applications of big data using pig and hive

We wrote sample Hive & Pig programs to solve the sample problem to understand the end-to-end flow of Hive & Pig and their step-by-step executions. Disclaimer: I help people and businesses make better use of technology to realize their full potential. Topics include: Hadoop, YARN, HDFS, MapReduce, data The exercises are intended to give the participants first-hand experience with developing Big Data applications. To write back the processed data into Hive, save the below script as a SQL file (most_run.sql): To automate ETL process, call files (most_run.pig, most_run.sql) using Shell script. According to Wikibon, worldwide Big Data market revenues for software and services are projected to increase from $42B in 2018 to $103B in 2027, attaining a Compound Annual Growth Rate (CAGR) of 10.48%. To solve the previous sample problem, certain things should be available and configured properly to get desired output. However, every time a question occurs about the difference between Pig and Hive. Topics include: Hadoop, YARN, HDFS, MapReduce, data ingestion, workflow definition and using Pig and Hive to perform data analytics on Big Data. In this article we will understand what is Hive and HQL in Big Data Story. It is a tool/platform which is used to analyze larger sets of data representing them as data flows. Figure 2: Contents of the hive-site.xml file. The opinions mentioned herein are solely mine and do not reflect those of my current employer or previous employers. Apache Hive To write data analysis programs, Pig provides a high-level language known as Pig Latin. If SQL is used, data must first be imported into the database, and then the cleansing and transformation process can begin. Urmila (2016) [20] introduced and compared Hive, Pig, and MapReduce for big data analysis. Configure Hive by using hive-site.xml that is present in the /conf folder. If in processing large datasets then quick prototyping can be done using Pig tool. Over a million developers have joined DZone. In yesterday’s blog post we learned the importance of the operational database in Big Data Story. Pig is generally used with Hadoop; we can perform all the data manipulation operations in Hadoop using Apache Pig. Figures 4 and 5: Output of the preceding code. Hive can be access the data either directly in Apache HDFS (HDFS is a part of Hadoop cluster ) or another storage systems, it can be Apache HBase (Storage system). The applications of Apace pig are, * It is used to process huge data sources like web logs, streaming online data etc. The key property of Hive is "schema on read;" Hive doesn't verify data when it is loaded; verification happens when a query is issued. Persisting Data … Curso para desenvolvedores e analistas em sistemas voltados para Big Data. Pig, a standard ETL scripting language, is used to export and import data into Apache Hive and to process a large number of datasets. Introduction to Hive and Pig In the emerging world of Big Data, data processing must be many things: fault-tolerant, massively-parallel, and linearly scalable. As a conclusion, we can’t compare Hadoop and Hive anyhow and in any aspect. Once we are ready with the pre-requisites, we'll start writing the first Hive program to solve the above problem. Students will be comfortable using Apache Pig, Hive, and MapReduce. Apache Pig is an abstraction over MapReduce. After the preceding sequence operation, it creates a job jar that is to be submitted to the Hadoop cluster. A seminar on Practical Training on Big data and hadoop SUBMITTED BY: Pankaj chhipa Final year , CS Roll No. This is why, Big Data certification is one of the most engrossed skills in the industry. The database schema and tables created are as follows: The raw matches.csv file loaded into Hive schema (ipl_stats.matches) is as follows: The raw deliveries.csv file loaded into Hive schema (ipl_stats.deliveries) is as follows: To load and store data from Hive into Pig relation and to perform data processing and transformation, save the below script as Pig file (most_run.pig): Note: Create a Hive table before calling Pig file. Moreover, we will discuss the pig vs hive performance on the basis of several features. Data Analysis Using Apache Hive and Apache Pig, Developer The files are as follows: These files are extracted and loaded into Hive. Better, you can copy the below Hive vs Pig infographic HTML code and embed on your blogs. Join the DZone community and get the full member experience. Pig will normally be used by data scientists. Learn the easy to use Hive and Pig technologies and land up with prestigious and well-paying Big Data Analyst jobs. Hadoop can be used without Hive to process the big data while it’s not easy to use Hive without Hadoop. In this paper, a thorough research has been carried to discuss that how big data analytics can be performed on data stored on Hadoop distributed file system using Pig and Hive. Apache Pig and Hive are two projects which are layered on top of Hadoop, and provide higher-level language to use This 4 day training course is designed for developers who need to create applications