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Posted to commits@helix.apache.org by ka...@apache.org on 2013/10/19 01:27:35 UTC
[2/3] [HELIX-270] Refactor website to have release-specific pages,
disable link to 0.6.1 page for now
http://git-wip-us.apache.org/repos/asf/incubator-helix/blob/80abba32/site-releases/0.6.1-incubating/src/site/markdown/UseCases.md
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+<!---
+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.
+-->
+
+
+# Use cases at LinkedIn
+
+At LinkedIn Helix framework is used to manage 3 distributed data systems which are quite different from each other.
+
+* Espresso
+* Databus
+* Search As A Service
+
+## Espresso
+
+Espresso is a distributed, timeline consistent, scal- able, document store that supports local secondary indexing and local transactions.
+Espresso databases are horizontally partitioned into a number of partitions, with each partition having a certain number of replicas
+distributed across the storage nodes.
+Espresso designates one replica of each partition as master and the rest as slaves; only one master may exist for each partition at any time.
+Espresso enforces timeline consistency where only the master of a partition can accept writes to its records, and all slaves receive and
+apply the same writes through a replication stream.
+For load balancing, both master and slave partitions are assigned evenly across all storage nodes.
+For fault tolerance, it adds the constraint that no two replicas of the same partition may be located on the same node.
+
+### State model
+Espresso follows a Master-Slave state model. A replica can be in Offline,Slave or Master state.
+The state machine table describes the next state given the Current State, Final State
+
+```
+ OFFLINE | SLAVE | MASTER
+ _____________________________
+ | | | |
+OFFLINE | N/A | SLAVE | SLAVE |
+ |__________|________|_________|
+ | | | |
+SLAVE | OFFLINE | N/A | MASTER |
+ |__________|________|_________|
+ | | | |
+MASTER | SLAVE | SLAVE | N/A |
+ |__________|________|_________|
+
+```
+
+### Constraints
+* Max number of replicas in Master state:1
+* Execution mode AUTO. i.e on node failure no new replicas will be created. Only the State of remaining replicas will be changed.
+* Number of mastered partitions on each node must be approximately same.
+* The above constraint must be satisfied when a node fails or a new node is added.
+* When new nodes are added the number of partitions moved must be minimized.
+* When new nodes are added the max number of OFFLINE-SLAVE transitions that can happen concurrently on new node is X.
+
+## Databus
+
+Databus is a change data capture (CDC) system that provides a common pipeline for transporting events
+from LinkedIn primary databases to caches within various applications.
+Databus deploys a cluster of relays that pull the change log from multiple databases and
+let consumers subscribe to the change log stream. Each Databus relay connects to one or more database servers and
+hosts a certain subset of databases (and partitions) from those database servers.
+
+For a large partitioned database (e.g. Espresso), the change log is consumed by a bank of consumers.
+Each databus partition is assigned to a consumer such that partitions are evenly distributed across consumers and each partition is
+assigned to exactly one consumer at a time. The set of consumers may grow over time, and consumers may leave the group due to planned or unplanned
+outages. In these cases, partitions must be reassigned, while maintaining balance and the single consumer-per-partition invariant.
+
+### State model
+Databus consumers follow a simple Offline-Online state model.
+The state machine table describes the next state given the Current State, Final State
+
+<pre><code>
+ OFFLINE | ONLINE |
+ ___________________|
+ | | |
+OFFLINE | N/A | ONLINE |
+ |__________|________|
+ | | |
+ONLINE | OFFLINE | N/A |
+ |__________|________|
+
+
+</code></pre>
+
+
+## Search As A Service
+
+LinkedIn�s Search-as-a-service lets internal customers define custom indexes on a chosen dataset
+and then makes those indexes searchable via a service API. The index service runs on a cluster of machines.
+The index is broken into partitions and each partition has a configured number of replicas.
+Each cluster server runs an instance of the Sensei system (an online index store) and hosts index partitions.
+Each new indexing service gets assigned to a set of servers, and the partition replicas must be evenly distributed across those servers.
+
+### State model
+
+
+
http://git-wip-us.apache.org/repos/asf/incubator-helix/blob/80abba32/site-releases/0.6.1-incubating/src/site/markdown/index.md
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+<!---
+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.
+-->
+
+Navigating the Documentation
+----------------------------
+
+### Conceptual Understanding
+
+[Concepts / Terminology](./Concepts.html)
+
+[Architecture](./Architecture.html)
+
+### Hands-on Helix
+
+[Quickstart](./Quickstart.html)
+
+[Tutorial](./Tutorial.html)
+
+[Javadocs](./apidocs/index.html)
+
+### Recipes
+
+[Distributed lock manager](./recipes/lock_manager.html)
+
+[Rabbit MQ consumer group](./recipes/rabbitmq_consumer_group.html)
+
+[Rsync replicated file store](./recipes/rsync_replicated_file_store.html)
+
+[Service discovery](./recipes/service_discovery.html)
+
+[Distributed Task DAG Execution](./recipes/task_dag_execution.html)
+
+### Download
+
+[0.6.1-incubating](./download.html)
+
+
+What Is Helix
+--------------
+Helix is a generic _cluster management_ framework used for the automatic management of partitioned, replicated and distributed resources hosted on a cluster of nodes.
+
+
+What Is Cluster Management
+--------------------------
+To understand Helix, first you need to understand what is _cluster management_. A distributed system typically runs on multiple nodes for the following reasons:
+
+* scalability
+* fault tolerance
+* load balancing
+
+Each node performs one or more of the primary function of the cluster, such as storing/serving data, producing/consuming data streams, etc. Once configured for your system, Helix acts as the global brain for the system. It is designed to make decisions that cannot be made in isolation. Examples of decisions that require global knowledge and coordination:
+
+* scheduling of maintainence tasks, such as backups, garbage collection, file consolidation, index rebuilds
+* repartitioning of data or resources across the cluster
+* informing dependent systems of changes so they can react appropriately to cluster changes
+* throttling system tasks and changes
+
+While it is possible to integrate these functions into the distributed system, it complicates the code. Helix has abstracted common cluster management tasks, enabling the system builder to model the desired behavior in a declarative state model, and let Helix manage the coordination. The result is less new code to write, and a robust, highly operable system.
+
+
+Key Features of Helix
+---------------------
+1. Automatic assignment of resource/partition to nodes
+2. Node failure detection and recovery
+3. Dynamic addition of Resources
+4. Dynamic addition of nodes to the cluster
+5. Pluggable distributed state machine to manage the state of a resource via state transitions
+6. Automatic load balancing and throttling of transitions
+
+
+Why Helix
+---------
+Modeling a distributed system as a state machine with constraints on state and transitions has the following benefits:
+
+* Separates cluster management from the core functionality.
+* Quick transformation from a single node system to an operable, distributed system.
+* Simplicity: System components do not have to manage global cluster. This division of labor makes it easier to build, debug, and maintain your system.
+
+
+Build Instructions
+------------------
+
+Requirements: Jdk 1.6+, Maven 2.0.8+
+
+```
+ git clone https://git-wip-us.apache.org/repos/asf/incubator-helix.git
+ cd incubator-helix
+ git checkout tags/helix-0.6.1-incubating
+ mvn install package -DskipTests
+```
+
+Maven dependency
+
+```
+ <dependency>
+ <groupId>org.apache.helix</groupId>
+ <artifactId>helix-core</artifactId>
+ <version>0.6.1-incubating</version>
+ </dependency>
+```
+
+[Download](./download.html) Helix artifacts from here.
