A Smooth Sea Never Made a Skillful Sailor

I'm a long-time user of Apache Bigtop. My experience with Hadoop and Bigtop predates Ambari. I started using Bigtop with version 0.3. I remember pulling bigtop.repo file and install Hadoop, Pig and Hive for some quick development. Bigtop makes it convenient and easy. Bigtop has matured since then and there are now multiple ways of deployment. There's still a way to pull repo and install manually but there's better ways now with Vagrant and Docker. I won't rehash how to deploy Bigtop using Docker as it was beautifly described here . Admittedly, I'm running it on Mac and was not able to provision a cluster using Docker. I did not try with non-OSX. This post is about Vagrant. Let's get started: Install VirtualBox and Vagrant Download 1.1.0 release wget http://www.apache.org/dist/bigtop/bigtop-1.1.0/bigtop-1.1.0-project.tar.gz uncompress the tarball tar -xvzf bigtop-1.1.0-project.tar.gz change directory to bigtop-1.1.0/bigtop-deploy/vm/vagrant-puppet-vm...

One of many reasons to be part of a vibrant and rich open source community is access to a treasure trove of information. One evening, I was reading through the Hive user mailing list and noticed how one user was suggesting to write Groovy to parse JSON. It was strange to suggest that approach when there are at least three ways to do so in Hive and they're built-in! It was astonishing because this feature is not very well documented. I decided to dig into it and wrote a couple of examples myself, the last two examples are contributed by Gopal from Hortonworks on that same mailing list. Now for the main event: Groovy UDF example Can be compiled at run time Currently only works in "hive" shell, does not work in beeline su guest hive paste the following code into the hive shell this will use Groovy String replace function to replace all instances of lower case 'e' with 'E' compile `import org.apache.hadoop.hive.ql.exec.UDF \; import org.apache.h...

I’m going to show you a neat way to work with CSV files and Apache Hive. Usually, you’d have to do some preparatory work on CSV data before you can consume it with Hive but I’d like to show you a built-in SerDe (Serializer/Deseriazlier) for Hive that will make it a lot more convenient to work with CSV. This work was merged in Hive 0.14 and there’s no additional steps necessary to work with CSV from Hive. Suppose you have a CSV file with the following entries  id first_name last_name email gender ip_address  1 James Coleman jcoleman0@cam.ac.uk Male 136.90.241.52  2 Lillian Lawrence llawrence1@statcounter.com Female 101.177.15.130  3 Theresa Hall thall2@sohu.com Female 114.123.153.64  4 Samuel Tucker stucker3@sun.com Male 89.60.227.31  5 Emily Dixon edixon4@surveymonkey.com Female 119.92.21.19 to consume it from within Hive, you’ll need to upload it to hdfs hdfs dfs -put sample .csv /tmp/serdes/ now all it takes is to create a table schema on top o...

I published a set of Pig, Hive and Spark scripts to interact with MongoDB using mongo-hadoop connector. Some of the published tutorials on Mongo and Hadoop on Databricks and MongoDB sites are no longer working, I decided to update them for HDP 2.3. Some things are still wonky, like Hive queries failing if you try to run anything other than select. Either way, give it a try and provide feedback. One more thing, I'm using Sandbox with HDP 2.3.2 and mongo is installed as an Ambari service using tutorial from github user nikunjness , made my work so much easier. The code is published on my github page as well as on Hortonworks Community Site. Thanks and enjoy. Sample tutorial on HDP integration with MongoDB using Ambari, Spark, Hive and Pig Prerequisites HDP 2.3.2 Sandbox Mongo 2.6.11 install MongoDB service as per  https://github.com/nikunjness/mongo-ambari IMPORTANT make sure you change directory to home after completing the mongo-ambari service insta...