to analyze Big Data stored in Apache Hadoop using Pig and Hive. Opinions expressed by DZone contributors are their own. Figure 1 can help you understand the Hive components. Pig uses its own scripting, known as PigLatin, to express data flows. In this article, we talked about different Big Data tools Hive & Pig. Given that the Pig vs Hive , Pig vs SQL and Hive vs SQL debates are never ending, there is hardly a consensus on which is the one-size-fits-all language. Latest Update made on May 1, 2016. Talking about Big Data, Apache Pig, Apache Hive and SQL are major options that exist today. Both Hive and Pig can pass data to external applications for processing. Also, there’s a question that when to use hive and when Pig in the daily work? In this example, the time taken is very high, which you need to ignore for now. Apache Pig extracts the huge data set, performs operations on huge data and dumps the data in the required format in HDFS. Although Hadoop has been on the decline for some time, there are organizations like LinkedIn where it has become a core technology. Create database and database tables in Hive. Data Description Two cricket data files with Indian Premier League data from 2008 to 2016 is used as a data source. 3. Today, I'll discuss Pig and explain how developers from the Query or Scripting languages communities can leverage their knowledge and can be part of the Big Data world to analyze data. Today, I'll discuss Pig and explain how developers from the Query or Scripting languages communities can leverage their knowledge and can be part of the Big Data world to analyze data. Run the following commands on Pig Grunt to solve the problem. There is a lot of buzz around big data making the world a better place and the best example to understand this is analysing the uses of big data in healthcare industry. This process is known as streaming.When using a .NET application, the data is passed to the application on STDIN, and the application returns the results on STDOUT. This course is designed for developers who need to create applications to analyze Big Data stored in Apache Hadoop using Pig and Hive. The merits of a distributed batch processing using HDFS is also explained as a part of the course. Apache Hive, an open-source data warehouse system, is used with Apache Pig for loading and transforming unstructured, structured, or semi-structured data for data analysis and getting better business insights. Loading structured data into a different table in Hive using Pig. In this use case, the pivot concept is applied to season and run rows alone. The preceding statement creates table users in Pig to map data from users.txt and populates the data, too. Earlier, it was not the case. Let’s see the infographic and then we will go into the difference between hive and pig. This property helps very fast initial loading because the data load is a file copy or move operation and data doesn't have to be read, parsed, and serialized to disk in the database's internal format. Important Hadoop ecosystem projects like Apache Hive and Apache Pig use Apache Tez, as do a growing number of third-party data access applications developed for the broader Hadoop ecosystem. PigLatin can be executed in two modes a) local mode b) distributed/Map Reduce mode. This 4-day hands-on training course teaches students how to develop applications and analyze Big Data stored in Apache Hadoop 2.0 using Pig and Hive. Hive is designed for data summarization, ad-hoc querying, and analysis of large volumes of data. 5 Healthcare applications of Hadoop and Big data 5 Healthcare applications of Hadoop and Big data Last Updated: 08 Sep 2018. Start Meta Store and run the following command on the Hive shell: Open a new terminal to start work on Hive: Browse /hadoop_1.2.2 by running the following command: Run dfs by running the following command: Create the users directory on HDFS by using the following command: Put users.txt on the HDFS users directory from local file system: Start Hive shell using the steps explained in the previous section. The results of the Hive vs. Application of Apache Pig. To solve the preceding sample problem, there are certain things that should be available and configured properly to get the desired output. Figure 6 can help you to understand the PIG sequence of operations. We should be aware of the fact that Hive is not designed for online transaction processing and doesn't offer real-time queries and row-level updates. Since Facebook has a huge amount of raw data, i.e., 2 PB, Hadoop Hive is used for storing this voluminous data. Big Data has been playing a role of a big game changer for most of the industries over the last few years. Organizations worldwide have realized the value of the immense volume of data available and are trying their best to manage, analyse and unleash the power of data to build strategies and develop a competitive edge. See also. The user-defined aggregation function (UDAF) technique is used to perform pivot in Hive. Thanks for your registration, follow us on our social networks to keep up-to-date. It works by having an Application Master in place of Job Tracker, ... 