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Tutorial: The Druid Cluster
Welcome back! In our first tutorial, we introduced you to the most basic Druid setup: a single realtime node. We streamed in some data and queried it. Realtime nodes collect very recent data and periodically hand that data off to the rest of the Druid cluster. Some questions about the architecture must naturally come to mind. What does the rest of Druid cluster look like?
This tutorial will hopefully answer these questions!
In this tutorial, we will set up other types of Druid nodes and external dependencies for a fully functional Druid cluster. The architecture of Druid is very much like the Megazord from the popular 90s show Mighty Morphin' Power Rangers. Each Druid node has a specific purpose and the nodes come together to form a fully functional system.
Downloading Druid
If you followed the first tutorial, you should already have Druid downloaded. If not, let's go back and do that first.
You can download the latest version of druid here
and untar the contents within by issuing:
tar -zxvf druid-services-*-bin.tar.gz
cd druid-services-*
You can also Build From Source.
External Dependencies
Druid requires 3 external dependencies. A "deep" storage that acts as a backup data repository, a relational database such as MySQL to hold configuration and metadata information, and Apache Zookeeper for coordination among different pieces of the cluster.
For deep storage, we will use local disk in this tutorial.
Set up Metadata storage
- If you don't already have it, download MySQL Community Server here: http://dev.mysql.com/downloads/mysql/.
- Install MySQL.
- Create a druid user and database.
mysql -u root
GRANT ALL ON druid.* TO 'druid'@'localhost' IDENTIFIED BY 'diurd';
CREATE database druid;
Set up Zookeeper
Download zookeeper from [http://www.apache.org/dyn/closer.cgi/zookeeper/](http://www.apache.org/dyn/closer.cgi/zookeeper/)
Install zookeeper.
e.g.
curl http://www.gtlib.gatech.edu/pub/apache/zookeeper/zookeeper-3.4.6/zookeeper-3.4.6.tar.gz -o zookeeper-3.4.6.tar.gz
tar xzf zookeeper-3.4.6.tar.gz
cd zookeeper-3.4.6
cp conf/zoo_sample.cfg conf/zoo.cfg
./bin/zkServer.sh start
cd ..
The Data
Similar to the first tutorial, the data we will be loading is based on edits that have occurred on Wikipedia. Every time someone edits a page in Wikipedia, metadata is generated about the editor and edited page. Druid collects each individual event and packages them together in a container known as a segment. Segments contain data over some span of time. We've prebuilt a segment for this tutorial and will cover making your own segments in other pages.The segment we are going to work with has the following format:
Dimensions (things to filter on):
"page"
"language"
"user"
"unpatrolled"
"newPage"
"robot"
"anonymous"
"namespace"
"continent"
"country"
"region"
"city"
Metrics (things to aggregate over):
"count"
"added"
"delta"
"deleted"
The Cluster
Before we get started, let's make sure we have configs in the config directory for our various nodes. Issue the following from the Druid home directory:
ls config
If you are interested in learning more about Druid configuration files, check out this link. Many aspects of Druid are customizable. For the purposes of this tutorial, we are going to use default values for most things.
Common Configuration
There are a couple of cluster wide configuration options we have to define. The common/cluster configuration files should exist under:
config/_common
In the directory, there should be a common.runtime.properties
file with the following contents:
# Extensions
druid.extensions.coordinates=["io.druid.extensions:druid-examples","io.druid.extensions:druid-kafka-seven","io.druid.extensions:mysql-metadata-storage"]
# Zookeeper
druid.zk.service.host=localhost
# Metadata Storage
druid.metadata.storage.type=mysql
druid.metadata.storage.connector.connectURI=jdbc\:mysql\://localhost\:3306/druid
druid.metadata.storage.connector.user=druid
druid.metadata.storage.connector.password=diurd
# Deep storage
druid.storage.type=local
druid.storage.storage.storageDirectory=/tmp/druid/localStorage
# Cache (we use a simple 10mb heap-based local cache on the broker)
druid.cache.type=local
druid.cache.sizeInBytes=10000000
# Indexing service discovery
druid.selectors.indexing.serviceName=overlord
# Monitoring (disabled for examples)
# druid.monitoring.monitors=["com.metamx.metrics.SysMonitor","com.metamx.metrics.JvmMonitor"]
# Metrics logging (disabled for examples)
druid.emitter=noop
In this file we define our external dependencies and cluster wide configs.
