- #INSTALL APACHE SPARK DOCKER IMAGE IN WINDOWS HOW TO#
- #INSTALL APACHE SPARK DOCKER IMAGE IN WINDOWS PROFESSIONAL#
Docker Hub is like an app store for Docker images.
This service defintion refers to where the image can be found on Docker Hub. I sometimes think of the Docker image as an installation file and the container is the actual application running. Docker images are like blueprints for Docker containers. The namenode service is based on an image prepared by Big Data Europe. That’s the version of the docker-compose file and 3 is the latest. CORE_CONF_fs_defaultFS=hdfs://namenode:8020 So here is a simplified example of one service I took from the Hadoop docker-compose.yml: version: "3" You can skip this section if you just want to run the Docker Hadoop environment and don’t really care how. Turns out that when you don’t define any network in docker-compose, the services are all part of the same network that Docker creates automatically. But after removing these Spark networks it worked much better. I’ve spent countless hours combining docker-compose services and trying to get it to work and not understanding why it would not. But from the docker-compose.yml file there can be references to shell scripts to run or files with environmental settings. And it is defined in a docker-compose.yml file. Perfect to create clusters, like a Hadoop cluster with a namenode and datanode. But I had no idea what the principles of this thing were.ĭocker-compose is a way to quickly create a multi-container environment. Now when you’ve worked with docker-compose for a while, you might think “how hard could it be?”.
It looks like sdesliva26’s version but it’s not that one either.)Īnyhow, I learned gradually I needed to combine the docker-compose.yml files somehow. And I can’t remember where I got it from. One that had a spark-net network defined. I thought I used Big Data Europe’s Spark setup, but it looks like I got a different one. (There was a reason for that and I just found out why.
#INSTALL APACHE SPARK DOCKER IMAGE IN WINDOWS HOW TO#
Their Spark version is also pretty much up to date.īut how to get the Spark nodes to connect to the Hadoop nodes? I could not get the docker-composed Hadoop nodes and the docker-composed Spark nodes to speak to each other. But it turned out that Big Data Europe has a Docker environment with Hadoop 3.2.1 and it’s only 9 months old. The quest for a lightweight and up to date Hadoop clusterĪfter searching and finding all kinds of Hadoop on Docker images, I found most of them where old. And off I went on a quest for lightweight Hadoop cluster on Docker. My thoughts were: Simpler? Yes! Old version? No way! We’re not going to start a new course with a 5 year old Hadoop version. Could we use an simpler (and much older) Hadoop implementation instead? So for the Hadoop module I suggested using the Cloudera sandbox on Docker, because our practice environments work on Docker and the Cloudera sandbox has it all.Īnd at one moment my colleague Hugo Koopmans told me we had a problem: building the Cloudera sandbox on his laptop took way too long and required way too much memory. You have to try the products/methods yourself. We’re not just going to bombard you with theory. Now our course has an important practical aspect.
It is a course where you learn all aspects we could think of of being a data engineer: the cool big data stuff, but also how data warehousing works and how it all can work together.
#INSTALL APACHE SPARK DOCKER IMAGE IN WINDOWS PROFESSIONAL#
We at DIKW are working on a Certified Data Engineering Professional course. You can find the necessary files for it here: TL DR: I made a Docker compose that runs Hadoop, Spark and Hive in a multi-container environment.