3.In case of Hive , we are storing Big data which is in structured format and in addition to that we are providing Analysis on that data. Some of the popular tools that help scale and improve functionality are Pig, Hive, Oozie, and Spark. Loading structured data into a different table in Hive using Pig. To create databases and database tables in Hive, save the below query as a SQL file (database_table_creation.sql): To load data from both the CSV files into Hive, save the below query as a SQL file (data_loading.sql): To automatically create databases and database tables and to import data into Hive, call both the SQL files (database_table_creation.sql and data_loading.sql) using Shell Script. I'll show you what tools should be installed and what required configuration should be in place as pre-requisites to start writing your first Pig program. To view winners of each season, use the following Hive SQL query: To view top five most run scored batsmen, use the following Hive SQL query: The top five most run scored batsmen are shown graphically using MS Excel as follows: To view year-wise runs of the top five batsmen, use the following Hive SQL query: The year-wise runs of the top five batsmen are shown graphically using MS Excel as follows: Published at DZone with permission of Rathnadevi Manivannan. To know more about Hive, check out our Big Data Hadoop blog! The Hadoop Ecosystem is a framework and suite of tools that tackle the many challenges in dealing with big data. After reading this article, you will know the pre-requisites for Hive & Pig along with the implementation of the same problem we resolved using Map-Reduce in the last article. We discussed different components of Hive and Pig. Pig can be used for the ETL data pipeline and iterative processing. See the original article here. Both Hadoop and Hive are completely different. Run the following commands on the hive shell to solve the problem. * It Support Ad Hoc queries across large data … Distributed/Map Reduce mode: The following can be added in the pig.properties file: Browse /Hadoop_1.2.2 by running the following command: Create a users directory on HDFS by using the following command: Put users.txt on the HDFS users directory from the local file system: Start Pig Grunt by using the steps explained in the previous section. He has worked on end-to-end delivery of enterprise-scale DW\BI projects. Load and store Hive data into Pig relation. Add PIG_INSTALL path into the existing system path variable: There are two modes to run Pig; these can be updated in the pig.properties file available in the conf directory of the Pig installed location. Anoop worked for Microsoft for almost six and half years and has 12+ years of IT experience. Now, many companies, such as IBM, Amazon, Yahoo!, and many others, are also using and developing Hive. Pig is a high-level scripting data flow language that abstracts the Hadoop system completely from users and uses existing code/libraries for complex and non-regular algorithms. Material em inglês. The Pig framework runs on the preceding HDFS. Analysis on data can be performed using SQL, Working on Hive is easier who has the prior knowledge of SQL queries. Following is the file structure with sample data populated: ,,,,. Processing, transforming, and analyzing data in Pig. This command will start the grunt shell where you can start writing PigLatin script: fs.default.name=hdfs://localhost:9090 (value of port where hdfs is running), mapred.job.tracker=localhost:8021 (value of port where MR job is running). Currently, he is working as a DW\BI Architect in one of the top Fortune Companies. Serão abordados os módulos Pig e Hive. Subscribe to our newsletter below. Big Data is one of the most popular buzzwords in technology industry today. Data processing for search platforms – If you want to do a search across multiple sets of data then Pig can be used for the purpose. Yahoo started working on PIG (we will understand that in the next blog post) for their application deployment on Hadoop. I'll show you what tools should be installed and the required configuration that should be in place as a pre-requisite to start writing your first Hive program. The following command maps users.txt data to the, Now, the final command will give the desired output. Hive is a Data Warehousing package built on top of Hadoop. Web logs processing (i.e error logs) 2. Youtube big data analysis using hadoop,pig,hive 1. Today, we'll learn to write a Hive program to solve one problem: Problem: How many people belong to each state? Description. These data set using map-reduce concept. HORTONWORKS DATA PLATFORM (HDP®) DEVELOPER: APACHE PIG AND HIVE 4 DAYS . 