Project: Druid (App Definition and Development / Database)
File: tutorial-batch-hadoop.md

id: tutorial-batch-hadoop title: Load batch data using Apache Hadoop sidebar_label: Load from Apache Hadoop <!-- ~ 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. --> 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 using Druid's native batch ingestion system and are using the automatic single-machine configuration as described in the . This tutorial requires 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": ```bash 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: ```bash mkdir -p /tmp/shared mkdir -p /tmp/shared/hadoop_xml ``` 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. ```bash docker run -it -h druid-hadoop-demo --name druid-hadoop-demo -p 2049:2049 -p 2122:2122 -p 8020:8020 -p 8021:8021 -p 8030:8030 -p 8031:8031 -p 8032:8032 -p 8033:8033 -p 8040:8040 -p 8042:8042 -p 8088:8088 -p 8443:8443 -p 9000:9000 -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: ```bash Starting sshd: [ OK ] 18/07/26 17:27:15 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable Starting namenodes on [druid-hadoop-demo] druid-hadoop-demo: starting namenode, logging to /usr/local/hadoop/logs/hadoop-root-namenode-druid-hadoop-demo.out localhost: starting datanode, logging to /usr/local/hadoop/logs/hadoop-root-datanode-druid-hadoop-demo.out Starting secondary namenodes [0.0.0.0] 0.0.0.0: starting secondarynamenode, logging to /usr/local/hadoop/logs/hadoop-root-secondarynamenode-druid-hadoop-demo.out 18/07/26 17:27:31 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your

using builtin-java classes where applicable starting yarn daemons starting resourcemanager, logging to /usr/local/hadoop/logs/yarn--resourcemanager-druid-hadoop-demo.out localhost: starting nodemanager, logging to /usr/local/hadoop/logs/yarn-root-nodemanager-druid-hadoop-demo.out starting historyserver, logging to /usr/local/hadoop/logs/mapred--historyserver-druid-hadoop-demo.out 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 ``` From the apache-druid-{{DRUIDVERSION}} package root on the host, copy the `quickstart/tutorial/wikiticker-2015-09-12-sampled.json.gz` sample data to the shared folder: ```bash cp quickstart/tutorial/wikiticker-2015-09-12-sampled.json.gz /tmp/shared/wikiticker-2015-09-12-sampled.json.gz ``` In the Hadoop container's shell, run the following commands to setup the HDFS directories needed by this tutorial and copy the input data to HDFS. ```bash cd /usr/local/hadoop/bin ./hdfs dfs -mkdir /druid ./hdfs dfs -mkdir /druid/segments ./hdfs dfs -mkdir /quickstart ./hdfs dfs -mkdir /user ./hdfs dfs -chmod 777 /druid ./hdfs dfs -chmod 777 /druid/segments ./hdfs dfs -chmod 777 /quickstart ./hdfs dfs -chmod -R 777 /tmp ./hdfs dfs -chmod -R 777 /user ./hdfs dfs -put /shared/wikiticker-2015-09-12-sampled.json.gz /quickstart/wikiticker-2015-09-12-sampled.json.gz ``` If you encounter namenode errors when running this command, the Hadoop container may not be finished initializing. When this occurs, wait a couple of minutes and retry the commands. Some 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: ```bash cp /usr/local/hadoop/etc/hadoop/*.xml /shared/hadoop_xml ``` From the host machine, run the following, where {PATHTODRUID} is replaced by the path to the Druid package. ```bash mkdir -p {PATHTODRUID}/conf/druid/single-server/micro-quickstart/_common/hadoop-xml cp /tmp/shared/hadoopxml/*.xml {PATHTODRUID}/conf/druid/single-server/micro-quickstart/common/hadoop-xml/ ``` In your favorite text editor, open `conf/druid/auto/_common/common.runtime.properties`, and make the following edits: ``` druid.storage.type=hdfs druid.storage.storageDirectory=/druid/segments ``` ``` 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 the `bin/start-druid` script, and re-run it to bring the Druid services back up. 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: ```bash bin/post-index-task --file quickstart/tutorial/wikipedia-index-hadoop3.json --url http://localhost:8081 ``` After the data load is complete, please follow the to run some example queries on the newly loaded data. This tutorial is only meant to be used together with the . If you wish to go through any of the other tutorials, you will need to: Shut down the cluster and reset the cluster state by removing the contents of the `var` directory under the druid package. Revert the deep storage and task storage config back to local types in `conf/druid/auto/_common/common.runtime.properties` Restart the cluster This 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: ``` druid.storage.type=local druid.storage.storageDirectory=var/druid/segments druid.indexer.logs.type=file druid.indexer.logs.directory=var/druid/indexing-logs ``` For more information on loading batch data with Hadoop, please see .