Apache bigtopwg7142013

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Apache bigtopwg7142013

  1. 1. Apache Bigtop Working Group 7/14/2013 Basic Skills Hadoop Pipelines (Roman's/Ron's Idea) Career positioning
  2. 2. Basic Skills ● Working group, you set your own goals. Structure: do a demo in front of the class. Focus on skills employers are looking for. ● Cluster skills using AWS; create instances, ec2-api, will have to extend this using scripts or your own code. Have to demo some skill – Goal:Manage multiple instances. You can do this manually but the number of keystrokes goes up exponentially as you add new components. Need some automation or code. – Bash scripts are good b/c they are used in Bigtop init.d files and Roman's code, e.g. copy the mkdir commands into script and run them.
  3. 3. Basic Skills ● Hadoop*, all the features of 2.0.0. No training course can give this to you. You will have to manually do this. – Use 2.0.X unit test code as a base
  4. 4. Hadoop 2.0.0 ● Basic FS Review: – Copy On Write – Write Through/Write Back, FSCK – Inodes/BTrees, NN/DN
  5. 5. Working Group ● Not a class which gives you answers. The answers classes give you are too simple to be valuable. ● E.g.; Does YARN/Hadoop 2.0.X support multitenancy? Multiple users/companies cant see each other's data and if they run a query, they can't crash the cluster for other users. This isn't the case now.
  6. 6. Hadoop 2.0.X ● Zookeeper in HDFS, requires some administration. Do you need to do a rollback of zookeeper logs when a zk cluster fails?
  7. 7. Bigtop Basic Skills ● Run Bigtop in AWS in distributed mode, start w/HDFS ● Create Hadoop* pipelines (Roman's/Ron's idea) – Ron: book. Great idea!!!!! ● Run mvn verify/learn to debug and write tests hers ● Will take months, demo driven. People do demos.
  8. 8. Career positioning ● Choose where to spend time. ● Bigdata = – Devops – App development (Astyanax) – Internals ● Don't get distracted into 3). Not enough time to do all well. Let Cloudera ppl help you. ● Do something new that people care about – Don't try to be better than people w/the same job skill – Learn efficiently, practice, practice, practice, Can't learn by watching
  9. 9. Big Company vs. Small ● Big: – Interpolate Cloudera's strategy. Hadoop 2.0.X runs in the cloud, users access from Desktop via browser, can run Hive/Pig on YOUR data, if you need to ingest data like w/flume a sys admin has to set this up. e.g. Don't spend time getting flume to work in Hue. But make sure you know 2.0.x security models/LDAP, pipeline debugging when things get stuck, failover, application development – HUE != Ambari. Why? – Value to building apps in HUE or w/HUE. Approach for webapps changing away from HUE to something like Ambari which is a simpler user defined MVC pattern. – User defined MVC better. Why? Think like a manager and what happens as Django adds more complicated features? – e.g. Jetty/J2EE example
  10. 10. Small ● Do everything, use BT, get to working app as fast as possible. 1) and 2) very important. Have to do things quickly. ● You decide how to spend your own time
  11. 11. Structure ● Schedule 3x meetings after this every 2 weeks ● Individual demos ● Install Bigtop, demo WC, PI, demo components and pipelines. ● Turn pipeline demos into integration tests ● Test on pseudo distributed mode and cluster ● Listen to Roman: Hue....
  12. 12. HBase/Hadoop ● HBase requirements: R/S 48GB, 8-12 cores/node Memory: M/R 1-2GB+, R/S 32GB+, OS 4-8GB, HDFS ● Disk: 25% for shuffle files for HDFS, <50% full, JBOD, no RAID
  13. 13. Starting Hadoop, M/R ● Look at the logs /var/log/hadoop-hdfs ● Cluster ID: under ~/cache/.../data, VERSION, change the text. DEMO ● No connection, check ping, check core-site.xml, /etc/hosts ● M/R/Yarn: mapred-site.xml. NOTE: M/R uses port 8021 and so does NAMENODE. Keep this port, run on differeent server; open port 8031 ● Telnet jt:8021, turn off iptables, disable selinux
  14. 14. M/R Setup ● 1 node manager – WRONG_REDUCE=0 – File Input Format Counters – Bytes Read=1180 – File Output Format Counters – Bytes Written=97 – Job Finished in 92.72 seconds – Estimated value of Pi is 3.14080000000000000000 –
  15. 15. M/R AWS ● 3 nodemanagers ● File Output Format Counters ● Bytes Written=97 ● Job Finished in 86.762 seconds ● Estimated value of Pi is 3.14080000000000000000 ●
  16. 16. Zookeeper Administration
  17. 17. Many options for projects ● Integration code testing when Roman gets here in 2 weeks ● Work w/Ron or Victor on projects ● Update the wiki w/ AWS cluster setup, automate w/whirr? + chef/puppet? ● Add HBase, Zookeeper management for Hadoop(monit/supervisord)

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