+
+Publications
+-------------
+
+* Untangling cluster management using Helix at [SOCC Oct 2012](http://www.socc2012.org/home/program)
+ - [paper](https://915bbc94-a-62cb3a1a-s-sites.googlegroups.com/site/acm2012socc/helix_onecol.pdf)
+ - [presentation](http://www.slideshare.net/KishoreGopalakrishna/helix-socc-v10final)
+* Building distributed systems using Helix Apache Con Feb 2013
+ - [presentation at ApacheCon](http://www.slideshare.net/KishoreGopalakrishna/apache-con-buildingddsusinghelix)
+ - [presentation at VMWare](http://www.slideshare.net/KishoreGopalakrishna/apache-helix-presentation-at-vmware)
+* Data driven testing:
+ - [short talk at LSPE meetup](http://www.slideshare.net/KishoreGopalakrishna/data-driven-testing)
+ - [paper DBTest 2013 acm SIGMOD:will be published on Jun 24, 2013](http://dbtest2013.soe.ucsc.edu/Program.htm)
+
http://git-wip-us.apache.org/repos/asf/incubator-helix/blob/80abba32/site-releases/0.6.1-incubating/src/site/markdown/recipes/lock_manager.md
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+<!---
+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.
+-->
+Distributed lock manager
+------------------------
+Distributed locks are used to synchronize accesses shared resources. Most applications use Zookeeper to model the distributed locks.
+
+The simplest way to model a lock using zookeeper is (See Zookeeper leader recipe for an exact and more advanced solution)
+
+* Each process tries to create an emphemeral node.
+* If can successfully create it then, it acquires the lock
+* Else it will watch on the znode and try to acquire the lock again if the current lock holder disappears
+
+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
+
+* Uneven distribution of locks among nodes, the node that starts first will acquire all the lock. Nodes that start later will be idle.
+* When a node fails, how the locks will be distributed among remaining nodes is not predicable.
+* When new nodes are added the current nodes dont relinquish the locks so that new nodes can acquire some locks
+
+In other words we want a system to satisfy the following requirements.
+
+* Distribute locks evenly among all nodes to get better hardware utilization
+* If a node fails, the locks that were acquired by that node should be evenly distributed among other nodes
+* If nodes are added, locks must be evenly re-distributed among nodes.
+
+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.
+
+To quickly see this working run the lock-manager-demo 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.
+
+----------------------------------------------------------------------------------------
+
+#### Short version
+ This version starts multiple threads with in same process to simulate a multi node deployment. Try the long version to get a better idea of how it works.
+
+```
+git clone https://git-wip-us.apache.org/repos/asf/incubator-helix.git
+cd incubator-helix
+mvn clean install package -DskipTests
+cd recipes/distributed-lock-manager/target/distributed-lock-manager-pkg/bin
+chmod +x *
+./lock-manager-demo
+```
+
+##### Output
+
+```
+./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
+
+```
+
+----------------------------------------------------------------------------------------
+
+#### Long version
+This provides more details on how to setup the cluster and where to plugin application code.
+
+##### start zookeeper
+
+```
+./start-standalone-zookeeper 2199
+```
+
+##### Create a cluster
+
+```
+./helix-admin --zkSvr localhost:2199 --addCluster lock-manager-demo
+```
+
+##### Create a lock group
+
+Create a lock group and specify the number of locks in the lock group.
+
+```
+./helix-admin --zkSvr localhost:2199 --addResource lock-manager-demo lock-group 6 OnlineOffline AUTO_REBALANCE
+```
+
+##### Start the nodes
+
+Create a Lock class that handles the callbacks.
+
+```
+
+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 );
+ }
+
+}
+
+```
+
+LockFactory that creates the lock
+
+```
+public class LockFactory extends StateModelFactory<Lock>{
+
+ /* Instantiates the lock handler, one per lockName*/
+ public Lock create(String lockName)
+ {
+ return new Lock(lockName);
+ }
+}
+```
+
+At node start up, simply join the cluster and helix will invoke the appropriate callbacks on 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.
+
+```
+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();
+ }
+
+}
+```
+
+##### Start the controller
+
+Controller can be started either as a separate process or can be embedded within each node process
+
+###### Separate process
+This is recommended when number of nodes in the cluster >100. For fault tolerance, you can run multiple controllers on different boxes.
+
+```
+./run-helix-controller --zkSvr localhost:2199 --cluster lock-manager-demo 2>&1 > /tmp/controller.log &
+```
+
+###### Embedded within the node process
+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
+
+```
+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();
+ }
+}
+```
+
+----------------------------------------------------------------------------------------
+
+
+
+
+
http://git-wip-us.apache.org/repos/asf/incubator-helix/blob/80abba32/site-releases/0.6.1-incubating/src/site/markdown/recipes/rabbitmq_consumer_group.md
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diff --git a/site-releases/0.6.1-incubating/src/site/markdown/recipes/rabbitmq_consumer_group.md b/site-releases/0.6.1-incubating/src/site/markdown/recipes/rabbitmq_consumer_group.md
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+<!---
+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.
+-->
+
+
+RabbitMQ Consumer Group
+=======================
+
+[RabbitMQ](http://www.rabbitmq.com/) is a well known Open source software the provides robust messaging for applications.
+
+One of the commonly implemented recipes using this software is a work queue. http://www.rabbitmq.com/tutorials/tutorial-four-java.html describes the use case where
+
+* A producer sends a message with a routing key.
+* The message is routed to the queue whose binding key exactly matches the routing key of the message.
+* There are multiple consumers and each consumer is interested in processing only a subset of the messages by binding to the interested keys
+
+The example provided [here](http://www.rabbitmq.com/tutorials/tutorial-four-java.html) describes how multiple consumers can be started to process all the messages.
+
+While this works, in production systems one needs the following
+
+* Ability to handle failures: when a consumers fails another consumer must be started or the other consumers must start processing these messages that should have been processed by the failed consumer.
+* 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.
+
+In this recipe, we demonstrate handling of consumer failures and new consumer additions using Helix.
+
+Mapping this usecase to Helix is pretty easy as the binding key/routing key is equivalent to a partition.
+
+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 which reduces the number of active consumers to 2. This means each consumer must process 3 queues.
+
+We showcase how such a dynamic App 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.
+
+Try it
+======
+
+```
+git clone https://git-wip-us.apache.org/repos/asf/incubator-helix.git
+cd incubator-helix
+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 $HELIX_RABBITMQ_ROOT/bin/*
+```
+
+
+Install Rabbit MQ
+----------------
+
+Setting up RabbitMQ on a local box is straightforward. You can find the instructions here
+http://www.rabbitmq.com/download.html
+
+Start ZK
+--------
+Start zookeeper at port 2199
+
+```
+$HELIX_PKG_ROOT/bin/start-standalone-zookeeper 2199
+```
+
+Setup the consumer group cluster
+--------------------------------
+This will setup the cluster by creating a "rabbitmq-consumer-group" cluster and adds a "topic" with "6" queues.
+
+```
+$HELIX_RABBITMQ_ROOT/bin/setup-cluster.sh localhost:2199
+```
+
+Add consumers
+-------------
+Start 2 consumers in 2 different terminals. Each consumer is given a unique id.
