:::caution[Deprecated]
Hadoop-based ingestion is deprecated. For more information, see the upgrade notes.
:::
This tutorial shows you how to load data files into Apache Druid using a remote Hadoop cluster.
For this tutorial, we‘ll assume that you’ve already completed the previous batch ingestion tutorial using Druid's native batch ingestion system and are using the automatic single-machine configuration as described in the quickstart.
This tutorial requires Docker to be installed on the tutorial machine.
Once the Docker install is complete, please proceed to the next steps in the tutorial.
For this tutorial, we‘ve provided a Dockerfile for a Hadoop 3.3.6 cluster, which we’ll use to run the batch indexing task.
This Dockerfile and related files are located at quickstart/tutorial/hadoop/docker.
From the apache-druid-{{DRUIDVERSION}} package root, run the following commands to build a Docker image named “druid-hadoop-demo” with version tag “3.3.6”:
cd quickstart/tutorial/hadoop/docker docker build -t druid-hadoop-demo:3.3.6 .
This will start building the Hadoop image. Once the image build is done, you should see the message Successfully tagged druid-hadoop-demo:3.3.6 printed to the console.
We'll need a shared folder between the host and the Hadoop container for transferring some files.
Let's create some folders under /tmp, we will use these later when starting the Hadoop container:
mkdir -p /tmp/shared
On the host machine, add the following entry to /etc/hosts:
127.0.0.1 druid-hadoop-demo
Once the /tmp/shared folder has been created and the etc/hosts entry has been added, run the following command to start the Hadoop container.
docker run -it -h druid-hadoop-demo --name druid-hadoop-demo -p 2049:2049 -p 2122:2122 -p 8020-8042:8020-8042 -p 8088:8088 -p 8443:8443 -p 9000:9000 -p 9820:9820 -p 9860-9880:9860-9880 -p 10020:10020 -p 19888:19888 -p 34455:34455 -p 49707:49707 -p 50010:50010 -p 50020:50020 -p 50030:50030 -p 50060:50060 -p 50070:50070 -p 50075:50075 -p 50090:50090 -p 51111:51111 -v /tmp/shared:/shared druid-hadoop-demo:3.3.6 /etc/bootstrap.sh -bash
Once the container is started, your terminal will attach to a bash shell running inside the container:
Starting namenodes on [druid-hadoop-demo] Starting datanodes Starting secondary namenodes [druid-hadoop-demo] WARNING: YARN_CONF_DIR has been replaced by HADOOP_CONF_DIR. Using value of YARN_CONF_DIR. WARNING: YARN_OPTS has been replaced by HADOOP_OPTS. Using value of YARN_OPTS. Starting resourcemanager WARNING: YARN_OPTS has been replaced by HADOOP_OPTS. Using value of YARN_OPTS. Starting nodemanagers WARNING: YARN_OPTS has been replaced by HADOOP_OPTS. Using value of YARN_OPTS. localhost: WARNING: YARN_OPTS has been replaced by HADOOP_OPTS. Using value of YARN_OPTS. WARNING: YARN_CONF_DIR has been replaced by HADOOP_CONF_DIR. Using value of YARN_CONF_DIR. WARNING: YARN_OPTS has been replaced by HADOOP_OPTS. Using value of YARN_OPTS. WARNING: Use of this script to start the MR JobHistory daemon is deprecated. WARNING: Attempting to execute replacement "mapred --daemon start" instead. * initialize hdfs for first run bash-4.1#
The Unable to load native-hadoop library for your platform... using builtin-java classes where applicable warning messages can be safely ignored.
To open another shell to the Hadoop container, run the following command:
docker exec -it druid-hadoop-demo bash
The startup script bootstrap.sh:
hadoop-conf.tgzSome additional steps are needed to configure the Druid cluster for Hadoop batch indexing.
From the Hadoop container's shell, run the following command to copy the Hadoop .xml configuration files to the shared folder:
cp /usr/local/hadoop/etc/hadoop/*.xml /shared/hadoop_xml
From the host machine, run the following, where PATH_TO_DRUID is replaced by the path to the Druid package.
cd $PATH_TO_DRUID mkdir -p conf/druid/single-server/micro-quickstart/_common/hadoop-xml tar xzf /tmp/shared/hadoop-conf.tgz -C conf/druid/single-server/micro-quickstart/_common/hadoop-xml
In your favorite text editor, open conf/druid/single-server/micro-quickstart/_common/common.runtime.properties, and make the following edits:
# # Deep storage # # For local disk (only viable in a cluster if this is a network mount): #druid.storage.type=local #druid.storage.storageDirectory=var/druid/segments # For HDFS: druid.storage.type=hdfs druid.storage.storageDirectory=/druid/segments
# # Indexing service logs # # For local disk (only viable in a cluster if this is a network mount): #druid.indexer.logs.type=file #druid.indexer.logs.directory=var/druid/indexing-logs # For HDFS: druid.indexer.logs.type=hdfs druid.indexer.logs.directory=/druid/indexing-logs
Once the Hadoop .xml files have been copied to the Druid cluster and the segment/log storage configuration has been updated to use HDFS, the Druid cluster needs to be restarted for the new configurations to take effect.
If the cluster is still running, CTRL-C to terminate it if running - and start it with:
bin/start-druid -c conf/druid/single-server/micro-quickstart
We've included a sample of Wikipedia edits from September 12, 2015 to get you started.
To load this data into Druid, you can submit an ingestion task pointing to the file. We've included a task that loads the wikiticker-2015-09-12-sampled.json.gz file included in the archive.
Let's submit the wikipedia-index-hadoop3.json task:
bin/post-index-task --file quickstart/tutorial/wikipedia-index-hadoop3.json --url http://localhost:8081
After the data load is complete, please follow the query tutorial to run some example queries on the newly loaded data.
This tutorial is only meant to be used together with the query tutorial.
If you wish to go through any of the other tutorials, you will need to:
var directory under the druid package.conf/druid/single-server/micro-quickstart/_common/common.runtime.propertiesThis is necessary because the other ingestion tutorials will write to the same “wikipedia” datasource, and later tutorials expect the cluster to use local deep storage.
Example reverted config:
# # Deep storage # # For local disk (only viable in a cluster if this is a network mount): druid.storage.type=local druid.storage.storageDirectory=var/druid/segments # For HDFS: #druid.storage.type=hdfs #druid.storage.storageDirectory=/druid/segments # # Indexing service logs # # For local disk (only viable in a cluster if this is a network mount): druid.indexer.logs.type=file druid.indexer.logs.directory=var/druid/indexing-logs # For HDFS: #druid.indexer.logs.type=hdfs #druid.indexer.logs.directory=/druid/indexing-logs
For more information on loading batch data with Hadoop, please see the Hadoop batch ingestion documentation.