一、HPCC介绍
HPCC (High-Performance Computing Cluster), also known as DAS (Data Analytics Supercomputer), is an open source, data-intensive computing system platform developed by LexisNexis Risk Solutions. The HPCC platform incorporates a software architecture implemented on commodity computing clusters to provide high-performance, data-parallel processing for applications utilizing big data. The HPCC platform includes system configurations to support both parallel batch data processing (Thor) and high-performance online query applications using indexed data files (Roxie). The HPCC platform also includes a data-centric declarative programming language for parallel data processing called ECL.
HPCC (High Performance Computing Cluster) 是一个大规模并行处理计算平台，用于解决大数据问题。
HPCC 是一个用来集群服务器并进行大数据分析的系统，HPCC 在 LexisNexis 内部使用多年，这是一个成熟可靠的系统，包含一系列的工具和名为 ECL 的高级编程语言以及数据仓库工具。
二、System architecture
The HPCC system architecture includes two distinct cluster processing environments, each of which can be optimized independently for its parallel data processing purpose. The first of these platforms is called a data refinery whose overall purpose is the general processing of massive volumes of raw data of any type for any purpose but typically used for data cleansing and hygiene, extract, transform, load processing of the raw data, record linking and entity resolution, large-scale ad-hoc complex analytics, and creation of keyed data and indexes to support high-performance structured queries and data warehouse applications. The data refinery is also referred to as Thor, a reference to the mythical Norse god of thunder with the large hammer symbolic of crushing large amounts of raw data into useful information. A Thor cluster is similar in its function, execution environment, filesystem, and capabilities to the Google and Hadoop MapReduce platforms.
The second of the parallel data processing platforms is called Roxie and functions as a rapid data delivery engine. This platform is designed as an online high-performance structured query and analysis platform or data warehouse delivering the parallel data access processing requirements of online applications through Web services interfaces supporting thousands of simultaneous queries and users with sub-second response times. Roxie utilizes a distributed indexed filesystem to provide parallel processing of queries using an optimized execution environment and filesystem for high-performance online processing. A Roxie cluster is similar in its function and capabilities to Hadoop with HBase and Hive capabilities added, and provides for near real time predictable query latencies. Both Thor and Roxie clusters utilize the ECL programming language for implementing applications, increasing continuity and programmer productivity.