+
+```
+//start-consumer.sh zookeeperAddress (e.g. localhost:2181) consumerId , rabbitmqServer (e.g. localhost)
+$HELIX_RABBITMQ_ROOT/bin/start-consumer.sh localhost:2199 0 localhost
+$HELIX_RABBITMQ_ROOT/bin/start-consumer.sh localhost:2199 1 localhost
+
+```
+
+Start HelixController
+--------------------
+Now start a Helix controller that starts managing the "rabbitmq-consumer-group" cluster.
+
+```
+$HELIX_RABBITMQ_ROOT/bin/start-cluster-manager.sh localhost:2199
+```
+
+Send messages to the Topic
+--------------------------
+
+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.
+
+```
+$HELIX_RABBITMQ_ROOT/bin/send-message.sh localhost 20
+```
+
+After running this, you should see all 20 messages being processed by 2 consumers.
+
+Add another consumer
+--------------------
+Once a new consumer is started, helix detects it. In order to balance the load between 3 consumers, it deallocates 1 partition from the existing consumers and allocates it to the new consumer. We see that
+each consumer is now processing only 2 queues.
+Helix makes sure that old nodes are asked to stop consuming before the new consumer is asked to start consuming for a given partition. But the transitions for each partition can happen in parallel.
+
+```
+$HELIX_RABBITMQ_ROOT/bin/start-consumer.sh localhost:2199 2 localhost
+```
+
+Send messages again to the topic.
+
+```
+$HELIX_RABBITMQ_ROOT/bin/send-message.sh localhost 100
+```
+
+You should see that messages are now received by all 3 consumers.
+
+Stop a consumer
+---------------
+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.
+
+
+How does it work
+================
+
+Find the entire code [here](https://git-wip-us.apache.org/repos/asf?p=incubator-helix.git;a=tree;f=recipes/rabbitmq-consumer-group/src/main/java/org/apache/helix/recipes/rabbitmq).
+
+Cluster setup
+-------------
+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.
+
+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.
+
+```
+ 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");
+```
+
+Starting the consumers
+----------------------
+The only thing consumers need to know is the zkaddress, cluster name and consumer id. It does not need to know anything else.
+
+```
+ _manager =
+ HelixManagerFactory.getZKHelixManager(_clusterName,
+ _consumerId,
+ InstanceType.PARTICIPANT,
+ _zkAddr);
+
+ StateMachineEngine stateMach = _manager.getStateMachineEngine();
+ ConsumerStateModelFactory modelFactory =
+ new ConsumerStateModelFactory(_consumerId, _mqServer);
+ stateMach.registerStateModelFactory("OnlineOffline", modelFactory);
+
+ _manager.connect();
+
+```
+
+Once the consumer has registered the statemodel 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.
+
+```
+ @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");
+
+ }
+ }
+```
\ No newline at end of file
http://git-wip-us.apache.org/repos/asf/incubator-helix/blob/80abba32/site-releases/0.6.1-incubating/src/site/markdown/recipes/rsync_replicated_file_store.md
----------------------------------------------------------------------
diff --git a/site-releases/0.6.1-incubating/src/site/markdown/recipes/rsync_replicated_file_store.md b/site-releases/0.6.1-incubating/src/site/markdown/recipes/rsync_replicated_file_store.md
new file mode 100644
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@@ -0,0 +1,165 @@
+<!---
+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.
+-->
+
+Near real time rsync replicated file system
+===========================================
+
+Quickdemo
+---------
+
+* This demo starts 3 instances with id's as ```localhost_12001, localhost_12002, localhost_12003```
+* Each instance stores its files under ```/tmp/<id>/filestore```
+* ``` localhost_12001 ``` is designated as the master and ``` localhost_12002 and localhost_12003``` are the slaves.
+* Files written to master are replicated to the slaves automatically. In this demo, a.txt and b.txt are written to ```/tmp/localhost_12001/filestore``` and it gets replicated to other folders.
+* When the master is stopped, ```localhost_12002``` is promoted to master.
+* The other slave ```localhost_12003``` stops replicating from ```localhost_12001``` and starts replicating from new master ```localhost_12002```
+* Files written to new master ```localhost_12002``` are replicated to ```localhost_12003```
+* In the end state of this quick demo, ```localhost_12002``` is the master and ```localhost_12003``` is the slave. Manually create files under ```/tmp/localhost_12002/filestore``` and see that appears in ```/tmp/localhost_12003/filestore```
+* Ignore the interrupted exceptions on the console :-).
+
+
+```
+git clone https://git-wip-us.apache.org/repos/asf/incubator-helix.git
+cd recipes/rsync-replicated-file-system/
+mvn clean install package -DskipTests
+cd target/rsync-replicated-file-system-pkg/bin
+chmod +x *
+./quickdemo
+
+```
+
+Overview
+--------
+
+There are many applications that require storage for storing large number of relatively small data files. Examples include media stores to store small videos, images, mail attachments etc. Each of these objects is typically kilobytes, often no larger than a few megabytes. An additional distinguishing feature of these usecases is also that files are typically only added or deleted, rarely updated. When there are updates, they are rare and do not have any concurrency requirements.
+
+These are much simpler requirements than what general purpose distributed file system have to satisfy including concurrent access to files, random access for reads and updates, posix compliance etc. To satisfy those requirements, general DFSs are also pretty complex that are expensive to build and maintain.
+
+A different implementation of a distributed file system includes HDFS which is inspired by Google's GFS. This is one of the most widely used distributed file system that forms the main data storage platform for Hadoop. HDFS is primary aimed at processing very large data sets and distributes files across a cluster of commodity servers by splitting up files in fixed size chunks. HDFS is not particularly well suited for storing a very large number of relatively tiny files.
+
+### File Store
+
+It's possible to build a vastly simpler system for the class of applications that have simpler requirements as we have pointed out.
+
+* Large number of files but each file is relatively small.
+* Access is limited to create, delete and get entire files.
+* No updates to files that are already created (or it's feasible to delete the old file and create a new one).
+
+
+We call this system a Partitioned File Store (PFS) to distinguish it from other distributed file systems. This system needs to provide the following features:
+
+* CRD access to large number of small files
+* Scalability: Files should be distributed across a large number of commodity servers based on the storage requirement.
+* Fault-tolerance: Each file should be replicated on multiple servers so that individual server failures do not reduce availability.
+* Elasticity: It should be possible to add capacity to the cluster easily.
+
+
+Apache Helix is a generic cluster management framework that makes it very easy to provide the scalability, fault-tolerance and elasticity features.
+Rsync can be easily used as a replication channel between servers so that each file gets replicated on multiple servers.
+
+Design
+------
+
+High level
+
+* Partition the file system based on the file name.
+* At any time a single writer can write, we call this a master.
+* For redundancy, we need to have additional replicas called slave. Slaves can optionally serve reads.
+* Slave replicates data from the master.
+* When a master fails, slave gets promoted to master.
+
+### Transaction log
+
+Every write on the master will result in creation/deletion of one or more files. In order to maintain timeline consistency slaves need to apply the changes in the same order.
+To facilitate this, the master logs each transaction in a file and each transaction is associated with an 64 bit id in which the 32 LSB represents a sequence number and MSB represents the generation number.
+Sequence gets incremented on every transaction and and generation is increment when a new master is elected.
