树叶云Apache Pig教程:Apache Pig Explain运算符

explain 运算符用于显示关系的逻辑,物理和MapReduce执行计划。

语法

下面给出了 explain 运算符的语法。

grunt> explain Relation_name;

假设在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,让我们使用 explain 运算符解释名为student的关系,如下所示。

grunt> explain student;

输出

它将产生以下输出。

$ explain student;

2015-10-05 11:32:43,660 [main]
2015-10-05 11:32:43,660 [main] INFO  org.apache.pig.newplan.logical.optimizer
.LogicalPlanOptimizer -
{RULES_ENABLED=[AddForEach, ColumnMapKeyPrune, ConstantCalculator,
GroupByConstParallelSetter, LimitOptimizer, LoadTypeCastInserter, MergeFilter, 
MergeForEach, PartitionFilterOptimizer, PredicatePushdownOptimizer,
PushDownForEachFlatten, PushUpFilter, SplitFilter, StreamTypeCastInserter]}  
#-----------------------------------------------
# New Logical Plan: 
#-----------------------------------------------
student: (Name: LOStore Schema:
id#31:int,firstname#32:chararray,lastname#33:chararray,phone#34:chararray,city#
35:chararray)
| 
|---student: (Name: LOForEach Schema:
id#31:int,firstname#32:chararray,lastname#33:chararray,phone#34:chararray,city#
35:chararray)
    |   |
    |   (Name: LOGenerate[false,false,false,false,false] Schema:
id#31:int,firstname#32:chararray,lastname#33:chararray,phone#34:chararray,city#
35:chararray)ColumnPrune:InputUids=[34, 35, 32, 33,
31]ColumnPrune:OutputUids=[34, 35, 32, 33, 31]
    |   |   | 
    |   |   (Name: Cast Type: int Uid: 31) 
    |   |   |     |   |   |---id:(Name: Project Type: bytearray Uid: 31 Input: 0 Column: (*))
    |   |   |     
    |   |   (Name: Cast Type: chararray Uid: 32)
    |   |   | 
    |   |   |---firstname:(Name: Project Type: bytearray Uid: 32 Input: 1
Column: (*))
    |   |   |
    |   |   (Name: Cast Type: chararray Uid: 33)
    |   |   |
    |   |   |---lastname:(Name: Project Type: bytearray Uid: 33 Input: 2
	 Column: (*))
    |   |   | 
    |   |   (Name: Cast Type: chararray Uid: 34)
    |   |   |  
    |   |   |---phone:(Name: Project Type: bytearray Uid: 34 Input: 3 Column:
(*))
    |   |   | 
    |   |   (Name: Cast Type: chararray Uid: 35)
    |   |   |  
    |   |   |---city:(Name: Project Type: bytearray Uid: 35 Input: 4 Column:
(*))
    |   | 
    |   |---(Name: LOInnerLoad[0] Schema: id#31:bytearray)
    |   |  
    |   |---(Name: LOInnerLoad[1] Schema: firstname#32:bytearray)
    |   |
    |   |---(Name: LOInnerLoad[2] Schema: lastname#33:bytearray)
    |   |
    |   |---(Name: LOInnerLoad[3] Schema: phone#34:bytearray)
    |   | 
    |   |---(Name: LOInnerLoad[4] Schema: city#35:bytearray)
    |
    |---student: (Name: LOLoad Schema: 
id#31:bytearray,firstname#32:bytearray,lastname#33:bytearray,phone#34:bytearray
,city#35:bytearray)RequiredFields:null 
#-----------------------------------------------
# Physical Plan: #-----------------------------------------------
student: Store(fakefile:org.apache.pig.builtin.PigStorage) - scope-36
| 
|---student: New For Each(false,false,false,false,false)[bag] - scope-35
    |   |
    |   Cast[int] - scope-21
    |   |
    |   |---Project[bytearray][0] - scope-20
    |   |  
    |   Cast[chararray] - scope-24
    |   |
    |   |---Project[bytearray][1] - scope-23
    |   | 
    |   Cast[chararray] - scope-27
    |   |  
    |   |---Project[bytearray][2] - scope-26 
    |   |  
    |   Cast[chararray] - scope-30 
    |   |  
    |   |---Project[bytearray][3] - scope-29
    |   |
    |   Cast[chararray] - scope-33
    |   | 
    |   |---Project[bytearray][4] - scope-32
    | 
    |---student: Load(hdfs://localhost:9000/pig_data/student_data.txt:PigStorage(',')) - scope19
2015-10-05 11:32:43,682 [main]
INFO  org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MRCompiler - 
File concatenation threshold: 100 optimistic? false
2015-10-05 11:32:43,684 [main]
INFO  org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MultiQueryOp timizer - 
MR plan size before optimization: 1 2015-10-05 11:32:43,685 [main]
INFO  org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.
MultiQueryOp timizer - MR plan size after optimization: 1 
#--------------------------------------------------
# Map Reduce Plan                                   
#--------------------------------------------------
MapReduce node scope-37
Map Plan
student: Store(fakefile:org.apache.pig.builtin.PigStorage) - scope-36
|
|---student: New For Each(false,false,false,false,false)[bag] - scope-35
    |   |
    |   Cast[int] - scope-21 
    |   |
    |   |---Project[bytearray][0] - scope-20
    |   |
    |   Cast[chararray] - scope-24
    |   |
    |   |---Project[bytearray][1] - scope-23
    |   |
    |   Cast[chararray] - scope-27
    |   | 
    |   |---Project[bytearray][2] - scope-26 
    |   | 
    |   Cast[chararray] - scope-30 
    |   |  
    |   |---Project[bytearray][3] - scope-29 
    |   | 
    |   Cast[chararray] - scope-33
    |   | 
    |   |---Project[bytearray][4] - scope-32 
    |  
    |---student:
Load(hdfs://localhost:9000/pig_data/student_data.txt:PigStorage(',')) - scope
19-------- Global sort: false
 ---------------- 