Start a Coordinator Node
Coordinator nodes are in charge of load assignment and distribution. Coordinator nodes monitor the status of the cluster and command historical nodes to assign and drop segments. For more information about coordinator nodes, see here.
The coordinator config file should already exist at:
config/coordinator
In the directory, there should be a runtime.properties
file with the following contents:
druid.host=localhost
druid.port=8082
druid.service=coordinator
# The coordinator begins assignment operations after the start delay.
# We override the default here to start things up faster for examples.
druid.coordinator.startDelay=PT70s
To start the coordinator node:
java -Xmx256m -Duser.timezone=UTC -Dfile.encoding=UTF-8 -classpath lib/*:config/coordinator io.druid.cli.Main server coordinator
Start a Historical Node
Historical nodes are the workhorses of a cluster and are in charge of loading historical segments and making them available for queries. Realtime nodes hand off segments to historical nodes. For more information about Historical nodes, see here.
The historical config file should exist at:
config/historical
In the directory we just created, we should have the file runtime.properties
with the following contents:
druid.host=localhost
druid.port=8081
druid.service=historical
# We can only 1 scan segment in parallel with these configs.
# Our intermediate buffer is also very small so longer topNs will be slow.
druid.processing.buffer.sizeBytes=100000000
druid.processing.numThreads=1
druid.segmentCache.locations=[{"path": "/tmp/druid/indexCache", "maxSize"\: 10000000000}]
druid.server.maxSize=10000000000
To start the historical node:
java -Xmx256m -Duser.timezone=UTC -Dfile.encoding=UTF-8 -classpath lib/*:config/historical io.druid.cli.Main server historical
Start a Broker Node
Broker nodes are responsible for figuring out which historical and/or realtime nodes correspond to which queries. They also merge partial results from these nodes in a scatter/gather fashion. For more information about Broker nodes, see here.
The broker config file should exist at:
config/broker
In the directory, there should be a runtime.properties
file with the following contents:
druid.host=localhost
druid.port=8080
druid.service=broker
druid.broker.cache.useCache=true
druid.broker.cache.populateCache=true
# Bump these up only for faster nested groupBy
druid.processing.buffer.sizeBytes=100000000
druid.processing.numThreads=1
To start the broker node:
java -Xmx256m -Duser.timezone=UTC -Dfile.encoding=UTF-8 -classpath lib/*:config/broker io.druid.cli.Main server broker
Start a Realtime Node
Our goal is to ingest some data and hand-off that data to the rest of our Druid cluster. To accomplish this goal, we need to make some small configuration changes.
In your favorite editor, open up:
examples/wikipedia/wikipedia_realtime.spec
We need to change some configuration in order to force hand-off faster.
Let's change:
"segmentGranularity": "HOUR",
to
"segmentGranularity": "FIVE_MINUTE",
and
"intermediatePersistPeriod": "PT10m",
"windowPeriod": "PT10m",
to
"intermediatePersistPeriod": "PT3m",
"windowPeriod": "PT1m",
Now we should be handing off segments every 6 minutes or so.
To start the realtime node that was used in our first tutorial, you simply have to issue:
java -Xmx256m -Duser.timezone=UTC -Dfile.encoding=UTF-8 -Ddruid.realtime.specFile=examples/wikipedia/wikipedia_realtime.spec -classpath lib/*:config/realtime io.druid.cli.Main server realtime
The configurations are located in config/realtime/runtime.properties
and should contain the following:
druid.host=localhost
druid.port=8083
druid.service=realtime
# We can only 1 scan segment in parallel with these configs.
# Our intermediate buffer is also very small so longer topNs will be slow.
druid.processing.buffer.sizeBytes=100000000
druid.processing.numThreads=1
# Enable Real monitoring
# druid.monitoring.monitors=["com.metamx.metrics.SysMonitor","com.metamx.metrics.JvmMonitor","io.druid.segment.realtime.RealtimeMetricsMonitor"]
Once the real-time node starts up, it should begin ingesting data and handing that data off to the rest of the Druid cluster. You can use a web UI located at coordinator_ip:port to view the status of data being loaded. Once data is handed off from the real-time nodes to historical nodes, the historical nodes should begin serving segments.
At any point during ingestion, we can query for data. The queries should span across both real-time and historical nodes. For more information on querying, see this link.
Next Steps
If you are interested in how data flows through the different Druid components, check out the Druid data flow architecture. Now that you have an understanding of what the Druid cluster looks like, why not load some of your own data? Check out the next tutorial section for more info!