+
+### Replication
+
+Replication is required to slave to keep up with the changes on the master. Every time the slave applies a change it checkpoints the last applied transaction id.
+During restarts, this allows the slave to pull changes from the last checkpointed id. Similar to master, the slave logs each transaction to the transaction logs but instead of generating new transaction id, it uses the same id generated by the master.
+
+
+### Fail over
+
+When a master fails, a new slave will be promoted to master. If the prev master node is reachable, then the new master will flush all the
+changes from previous master before taking up mastership. The new master will record the end transaction id of the current generation and then starts new generation
+with sequence starting from 1. After this the master will begin accepting writes.
+
+
+
+
+
+
+Rsync based solution
+-------------------
+
+
+
+
+This application demonstrate a file store that uses rsync as the replication mechanism. One can envision a similar system where instead of using rsync,
+can implement a custom solution to notify the slave of the changes and also provide an api to pull the change files.
+#### Concept
+* file_store_dir: Root directory for the actual data files
+* change_log_dir: The transaction logs are generated under this folder.
+* check_point_dir: The slave stores the check points ( last processed transaction) here.
+
+#### Master
+* File server: This component support file uploads and downloads and writes the files to ```file_store_dir```. This is not included in this application. Idea is that most applications have different ways of implementing this component and has some business logic associated with it. It is not hard to come up with such a component if needed.
+* File store watcher: This component watches the ```file_store_dir``` directory on the local file system for any changes and notifies the registered listeners of the changes.
+* Change Log Generator: This registers as a listener of File System Watcher and on each notification logs the changes into a file under ```change_log_dir```.
+
+####Slave
+* File server: This component on the slave will only support reads.
+* Cluster state observer: Slave observes the cluster state and is able to know who is the current master.
+* Replicator: This has two subcomponents
+ - Periodic rsync of change log: This is a background process that periodically rsyncs the ```change_log_dir``` of the master to its local directory
+ - Change Log Watcher: This watches the ```change_log_dir``` for changes and notifies the registered listeners of the change
+ - On demand rsync invoker: This is registered as a listener to change log watcher and on every change invokes rsync to sync only the changed file.
+
+
+#### Coordination
+
+The coordination between nodes is done by Helix. Helix does the partition management and assigns the partition to multiple nodes based on the replication factor. It elects one the nodes as master and designates others as slaves.
+It provides notifications to each node in the form of state transitions ( Offline to Slave, Slave to Master). It also provides notification when there is change is cluster state.
+This allows the slave to stop replicating from current master and start replicating from new master.
+
+In this application, we have only one partition but its very easy to extend it to support multiple partitions. By partitioning the file store, one can add new nodes and Helix will automatically
+re-distribute partitions among the nodes. To summarize, Helix provides partition management, fault tolerance and facilitates automated cluster expansion.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
http://git-wip-us.apache.org/repos/asf/incubator-helix/blob/80abba32/site-releases/0.6.1-incubating/src/site/markdown/recipes/service_discovery.md
----------------------------------------------------------------------
diff --git a/site-releases/0.6.1-incubating/src/site/markdown/recipes/service_discovery.md b/site-releases/0.6.1-incubating/src/site/markdown/recipes/service_discovery.md
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@@ -0,0 +1,191 @@
+<!---
+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.
+-->
+Service Discovery
+-----------------
+
+One of the common usage of zookeeper is enable service discovery.
+The basic idea is that when a server starts up it advertises its configuration/metadata such as host name port etc on zookeeper.
+This allows clients to dynamically discover the servers that are currently active. One can think of this like a service registry to which a server registers when it starts and
+is automatically deregistered when it shutdowns or crashes. In many cases it serves as an alternative to vips.
+
+The core idea behind this is to use zookeeper ephemeral nodes. The ephemeral nodes are created when the server registers and all its metadata is put into a znode.
+When the server shutdowns, zookeeper automatically removes this znode.
+
+There are two ways the clients can dynamically discover the active servers
+
+#### ZOOKEEPER WATCH
+
+Clients can set a child watch under specific path on zookeeper.
+When a new service is registered/deregistered, zookeeper notifies the client via watchevent and the client can read the list of services. Even though this looks trivial,
+there are lot of things one needs to keep in mind like ensuring that you first set the watch back on zookeeper before reading data from zookeeper.
+
+
+#### POLL
+
+Another approach is for the client to periodically read the zookeeper path and get the list of services.
+
+
+Both approaches have pros and cons, for example setting a watch might trigger herd effect if there are large number of clients. This is worst especially when servers are starting up.
+But good thing about setting watch is that clients are immediately notified of a change which is not true in case of polling.
+In some cases, having both WATCH and POLL makes sense, WATCH allows one to get notifications as soon as possible while POLL provides a safety net if a watch event is missed because of code bug or zookeeper fails to notify.
+
+##### Other important scenarios to take care of
+* What happens when zookeeper session expires. All the watches/ephemeral nodes previously added/created by this server are lost.
+One needs to add the watches again , recreate the ephemeral nodes etc.
+* Due to network issues or java GC pauses session expiry might happen again and again also known as flapping. Its important for the server to detect this and deregister itself.
+
+##### Other operational things to consider
+* What if the node is behaving badly, one might kill the server but will lose the ability to debug.
+It would be nice to have the ability to mark a server as disabled and clients know that a node is disabled and will not contact that node.
+
+#### Configuration ownership
+
+This is an important aspect that is often ignored in the initial stages of your development. In common, service discovery pattern means that servers start up with some configuration and then simply puts its configuration/metadata in zookeeper. While this works well in the beginning,
+configuration management becomes very difficult since the servers themselves are statically configured. Any change in server configuration implies restarting of the server. Ideally, it will be nice to have the ability to change configuration dynamically without having to restart a server.
+
+Ideally you want a hybrid solution, a node starts with minimal configuration and gets the rest of configuration from zookeeper.
+
+h3. How to use Helix to achieve this
+
+Even though Helix has higher level abstraction in terms of statemachine, constraints and objectives,
+service discovery is one of things that existed since we started.
+The controller uses the exact mechanism we described above to discover when new servers join the cluster.
+We create these znodes under /CLUSTERNAME/LIVEINSTANCES.
+Since at any time there is only one controller, we use ZK watch to track the liveness of a server.
+
+This recipe, simply demonstrate how one can re-use that part for implementing service discovery. This demonstrates multiple MODE's of service discovery
+
+* POLL: The client reads from zookeeper at regular intervals 30 seconds. Use this if you have 100's of clients
+* WATCH: The client sets up watcher and gets notified of the changes. Use this if you have 10's of clients.
+* NONE: This does neither of the above, but reads directly from zookeeper when ever needed.
+
+Helix provides these additional features compared to other implementations available else where
+
+* It has the concept of disabling a node which means that a badly behaving node, can be disabled using helix admin api.
+* It automatically detects if a node connects/disconnects from zookeeper repeatedly and disables the node.
+* Configuration management
+ * Allows one to set configuration via admin api at various granulaties like cluster, instance, resource, partition
+ * Configuration can be dynamically changed.
+ * Notifies the server when configuration changes.