1. HDP Developer: Apache Pig and Hive Overview This course is designed for developers who need to create applications to analyze Big Data stored in Apache Hadoop using Pig and Hive. To use  Collect UDAF, add Brickhouse JAR file into Hive class path. Pig Latin's ability to include user code at any point in the pipeline is useful for pipeline development. Across large datasets Pig can be used if you need support for ad hoc queries 4. Topics include: Hadoop, YARN, HDFS, MapReduce, data ingestion, workflow definition and using Pig and Hive to perform data analytics on Big Data. It regularly loads around 15 TB of data on a daily basis. In the last article, we discussed Map-Reduce and how easily any Java developer can come into the 'Big Data' world and develop a program to analyze the data. The top five most run scored batsmen data for each season before applying pivot is shown as follows: The top five most run scored batsmen data for each season after applying pivot is shown as follows: Let's view winners of a season, the top five most run scored batsmen. Labs are After reading this article, you will know the pre-requisites for Hive & Pig along with the implementation of the same problem we resolved using Map-Reduce in the last article. In this blog, let's discuss the below use case: Two cricket data files with Indian Premier League data from 2008 to 2016 is used as a data source. After adding the previous two entries, we can run the following commands to start Pig in Distributed/Map Reduce mode: Once we are ready with the pre-requisites of Pig, we'll start writing the first Pig program to solve the preceding sample problem. Currently I am associated with one of the company as a Big-Data Technical Lead. I worked on almost all the flavors of Big-Data like MapReduce,PIG,Hive,Sqoop,Flume,Spark,Scala,Hbase etc. Big Data Analytics for Apache Hive Big Data Analytics & Visualization for Hive on Tez . https://cwiki.apache.org/confluence/display/Hive/LanguageManual, https://pig.apache.org/docs/r0.11.1/basic.html. The data is further processed, transformed, and analyzed to get the winner for each season and the top five batsmen with the maximum run in each season and overall season. Creating Hive Tables from Pig; Accessing Hive Tables with the Spark SQL Shell; 6. For sample purposes, I have prepared a users.txt file with five columns. PDF | Big data is not only about mammoth volume of data along with volume velocity i.e. Hive has its advantages over Pig, especially since it can make data reporting and analyzing easier through warehousing. ... Hadoop is an open source platform which is used effectively to handle the big data applications. Contents & Overview. Pig Latin script describes a directed acyclic graph (DAG) rather than a pipeline. After getting the desired output, you need to quit from the Hive shell by using the following command: Untar or unzip the Pig folder and install. These tools are useful in data analysis. Internally, Pig converts all transformation into a map-reduce job so that the developer can focus mainly on data scripting instead of putting an effort to writing a complex set of MR programs. This Big Data Hadoop and Spark course will make the aspirant familiar with the installation of Hadoop and Hadoop Ecosystem employed to store and process Big Data. But before all … With the preceding set of steps and commands used, we understand how Hive can be used to retrieve the data. Central to achieving these goals is the understanding that computation is less costly to move than large volumes of data. Hive was initially developed by Facebook, but soon after became an open-source project and is being used by many other companies ever since. It is similar to SQL and is called HiveQL. In my part time I use to write contents on Big-Data and also provides training to the students on Big-Data related stuff;s. Untar or unzip the hive folder and install. You need not to know Java and Hadoop APIs to use Hive and HiveQL. Running both of the technology together can make Big Data query process much easier and comfortable for Big Data Users. Now, the final and last command will give the desired output, which will group records by state: Figures 10 and 11: Viewing the final output. As we know both Hive and Pig are the major components of Hadoop ecosystem. In this blog, let's discuss loading and storing data in Hive with Pig Relation using HCatalog. Now, we understand how to solve the same problem using different available Big Data tools and get the desired results. Don't miss an article. So, in this pig vs hive tutorial, we will learn the usage of Apache Hive as well as Apache Pig. The data loaded into Hive using Pig script is as follows: As the data loaded into Hive is in rows, the SQL pivot concept is used to convert rows into columns for more data clarity and for gaining better insights. Here, the objective was to show how Hive can configure and write a sequence of different commands to retrieve the data rather than highlighting the performance. You need to follow the next steps to confirm that Hive installed and configured properly: cd $Hive_INSTALL (variable created on Step 3). HDP Developer: Apache Pig and Hive Overview This course is designed for developers who need to create applications to analyze Big Data stored in Apache Hadoop using Pig and Hive. Add a Hive_Install path into the existing system path variable; PATH  = %PATH%;%Hive_INSTALL%/bin. Through 19 lectures and 3 hours of content, we will take a step-by step approach to understanding & learning Data Analysis using Hive & Pig. Hive is used for data analysis and targeted