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Introduction to Apache Hadoop HDFS

This presentation introduces Apache Hadoop HDFS. It describes the HDFS file system in terms of Hadoop and big data. It looks at its architecture and resiliance.

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Introduction to Apache Hadoop HDFS

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  1. Apache Hadoop HDFS • What is it ? • What is it for ? • Architecture • Resilience • Administration • Data access • Future changes ?

  2. HDFS – What is it ? • HDSF = Hadoop Distributed File System • It is a distributed file system • Runs on low cost hardware • It is open source • Written in Java • Fault tolerant • Designed for very large data sets • Tuned for high throughput

  3. HDFS – What is it for ? • Designed for batch processing • Streaming access to data • Large data sizes i.e. Terabytes • Highly reliable using data replication • Supports very large node clusters • Supports large files • Supports file numbers into millions

  4. HDFS – Architecture

  5. HDFS – Architecture • Has a master / slave architecture • A master NameNode • Controls file system operations • Maps data blocks to DataNodes • Logs all changes • Slave DataNodes • Store file blocks • Store replicated data

  6. HDFS – Resilience • Data is replicated across DataNodes • Nodes may fail but data is still available • DataNodes indicate state via heart beat report • Single point of failure in master NameNode • Data integrity via check sums

  7. HDFS – Administration • Access via Java API • FS Shell commands language • HTTP browser • C wrapper for Java API • Space reclamation • Via control of replication factor • Deleted files sent to trash folder • Trash folder cleaned after configurable time

  8. HDFS – Future changes Things they might consider for HDFS • File append • User quotas • File links • Stand by nodes

  9. Other Areas • Want to know about ? • Big Data • Nutch • Solr • see my other presentations

  10. Contact Us • Feel free to contact us at • www.semtech-solutions.co.nz • info@semtech-solutions.co.nz • We offer IT project consultancy • We are happy to hear about your problems • You can just pay for those hours that you need • To solve your problems

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