+
+
+##### checkout and build
+
+```
+git clone https://git-wip-us.apache.org/repos/asf/incubator-helix.git
+cd incubator-helix
+mvn clean install package -DskipTests
+cd recipes/service-discovery/target/service-discovery-pkg/bin
+chmod +x *
+```
+
+##### start zookeeper
+
+```
+./start-standalone-zookeeper 2199
+```
+
+#### Run the demo
+
+```
+./service-discovery-demo.sh
+```
+
+#### Output
+
+```
+START:Service discovery demo mode:WATCH
+ Registering service
+ host.x.y.z_12000
+ host.x.y.z_12001
+ host.x.y.z_12002
+ host.x.y.z_12003
+ host.x.y.z_12004
+ SERVICES AVAILABLE
+ SERVICENAME HOST PORT
+ myServiceName host.x.y.z 12000
+ myServiceName host.x.y.z 12001
+ myServiceName host.x.y.z 12002
+ myServiceName host.x.y.z 12003
+ myServiceName host.x.y.z 12004
+ Deregistering service:
+ host.x.y.z_12002
+ SERVICES AVAILABLE
+ SERVICENAME HOST PORT
+ myServiceName host.x.y.z 12000
+ myServiceName host.x.y.z 12001
+ myServiceName host.x.y.z 12003
+ myServiceName host.x.y.z 12004
+ Registering service:host.x.y.z_12002
+END:Service discovery demo mode:WATCH
+=============================================
+START:Service discovery demo mode:POLL
+ Registering service
+ host.x.y.z_12000
+ host.x.y.z_12001
+ host.x.y.z_12002
+ host.x.y.z_12003
+ host.x.y.z_12004
+ SERVICES AVAILABLE
+ SERVICENAME HOST PORT
+ myServiceName host.x.y.z 12000
+ myServiceName host.x.y.z 12001
+ myServiceName host.x.y.z 12002
+ myServiceName host.x.y.z 12003
+ myServiceName host.x.y.z 12004
+ Deregistering service:
+ host.x.y.z_12002
+ Sleeping for poll interval:30000
+ SERVICES AVAILABLE
+ SERVICENAME HOST PORT
+ myServiceName host.x.y.z 12000
+ myServiceName host.x.y.z 12001
+ myServiceName host.x.y.z 12003
+ myServiceName host.x.y.z 12004
+ Registering service:host.x.y.z_12002
+END:Service discovery demo mode:POLL
+=============================================
+START:Service discovery demo mode:NONE
+ Registering service
+ host.x.y.z_12000
+ host.x.y.z_12001
+ host.x.y.z_12002
+ host.x.y.z_12003
+ host.x.y.z_12004
+ SERVICES AVAILABLE
+ SERVICENAME HOST PORT
+ myServiceName host.x.y.z 12000
+ myServiceName host.x.y.z 12001
+ myServiceName host.x.y.z 12002
+ myServiceName host.x.y.z 12003
+ myServiceName host.x.y.z 12004
+ Deregistering service:
+ host.x.y.z_12000
+ SERVICES AVAILABLE
+ SERVICENAME HOST PORT
+ myServiceName host.x.y.z 12001
+ myServiceName host.x.y.z 12002
+ myServiceName host.x.y.z 12003
+ myServiceName host.x.y.z 12004
+ Registering service:host.x.y.z_12000
+END:Service discovery demo mode:NONE
+=============================================
+
+```
+
http://git-wip-us.apache.org/repos/asf/incubator-helix/blob/80abba32/site-releases/0.6.1-incubating/src/site/markdown/recipes/task_dag_execution.md
----------------------------------------------------------------------
diff --git a/site-releases/0.6.1-incubating/src/site/markdown/recipes/task_dag_execution.md b/site-releases/0.6.1-incubating/src/site/markdown/recipes/task_dag_execution.md
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--- /dev/null
+++ b/site-releases/0.6.1-incubating/src/site/markdown/recipes/task_dag_execution.md
@@ -0,0 +1,204 @@
+<!---
+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.
+-->
+
+# Distributed task execution
+
+
+This recipe is intended to demonstrate how task dependencies can be modeled using primitives provided by Helix. A given task can be run with desired parallelism and will start only when up-stream dependencies are met. The demo executes the task DAG described below using 10 workers. Although the demo starts the workers as threads, there is no requirement that all the workers need to run in the same process. In reality, these workers run on many different boxes on a cluster. When worker fails, Helix takes care of
+re-assigning a failed task partition to a new worker.
+
+Redis is used as a result store. Any other suitable implementation for TaskResultStore can be plugged in.
+
+### Workflow
+
+
+#### Input
+
+10000 impression events and around 100 click events are pre-populated in task result store (redis).
+
+* **ImpEvent**: format: id,isFraudulent,country,gender
+
+* **ClickEvent**: format: id,isFraudulent,impEventId
+
+#### Stages
+
++ **FilterImps**: Filters impression where isFraudulent=true.
+
++ **FilterClicks**: Filters clicks where isFraudulent=true
+
++ **impCountsByGender**: Generates impression counts grouped by gender. It does this by incrementing the count for 'impression_gender_counts:<gender_value>' in the task result store (redis hash). Depends on: **FilterImps**
+
++ **impCountsByCountry**: Generates impression counts grouped by country. It does this by incrementing the count for 'impression_country_counts:<country_value>' in the task result store (redis hash). Depends on: **FilterClicks**
+
++ **impClickJoin**: Joins clicks with corresponding impression event using impEventId as the join key. Join is needed to pull dimensions not present in click event. Depends on: **FilterImps, FilterClicks**
+
++ **clickCountsByGender**: Generates click counts grouped by gender. It does this by incrementing the count for click_gender_counts:<gender_value> in the task result store (redis hash). Depends on: **impClickJoin**
+
++ **clickCountsByGender**: Generates click counts grouped by country. It does this by incrementing the count for click_country_counts:<country_value> in the task result store (redis hash). Depends on: **impClickJoin**
+
++ **report**: Reads from all aggregates generated by previous stages and prints them. Depends on: **impCountsByGender, impCountsByCountry, clickCountsByGender,clickCountsByGender**
+
+
+### Creating DAG
+
+Each stage is represented as a Node along with the upstream dependency and desired parallelism. Each stage is modelled as a resource in Helix using OnlineOffline state model. As part of Offline to Online transition, we watch the external view of upstream resources and wait for them to transition to online state. See Task.java for additional info.
