MapReduce 服务(MapReduce Service,简称 MRS)是一个基于开源 Hadoop 生态环境而运行的大数据集群,对外提供大容量数据的存储和分析能力,可解决用户的数据存储和处理需求。用户可以将海量业务数据,存储在 MRS 的分析集群,即使用 Hive/Spark 组件保存。Hive/Spark 的数据文件则保存在 HDFS 中。GaussDB (DWS) 支持在相同网络中,配置一个 GaussDB (DWS) 集群连接到一个 MRS 集群,然后将数据从 HDFS 中的文件读取到 GaussDB (DWS)。从 MRS 导入数据到集群的流程,大致可以分为 5 个步骤:
从 MRS 导入数据到 GaussDB (DWS) 集群之前,假设您已经完成了以下准备工作:
(1)已创建 MRS 集群。
(2)在 MRS 集群上创建了 Hive/Spark ORC 表,且表数据已经存储到该表对应的 HDFS 路径上。
如果您已经完成上述准备,则可以跳过本章节。
为方便起见,我们将以在 MRS 集群上创建 Hive ORC 表作为示例,完成上述准备工作。在 MRS 集群上创建 Spark ORC 表的大致流程和 SQL 语法,同 Hive 类似,在本文中不再展开描述。
假设有数据文件 product_info.txt,示例数据如下所示:
100,XHDK-A-1293-#fJ3,2017-09-01,A,2017 Autumn New Shirt Women,red,M,328,2017-09-04,715,good
205,KDKE-B-9947-#kL5,2017-09-01,A,2017 Autumn New Knitwear Women,pink,L,584,2017-09-05,406,very good!
300,JODL-X-1937-#pV7,2017-09-01,A,2017 autumn new T-shirt men,red,XL,1245,2017-09-03,502,Bad.
310,QQPX-R-3956-#aD8,2017-09-02,B,2017 autumn new jacket women,red,L,411,2017-09-05,436,It's really super nice
150,ABEF-C-1820-#mC6,2017-09-03,B,2017 Autumn New Jeans Women,blue,M,1223,2017-09-06,1200,The seller's packaging is exquisite
200,BCQP-E-2365-#qE4,2017-09-04,B,2017 autumn new casual pants men,black,L,997,2017-09-10,301,The clothes are of good quality.
250,EABE-D-1476-#oB1,2017-09-10,A,2017 autumn new dress women,black,S,841,2017-09-15,299,Follow the store for a long time.
108,CDXK-F-1527-#pL2,2017-09-11,A,2017 autumn new dress women,red,M,85,2017-09-14,22,It's really amazing to buy
450,MMCE-H-4728-#nP9,2017-09-11,A,2017 autumn new jacket women,white,M,114,2017-09-14,22,Open the package and the clothes have no odor
260,OCDA-G-2817-#bD3,2017-09-12,B,2017 autumn new woolen coat women,red,L,2004,2017-09-15,826,Very favorite clothes
980,ZKDS-J-5490-#cW4,2017-09-13,B,2017 Autumn New Women's Cotton Clothing,red,M,112,2017-09-16,219,The clothes are small
98,FKQB-I-2564-#dA5,2017-09-15,B,2017 autumn new shoes men,green,M,4345,2017-09-18,5473,The clothes are thick and it's better this winter.
150,DMQY-K-6579-#eS6,2017-09-21,A,2017 autumn new underwear men,yellow,37,2840,2017-09-25,5831,This price is very cost effective
200,GKLW-l-2897-#wQ7,2017-09-22,A,2017 Autumn New Jeans Men,blue,39,5879,2017-09-25,7200,The clothes are very comfortable to wear
300,HWEC-L-2531-#xP8,2017-09-23,A,2017 autumn new shoes women,brown,M,403,2017-09-26,607,good
100,IQPD-M-3214-#yQ1,2017-09-24,B,2017 Autumn New Wide Leg Pants Women,black,M,3045,2017-09-27,5021,very good.
350,LPEC-N-4572-#zX2,2017-09-25,B,2017 Autumn New Underwear Women,red,M,239,2017-09-28,407,The seller's service is very good
110,NQAB-O-3768-#sM3,2017-09-26,B,2017 autumn new underwear women,red,S,6089,2017-09-29,7021,The color is very good
210,HWNB-P-7879-#tN4,2017-09-27,B,2017 autumn new underwear women,red,L,3201,2017-09-30,4059,I like it very much and the quality is good.
230,JKHU-Q-8865-#uO5,2017-09-29,C,2017 Autumn New Clothes with Chiffon Shirt,black,M,2056,2017-10-02,3842,very good
(1)创建了 MRS 集群。
(2)登录 MRS 集群的 Hive 客户端。
sudo su - omm
cd /opt/client
source bigdata_env