a href="" title="Rsync replicated file store">Rsync replicated 
file store </a></li>
-                                                                       <li 
class="active"><a href="" title="Service discovery">Service discovery </a></li>
-                                                                       <li 
class="active"><a href="" title="Distributed task DAG execution">Distributed 
task DAG execution </a></li>
+                                                                       <li ><a 
href="lock_manager.html" title="Distributed lock manager">Distributed lock 
manager</a></li>
+                                                                       <li 
class="active"><a href="" title="Rabbit MQ consumer group">Rabbit MQ consumer 
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+                                                                       <li ><a 
href="rsync_replicated_file_store.html" title="Rsync replicated file 
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@@ -75,30 +103,36 @@
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+                                       <a href="../../" id="bannerLeft"><img 
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id="bannerRight"><img src="" alt='"''"' /></a>
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Helix </a></li>
+                               <li><a href="http://helix.apache.org/"; 
title="Apache Helix" class="externalLink">Apache Helix</a></li>
                                <li class="divider">/</li>
-                               <li><a href="" title="Release 1.0.2">Release 
1.0.2 </a></li>
+                               <li><a href="../../" title="Apache 
Helix">Apache Helix</a></li>
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+                               <li><a href="../" title="Release 1.0.2">Release 
1.0.2</a></li>
                                <li class="divider">/</li>
                                <li>RabbitMQ Consumer Group</li>
-                               <li class="publishDate version-date 
pull-right">Last Published: 2022-04-15</li>
+                               <li class="publishDate version-date 
pull-right">Last Published: 2022-10-19</li>
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@@ -107,94 +141,289 @@
        <div class="row">
                <div class="span12">
                        <div class="body-content">
-$bodyWithHeader
+<!--
+Licensed to the Apache Software Foundation (ASF) under one
+or more contributor license agreements.  See the NOTICE file
+distributed with this work for additional information
+regarding copyright ownership.  The ASF licenses this file
+to you under the Apache License, Version 2.0 (the
+"License"); you may not use this file except in compliance
+with the License.  You may obtain a copy of the License at
+
+  http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing,
+software distributed under the License is distributed on an
+"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+KIND, either express or implied.  See the License for the
+specific language governing permissions and limitations
+under the License.
+--> 
+<section> 
+ <div class="page-header">
+  <h2 id="RabbitMQ_Consumer_Group">RabbitMQ Consumer Group</h2>
+ </div> 
+ <p><a class="externalLink" href="http://www.rabbitmq.com/";>RabbitMQ</a> is 
well-known open source software the provides robust messaging for 
applications.</p> 
+ <p>One of the commonly implemented recipes using this software is a work 
queue. <a class="externalLink" 
href="http://www.rabbitmq.com/tutorials/tutorial-four-java.html";>http://www.rabbitmq.com/tutorials/tutorial-four-java.html</a>
 describes the use case where</p> 
+ <ul> 
+  <li>A producer sends a message with a routing key</li> 
+  <li>The message is routed to the queue whose binding key exactly matches the 
routing key of the message</li> 
+  <li>There are multiple consumers and each consumer is interested in 
processing only a subset of the messages by binding to the interested keys</li> 
+ </ul> 
+ <p>The example provided <a class="externalLink" 
href="http://www.rabbitmq.com/tutorials/tutorial-four-java.html";>here</a> 
describes how multiple consumers can be started to process all the 
messages.</p> 
+ <p>While this works, in production systems one needs the following:</p> 
+ <ul> 
+  <li>Ability to handle failures: when a consumer fails, another consumer must 
be started or the other consumers must start processing these messages that 
should have been processed by the failed consumer</li> 
+  <li>When the existing consumers cannot keep up with the task generation 
rate, new consumers will be added. The tasks must be redistributed among all 
the consumers</li> 
+ </ul> 
+ <p>In this recipe, we demonstrate handling of consumer failures and new 
consumer additions using Helix.</p> 
+ <p>Mapping this usecase to Helix is pretty easy as the binding key/routing 
key is equivalent to a partition.</p> 
+ <p>Let's take an example. Lets say the queue has 6 partitions, and we have 2 
consumers to process all the queues. What we want is all 6 queues to be evenly 
divided among 2 consumers. Eventually when the system scales, we add more 
consumers to keep up. This will make each consumer process tasks from 2 queues. 
Now let's say that a consumer failed, reducing the number of active consumers 
to 2. This means each consumer must process 3 queues.</p> 
+ <p>We showcase how such a dynamic application can be developed using Helix. 