+
+```
+
+ Dag dag = new Dag();
+ dag.addNode(new Node("filterImps", 10, ""));
+ dag.addNode(new Node("filterClicks", 5, ""));
+ dag.addNode(new Node("impClickJoin", 10, "filterImps,filterClicks"));
+ dag.addNode(new Node("impCountsByGender", 10, "filterImps"));
+ dag.addNode(new Node("impCountsByCountry", 10, "filterImps"));
+ dag.addNode(new Node("clickCountsByGender", 5, "impClickJoin"));
+ dag.addNode(new Node("clickCountsByCountry", 5, "impClickJoin"));
+ dag.addNode(new Node("report",1,"impCountsByGender,impCountsByCountry,clickCountsByGender,clickCountsByCountry"));
+
+
+```
+
+### DEMO
+
+In order to run the demo, use the following steps
+
+See http://redis.io/topics/quickstart on how to install redis server
+
+```
+
+Start redis e.g:
+./redis-server --port 6379
+
+git clone https://git-wip-us.apache.org/repos/asf/incubator-helix.git
+cd recipes/task-execution
+mvn clean install package -DskipTests
+cd target/task-execution-pkg/bin
+chmod +x task-execution-demo.sh
+./task-execution-demo.sh 2181 localhost 6379
+
+```
+
+```
+
+
+
+
+
+ +-----------------+ +----------------+
+ | filterImps | | filterClicks |
+ | (parallelism=10)| | (parallelism=5)|
+ +----------+-----++ +-------+--------+
+ | | | |
+ | | | |
+ | | | |
+ | | +------->--------v------------+
+ +--------------<-+ +------v-------+ | impClickJoin |
+ |impCountsByGender |impCountsByCountry | (parallelism=10) |
+ |(parallelism=10) |(parallelism=10) ++-------------------+-+
+ +-----------+--+ +---+----------+ | |
+ | | | |
+ | | | |
+ | | +--------v---------+ +-v-------------------+
+ | | |clickCountsByGender |clickCountsByCountry |
+ | | |(parallelism=5) | |(parallelism=5) |
+ | | +----+-------------+ +---------------------+
+ | | | |
+ | | | |
+ | | | |
+ +----->+-----+>-----------v----+<---------------+
+ | report |
+ |(parallelism=1) |
+ +-----------------------+
+
+```
+
+(credit for above ascii art: http://www.asciiflow.com)
+
+### OUTPUT
+
+```
+Done populating dummy data
+Executing filter task for filterImps_3 for impressions_demo
+Executing filter task for filterImps_2 for impressions_demo
+Executing filter task for filterImps_0 for impressions_demo
+Executing filter task for filterImps_1 for impressions_demo
+Executing filter task for filterImps_4 for impressions_demo
+Executing filter task for filterClicks_3 for clicks_demo
+Executing filter task for filterClicks_1 for clicks_demo
+Executing filter task for filterImps_8 for impressions_demo
+Executing filter task for filterImps_6 for impressions_demo
+Executing filter task for filterClicks_2 for clicks_demo
+Executing filter task for filterClicks_0 for clicks_demo
+Executing filter task for filterImps_7 for impressions_demo
+Executing filter task for filterImps_5 for impressions_demo
+Executing filter task for filterClicks_4 for clicks_demo
+Executing filter task for filterImps_9 for impressions_demo
+Running AggTask for impCountsByGender_3 for filtered_impressions_demo gender
+Running AggTask for impCountsByGender_2 for filtered_impressions_demo gender
+Running AggTask for impCountsByGender_0 for filtered_impressions_demo gender
+Running AggTask for impCountsByGender_9 for filtered_impressions_demo gender
+Running AggTask for impCountsByGender_1 for filtered_impressions_demo gender
+Running AggTask for impCountsByGender_4 for filtered_impressions_demo gender
+Running AggTask for impCountsByCountry_4 for filtered_impressions_demo country
+Running AggTask for impCountsByGender_5 for filtered_impressions_demo gender
+Executing JoinTask for impClickJoin_2
+Running AggTask for impCountsByCountry_3 for filtered_impressions_demo country
+Running AggTask for impCountsByCountry_1 for filtered_impressions_demo country
+Running AggTask for impCountsByCountry_0 for filtered_impressions_demo country
+Running AggTask for impCountsByCountry_2 for filtered_impressions_demo country
+Running AggTask for impCountsByGender_6 for filtered_impressions_demo gender
+Executing JoinTask for impClickJoin_1
+Executing JoinTask for impClickJoin_0
+Executing JoinTask for impClickJoin_3
+Running AggTask for impCountsByGender_8 for filtered_impressions_demo gender
+Executing JoinTask for impClickJoin_4
+Running AggTask for impCountsByGender_7 for filtered_impressions_demo gender
+Running AggTask for impCountsByCountry_5 for filtered_impressions_demo country
+Running AggTask for impCountsByCountry_6 for filtered_impressions_demo country
+Executing JoinTask for impClickJoin_9
+Running AggTask for impCountsByCountry_8 for filtered_impressions_demo country
+Running AggTask for impCountsByCountry_7 for filtered_impressions_demo country
+Executing JoinTask for impClickJoin_5
+Executing JoinTask for impClickJoin_6
+Running AggTask for impCountsByCountry_9 for filtered_impressions_demo country
+Executing JoinTask for impClickJoin_8
+Executing JoinTask for impClickJoin_7
+Running AggTask for clickCountsByCountry_1 for joined_clicks_demo country
+Running AggTask for clickCountsByCountry_0 for joined_clicks_demo country
+Running AggTask for clickCountsByCountry_2 for joined_clicks_demo country
+Running AggTask for clickCountsByCountry_3 for joined_clicks_demo country
+Running AggTask for clickCountsByGender_1 for joined_clicks_demo gender
+Running AggTask for clickCountsByCountry_4 for joined_clicks_demo country
+Running AggTask for clickCountsByGender_3 for joined_clicks_demo gender
+Running AggTask for clickCountsByGender_2 for joined_clicks_demo gender
+Running AggTask for clickCountsByGender_4 for joined_clicks_demo gender
+Running AggTask for clickCountsByGender_0 for joined_clicks_demo gender
+Running reports task
+Impression counts per country
+{CANADA=1940, US=1958, CHINA=2014, UNKNOWN=2022, UK=1946}
+Click counts per country
+{US=24, CANADA=14, CHINA=26, UNKNOWN=14, UK=22}
+Impression counts per gender
+{F=3325, UNKNOWN=3259, M=3296}
+Click counts per gender
+{F=33, UNKNOWN=32, M=35}
+
+
+```
+
http://git-wip-us.apache.org/repos/asf/incubator-helix/blob/80abba32/site-releases/0.6.1-incubating/src/site/markdown/tutorial_admin.md
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diff --git a/site-releases/0.6.1-incubating/src/site/markdown/tutorial_admin.md b/site-releases/0.6.1-incubating/src/site/markdown/tutorial_admin.md
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@@ -0,0 +1,167 @@
+<!---
+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.
+-->
+
+# Helix Tutorial: Admin Operations
+
+Helix provides interfaces for the operator to administer the cluster. For convenience, there is a command line interface as well as a REST interface.
+
+### Helix Admin operations
+
+First, make sure you get to the command-line tool, or include it in your shell PATH.
+
+```
+cd helix/helix-core/target/helix-core-pkg/bin
+```
+
+Get help
+
+```
+./helix-admin.sh --help
+```
+
+All other commands have this form:
+
+```
+./helix-admin.sh --zkSvr <ZookeeperServerAddress (Required)> <command> <parameters>
+```
+
+Now, here are the admin commands:
+
+Add a new cluster
+
+```
+ --addCluster <clusterName>
+```
+
+Add a new Instance to a cluster
+
+```
+ --addNode <clusterName> <InstanceAddress (host:port)>
+```
+
+Add a State model to a cluster
+_WE NEED A SPEC FOR A VALID STATE MODEL_
+
+```
+ --addStateModelDef <clusterName> <filename>>
+```
+
+Add a resource to a cluster
+
+```
+ --addResource <clusterName> <resourceName> <partitionNum> <stateModelRef> <mode (AUTO_REBALANCE|AUTO|CUSTOM)>
+```
+
+Upload an IdealState (Partition to Node Mapping)
+_WE NEED A SPEC FOR A VALID IDEAL STATE_
+
+```
+ --addIdealState <clusterName> <resourceName> <filename>
+```
+
+Delete a cluster
+
+```
+ --dropCluster <clusterName>
+```
+
+Delete a resource (drop an existing resource from a cluster)
+
+```
+ --dropResource <clusterName> <resourceName>
+```
+
+Drop an existing instance from a cluster
+
+```
+ --dropNode <clusterName> <InstanceAddress (host:port)>
+```
+
+Enable/disable the entire cluster. This will pause the controller, which means no transitions will be trigger, but the existing nodes in the cluster continue to function, but without any management by the controller.
