Apache Pig中Explain运算符能解决什么问题,如何用
Admin 2022-09-27 群英技术资讯 489 次浏览
explain 运算符用于显示关系的逻辑,物理和MapReduce执行计划。
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;
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 ----------------
到此,关于“Apache Pig中Explain运算符能解决什么问题,如何用”的学习就结束了,希望能够解决大家的疑惑,另外大家动手实践也很重要,对大家加深理解和学习很有帮助。如果想要学习更多的相关知识,欢迎关注群英网络资讯站,小编每天都会给大家分享实用的文章!
免责声明:本站发布的内容(图片、视频和文字)以原创、转载和分享为主,文章观点不代表本网站立场,如果涉及侵权请联系站长邮箱:mmqy2019@163.com进行举报,并提供相关证据,查实之后,将立刻删除涉嫌侵权内容。
猜你喜欢
COGROUP 运算符的运作方式与 GROUP 运算符相同。两个运算符之间的唯一区别是 group 运算符通常用于一个关系,而 cogroup 运算符用于涉及两个或多个关系的语句。
我们在Apache Pig中有以下Math(数学)函数:S.N.函数 & 描述1ABS(expression)获取表达式的绝对值。2ACOS(expression)获得表达式的反余弦值。3ASIN(expression)获取表达式的反正弦值。
除了内置函数之外,Apache Pig还为 User Defined Function(UDF:用户定义函数)提供广泛的支持。使用这些UDF,可以定义我们自己的函数并使用它们。UDF支持六种编程语言,即Java,Jython,Python,JavaScript,Ruby和Groovy。
在上一章中,我们解释了如何安装Apache Pig。在本章中,我们将讨论如何执行Apache Pig。Apache Pig执行模式你可以以两种模式运行Apache Pig,即Local(本地)模式和HDFS模式。Local模式在此模式下,所有文件都从本地主机和本地文件系统安装和运行
illustrate 运算符为你提供了一系列语句的逐步执行。语法下面给出了illustrate运算符的语法。grunt> illustrate Relation_name; 例假设在HDFS中有一个包含以下内容的文件 student_data.txt 。
成为群英会员,开启智能安全云计算之旅
立即注册Copyright © QY Network Company Ltd. All Rights Reserved. 2003-2020 群英 版权所有
增值电信经营许可证 : B1.B2-20140078 粤ICP备09006778号 域名注册商资质 粤 D3.1-20240008