Reporting & Analytics for Apache Hadoop & Big Data Users with Hortonworks

Hortonworks was formed by the key architects, builders and operators from the Yahoo! Hadoop software engineering team that led the effort to design and build every major release of Apache Hadoop from 0.1 to the most current stable release, contributing more than 80% of the code along the way.

The partnership between Hortonworks and Jaspersoft provides a good combination– Jaspersoft provides the ideal complement for reporting and analysis of Hadoop-based Big Data systems through a full suite of ETL, Apache Hive, and native Apache HBase connectors for low-latency data exploration.

Our Guest Speaker for this event will be Adam Muise:

Adam Muise is a Solution Engineer at Hortonworks, a company focused on taking 100% Open Source Hadoop to the Enterprise. He has spent years developing, implementing, and designing Data Management solutions at such companies as CIBC, HP, IBM, and Cloudera. With eyes firmly set on the killer app for this decade, Adam takes Big Data seriously and has implemented some of the largest clusters in production today.

 

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  • Sergei S.

    It was great presentation of Hadoop internals and JasperSoft

    1 · May 2, 2013

  • Teodor O.

    It's an odd emergence that the massive scale of hardware normally reserved for high performance scientific computing is being applied to conventional business reporting. I never thought that would ever happen.

    It makes perfect sense that "slow" languages like Java are applied to big data problems because the delay from running the Java virtual machine is nothing compared to delay in waiting for the disk sub-system to respond. Just as Donald Knuth found in the 1960s, if your program is largely I/O-bound, there's little point in hand-optimizing that code or in switching to a low level language. The speed limit is imposed by the response time of the peripheral hardware.

    The sample uses of MapReduce mentioned in the meeting don't place a heavy load on the CPU. This is a surprise to me. Up to now whenever someone mentioned massively parallel computing I would immediately think of physical simulations (airflow, impact of mechanical forces etc), all of which are highly CPU-intensive.

    May 1, 2013

  • Usher

    I m a consultant

    April 27, 2013

  • Victor A.

    Should we be installing the sandbox?

    April 25, 2013

    • Luke S.

      Hi Victor. I am not sure what Adam has planned for tonight.

      May 1, 2013

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