+
+```
+ --enableCluster <clusterName> <true/false>
+```
+
+Enable/disable an instance. Useful to take a node out of the cluster for maintenance/upgrade.
+
+```
+ --enableInstance <clusterName> <InstanceName> <true/false>
+```
+
+Enable/disable a partition
+
+```
+ --enablePartition <clusterName> <instanceName> <resourceName> <partitionName> <true/false>
+```
+
+Query info of a cluster
+
+```
+ --listClusterInfo <clusterName>
+```
+
+List existing clusters (remember, Helix can manage multiple clusters)
+
+```
+ --listClusters
+```
+
+Query info of a single Instance in a cluster
+
+```
+ --listInstanceInfo <clusterName> <InstanceName>
+```
+
+List instances in a cluster
+
+```
+ --listInstances <clusterName>
+```
+
+Query info of a partition
+
+```
+ --listPartitionInfo <clusterName> <resourceName> <partitionName>
+```
+
+Query info of a resource
+
+```
+ --listResourceInfo <clusterName> <resourceName>
+```
+
+List resources hosted in a cluster
+
+```
+ --listResources <clusterName>
+```
+
+Query info of a state model in a cluster
+
+```
+ --listStateModel <clusterName> <stateModelName>
+```
+
+Query info of state models in a cluster
+
+```
+ --listStateModels <clusterName>
+```
+
http://git-wip-us.apache.org/repos/asf/incubator-helix/blob/80abba32/site-releases/0.6.1-incubating/src/site/markdown/tutorial_controller.md
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diff --git a/site-releases/0.6.1-incubating/src/site/markdown/tutorial_controller.md b/site-releases/0.6.1-incubating/src/site/markdown/tutorial_controller.md
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@@ -0,0 +1,90 @@
+<!---
+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.
+-->
+
+# Helix Tutorial: Controller
+
+Next, let\'s implement the controller. This is the brain of the cluster. Helix makes sure there is exactly one active controller running the cluster.
+
+### Start the Helix agent
+
+
+It requires the following parameters:
+
+* clusterName: A logical name to represent the group of nodes
+* instanceName: A logical name of the process creating the manager instance. Generally this is host:port.
+* instanceType: Type of the process. This can be one of the following types, in this case use CONTROLLER:
+ * CONTROLLER: Process that controls the cluster, any number of controllers can be started but only one will be active at any given time.
+ * PARTICIPANT: Process that performs the actual task in the distributed system.
+ * SPECTATOR: Process that observes the changes in the cluster.
+ * ADMIN: To carry out system admin actions.
+* zkConnectString: Connection string to Zookeeper. This is of the form host1:port1,host2:port2,host3:port3.
+
+```
+ manager = HelixManagerFactory.getZKHelixManager(clusterName,
+ instanceName,
+ instanceType,
+ zkConnectString);
+```
+
+### Controller Code
+
+The Controller needs to know about all changes in the cluster. Helix takes care of this with the default implementation.
+If you need additional functionality, see GenericHelixController on how to configure the pipeline.
+
+```
+ manager = HelixManagerFactory.getZKHelixManager(clusterName,
+ instanceName,
+ InstanceType.CONTROLLER,
+ zkConnectString);
+ manager.connect();
+ GenericHelixController controller = new GenericHelixController();
+ manager.addConfigChangeListener(controller);
+ manager.addLiveInstanceChangeListener(controller);
+ manager.addIdealStateChangeListener(controller);
+ manager.addExternalViewChangeListener(controller);
+ manager.addControllerListener(controller);
+```
+The snippet above shows how the controller is started. You can also start the controller using command line interface.
+
+```
+cd helix/helix-core/target/helix-core-pkg/bin
+./run-helix-controller.sh --zkSvr <Zookeeper ServerAddress (Required)> --cluster <Cluster name (Required)>
+```
+
+### Controller deployment modes
+
+Helix provides multiple options to deploy the controller.
+
+#### STANDALONE
+
+The Controller can be started as a separate process to manage a cluster. This is the recommended approach. However, since one controller can be a single point of failure, multiple controller processes are required for reliability. Even if multiple controllers are running, only one will be actively managing the cluster at any time and is decided by a leader-election process. If the leader fails, another leader will take over managing the cluster.
+
+Even though we recommend this method of deployment, it has the drawback of having to manage an additional service for each cluster. See Controller As a Service option.
+
+#### EMBEDDED
+
+If setting up a separate controller process is not viable, then it is possible to embed the controller as a library in each of the participants.
+
+#### CONTROLLER AS A SERVICE
+
+One of the cool feature we added in Helix was to use a set of controllers to manage a large number of clusters.
+
+For example if you have X clusters to be managed, instead of deploying X*3 (3 controllers for fault tolerance) controllers for each cluster, one can deploy just 3 controllers. Each controller can manage X/3 clusters. If any controller fails, the remaining two will manage X/2 clusters.
+
+
http://git-wip-us.apache.org/repos/asf/incubator-helix/blob/80abba32/site-releases/0.6.1-incubating/src/site/markdown/tutorial_health.md
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diff --git a/site-releases/0.6.1-incubating/src/site/markdown/tutorial_health.md b/site-releases/0.6.1-incubating/src/site/markdown/tutorial_health.md
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@@ -0,0 +1,42 @@
+<!---
+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.
+-->
+
+# Helix Tutorial: Customizing Health Checks
+
+In this chapter, we\'ll learn how to customize the health check, based on metrics of your distributed system.
+
+### Health Checks
+
+Note: _this in currently in development mode, not yet ready for production._
+
+Helix provides the ability for each node in the system to report health metrics on a periodic basis.
+
+Helix supports multiple ways to aggregate these metrics:
+
+* SUM
+* AVG
+* EXPONENTIAL DECAY
+* WINDOW
+
+Helix persists the aggregated value only.
+
+Applications can define a threshold on the aggregate values according to the SLAs, and when the SLA is violated Helix will fire an alert.
+Currently Helix only fires an alert, but in a future release we plan to use these metrics to either mark the node dead or load balance the partitions.
+This feature will be valuable for distributed systems that support multi-tenancy and have a large variation in work load patterns. In addition, this can be used to detect skewed partitions (hotspots) and rebalance the cluster.
+
http://git-wip-us.apache.org/repos/asf/incubator-helix/blob/80abba32/site-releases/0.6.1-incubating/src/site/markdown/tutorial_messaging.md
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diff --git a/site-releases/0.6.1-incubating/src/site/markdown/tutorial_messaging.md b/site-releases/0.6.1-incubating/src/site/markdown/tutorial_messaging.md
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+<!---
+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.
+-->
+
+# Helix Tutorial: Messaging
+
+In this chapter, we\'ll learn about messaging, a convenient feature in Helix for sending messages between nodes of a cluster. This is an interesting feature which is quite useful in practice. It is common that nodes in a distributed system require a mechanism to interact with each other.
