Pig 存储数据 | Pig 教程

#Pig 存储数据
在上一章中，我们学习了如何将数据加载到Apache Pig中。您可以使用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。
 
**语法**
下面给出了Store语句的语法。
```bash
STORE Relation_name INTO ' required_directory_path ' [USING function];
```
假设我们在HDFS中有一个具有以下内容的文件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
```
如下所示，我们已使用LOAD运算符将其读入关系student。
```bash
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。
```bash
grunt> STORE student INTO 'hdfs://localhost:9000/Pig_Output/' USING PigStorage (',');   
```
执行store语句后，您将获得以下输出。使用指定名称创建目录，数据将存储在其中。
```bash
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!
```

您可以如下所示验证存储的数据。
第1步：
使用ls命令列出目录Pig_output中的文件，如下所示。
```bash
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
```
您可以观察到在执行store语句后创建了两个文件。
 
第2步：
使用cat命令，列出名为part-m-00000的文件的内容，如下所示。
```bash
$ 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
```

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