在上一章中,我们学习了如何将数据加载到Apache Pig中。你可以使用 store 运算符将加载的数据存储在文件系统中,本章介绍如何使用 Store 运算符在Apache Pig中存储数据。
下面给出了Store语句的语法。
STORE Relation_name INTO ' required_directory_path ' [USING function];
假设我们在HDFS中有一个包含以下内容的文件 student_data.txt 。
001,Rajiv,Reddy,9848022337,Hyderabad 002,siddarth,Battacharya,9848022338,Kolkata 003,Rajesh,Khanna,9848022339,Delhi 004,Preethi,Agarwal,9848022330,Pune 005,Trupthi,Mohanthy,9848022336,Bhuwaneshwar 006,Archana,Mishra,9848022335,Chennai.使用LOAD运算符将它读入关系 student ,如下所示。
grunt> student = LOAD 'hdfs://localhost:9000/pig_data/student_data.txt' USING PigStorage(',') as ( id:int, firstname:chararray, lastname:chararray, phone:chararray, city:chararray );现在,让我们将关系存储在HDFS目录“/pig_Output/"中,如下所示。
grunt> STORE student INTO ' hdfs://localhost:9000/pig_Output/ ' USING PigStorage (',');输出
执行 store 语句后,将获得以下输出。使用指定的名称创建目录,并将数据存储在其中。
2015-10-05 13:05:05,429 [main] INFO org.apache.pig.backend.hadoop.executionengine.mapReduceLayer. MapReduceLau ncher - 100% complete 2015-10-05 13:05:05,429 [main] INFO org.apache.pig.tools.pigstats.mapreduce.SimplePigStats - Script Statistics: HadoopVersion PigVersion UserId StartedAt FinishedAt Features 2.6.0 0.15.0 Hadoop 2015-10-0 13:03:03 2015-10-05 13:05:05 UNKNOWN Success! Job Stats (time in seconds): JobId Maps Reduces MaxMapTime MinMapTime AvgMapTime MedianMapTime job_14459_06 1 0 n/a n/a n/a n/a MaxReduceTime MinReduceTime AvgReduceTime MedianReducetime Alias Feature 0 0 0 0 student MAP_ONLY OutPut folder hdfs://localhost:9000/pig_Output/ Input(s): Successfully read 0 records from: "hdfs://localhost:9000/pig_data/student_data.txt" Output(s): Successfully stored 0 records in: "hdfs://localhost:9000/pig_Output" Counters: Total records written : 0 Total bytes written : 0 Spillable Memory Manager spill count : 0 Total bags proactively spilled: 0 Total records proactively spilled: 0 Job DAG: job_1443519499159_0006 2015-10-05 13:06:06,192 [main] INFO org.apache.pig.backend.hadoop.executionengine .mapReduceLayer.MapReduceLau ncher - Success!
你可以如下所示验证存储的数据。
首先,使用 ls 命令列出名为 pig_output 的目录中的文件,如下所示。
hdfs dfs -ls 'hdfs://localhost:9000/pig_Output/' Found 2 items rw-r--r- 1 Hadoop supergroup 0 2015-10-05 13:03 hdfs://localhost:9000/pig_Output/_SUCCESS rw-r--r- 1 Hadoop supergroup 224 2015-10-05 13:03 hdfs://localhost:9000/pig_Output/part-m-00000可以观察到在执行 store 语句后创建了两个文件。
使用 cat 命令,列出名为 part-m-00000 的文件的内容,如下所示。
$ hdfs dfs -cat 'hdfs://localhost:9000/pig_Output/part-m-00000' 1,Rajiv,Reddy,9848022337,Hyderabad 2,siddarth,Battacharya,9848022338,Kolkata 3,Rajesh,Khanna,9848022339,Delhi 4,Preethi,Agarwal,9848022330,Pune 5,Trupthi,Mohanthy,9848022336,Bhuwaneshwar 6,Archana,Mishra,9848022335,Chennai