Even though we use RabbitMQ as the pub/sub system one can extend this solution 
to other pub/sub systems.</p> 
+ <section> 
+  <h3 id="Try_It">Try It</h3> 
+  <div class="source"> 
+   <pre><code>git clone https://git-wip-us.apache.org/repos/asf/helix.git
+cd helix
+git checkout tags/helix-1.0.2
+mvn clean install package -DskipTests
+cd recipes/rabbitmq-consumer-group/bin
+chmod +x *
+export HELIX_PKG_ROOT=`pwd`/helix-core/target/helix-core-pkg
+export HELIX_RABBITMQ_ROOT=`pwd`/recipes/rabbitmq-consumer-group/
+chmod +x $HELIX_PKG_ROOT/bin/*
+chmod +x $HELIX_RABBITMQ_ROOT/bin/*
+</code></pre> 
+  </div> 
+  <section> 
+   <h4 id="Install_RabbitMQ">Install RabbitMQ</h4> 
+   <p>Setting up RabbitMQ on a local box is straightforward. You can find the 
instructions here <a class="externalLink" 
href="http://www.rabbitmq.com/download.html";>http://www.rabbitmq.com/download.html</a></p>
 
+  </section> 
+  <section> 
+   <h4 id="Start_ZK">Start ZK</h4> 
+   <p>Start ZooKeeper at port 2199</p> 
+   <div class="source"> 
+    <pre><code>$HELIX_PKG_ROOT/bin/start-standalone-zookeeper 2199
+</code></pre> 
+   </div> 
+  </section> 
+  <section> 
+   <h4 id="Setup_the_Consumer_Group_Cluster">Setup the Consumer Group 
Cluster</h4> 
+   <p>This will setup the cluster by creating a “rabbitmq-consumer-group” 
cluster and adds a “topic” with “6” queues.</p> 
+   <div class="source"> 
+    <pre><code>$HELIX_RABBITMQ_ROOT/bin/setup-cluster.sh localhost:2199
+</code></pre> 
+   </div> 
+  </section> 
+  <section> 
+   <h4 id="Add_Consumers">Add Consumers</h4> 
+   <p>Start 2 consumers in 2 different terminals. Each consumer is given a 
unique ID.</p> 
+   <div class="source"> 
+    <pre><code>//start-consumer.sh zookeeperAddress (e.g. localhost:2181) 
consumerId , rabbitmqServer (e.g. localhost)
+$HELIX_RABBITMQ_ROOT/bin/start-consumer.sh localhost:2199 0 localhost
+$HELIX_RABBITMQ_ROOT/bin/start-consumer.sh localhost:2199 1 localhost
+
+</code></pre> 
+   </div> 
+  </section> 
+  <section> 
+   <h4 id="Start_the_Helix_Controller">Start the Helix Controller</h4> 
+   <p>Now start a Helix controller that starts managing the 
“rabbitmq-consumer-group” cluster.</p> 
+   <div class="source"> 
+    <pre><code>$HELIX_RABBITMQ_ROOT/bin/start-cluster-manager.sh localhost:2199
+</code></pre> 
+   </div> 
+  </section> 
+  <section> 
+   <h4 id="Send_Messages_to_the_Topic">Send Messages to the Topic</h4> 
+   <p>Start sending messages to the topic. This script randomly selects a 
routing key (1-6) and sends the message to topic. Based on the key, messages 
gets routed to the appropriate queue.</p> 
+   <div class="source"> 
+    <pre><code>$HELIX_RABBITMQ_ROOT/bin/send-message.sh localhost 20
+</code></pre> 
+   </div> 
+   <p>After running this, you should see all 20 messages being processed by 2 
consumers.</p> 
+  </section> 
+  <section> 
+   <h4 id="Add_Another_Consumer">Add Another Consumer</h4> 
+   <p>Once a new consumer is started, Helix detects it. In order to balance 
the load between 3 consumers, it deallocates 1 partition from the existing 
consumers and allocates it to the new consumer. We see that each consumer is 
now processing only 2 queues. Helix makes sure that old nodes are asked to stop 
consuming before the new consumer is asked to start consuming for a given 
partition. But the transitions for each partition can happen in parallel.</p> 
+   <div class="source"> 
+    <pre><code>$HELIX_RABBITMQ_ROOT/bin/start-consumer.sh localhost:2199 2 
localhost
+</code></pre> 
+   </div> 
+   <p>Send messages again to the topic</p> 
+   <div class="source"> 
+    <pre><code>$HELIX_RABBITMQ_ROOT/bin/send-message.sh localhost 100
+</code></pre> 
+   </div> 
+   <p>You should see that messages are now received by all 3 consumers.</p> 
+  </section> 
+  <section> 
+   <h4 id="Stop_a_Consumer">Stop a Consumer</h4> 
+   <p>In any terminal press CTRL^C and notice that Helix detects the consumer 
failure and distributes the 2 partitions that were processed by failed consumer 
to the remaining 2 active consumers.</p> 
+  </section> 
+ </section> 
+ <section> 
