【正文】
world” 0, “hello mapreduce” 0, “bye bye” “hello”, 1 “world”, 1 “bye”, 2 “hello”, 1 “mpareduce”, 1 “hello”, 2 “world”, 1 “mapreduce”, 1 “bye”, 2 files line offset, line content word, count word, count files 目錄 ? Hadoop簡(jiǎn)介 –HDFS (Hadoop Distributed File System) –MapReduce ? Hive ? Hadoop的企業(yè)級(jí)應(yīng)用 What is HIVE ? 數(shù)據(jù)倉(cāng)庫(kù)業(yè)務(wù)具有多樣性、多變性和邏輯復(fù)雜性,傳統(tǒng)的Parallel DBMSs只能使用 SQL語(yǔ)句,語(yǔ)言表達(dá)力不夠應(yīng)付現(xiàn)有的類(lèi)似 google, facebook等的數(shù)據(jù)倉(cāng)庫(kù)需求(若使用 UDF或 UDA自己定義 aggregate,則失去了其強(qiáng)大的優(yōu)化功能),而自己定制的 maper和 reducer的代碼較為低層比較繁瑣且重用性也不好,所以就有了 Hive,提供一個(gè)類(lèi) SQL的編程接口,簡(jiǎn)單又不失靈活性,且基于mapreduce. What is HIVE ? (論文翻譯) hive是一個(gè)基于 hadoop的數(shù)據(jù)倉(cāng)庫(kù)。 ? Hadoop在大量的公司中被使用和研究 Hadoop的體系架構(gòu) Hadoop由以下幾個(gè)部件組成 : Hadoop Common: The mon utilities that support the other Hadoop subprojects. Avro: A data serialization system that provides dynamic integration with scripting languages. Chukwa: A data collection system for managing large distributed systems. HBase: A scalable, distributed database that supports structured data storage for large tables. HDFS: A distributed file system that provides high throughput access to application data. Hive: A data warehouse infrastructure that provides data summarization and ad hoc querying. MapReduce: A software framework for distributed processing of large data sets on pute clusters. Pig: A highlev