Big Data

HPCC Systems – massively scalable supercomputing platform

HPCC (High-Performance Computing Cluster) is an open source data-intensive computing system platform designed for the enterprise to resolve Big Data challenges. It stores and processes large quantities of data, processing billions of records per second using massive parallel processing technology. Large amounts of data across disparate data sources can be accessed, analyzed and manipulated in fractions of seconds. HPCC functions as both a processing and a distributed data storage environment, capable of analyzing terabytes of information.

The HPCC Thor (The Data Refinery Cluster) technology is designed to effectively process, analyze, and find links and associations within high volumes of complex data. It functions as a distributed file system with parallel processing power spread across several nodes. A cluster can scale from a single node to thousands of nodes. This can detect non-obvious relationships, scale to support petabytes of data, and is significantly faster than competing technologies while requiring less hardware and resources. HPCC Thor works well on Amazon AWS EC2.

The HPCC Roxie technology – also known as the Rapid Online XML Inquiry Engine or RDDE – uses a combination of technologies and techniques that produce extremely fast throughput for queries on indexed data. It is the data delivery engine used in HPCC to serve data quickly and can support many thousands of requests per node per second.

HPCC generates C++ and not Java which gives it an efficiency advantage. HPCC has also been in critical production environments for over a decade. The Community Edition is an open source version of the HPCC platform that is supported by an active community of open source developers and enthusiasts.

Features include:

  • Services for job execution.
  • Services for distributed file system access.
  • A Thor cluster is also configured with a master node and multiple slave nodes.
  • A Roxie cluster is a peer-coupled cluster where each node runs Server and Agent tasks for query execution and key and file processing.
  • The file system on the Roxie cluster is a distributed indexed-based file system which uses a custom B+Tree structure for data storage.
  • Indexes and data supporting queries are pre-built on Thor clusters and deployed to Roxie with portions of the index and data stored on each node.
  • ECL Agent acting on behalf of a client program to manage the execution of a job on a Thor cluster.
  • Roxie file system is optimized for high concurrent query processing.
  • ESP Server (Enterprise Services Platform) providing authentication, logging, security, and other services for the job execution and Web services environment.
  • Dali server which functions as the system data store for job workunit information and provides naming services for the distributed file systems.
  • ECL IDE – an integrated development environment for the ECL language designed to make ECL coding easy and programmer-friendly. Using the ECL IDE you can build, edit and execute ECL queries, and mix and match your data with any of the ECL built-in functions and/or definitions that you have created. The ECL IDE offers a built-in Attribute Editor, Syntax Checking, and ECL Repository Access. You can execute queries and review your results interactively, making the ECL IDE a robust and powerful programming tool.
  • ECL code migration tool.
  • Distributed File Utility (DFU).
  • Environment Configuration Utility.
  • ECLWatch is a Web-based utility program for monitoring the HPCC environment and includes queue management, distributed file system management, job monitoring, and system performance monitoring tools.

Support: GitHub
Developer: HPCC Systems, LexisNexis Risk Solutions
License: Apache License 2.0

HPCC is written in C++. Learn C++ with our recommended free books and free tutorials.

Return to Data Analysis Tools for Big Data

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