+  <h3 id="How_does_this_work.3F">How does this work?</h3> 
+  <p>Find the entire code <a class="externalLink" 
href="https://git-wip-us.apache.org/repos/asf?p=helix.git;a=tree;f=recipes/rabbitmq-consumer-group/src/main/java/org/apache/helix/recipes/rabbitmq";>here</a>.</p>
 
+  <section> 
+   <h4 id="Cluster_Setup">Cluster Setup</h4> 
+   <p>This step creates ZNode on ZooKeeper for the cluster and adds the state 
model. We use online offline state model since there is no need for other 
states. The consumer is either processing a queue or it is not.</p> 
+   <p>It creates a resource called “rabbitmq-consumer-group” with 6 
partitions. The execution mode is set to AUTO_REBALANCE. This means that the 
Helix controls the assignment of partition to consumers and automatically 
distributes the partitions evenly among the active consumers. When a consumer 
is added or removed, it ensures that a minimum number of partitions are 
shuffled.</p> 
+   <div class="source"> 
+    <pre><code>zkclient = new ZkClient(zkAddr, 
ZkClient.DEFAULT_SESSION_TIMEOUT,
+    ZkClient.DEFAULT_CONNECTION_TIMEOUT, new ZNRecordSerializer());
+ZKHelixAdmin admin = new ZKHelixAdmin(zkclient);
+
+// add cluster
+admin.addCluster(clusterName, true);
+
+// add state model definition
+StateModelConfigGenerator generator = new StateModelConfigGenerator();
+admin.addStateModelDef(clusterName, "OnlineOffline",
+    new StateModelDefinition(generator.generateConfigForOnlineOffline()));
+
+// add resource "topic" which has 6 partitions
+String resourceName = "rabbitmq-consumer-group";
+admin.addResource(clusterName, resourceName, 6, "OnlineOffline", 
"AUTO_REBALANCE");
+</code></pre> 
+   </div> 
+  </section> 
+ </section> 
+ <section> 
+  <h3 id="Starting_the_Consumers">Starting the Consumers</h3> 
+  <p>The only thing consumers need to know is the ZooKeeper address, cluster 
name and consumer ID. It does not need to know anything else.</p> 
+  <div class="source"> 
+   <pre><code>_manager = HelixManagerFactory.getZKHelixManager(_clusterName,
+                                                 _consumerId,
+                                                 InstanceType.PARTICIPANT,
+                                                 _zkAddr);
+
+StateMachineEngine stateMach = _manager.getStateMachineEngine();
+ConsumerStateModelFactory modelFactory =
+    new ConsumerStateModelFactory(_consumerId, _mqServer);
+stateMach.registerStateModelFactory("OnlineOffline", modelFactory);
+
+_manager.connect();
+</code></pre> 
+  </div> 
+  <p>Once the consumer has registered the state model and the controller is 
started, the consumer starts getting callbacks (onBecomeOnlineFromOffline) for 
the partition it needs to host. All it needs to do as part of the callback is 
to start consuming messages from the appropriate queue. Similarly, when the 
controller deallocates a partitions from a consumer, it fires 
onBecomeOfflineFromOnline for the same partition. As a part of this transition, 
the consumer will stop consuming from a that queue.</p> 
+  <div class="source"> 
+   <pre><code>@Transition(to = "ONLINE", from = "OFFLINE")
+public void onBecomeOnlineFromOffline(Message message, NotificationContext 
context) {
+  LOG.debug(_consumerId + " becomes ONLINE from OFFLINE for " + _partition);
+  if (_thread == null) {
+    LOG.debug("Starting ConsumerThread for " + _partition + "...");
+    _thread = new ConsumerThread(_partition, _mqServer, _consumerId);
+    _thread.start();
+    LOG.debug("Starting ConsumerThread for " + _partition + " done");
+
+  }
+}
+
+@Transition(to = "OFFLINE", from = "ONLINE")
+public void onBecomeOfflineFromOnline(Message message, NotificationContext 
context)
+    throws InterruptedException {
+  LOG.debug(_consumerId + " becomes OFFLINE from ONLINE for " + _partition);
+  if (_thread != null) {
+    LOG.debug("Stopping " + _consumerId + " for " + _partition + "...");
+    _thread.interrupt();
+    _thread.join(2000);
+    _thread = null;
+    LOG.debug("Stopping " +  _consumerId + " for " + _partition + " done");
+  }
+}
+</code></pre> 
+  </div> 
+ </section> 
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