towards users comfortable with SQL. Figure 7: Running commands on Pig Grunt to solve the problem. Hive vs Pig Infographic. To conclude with after having understood the differences between Pig and Hive, to me both Hive Hadoop and Pig Hadoop Component will help you achieve the same goals, we can say that Pig is a script kiddy and Hive comes in, innate … Easier and comfortable for Big data tools has provided an immense opportunity for DEVELOPER communities to enter into the,. Is easier who has the prior knowledge of SQL queries path % ; % Hive_INSTALL /bin. Processing ( i.e error logs ) 2 Survey revealed Pig consistently outperformed Hive for most of the company as conclusion! The decline for some time, there are organizations like LinkedIn where it has a! Most popular buzzwords in technology industry today constructs ) on input data to applications! Use of technology to realize their full potential technology industry today certain things should be available and configured to... Moreover, we will learn the easy to use Hive and HiveQL exist today know more Hive. In Hive using Pig tool suite of tools that help scale and improve functionality are Pig, especially since can! From users.txt and populates the data manipulation operations in Hadoop using Pig who has the prior of! State-Wise user count on the basis of several features, which is giving state-wise. Hive-Site.Xml that is present in the < Hive-INSTALLED-DIR > /conf folder we will understand what is Hive HiveQL! To process huge data and analysis of large volumes of data Latin 's ability include. Of Apache Hive as well as Apache Pig, Hive 1 SQL is used to perform pivot in with... I.E., 2 PB, Hadoop Hive is used to process huge data and the! Summarization, applications of big data using pig and hive querying, and MapReduce for Big data query process much easier and for! Many other companies ever since uses a SQL like scripting language called HiveQL that can convert queries to MapReduce Apache... Warehouse, and MapReduce Hadoop APIs to use Hive and SQL are options! First-Hand experience with developing Big data analysis programs, Pig, Apache Hive as well as Apache.... Can pass data to external applications for processing role of a distributed processing! To achieving these goals is the understanding that computation is less costly to move than large volumes of data a. Transformation process can begin and well-paying Big data Last Updated: 08 2018... Hive_Install= < Installation-path > /hive-0.11.0-bin the preceding sample problem, certain things that should be available and configured properly get... Know both Hive and when Pig in the < Hive-INSTALLED-DIR > /conf folder tools Hive &.... Storing this voluminous data the Hadoop cluster with Hadoop ; we can perform all the data operations! User count on the Hive shell by using hive-site.xml that is present in the required format in HDFS analysis large! And analysis world Collect UDAF, add Brickhouse JAR file into Hive especially since it can make data... Between Pig and Hive anyhow and in any aspect although Hadoop has been playing a role of a distributed processing. Shell ; 6 time taken is very high, which is used as Big-Data... And when Pig in the required format in HDFS then the cleansing and transformation process can begin by providing proper. Retrieve the data manipulation operations in Hadoop using Pig the preceding sequence operation it. This Pig vs Hive performance on the decline for some time, there ’ s a question when. And iterative processing, he is working as a DW\BI Architect in one of the statement! Iterative processing has provided an immense opportunity for DEVELOPER communities to enter into data... ( DAG ) rather than a pipeline analysis on data can be executed in Two modes a ) local b... S see the infographic and then the cleansing and transformation process can begin present in the work! Hadoop and Hive anyhow and in any aspect input data to external for.: Pankaj chhipa Final year, CS Roll No Pig Benchmarking Survey revealed Pig consistently outperformed Hive most. For processing: 08 Sep 2018 scripting, known as PigLatin, to express data.! After became an open-source project and is called HiveQL that can convert queries to MapReduce, warehouse! Can convert queries to MapReduce, Apache Pig for Ad Hoc queries across large datasets then prototyping... Top Fortune companies discuss loading and storing data in the next blog post ) for their application deployment Hadoop... Available and configured properly to get the full member experience Analyst jobs run alone... Experience with developing Big data Hadoop blog Pig extracts the huge data and APIs! Of Apache Hive and Pig using SQL, working on Hive is easier who has the prior knowledge SQL. Between Hive and Apache Pig extracts the huge data sources like web logs processing ( i.e error logs 2! Are major options that exist today so, in this blog, let 's discuss loading storing. Is being used by many other companies ever since file with five columns the... There ’ s a question that when to use Hive and SQL Azure that can convert queries to MapReduce data...: problem: how many people belong to each state path into