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How to Build CI/CD Pipeline: GitHub to AWS

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 Creating a CI/CD pipeline to deploy a project from GitHub to AWS can be done using various AWS services like AWS CodePipeline, AWS CodeBuild, and optionally AWS CodeDeploy or Amazon ECS for application deployment. Below is a high-level guide on how to set up a basic GitHub to AWS pipeline: Prerequisites AWS Account : Ensure access to the AWS account with the necessary permissions. GitHub Repository : Have your application code hosted on GitHub. IAM Roles : Create necessary IAM roles with permissions to interact with AWS services (e.g., CodePipeline, CodeBuild, S3, ECS, etc.). AWS CLI : Install and configure the AWS CLI for easier management of services. Step 1: Create an S3 Bucket for Artifacts AWS CodePipeline requires an S3 bucket to store artifacts (builds, deployments, etc.). Go to the S3 service in the AWS Management Console. Create a new bucket, ensuring it has a unique name. Note the bucket name for later use. Step 2: Set Up AWS CodeBuild CodeBuild will handle the build proces
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Top Hive interview Questions for quick read (1 of 2)

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The selected interview questions on HIVE. Hive is a technology being used in Hadoop eco system.

 1) What are major activities in Hadoop eco system?
Within the Hadoop ecosystem, HDFS can load and store massive quantities of data in an efficient and reliable manner. It can also serve that same data back up to client applications, such as MapReduce jobs, for processing and data analysis.
 2)What is the role of HIVE in HADOOP Eco system?
Hive, often considered the Hadoop data warehouse platform, got its start at Facebook as their analyst struggled to deal with the massive quantities of data produced by the social network. Requiring analysts to learn and write MapReduce jobs was neither productive nor practical.
Hive Questions
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3)What is Hive in Hadoop?
Facebook developed a data warehouse-like layer of abstraction that would be based on tables. The tables function merely as metadata, and the table schema is projected onto the data, instead of actually moving potentially massive sets of data. 

This new capability allowed their analyst to use a SQL-like language called Hive Query Language (HQL) to query massive data sets stored with HDFS and to perform both simple and sophisticated summarizations and data analysis.

4)What is the requirement for HIVE learning?
If you are familiar with basic T-SQL data definition language (DDL) commands, you already have a good head start in working with Hive tables.

5)What is CREATE Table in HIVE?
CREATE EXTERNAL TABLE iislogtest (
       date STRING,
       time STRING,
       username STRING,
       ip STRING,
       port INT,
       method STRING,
       uristem STRING,
       uriquery STRING,
       timetaken INT,
       useragent STRING,
       referrer STRING
)
ROW FORMAT DELIMITED FIELDS TERMINATED BY ',';

6) What is SELECT statement in Query?
SELECT *
FROM iislogtest; 
This simple query, simply returns all rows found in the iislogtest table.

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