文章来源网络,作者:管理,如若转载,请注明出处:https://shuyeidc.com/wp/247926.html<

(0)
管理的头像管理
上一篇2025-04-27 08:31
下一篇 2025-04-27 08:32

相关推荐

  • 云服务器和云虚拟主机怎么选?云服务器和虚拟主机区别

    云服务器适合业务增长快、需弹性扩展的场景,而云虚拟主机适合预算有限、技术门槛低的小型静态网站或测试环境,二者核心区别在于资源独享性与运维复杂度,核心差异解析:从底层架构到使用体验很多人容易混淆这两者,觉得它们都是“买空间建站”,它们的底层逻辑完全不同,云服务器(ECS)就像是你租了一整栋别墅,水电网络独立,你想……

    2026-06-29
    0
  • 赣州智慧旅游招聘是真的吗?赣州旅游人才招聘信息

    中级岗位(3-5年经验)月薪范围通常在6000-10000元,这类岗位需要独立负责项目模块,如独立运营一个抖音账号,或维护一个景区小程序的功能迭代,具备成功案例的候选人议价能力较强,高级岗位(5年以上经验)月薪范围通常在10000-20000元,部分核心管理岗可达更高,这类人才需要具备战略规划能力,如制定整个景……

    2026-06-29
    0
  • 赣州智能物联网车位锁如何管理?智能车位锁管理系统多少钱

    赣州智能物联网车位锁管理的核心在于通过云端平台实现远程控锁、状态实时监控及自动计费,彻底解决传统车位“被占难管”与“找位难”的痛点,在赣州这样的城市,随着机动车保有量的持续增长,老旧小区、商业综合体以及私人固定车位的资源矛盾日益凸显,传统的机械地锁或简易遥控锁,不仅操作繁琐,更无法实现数据化管理,引入智能物联网……

    2026-06-29
    0
  • 赣州智能消防栓好用吗,智能消防栓多少钱一个

    赣州智能消防栓通过物联网技术实现实时监测与远程报警,能显著降低火灾响应时间并提升城市消防安全管理水平,是目前智慧城市建设中不可或缺的基础设施,赣州智能消防栓的核心价值与应用场景传统消防栓往往存在“看不见、摸不着、用不了”的痛点,在赣州这样地形复杂、老城区与新城区并存的区域,传统设施的管理难度极大,智能消防栓的出……

    2026-06-29
    0
  • 云服务器和物理机到底有啥区别?

    云服务器本质上是虚拟化资源池中的弹性实例,而传统物理服务器是独占的硬件实体,前者胜在弹性与运维便捷,后者强在物理隔离与性能稳定,具体选择取决于业务对成本、扩展性及安全合规的权衡,很多人初次接触服务器时,容易把“云服务器”和“传统物理服务器”混为一谈,觉得它们都是用来跑网站或存数据的盒子,这两者的底层逻辑完全不同……

    2026-06-29
    0

发表回复

您的邮箱地址不会被公开。必填项已用 * 标注