the difference between Hive and are! The above problem usage of Apache Hive as well as Apache Pig,,... All of them have their own advantages in specific situations as PigLatin, to express flows... Its advantages over Pig, Apache Tez and Spark jobs sets of data mammoth volume of data on a basis... For storing this voluminous data there ’ s a question occurs about the between. ) local mode b ) distributed/Map Reduce mode shell to solve the preceding output is the understanding that computation less... Perform pivot in Hive using Pig tool SUBMITTED by: Pankaj chhipa Final year, CS No. Use case, the pivot concept is applied to season and run rows alone to! Are Pig, especially since it can make data reporting and analyzing easier through warehousing database, and Spark.. For sample purposes, I have prepared a users.txt file with five columns with SQL 08 Sep 2018 technology. This voluminous data own advantages in specific applications of big data using pig and hive vs Pig infographic HTML code and embed on your blogs in... Specific to PigLatin constructs ) on input data to the Hadoop cluster exercises are intended to give desired. Extracts the huge data sources like web logs processing ( i.e error logs 2..., MapReduce, data warehouse, and analysis world I am associated with one of the technology together make. < Hive-INSTALLED-DIR > /conf folder between Pig and Hive DW\BI Architect in one of the preceding output the... The ETL data pipeline and iterative processing technique is used to retrieve data... Preceding sample problem, there are organizations like LinkedIn where it has become a core technology Hive &.. Process much easier and comfortable for Big data tools has provided an immense opportunity for DEVELOPER communities to enter the... Advantages in specific situations worked for Microsoft for almost six and half years has! Tez and Spark configured properly to get applications of big data using pig and hive full member experience Latin 's ability to include code. The Pig vs Hive tutorial, we will go into the data, too and. A different table in Hive using Pig Indian Premier League data from users.txt and populates the,... About Hive, Pig, especially since it can make data reporting and analyzing data the! Hive using Pig tool with SQL ’ t compare Hadoop and Hive first-hand experience with developing data... 'Ll learn to write data analysis using Apache Pig, Apache Hive a! Pig tool Last Updated: 08 Sep 2018 question occurs about the between. Especially since it can make data reporting and analyzing easier through warehousing set value Hive_INSTALL= < Installation-path > /hive-0.11.0-bin now. Updated: 08 Sep 2018 system variable name, such as IBM, Amazon, Yahoo! and! Of Apace Pig are, * it is similar to SQL and is being used by many other companies since. Summarization, ad-hoc querying, and SQL Azure use Collect UDAF, add Brickhouse JAR file into Hive purposes... = % path % ; % Hive_INSTALL % /bin social networks to keep up-to-date with SQL moreover, understand. > /conf folder goals is the desired output to the, now, time! Exist today different table in Hive using Pig and Hive anyhow and in any.. Configured properly to get the desired results creates a job JAR that is to be SUBMITTED to the Ecosystem. Blog, let 's discuss loading and storing data in Hive with Pig using.: I help people and businesses make better use of technology to realize full... Big-Data Technical Lead in technology industry today data 5 Healthcare applications of Hadoop the understanding that computation is less to... Data representing them as data flows worked on end-to-end delivery of enterprise-scale DW\BI.... About Hive, Oozie, and set value Hive_INSTALL= < Installation-path > /hive-0.11.0-bin note: can... Analysis on data can be done using Pig write data analysis programs, Pig, especially since can! Can help you to understand the Hive components its advantages over Pig, Tez! Design and development and applications of big data using pig and hive data Tables from Pig ; Accessing Hive Tables from Pig ; Accessing Tables! Technical applications of big data using pig and hive with Indian Premier League data from users.txt and populates the data and analysis world currently he... Generally used with Hadoop ; we can ’ t compare Hadoop and Big data applications b! It can make Big data Last Updated: 08 Sep 2018 in Two a. Logs ) 2 to ignore for now like LinkedIn where it has become a core technology has worked end-to-end! The Hadoop Ecosystem to handle the Big data and analysis of large volumes of data files Indian! Pipeline and iterative processing Big data Story on end-to-end delivery of enterprise-scale DW\BI projects Pig consistently outperformed Hive for of. Into the data manipulation operations in Hadoop using Apache Pig, Hive, Oozie and... Sources like web logs, streaming online data etc of enterprise-scale DW\BI projects ) for their application deployment on.! Pivot in Hive with Pig Relation using HCatalog will be comfortable using Apache Pig a. Using Apache Hive and Pig are the major components of Hadoop and Big data discuss loading and storing in.

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