+
+### Example: Bootstrapping a Replica
+
+Consider a search system where the index replica starts up and it does not have an index. A typical solution is to get the index from a common location, or to copy the index from another replica.
+
+Helix provides a messaging api for intra-cluster communication between nodes in the system. Helix provides a mechanism to specify the message recipient in terms of resource, partition, and state rather than specifying hostnames. Helix ensures that the message is delivered to all of the required recipients. In this particular use case, the instance can specify the recipient criteria as all replicas of the desired partition to bootstrap.
+Since Helix is aware of the global state of the system, it can send the message to appropriate nodes. Once the nodes respond, Helix provides the bootstrapping replica with all the responses.
+
+This is a very generic api and can also be used to schedule various periodic tasks in the cluster, such as data backups, log cleanup, etc.
+System Admins can also perform ad-hoc tasks, such as on-demand backups or a system command (such as rm -rf ;) across all nodes of the cluster
+
+```
+ ClusterMessagingService messagingService = manager.getMessagingService();
+
+ // Construct the Message
+ Message requestBackupUriRequest = new Message(
+ MessageType.USER_DEFINE_MSG, UUID.randomUUID().toString());
+ requestBackupUriRequest
+ .setMsgSubType(BootstrapProcess.REQUEST_BOOTSTRAP_URL);
+ requestBackupUriRequest.setMsgState(MessageState.NEW);
+
+ // Set the Recipient criteria: all nodes that satisfy the criteria will receive the message
+ Criteria recipientCriteria = new Criteria();
+ recipientCriteria.setInstanceName("%");
+ recipientCriteria.setRecipientInstanceType(InstanceType.PARTICIPANT);
+ recipientCriteria.setResource("MyDB");
+ recipientCriteria.setPartition("");
+
+ // Should be processed only by process(es) that are active at the time of sending the message
+ // This means if the recipient is restarted after message is sent, it will not be processe.
+ recipientCriteria.setSessionSpecific(true);
+
+ // wait for 30 seconds
+ int timeout = 30000;
+
+ // the handler that will be invoked when any recipient responds to the message.
+ BootstrapReplyHandler responseHandler = new BootstrapReplyHandler();
+
+ // this will return only after all recipients respond or after timeout
+ int sentMessageCount = messagingService.sendAndWait(recipientCriteria,
+ requestBackupUriRequest, responseHandler, timeout);
+```
+
+See HelixManager.DefaultMessagingService in [Javadocs](./apidocs/reference/org/apache/helix/messaging/DefaultMessagingService.html) for more info.
+
http://git-wip-us.apache.org/repos/asf/incubator-helix/blob/80abba32/site-releases/0.6.1-incubating/src/site/markdown/tutorial_participant.md
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diff --git a/site-releases/0.6.1-incubating/src/site/markdown/tutorial_participant.md b/site-releases/0.6.1-incubating/src/site/markdown/tutorial_participant.md
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@@ -0,0 +1,100 @@
+<!---
+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.
+-->
+
+# Helix Tutorial: Participant
+
+In this chapter, we\'ll learn how to implement a PARTICIPANT, which is a primary functional component of a distributed system.
+
+
+### Start the Helix agent
+
+The Helix agent is a common component that connects each system component with the controller.
+
+It requires the following parameters:
+
+* clusterName: A logical name to represent the group of nodes
+* instanceName: A logical name of the process creating the manager instance. Generally this is host:port.
+* instanceType: Type of the process. This can be one of the following types, in this case, use PARTICIPANT
+ * CONTROLLER: Process that controls the cluster, any number of controllers can be started but only one will be active at any given time.
+ * PARTICIPANT: Process that performs the actual task in the distributed system.
+ * SPECTATOR: Process that observes the changes in the cluster.
+ * ADMIN: To carry out system admin actions.
+* zkConnectString: Connection string to Zookeeper. This is of the form host1:port1,host2:port2,host3:port3.
+
+After the Helix manager instance is created, only thing that needs to be registered is the state model factory.
+The methods of the State Model will be called when controller sends transitions to the Participant. In this example, we'll use the OnlineOffline factory. Other options include:
+
+* MasterSlaveStateModelFactory
+* LeaderStandbyStateModelFactory
+* BootstrapHandler
+
+
+```
+ manager = HelixManagerFactory.getZKHelixManager(clusterName,
+ instanceName,
+ InstanceType.PARTICIPANT,
+ zkConnectString);
+ StateMachineEngine stateMach = manager.getStateMachineEngine();
+
+ //create a stateModelFactory that returns a statemodel object for each partition.
+ stateModelFactory = new OnlineOfflineStateModelFactory();
+ stateMach.registerStateModelFactory(stateModelType, stateModelFactory);
+ manager.connect();
+```
+
+Helix doesn\'t know what it means to change from OFFLIN\-\-\>ONLINE or ONLINE\-\-\>OFFLINE. The following code snippet shows where you insert your system logic for these two state transitions.
+
+```
+public class OnlineOfflineStateModelFactory extends
+ StateModelFactory<StateModel> {
+ @Override
+ public StateModel createNewStateModel(String stateUnitKey) {
+ OnlineOfflineStateModel stateModel = new OnlineOfflineStateModel();
+ return stateModel;
+ }
+ @StateModelInfo(states = "{'OFFLINE','ONLINE'}", initialState = "OFFINE")
+ public static class OnlineOfflineStateModel extends StateModel {
+
+ @Transition(from = "OFFLINE", to = "ONLINE")
+ public void onBecomeOnlineFromOffline(Message message,
+ NotificationContext context) {
+
+ System.out.println("OnlineOfflineStateModel.onBecomeOnlineFromOffline()");
+
+ ////////////////////////////////////////////////////////////////////////////////////////////////
+ // Application logic to handle transition //
+ // For example, you might start a service, run initialization, etc //
+ ////////////////////////////////////////////////////////////////////////////////////////////////
+ }
+
+ @Transition(from = "ONLINE", to = "OFFLINE")
+ public void onBecomeOfflineFromOnline(Message message,
+ NotificationContext context) {
+
+ System.out.println("OnlineOfflineStateModel.onBecomeOfflineFromOnline()");
+
+ ////////////////////////////////////////////////////////////////////////////////////////////////
+ // Application logic to handle transition //
+ // For example, you might shutdown a service, log this event, or change monitoring settings //
+ ////////////////////////////////////////////////////////////////////////////////////////////////
+ }
+ }
+}
+```
+
http://git-wip-us.apache.org/repos/asf/incubator-helix/blob/80abba32/site-releases/0.6.1-incubating/src/site/markdown/tutorial_propstore.md
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diff --git a/site-releases/0.6.1-incubating/src/site/markdown/tutorial_propstore.md b/site-releases/0.6.1-incubating/src/site/markdown/tutorial_propstore.md
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+<!---
+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.
+-->
+
+# Helix Tutorial: Application Property Store
+
+In this chapter, we\'ll learn how to use the application property store.
+
+### Property Store
+
+It is common that an application needs support for distributed, shared data structures. Helix uses Zookeeper to store the application data and hence provides notifications when the data changes.
+
+While you could use Zookeeper directly, Helix supports caching the data and a write-through cache. This is far more efficient than reading from Zookeeper for every access.
+
+See [HelixManager.getHelixPropertyStore](./apidocs/reference/org/apache/helix/store/package-summary.html) for details.